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Health Monitoring of Structural Materials and Components:

Health Monitoring 3/2/2007© D. Adams 2006

Appendix B

B.1 Journals and Conferences Dealing with Health Monitoring

Table B.1 and Table B.2 in this section provide lists of technical Journals and conferences that highlight developments in health monitoring. These tables will be updated as necessary to provide up-to-date information

B.2 Sensors

In Table B.3-Table B.10, different types of displacement, velocity, acceleration, strain, force, temperature, and pressure sensors are summarized.

B.3 References on Data Analysis from the Literature

In Table B.11-Table B.18, references from the literature on a wide range of data analysis topics in health monitoring are summarized and cited. These references will be updated as necessary to provide up-to-date information.

Table B.1 – Technical Journals in health monitoring.

Journal Name

Publisher

AIAA Journal

American Institute of Aeronautics and Astronautics

Experimental Mechanics

Society of Experimental Mechanics

International Journal of Analytical and Experimental Modal Analysis

CSA Illumina

International Journal of Engineering Science

CSA Illumina

International Journal of Fatigue

Elsevier Science

International Journal of Fracture

Springer

Journal of Applied Mechanics

American Society of Mechanical Engineers

Journal of Dynamic Systems, Measurement, and Control


Journal of Engineering Mechanics

American Society of Civil Engineers

Journal of Intelligent Material Systems and Structures

Sage Publishers

Journal of Pressure Vessel Technology


Journal of Sound and Vibration

Academic Press

Journal of Structural Engineering

American Society of Civil Engineers

Journal of Vibration and Acoustics


Mechanical Systems and Signal Processing

Academic Press

NDT&E International

Elsevier Science

Physical Review Letters

American Physical Society

Sensors Actuators

CSA Illumina

Smart Materials and Structures

Institute of Physics

Structural Health Monitoring: An International Journal

Sage Publishers

The Journal of the Acoustical Society of America

Acoustical Society of America

The Shock and Vibration Digest

Sage Publishers

Table B.2 – Technical conferences in health monitoring.

Conference Name

International Modal Analysis Conference

European Workshop on Structural Health Monitoring

International Workshop on Structural Health Monitoring

The International Society for Optical Engineering (SPIE)

International Mechanical Engineering Congress

Asia-Pacific Conference on Systems Integrity and Maintenance (ACSIM)

IEEE Aerospace Conference

International Conference on Adaptive Structures and Technologies

AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference

International Conference on Adaptive Structures

IEEE Conference on Antennas and Propagation

International Conference on Damage Assessment of Structures

International Design Engineering Technical Conference

Society for the Advancement of Material and Process Engineering Conference

Integrated Systems Health Management Conference

Health and Usage Monitoring Conference

Machinery Failure Prevention Technology Annual Meeting

Materials Science and Technology Conference

Quantitative NDE Conference

AIAA/ASME/ASCE/ASC Structures, Structural Dynamics & Materials Conference

Table B.3 – Displacement sensors.

Sensor Type:

Advantages

Disadvantages

Applications

Example

1. Low susceptibility to noise and

interference

1. Accurate for small distance (1mm

-

150mm)

1. Crack detection in turbine

blades

2. Accurate at high temperatures

while being unsusceptible to

enviromental conditions

2. Surface conditions affect high

resolution measurements

2.

Corrosion thinning

measurements on aircraft

skins

1. Can be used on conductive and

non

-

conductive materials

1. Sensitive to environmental

parameters

1. Measure aircraft engine

door cowling gaps

2. Wide bandwidth and high

resolutions

2. Su

sceptible to electrostatic

charge due to friction

2. Monitor aircraft cargo door

alignment.

1. Capable of operating under hostile

environments

1. Mechanical gyros accumulate

drift between actual and sensed

values over time

1. Measuring angula

r

displacement of aircraft wings

due to turbulence.

2. Have a high signal to noise ratio

and low power consumption

2. Provide only relative information

2. Satellite position monitoring

and control

1. Are more stable in noisy

environments

1.

Are susceptible to external

magnetic interference.

1. Monitor crackshaft for

ignition timing and misfire

2. Capable of achieveing low

temperature sensitivity.

2. Can only be used for

ferromagnetic materials.

2. Monitoring weld health in

welde

d steel armor plates

1. Absence of loading effects on the

structure.

1.Not suitable to be bent at steep

angles due to refraction of light

1. Monitoring hull deflection on

a composite patrol boat

2. Insensitivity to stray magnetic fields

or elec

trostatic interference

2. Fibers are delicate and can be

easily damaged.

2. Measure displacement of

composite bridge decks due to

automotive loading.

1. Resistant to external disturbances

such as vibration, ambient noise and

EM radiation.

1.

Sensors have a "dead" region

directly below them where damage

cannot be detected.

1. Study of wear,

chipping/breakage and

temperature in tooling parts

2. Capable of detecting small defects

at large distances

2. Time consuming and requires

h

igher level of user skill

2. Examining bolts or rivets in

aircraft wings

1. Is less sensitive to material surface

roughness or geometry

1. Susceptible ot extraneous noise

1. Monitor seal and blade

-

tip

rubbing in turbo machinery

2. High sensit

ivities allow for crack

formation detection.

2. Sensors must be mounted to

surface, resulting in possible mass

loading issues

2. Damage assessment in a

steel

-

concrete composite

bridge deck

Capacitive

Gyroscope

Magnetic

Optical

Ultrasonic

Acoustic Emission

Inductive

Table B.4 – Velocity sensors.

Table B.5 – Acceleration sensors.

Table B.6 – Strain sensors.

Table B.7 – Force sensors.

Table B.8 – Temperature sensors.

Table B.9 – Pressure sensors.

Table B.10 – Piezoelectric actuators.

Configuration:Sensing Direction: Advantages:

Disadvantages:

Applications:

Transverse

1. Ideal for static and low

frequency applications.

2. Capable of applying tension

and compression loads

1. Low electro-mechanical

coupling

2. Requires strong bonds to

ensure high fidelity.

3. Stability problems for large

displacement

1. Fine tuning of laser

equipment.

2. Alignment of fiber optics.

3. Control injection valves in

the automotive industry

Shear

1. Extremely reliable (>10

9

cycles).

2. High resonant frequencies.

1. Needs to be pre-loaded to

avoid un-poling resulting in

lowered operational

frequencies.

1. Atomic force microscopy.

2. Active vibration

cancellation.

TubeTransverse

1. Capable of measuring

displacements along all three

axes.

2. Sub-nanometer resolution

1. Small Displacement

2. Relative to stack actuators,

small force

1. Hard drive read/write head

testing.

2. Needle valve actuation.

RingTransverse

1. Available with clear

aperatures for transmitted-light

applications.

2. High resolution for

static/dynamic applications.

1. More delicate than other

configurations due to the

center bore

2. Low force

1. Image positioning.

2. Micropositioning

DiskTransverse

1. Provide a relatively large

travel range for their size.

2. Fast response w/ sub-

nanometer resolution

1. Low force

1. Knife edge control in

extrusion tools.

2. Tuning of circular boring,

drilling processes.

Bimorph (PVDF)Transverse/Shear

1. Low operating voltage.

2. Excellent resistance to

humidity.

1. Low frequency operation.

2. Low resolution (unsuitable

for precision). 3.

Low force and slow response

1. Position control of

pneumatic valves.

2. Measuring accelerations of

flexible structures.

Stack

Table B.11 – References on methods for loads identification.

Reference

Summary

Stevens, K.K., 1987, “Force Identification Problems-An Overview”

Conference: Overview of indirect force estimation for linear systems.

Chae et al., 1999, “A Feasibility Study in Indirect Identification of Transmission Forces through Rubber Bushing in Vehicle Suspension System by Using Vibration Signals Measured on Links”

Journal: Relates the transmission force to the deformation of rubber bushings through an appropriate model.

Decker, M. and Savaidis, G., 2002, “Measurement and Analysis of Wheel Loads for Design and Fatigue Evaluation of Vehicle Chassis Components”

Journal: Discussed the interactions of wheel forces and moments, forces acting in a suspension, and the stress response of an axle casing.

O’Connor, C., and Chan, T.H.T., 1988, “Dynamic Wheel loads From Bridge Strains”

Journal: Modeled the bridge deck as lumped masses interconnected by mass-less elastic beams and estimated loading of bridge due to wheels.

Chan, T.H.T., Law, S.S., Yung, T.H. and Yuan, X.R., 1999, “An Interpretive Method for Moving Force Identification”

Journal: Modeled the bridge deck using Bernoulli-Euler beams and estimated loading of bridge due to wheels.

Zhu, X.Q. and Law, S.S., 2000, “Identification of Vehicle Axle Loads from Bridge Responses”

Journal: Modeled the bridge deck as orthotropic plates and estimated loading of bridge due to wheels.

Wang, M.L. and Kreitinger, T.J., 1994, “Identification of Force from Response Data of a Nonlinear System”

Journal: Presented the sum of weighted acceleration technique (SWAT) to estimate the input force.

Giergil, J. and Uhl, T., 1989, “Identification of the Input excitation forces in mechanical structures”

Journal: Presented an iterative formula for calculation of excitation forces in mechanical structures based on properties of the Toeplitz matrix.

Haas, D.J., Milano and Flitter, L., 1995, “Prediction of Helicopter Component Loads Using Neural Networks”

Journal: Used a neural network approach to relate rotor system component loads to flight data recorded using a flight recorder.

Giasante et al., 1983, “Determination of In-Flight Helicopter Loads”

Journal: Identified the external vibratory forces acting on a helicopter in flight using a calibration matrix.

Li, J., 1988, “Application of Mutual Energy Theorem for Determining Unknown Force Sources”

Conference: Identified spectrum of loads based on vibration velocity response measurements.

Zion, L., 1994, “Predicting Fatigue Loads Using Regression Diagnostics”

Conference: Presented an approach based on a regression model relating loads and flight data in a helicopter.

Uhl, T. and Pieczara, J., 2003, “Identification of Operational Loading Forces for Mechanical Structures”

Journal: Based on the difference between measured and simulated system responses, genetic algorithm estimates loads.

Starkey, J.M., and G.L. Merrill, 1989, “On the Ill-Conditioned Nature of Indirect Force-Measurement Techniques”

Journal: Investigated the ill-conditioned nature of the inverse problem and found that the condition of the FRF matrix is a good indicator of errors.

Bartlett, F.D., Jr., and W.G. Flannelly, 1979, “Model Verification of Force Determination for Measuring Vibratory Loads”

Journal: Found that the pseudo-inverse method of force estimation worked well for identifying vibrations forces on the rotary hub of a helicopter model

Hundhausen, R.J., D.E. Adams, M. Derriso, Kukuchek, P., and Alloway, R., 2005, “Transient Loads Identification for a Standoff Metallic Thermal Protection System Panel”

Conference: Used two methods for identifying transient loads on standoff metallic panels: 1) rigid body approach, and 2) inverse FRF approach.

Turco, E., 2005, “A Strategy to Identify Exciting Forces Acting on Structures”

Journal: Explores the use of the Tikhonov regularization technique to reduce ill-conditioning effects of frequency domain equations for pin-jointed trusses.

Kammer, D.C., 1996, “Input Force Reconstruction Using a Time Domain Technique”

Journal: Convolves the measured response and an inverse system of Markov parameters to estimate input forces on a structure in the time domain.

Jacquelin, E., Bennani, A., and Hamelin, P, 2003, “Force Reconstruction: Analysis and Regularization of a Deconvolution Problem”

Journal: Applies Tikhonov and trunctation regularization techniques to the indirect force estimation problem and chooses the regularization parameters.

Fabunmi, J.A., 1986, “Effects of Structural Modes on Vibratory Force Determination by the Pseudoinverse Technique”

Journal: Studied the implication of using the least-squares method of force identification without considering the modes and mode shapes.

Carne, T.G., Mayes, R.L., and Bateman, V.I., 1994, “Force Reconstruction Using the Sum of Weighted Acceleration Technique—Max-Flat Procedure”

Conference: Used FRF data to determine appropriate scalar weights to use in the Sum of Weighted Acceleration Technique for force reconstruction.

Mayes, R.L., 1994, “Measurement of Lateral Launch Loads on Re-Entry Vehicles Using SWAT”

Conference: Uses the SWAT method to reconstruct forces acting on a structure, but uses the free decay time histories to calculate the weights.

Liu, Y., and Shepard, S., Jr., 2005, “Dynamic Force Identification Nased on Enhanced Least Squares and Total Least-Squares Schemes in the Frequency Domain”

Journal: Utilizes and compares the least-square method of indirect force estimation without regularization and with truncated SVD and regularization.

1. Chae, C.K., Bae, B.K., Kim, K.J., Park, J.H. and Choe, N.C., “A Feasibility Study in Indirect Identification of Transmission Forces through Rubber Bushing in Vehicle Suspension System by Using Vibration Signals Measured on Links,” 1999, Vehicle System Dynamics, Vol. 33, No. 5, pp. 327-349.

2. Decker, M. and Savaidis, G., “Measurement and Analysis of Wheel Loads for Design and Fatigue Evaluation of Vehicle Chassis Components,” 2002, Fatigue and Fracture of Engineering Materials and Structures, Vol. 25, Issue 12, 1103.

3. O’Connor, C., and Chan, T.H.T., “Dynamic Wheel Loads from Bridge Strains,” 1998, J. Struct. Div. ASCE, 114(8), pp. 1703-1723.

4. Chan, T.H.T., Law, S.S., Yung, T.H. and Yuan, X.R., “An Interpretive Method for Moving Force Identification,” 1999, Journal of Sound and Vibration, 219(3), pp. 503-524.

5. Zhu, X.Q. and Law, S.S., “Identification of Vehicle Axle Loads from Bridge Responses,” 2000, Journal of Sound and Vibration, 236(4), pp. 705-724

6. Wang, M.L. and Kreitinger, T.J., “Identification of Force from Response Data of a Nonlinear System,” 1994, Soil Dynamics and Earthquake Engineering, Vol. 13, pp. 267-280.

7. Giergil, J. and Uhl, T., “Identification of the Input Excitation Forces in Mechanical Structures,” 1989, The Archives of Transport, Vol. 1, No. 1.

8. Haas, D.J., Milano and Flitter, L., “Prediction of Helicopter Component Loads Using Neural Networks,” 1995, Journal of the American Helicopter Society, No. 1, pp. 72-82.

9. Giasante, N., Jones, R. and Calapodas, N. J., “Determination of In-Flight Helicopter Loads,” 1983, Journal of the American Helicopter Society, 27, pp. 58-64.

10. Li, J., “Application of Mutual Energy Theorem for Determining Unknown Force Sources,” 1988, Proc. of Internoise 88, Avignion.

11. Zion, L., “Predicting Fatigue Loads Using Regression Diagnostics,” 1994, Proc. of the American Helicopter Society 50 Annual Forum, Washington D.C.

12. Uhl, T. and Pieczara, J., “Identification of Operational Loading Forces for Mechanical Structures,” 2003, The Archives of Transport, Vol. 16, No. 2.

13. Stevens, K.K., “Force Identification Problems-An Overview,” 1987, Proc. of SEM Spring Conference on Experimental Mechanics, pp. 838-844.

14. Starkey, J.M., and G.L. Merrill, “On the Ill-Conditioned Nature of Indirect Force-Measurement Techniques,” 1989, Journal of Modal Analysis, pp. 103-108.

15. Bartlett, F.D., Jr., and W.G. Flannelly, “Model Verification of Force Determination for Measuring Vibratory Loads,” 1979, J. American Helicopter Society, 24:10-18.

16. Hundhausen, R.J., D.E. Adams, M. Derriso, P. Kukuchek, and R. Alloway, “Transient Loads Identification for a Standoff Metallic Thermal Protection System Panel,” 2005, Proc. of the IMAC-XXIII: A Conference & Exposition on Structural Dynamics, No. 394.

17. Turco, E., “A Strategy to Identify Exciting Forces Acting on Structures,” 2005, International Journal for Numerical Methods in Engineering, 64:1483-1508.

18. Kammer, D.C., “Input Force Reconstruction Using a Time Domain Technique,” 1996, American Institute of Aeronautics and Astronautics, Inc., pp. 21-30.

19. Jacquelin, E., A. Bennani, and P. Hamelin, “Force Reconstruction: Analysis and Regularization of a Deconvolution Problem,” 2003, Journal of Sound and Vibration, 265: 81-107.

20. Fabunmi, J.A., “Effects of Structural Modes on Vibratory Force Determination by the Pseudoinverse Technique,” 1986, American Institute of Aeronautics and Astronautics, Inc., 24(3):504-509.

21. Carne, T.G., R.L. Mayes, and V.I. Bateman, “Force Reconstruction Using the Sum of Weighted Acceleration Technique--Max-Flat Procedure,” 1994, Proc. of 12th International Modal Analysis Conference, pp. 1054-1062.

22. Mayes, R.L., “Measurement of Lateral Launch Loads on Re-entry Vehicles Using SWAT,” 1994, Proc. of 12th International Modal Analysis Conference, pp. 1063-1068.

23. Liu, Y., and S. Shepard, Jr., “Dynamic Force Identification Based on Enhanced Least Squares and Total Least-Squares Schemes in the Frequency Domain,” 1995, Journal of Sound and Vibration, 282: 37-60.

Table B.12 – References on vibration-based damage identification methods.

Reference

Summary

Doebling et al., 1996, “Damage Identification and Health Monitoring of Structural and Mechanical Systems from Changes in Their Vibration Characteristics: A Literature Review”

Report: Comprehensive survey of vibrations-based techniques for damage detection, location and characterization.

Hoon et al., 2001, “A Review of Structural Health Monitoring Literature: 1996-2001”

Report: An update to the work by Doebling et al. (1996) that outlines feature extraction and damage quantification methods among other issues.

Afolabi, D., 1987, “An Anti-Resonance Technique for Detecting Structural Damage”

Conference: Showed how data around anti-resonances is much more sensitive to structural damage compared to the resonances.

Zhang et al., 1999, “Structural Health Monitoring Using Transmittance Functions”

Journal: Showed that transmissibility functions are reliable detection features to locate perturbations in experiments on a composite beam.

Johnson, T. J. and Adams, D. E., 2002, "Transmissibility as a Differential Indicator of Structural Damage"

Journal: Developed a transmissibility-based detection feature that was able to detect and locate damage.

Wang, W. and Zhang, A., 1987, “Sensitivity Analysis in Fault Vibration Diagnosis of Structures”

Conference: Determined that certain frequency ranges in FRFs, including those near anti-resonances, are sensitive to changes in structural parameters.

I. Trendafilova et al., 1998, “Damage Localization in Structures. A Pattern Recognition Perspective”

Conference: Presented a pattern recognition approach for damage localization in structures.

Sohn, H. and Farrar, C.F., 2001, “Damage Diagnosis Using Time Series Analysis of Vibration Signals”

Journal: Used standard deviation of residual errors from a combination of AR and ARX models as a damage-sensitive feature to locate damage.

Nair et al., 2003, “Application of Time Series Analysis in Structural Damage Evaluation”

Conference: Previous algorithm is modified to increase the effectiveness in identifying small damage patterns by using normalized relative accelerations.

Adams, D.E. and Farrar, C.R., 2002, “Classifying Linear And Non-Linear Structural Damage Using Frequency Domain ARX Models”

Journal: Used frequency domain autoregressive models to develop linear and nonlinear damage features in a three-story building frame.

Johnson et al., 2005, “Embedded Sensitivity Functions for Characterizing Structural Damage”

Journal: Presented the use of algebraic combinations of measured FRF data to estimate perturbations in mass, damping, or stiffness due to damage.

Adams, D.E., 2002, “Nonlinear Damage Models for Diagnosis and Prognosis in Structural Dynamic Systems”

Conference: Demonstrated that model reduction near bifurcations caused by structural damage is a useful way to identify damage features.

Farrar et al., 1999, “A Statistical Pattern Recognition Paradigm of Vibration-Based Structural Health Monitoring”

Conference: Discussed the process of vibration-based structural health monitoring as a statistical pattern recognition problem.

Corbin et al., 2000, “Locating Damage Regions Using Wavelet Approach”

Conference: Detected damage using wavelet decomposition of acceleration response data.

Moyo, P. and Brownjohn, J.M.W., 2002, “Detection of Anomalous Structural Behavior Using Wavelet Analysis”

Journal: Used wavelet analysis to detect anomalies using strain data from a bridge but does not distinguish damage from other sources of variability.

Sun, Z., and Chang, C.C., 2002, “Structural Damage Assessment Based on Wavelet Packet Transform”

Journal: Developed a damage assessment method using the wavelet packet transform to produce inputs to neural network models.

Hou et al., 2000, “Application Wavelet-Based Approach for Structural Damage Detection”

Journal: Showed that damage can be detected by decomposing response data using wavelets with the potential to locate damage as well.

Haroon, M., and Adams, D.E., 2005, “Active and Event-Driven Passive Mechanical Fault Identification in Ground Vehicle Suspension Systems”

Conference: Presented active and passive data interrogation methodologies for damage identification based on the frequency bandwidth of signals.

Haroon, M., and Adams, D.E., 2006, “Nonlinear Fault Identification Methods for Ground Vehicle Suspension Systems”

Conference: Discussed nonlinear damage identification methods which track nonlinear changes accompanying damage using response acceleration data.

Worden et al., 2003, “Experimental Validation of Structural Health Monitoring Methodology I: Novelty Detection on a Laboratory Structure”

Journal: Presented experimental verification of the novelty detection method for damage identification based on transmissibility functions.

Manson et al., 2003, “Experimental Validation of Structural Health Monitoring Methodology II: Novelty Detection on an Aircraft Wing”

Journal: Applied the previously discussed outlier analysis based novelty detection algorithm on a realistic structure, the wing of a Gnat aircraft.

Monaco, E., Calandra, G., and Lecce, L., 2000, “Experimental Activities on Damage Detection Using Magnetorestricitve Actuators and Statistical Analysis”

Conference: Used averages of differences between healthy and damaged structure FRFs as damage detection features.

Natke, H.G., and Cempel, C., 1997, “Model-Aided Diagnosis Based on Symptoms”

Conference: Used changes in natural frequencies and mode shapes in a finite element model of a cable-stayed steel bridge to detect damage.

Garcia et al., 1998, “Comparison of the Damage Detection Results Utilizing an ARMA Model and a FRF Model to Extract Modal Parameters”

Conference: Time domain ARMA model and FRF modal extraction techniques are compared, and ARMA model out performs modal parameters.

Garcia, G., and Osegueda, R., 1999, “Damage Detection Using ARMA Model Coefficients”

Conference: Parameters of time domain ARMA model are used for damage detection; location was possible with ambiguity for multiple damage sites.

Sohn, H. and Farrar, C.R., 2000, “Statistical Process Control and Projection Techniques for Structural Health Monitoring”

Conference: Combined statistical process control with projection techniques, such as principal component analysis, for damage detection.

Bodeux, J.B., and Golinval, J.C., 2000, “ARMAV Model Technique for System Identification and Damage Detection”

Conference: Demonstrated the use of time-domain Auto-Regressive Moving-Average Vector (ARMAV) models for detecting damage.

Heyns, P.S., 1997, “Structural Damage Assessment Using Response-Only Measurements”

Conference: Used a Multivariate Auto-Regressive Vector (ARV) model based approach to detect and locate damage in a cantilever beam.

Tsyfansky, S.L. and Beresnevich, V.I., 1997, “Vibrodiagnosis of Fatigue Cracks in Geometrically Nonlinear Beams”

Conference: Attempted to detect and quantify fatigue cracks in a beam by analyzing the nonlinear harmonics in the Fourier spectrum of the response.

Masri et al., 2000, “Application of Neural Networks fort Detection of Changes in Nonlinear Systems”

Journal: Presented a neural network technique for health monitoring using vibration measurements; prediction error was used for detecting damage.

Feng, M., and Bahng, E., 1999, “Damage Assessment of Bridges with Jacketed RC Columns Using Vibration Test”

Conference: Proposed a jacketed column monitoring method that combines vibration testing, neural network, and finite element techniques.

Worden, K. and Fieller, N.R.J., 1999, “Damage Detection Using Outlier Analysis”

Journal: Studied outlier analysis for damage detection with a Mahalanobis distance based on measured transmissibility functions as damage feature.

Salawu, O.S., 1997, “Detection of Structural Damage through Changes in Frequency: A Review”

Journal: Reviewed methods for detecting damage using natural frequencies and discussed relationships between frequency changes and structural damage.

Farrar, C.R., 1997, “Variability of Modal Parameters on the Alamosa Canyon Bridge”

Doebling et al. 1997, “Effects of Measurements Statistics on the Detection of Damage in the Alamosa Canyon Bridge”

Conference: Showed that the sensitivity of frequency shifts to damage is low but these shifts exhibit less statistical variation from random error.

Cawley, P., and Adams, R.D., 1979, “Location of Defects in Structures from Measurements of Natural Frequencies”

Journal: Detected damage in composite materials using ratios between frequency shifts for two different modes.

Pandey et al., 1991, “Damage Detection from Changes in Curvature Mode Shapes”

Journal: Showed that absolute changes in mode shape curvature can be a good indicators of damage.

Pandey, A.K. and Biswas, M., 1994, “ Damage Detection in Structures Using Changes in Flexibility”

Pandey, A.K. and Biswas, M., 1995, “Damage Diagnosis of Truss Structures by Estimation of Flexibility Change”

Journal: Presented a damage detection and location method based on changes in the measured flexibility matrix using lowest frequency vibration modes.

Lim, T.W., 1991, “Structural Damage Detection Using Modal Test Data”

Journal: Used the unity check methods for damage detection by defining a least-squares problem for the elemental stiffness changes in a truss.

Banks, H. T., Inman, D. J., Leo, D. J., Want, Y., 1996, “An Experimentally Validated Damage Detection Theory in Smart Structures”

Journal: Developed a damage detection theory based on the derivative of frequency with respect to either stiffness or mass.

Doebling, S. W., 1996, “Minimum-Rank Optimal Update of Elemental Stiffness Parameters for Structural Damage Identification”

Journal: Developed an optimal minimum-rank update of stiffness parameters for damage identification.

Escobar, J. A., Sosa, J. J., Gomez, R., 2005, “Structural Damage Detection using the Transformation Matrix”

Journal: Used transformation matrix in two- and three-dimensional analytical building models to detect damage.

Fritzen, C. P., Jennewein, D., Kiefer, T., 1998, “Damage Detection Based on Model Updating Methods”

Journal: Applied a sensitivity approach that used both time and frequency to localize damage in a finite element beam model.

Hajela, P. and Soeiro, F. J., 1989, “Structural Damage Detection Based on Static and Modal Analysis”

Journal: Eigenmodes and static displacements were used to detect changes in stiffness.

Hwang, H.Y., Kim C., 2004, “Damage detection using a few frequency response measurements”

Journal: Modeled damage using changes in the component stiffness matrix and treated the damage detection problem as a minimization problem.

Lew, J. S., 1995, “Using Transfer Function Parameter Changes for Damage Detection of Structures”

Journal: Found that changes in environmental factors contribute less significantly to the structural natural frequencies than actual damage.

Kaouk, M., Zimmerman, D. C., 1994, “Structural Damage Assessment Using a Generalized Minimum Rank Perturbation Theory”

Journal: Addressed unsymmetric impedance matrices with singular value decomposition to acquire a damage vector.

Samuel, P. D., Pines, D. J., 2004, “A Review of Vibration-based Techniques for Helicopter Transmission Diagnostics”

Journal: Points out progress in the area of vibration-based fault detection.

Sheinman, I., 1996, “Damage Detection and Updating of Stiffness and Mass Matrices using Mode Data”

Journal: Damage was detected using minimal static and dynamic measurements through a closed form algorithm.

Tsuei, Y. G., Yee, E. K. L., 1989, “A Method for Modifying Dynamic Properties of Undamped Mechanical Systems”

Journal: Modified mass and stiffness matrices by adding small changes in mass and stiffness to the forcing function of the unmodified structure.

Zimmerman, D. C., Kaouk, M., 2005, “Model Correlation and System Health Monitoring using Frequency Domain Measurements”

Journal: Addressed unsymmetric impedance matrices with singular value decomposition to acquire a damage vector.

1. Doebling, S.W., Farrar, C.R., Prime, M.B. and Shevitz. D.W., “Damage Identification and Health Monitoring of Structural and Mechanical Systems from Changes in Their Vibration Characteristics: A Literature Review,” 1996, Los Alamos National Laboratory report, LA-13070-MS.

2. Sohan, H., Farrar, C.R., Hemez, F.M., Shunk, D.D., Stinemates, D.W. and Nadler, B.R., 20031, “A review of structural health monitoring literature: 1996-2001,” Los Alamos National Laboratory report, LA-13976-MS.

3. Afolabi, D., “An Anti-Resonance Technique for Detecting Structural Damage,” 1987, Proc. of the 5th International Modal Analysis Conference, pp. 491-495.

4. Zhang, H., Schulz, M. J., Naser, A., Ferguson, F., and Pai, P.F., “Structural Health Monitoring Using Transmittance Functions,” 1999, Mechanical Systems and Signal Processing, 13(5), pp. 765-787.

5. Johnson, T. J. and Adams, D. E., “Transmissibility as a Differential Indicator of Structural Damage,” 2002, ASME Journal of Vibration and Acoustics, 124(4), pp. 634-641.

6. Wang, W. and Zhang, A., “Sensitivity Analysis in Fault Vibration Diagnosis of Structures,” 1987, Proc. of the 5th International Modal Analysis Conference, pp. 496-501.

7. Trendafilova, I., Heylen, W., Sas, P., “Damage Localization in Structures. A Pattern Recognition Perspective,” 1998, ISMA 23, pp. 99-106.

8. Sohn, H. and Farrar, C.F., “Damage Diagnosis Using Time Series Analysis of Vibration Signals,” 2001, Smart Materials and Structures, Vol. 10, pp. 446-451.

9. Nair, K.K., Kiremidjian, A.S., Lei, Y., Lynch, J.P., and Law, K.H., “Application of Time Series Analysis in Structural Damage Evaluation,” 2003, Proc. of the International Conference on Structural Health Monitoring, Tokyo, Japan.

10. Adams, D.E. and Farrar, C.R., “Classifying Linear and Non-linear Structural Damage Using Frequency Domain ARX Models,” 2002, Structural Health Monitoring, 1(2), pp.185-201.

11. Johnson, T.J., Yang, C., Adams, D.E., and Ciray, S., “Embedded Sensitivity Functions for Characterizing Structural Damage,” 2005, Smart Materials and Structures, Vol. 14, pp. 155-169.

12. Adams, D.E., “Nonlinear Damage Models for Diagnosis and Prognosis in Structural Dynamic Systems,” 2002, SPIE, Vol. 4733.

13. Farrar, C.R., Duffey, T.A., Doebling, S.W., and Nix, D.A., “A Statistical Pattern Recognition Paradigm of Vibration-Based Structural Health Monitoring,” 1999, 2nd International Workshop on Structural Health Monitoring, Stanford, CA, pp. 764-773.

14. Corbin, M., Hera, A., and Hou, Z., “Locating Damage Regions Using Wavelet Approach,” 2000, Proc. of the 14th Engineering Mechanics Conference (EM2000), Austin, Texas.

15. Moyo, P. and Brownjohn, J.M.W., “Detection of Anomalous Structural Behavior Using Wavelet Analysis,” 2002, Mechanical Systems and Signal Processing, Vol. 16(2-3), pp. 429-445.

16. Sun, Z., and Chang, C.C., “Structural Damage Assessment Based on Wavelet Packet Transform,” 2002, Journal of Structural Engineering, Vol. 128(10), pp. 1354-1361.

17. Hou et al., “Application Wavelet-Based Approach for Structural Damage Detection,” 2000, Journal of Engineering Mechanics, Vol. 126(7), pp. 677-683

18. Haroon, M., and Adams, D.E., “Active and Event-Driven Passive Mechanical Fault Identification in Ground Vehicle Suspension Systems,” 2005, Proc. of IMECE: ASME International Mechanical Engineering Congress and Exposition, Orlando, FL, Paper #: 80582.

19. Haroon, M., and Adams, D.E., “Nonlinear Fault Identification Methods for Ground Vehicle Suspension Systems,” 2006, IMAC-XXIV, St. Louis, MO, Paper #: 44.

20. Worden, K., Manson, G., and Allman, D., “Experimental Validation of Structural Health Monitoring Methodology I: Novelty Detection on a Laboratory Structure,” 2003, Journal of Sound and Vibration, Vol. 259, pp. 323-343.

21. Manson, G., Worden, K., and Allman, D., “Experimental Validation of Structural Health Monitoring Methodology II: Novelty Detection on an Aircraft Wing,” 2003, Journal of Sound and Vibration, Vol. 259, pp. 343-363.

22. Monaco, E., Calandra, G., and Lecce, L., “Experimental Activities on Damage Detection Using Magnetorestricitve Actuators and Statistical Analysis,” 2000, Smart Structures and Materials 2000: Smart Structures and Integrated Systems, Proc. of SPIE, Vol. 3985, pp. 186-196.

23. Natke, H.G., and Cempel, C., “Model-Aided Diagnosis Based on Symptoms,” 1997, Structural Damage Assessment Using Advanced Signal Processing Procedures, Proc. of DAMAS ’97, Univ. of Sheffield, UK, pp. 363-375.

24. Garcia, G., Osegueda, R. and Meza, D., “Comparison of the Damage Detection Results Utilizing an ARMA Model and a FRF Model to Extract Modal Parameters,” 1998, Smart Systems for Bridges, Structures, and Highways, Proc. of SPIE, Vol. 3325, pp. 244-252.

25. Garcia, G., and Osegueda, R., “Damage Detection Using ARMA Model Coefficients,” 1999, Smart Systems for Bridges, Structures, and Highways, Proc. of SPIE, Vol. 3671, pp. 289-296.

26. Sohn, H. and Farrar, C.R., “Statistical Process Control and Projection Techniques for Structural Health Monitoring,” 2000, European COST F3 Conference on System Identification and Structural Health Monitoring, Madrid, Spain, pp. 105-114.

27. Bodeux, J.B., and Golinval, J.C., “ARMAV Model Technique for System Identification and Damage Detection,” 2000, European COST F3 Conference on System Identification and Structural Health Monitoring, Madrid, Spain, pp. 303-312.

28. Heyns, P.S., “Structural Damage Assessment Using Response-Only Measurements,” 1997, Structural Damage Assessment Using Advanced Signal Processing Procedures, Proceeding of DAMAS ’97, Univ. of Sheffield, UK, pp. 213-223.

29. Tsyfansky, S.L. and Beresnevich, V.I., “Vibrodiagnosis of Fatigue Cracks in Geometrically Nonlinear Beams,” 1997, Structural Damage Assessment Using Advanced Signal Processing Procedures, Proceeding of DAMAS ’97, Univ. of Sheffield, UK, pp. 299-311.

30. Masri, S.F., Smyth, A.W., Chassiakos, A.G., Caughey, T.K., and Hunter, N.F., “Application of Neural Networks fort Detection of Changes in Nonlinear Systems,” 2000, Journal of Engineering Mechanics, July, pp. 666-676.

31. Feng, M., and Bahng, E., “Damage Assessment of Bridges with Jacketed RC Columns Using Vibration Test,” 1999, Smart Structures and Materials 1999: Smart Systems for Bridges, Structures, and Highways, Proc. of SPIE, Vol. 3671, pp. 316-327.

32. Worden, K. and Fieller, N.R.J., “Damage Detection Using Outlier Analysis,” 1999, Journal of Sound and Vibration, 229(3), pp.647-667.

33. Salawu, O.S., “Detection of Structural Damage through Changes in Frequency: A Review,” 1997, Engineering Structures, Vol. 19, No. 9, pp. 718-723.

34. Farrar, C.R., Doebling, S.W., Cornwell, P.J., and Straser, E.G., “Variability of Modal Parameters on the Alamosa Canyon Bridge,” 1997, Proc. 15th International Modal Analysis Conference, Orlando, FL, pp. 257-263.

35. Doebling, S.W., Farrar, C.R., and Goodman, E.S., “Effects of Measurements Statistics on the Detection of Damage in the Alamosa Canyon Bridge,” 1997, Proc. 15th International Modal Analysis Conference, Orlando, FL, pp. 919-929.

36. Cawley, P., and Adams, R.D., “Location of Defects in Structures from Measurements of Natural Frequencies,” 1979, Journal of Strain for Engineering Design, Vol. 14, No. 2, pp. 49-57.

37. Pandey, A.K., Biswas, M., and Samman, M.M., “Damage Detection from Changes in Curvature Mode Shapes,” 1991, Journal of Sound and Vibration, Vol. 145, No. 2, pp. 321-332.

38. Pandey, A.K. and Biswas, M., “Damage Detection in Structures Using Changes in Flexibility,” 1994, Journal of Sound and Vibration, Vol. 169, No.1, pp. 3-17.

39. Pandey, A.K. and Biswas, M., “Damage Diagnosis of Truss Structures by Estimation of Flexibility Change,” 1995, Modal Analysis – The International Journal of Analytical and Experimental Modal Analysis, Vol. 10, No. 2, pp. 104-117.

40. Lim, T.W., “Structural Damage Detection Using Modal Test Data,” 1991, AIAA Journal, Vol. 29, No. 12, pp. 2271-2274.

41. Lew, J.-S., “Using Transfer Function Parameter Changes for Damage Detection of Structures,” 1995 AIAA Journal, 33(11):2189-2193.

42. Banks, H. T., Inman, D. J., Leo, D. J., Want, Y., “An Experimentally Validated Damage Detection Theory in Smart Structures,” 1996, Journal of Sound and Vibration 191 (5), pp. 2615-2621.

43. Doebling, S. W., “Minimum-Rank Optimal Update of Elemental Stiffness Parameters for Structural Damage Identification,” 1996, AIAA Journal 34 (12), pp. 2615-2621.

44. Escobar, J. A., Sosa, J. J., Gomez, R., “Structural Damage Detection using the Transformation Matrix,” 2005, Computers and Structures 83, pp. 357-368.

45. Fritzen, C. P., Jennewein, D., Kiefer, T., “Damage Detection Based on Model Updating Methods,” 1998, Mechanical Systems and Signal Processing 12 (1), pp. 163-186.

46. Hajela, P. and Soeiro, F. J., “Structural Damage Detection Based on Static and Modal Analysis,” 1989, AIAA Journal 28 (6), pp. 1110-1115.

47. Hwang, H.Y., Kim C., “Damage detection using a few frequency response measurements,” 2004, Journal of Sound and Vibration 270, pp. 1-14.

48. Lew, J. S., “Using Transfer Function Parameter Changes for Damage Detection of Structures,” 1995, AIAA Journal 33 (11), pp. 2189-2193.

49. Kaouk, M., Zimmerman, D. C., “Structural Damage Assessment Using a Generalized Minimum Rank Perturbation Theory,” 1994, AIAA Journal 32 (4), pp. 836-842.

50. Samuel, P. D., Pines, D. J., “A Review of Vibration-based Techniques for Helicopter Transmission Diagnostics,” 2004, Journal of Sound and Vibration 282, pp. 475-508.

51. Sheinman, I., “Damage Detection and Updating of Stiffness and Mass Matrices using Mode Data,” 1996, Computers & Structures 59 (1), pp. 149-156.

52. Tsuei, Y. G., Yee, E. K. L., “A Method for Modifying Dynamic Properties of Undamped Mechanical Systems,” 1989, Dynamic System Measurement Control 111, pp. 403-408.

53. Zimmerman, D. C., Kaouk, M., “Model Correlation and System Health Monitoring using Frequency Domain Measurements,” 2005, Structural Health Monitoring 4 (3), pp. 213-215.

Table B.13 – References on wave propagation for damage identification.

Reference

Summary

Doebling et al., 1996, “Damage Identification and Health Monitoring of Structural and Mechanical Systems from Changes in Their Vibration Characteristics: A Literature Review”

Report: Includes a review of literature on damage identification using propagating elastic waves.

Sohn et al., 2001, “A Review of Structural Health Monitoring Literature: 1996-2001”

Report: Includes a review of literature on damage identification using propagating elastic waves.

Kessler, 2002, “Piezoelectric-Based In-Situ Damage Detection of Composite Materials for Structural Health Monitoring Systems”

Thesis: Damage identification using guided waves on an Al plate and composite cylinder. Literature review of guided waves.

Wilcox et al, 1999, “Mode Selection and Transduction for Structural Monitoring Using Lamb Waves”

Conference: Developed mode selection and transduction rules for monitoring structures using Lamb waves.

Bar-Cohen et al., 1998, “Composite Material Defects Characterization Using Leaky Lamb wave Dispersion Data”

Conference: Monitored the changes in dispersion characteristics of a leaky Lamb wave to characterize porosity in a composite plate.

Grisso, 2004, “Considerations of the Impedance Method, Wave Propagation, and Wireless Systems for Structural Health Monitoring”

Thesis: Studied temperature influences on wave propagation. Presented a method to quantify damage using the impedance method.

Lakshmanan and Pines, 1997, “Modeling Damage in Rotorcraft Flexbeams using Wave Mechanics”

Journal: Used and developed a wave propagation method to identify delaminations and transverse cracks in Gr/Ep composite rotorcraft.

Pines, 1997, “The Use of Wave Propagation Models for Structural Damage Identification”

Conference: Identified damage in beams using wave propagation by modeling damage as a local change in dispersion; local and global defects.

Prosser et al, 1995, “Advanced, Waveform Based Acoustic Emission Detection of Matrix Cracking in Composites”

Journal: Used acoustic emission to identify cracking of thin composite specimens; also outlined the difficulties associated with acoustic emission.

Wevers, 1997, “Listening to the Sound of Materials: Acoustic Emission for the Analysis of Material Behavior”

Journal: Outlined the advantages of acoustic emission techniques over other NDE methods for identifying damage in a loaded composite component.

Shah et al, 2000, “New Directions in Concrete Health Monitoring Technology”

Journal: Used stress waves (0-100 kHz) and found that changes in signal amplitude across a crack were sensitive to crack.

Adamou, and Craster, 2004, “Spectral Methods for Modeling Guided Waves in Elastic Media”

Journal: Spectral method for dispersion curve generation of inhomogeneous, curved, multilayered and materially damped structures.

Alleyne, and Cawley, 1992a, “The Interaction of Lamb Waves with Defects”

Journal: Numerical and experimental study of defect identification using Lamb waves and two-dimensional fast Fourier transforms.

Alleyne, and Cawley, 1992b, “Optimization of Lamb Wave Inspection Techniques”

Journal: Tests conducted on a butt-welded steel plate using A1 mode Lamb wave.

Beard, 2002, “Guided Wave Inspection of Embedded Cylindrical Structures”

Thesis: Detailed literature review and numerical development of guided wave inspection of curved plates and cylindrical structures.

Banerjee et al, 2003, “Lamb Wave Propagation and Scattering in Layered Composite Plates”

Conference: Lamb waves for crack identification in composite plates.

Bar Cohen, 2000, “Emerging NDE Technologies and Challenges at the Beginning of the 3rd Millennium - Part I”

Journal: Traditional NDE techniques (ultrasonics, radiography, shearography) and associated challenges are reviewed.

Mustafa et al., 1997, “Imaging of Disbond in Adhesive Joints with Lamb Waves”

Online Journal: Detect and image disbonds in the tear-strap by using angle wedge transducers to excite select Lamb modes.

Chahbaz, et al., 1996, “Corrosion Detection in Aircraft Structures using Guided Lamb Waves”

Online Journal: Demonstrated the use of Lamb waves to detect corrosion damage in an aluminum fuselage panel.

Fromme, 2001, “Defect Detection in Plates using Guided Waves”

Thesis: Studied and compared scatter patterns of the antisymmetric Lamb wave mode using both experimental and analytical results.

Giurgiutiu, 2003, “Lamb Wave Generation with Piezoelectric Wafer Active Sensors for Structural Health Monitoring”

Conference: Used piezoelectric sensors for detecting damage in an aluminum plate.

Lamb, 1917, “On Waves in An Elastic Plate”

Journal: The first work dealing with guided wave propagation in thin elastic specimens.

Lord-Rayleigh, 1889, “On the Free Vibrations of An Infinite Plate of Homogeneous Isotropic Matter”

Journal: The first work dealing with wave propagation in a semi-infinite solid.

Lowe, 1995, “Matrix Techniques for Modeling Ultrasonic Waves in Multilayered Media”

Journal: Literature review of work involving guided wave dispersion curve generation.

Pavlakovic et al, 1997, “Disperse: A General Purpose Program for Creating Dispersion Curves”

Conference: Outlines the software developed by researchers at Imperial College for generating guided wave dispersion curves and mode shapes.

Pavlakovic, 1998, “Leaky Guided Ultrasonic Waves in NDT”

Thesis: Provided design rules for generating Lamb waves; also carried out defect identification studies in plates and shells.

Pavlakovic, and Lowe, 1999, “A General Purpose Approach to Calculating the Longitudinal and Flexural Modes of Multi-layered, Embedded, Transversely Isotropic Cylinders”

Conference: Outlined dispersion curve (longitudinal and flexural modes) characterization in a composite cylinder.

Purekar, and Pines, 2002, “A Phased Sensor/Actuator Array for Detecting Damage in 2-d Structures”

Conference: Outlined phased arrays for damage identification in 2-d structures; testing was carried out on aluminum beam and plate specimens.

Purekar and Pines, 2005, Damage Detection in Plate Structures Using Lamb Waves with Directional Filtering Sensor Arrays”

Conference: Use of a directional filtering algorithm for defect localization in structures.

Raghavan and Cessnik, 2005, , “Piezoelectric-Actuator Excited-Wavefield Solutions for Guided-Wave Structural Health Monitoring”

Conference: Analytical development of arbitrary shaped piezoelectric actuator to excite Ao and So mode Lamb waves from 3-D elasticity.

Rose, 1999, “Ultrasonic Waves in Solid Media”

Book: A detailed outline of structural wave propagation with specific emphasis on free and forced guided waves for NDE applications.

Schmerr Jr., 1998, “Fundamentals of Ultrasonic Nondestructive Evaluation: A Modeling Approach”

Book: A mathematical approach to ultrasonic nondestructive evaluation using transfer functions including traditional ultrasonic testing methods.

Sohn et al, 2004, “Multi-Scale Structural Health Monitoring for Composite Structures”

Conference: Used Lamb waves to identify areas of delamination by implementing the ideas of time reversal acoustics.

Sundararaman, 2003, “Structural Diagnostics through Beamforming of Phased Arrays: Characterizing Damage in Steel and Composite Plates”

Thesis: Outlined a phased array directional filtering algorithm for damage localization in steel and woven composite structures.

Tucker, 2001, “Ultrasonic Waves in Wood-based Composite Panels”

Thesis: Includes a literature review of the use of ultrasonics in NDE. Demonstrated defect identification in wood analytically and experimentally.

Viktorov, I.A., 1967, “Rayleigh and Lamb Waves: Physical Theory and Applications”

Book: Includes models for the generation of Lamb and Rayleigh waves using ultrasonic transducers.

Wilcox, 1998, “Lamb Wave Inspection of Large Structures using Permanently Attached Transducers”

Thesis: Includes analytical and experimental development of piezoelectric transducers for defect identification of large structures using Lamb waves.

Worlton, 1961, “Experimental Confirmation of Lamb Waves at Megacycle Frequencies”

Journal: One of the first works to identify the usefulness of Lamb waves for NDE applications.

Rizzo, and di Scalea, 2005, “Ultrasonic Inspection of Multi-wire Steel Strands with the Aid of the Wavelet Transform”

Journal: Used discrete wavelet transforms to filter (denoise) data and compress data for feature extraction; applied to multi-wire steel strands.

Sundararaman et al, 2004a, “Incipient Damage Identification using Elastic Wave Propagation through a Friction Stir Welded Al-Li Interface for Cryogenic Tank Applications”

Conference: Guided wave experimental investigation using acoustic emission transducers and piezoelectric actuators.

Sundararaman et al, 2004b, “Structural Health Monitoring Studies of a Friction Stir Welded Al-Li Plate for Cryotank Application”

Conference: Presented wavelet and statistical analysis techniques for defect identification in a friction stir welded Al-Li plate.

Purekar, and Pines, 2001, “Interrogation of Beam and Plate Structures Using Phased Array Concepts”

Conference: Presented a phased array method using a sweep sine broadband signal to identify damage in beam and plate structures.

Purekar et al, 2004, “Directional Piezoelectric Phased Array Filters for Detecting Damage in Isotropic Plates”

Journal: A detailed numerical and experimental presentation of the phased array method for defect localization in an aluminum plate.

Giurgiutiu, and Bao, 2002, “Embedded Ultrasonic Structural Radar with Piezoelectric Wafer Active Sensors for the NDE of Thin-Wall Structures”

Conference: A detailed experimental presentation for defect identification using phased arrays consisting of piezoelectric wafers.

Yu, and Giurgiutiu, 2005, “Improvement of Damage Detection with the Embedded Ultrasonics Structural Radar for Structural Health Monitoring”

Conference: Presented new techniques for improving defect identification using unitized phased arrays.

Bardouillet, P., 1984, “Application of Electronic Focusing and Scanning Systems to Ultrasonic Testing”

Journal: One of the early works to use ultrasonic phased arrays for detecting defects in welds.

Ihn and Chang, 2004, “Detection and Monitoring of Hidden Fatigue Crack Growth Using a Built-in Piezoelectric Sensor/Actuator Network: I. Diagnostics”

Journal: Used spectrograms to process guided wave signals obtained from an array of piezoelectric transducers to detect and monitor fatigue crack growth.

MacLauchlan et al, 1998, “Phased Array EMATs for Flaw Sizing”

Conference: Used phased array EMATs to generate and direct high frequency shear horizontal (SH) waves for defect identification of weld samples.

McNab, and Campbell, 1987, “Ultrasonic Phased Arrays for Nondestructive Testing”

Journal: Conducted a feasibility study (cost vs sample rate vs instrumentation) for using ultrasonic phased arrays for NDE.

Sundararaman, and Adams, 2002, “Phased transducer arrays for Structural Diagnostics Through Beamforming”

Conference: Developed a spatio-temporal directional filtering methodology for defect localization in isotropic structures.

Sundararaman et al, 2005a, “Biologically Inspired Structural Diagnostics through Beamforming with Phased Transducer Arrays”

Journal: Presented an experimental study for directional filtering using antisymmetric (Ao) mode Lamb waves in steel and woven composites.

Sundararaman et al, 2005b, “Structural Damage Identification in Homogeneous and Heterogeneous Structures Using Beamforming”

Journal: Presented an experimental study for directional filtering using antisymmetric (Ao) mode Lamb waves in steel and woven composites.

Tua et al, 2004, “Detection of Cracks in Plates using Piezo-actuated Lamb Waves”

Journal: Used the Hilbert Huang transform to detect cracks in plates interrogated by piezo-actuated Lamb waves.

Li and Rose, 2001, “Implementing Guided Wave Mode Control by use of a Phased Transducer Array”

Journal: Use of guided waves for inspection of long pipes with a phased transducer array.

Lin, 2000, “Structural Health Monitoring using Geophysical Migration Technique with Built-in Piezoelectric Sensor/Actuator Arrays”

Thesis: Presented a NDE technique based on ultrasonic sensor arrays using the ideas of geophysical migration.

Lin and Yuan, 2001, “Diagnostic Lamb Waves in an Integrated Piezoelectric Sensor/Actuator Plate: Analytical and Experimental Studies”

Journal: Modeled guided waves in an infinite isotropic plate (incorporating Mindlin plate theory) using a pair of circular actuators.

Wang, 2004, “Elastic Wave Propagation in Composites and Least-Squares Damage Localization Technique”

Thesis: Used a least squares approach with iterative minimization for damage localization using distributed arrays.

Wang, and Yuan, 2005, “Damage Identification in a Composite Plate using Prestack Reverse-time Migration Technique”

Journal: A pre-stack migration technique was used to locate damage in composite structures.

Wilcox et al, 2001, “The Effect of Dispersion on Long-range Inspection using Ultrasonic Guided Waves”

Journal: Studied the effects of dispersion and mode sensitivity for defect identification in order to develop design guidelines for guided wave testing.

Wilcox et al, 2000, “Lamb and SH Wave Transducer Arrays for the Inspection of Large Areas of Thick Plates”

Conference: Presented a method of using antisymmetric Lamb and shear horizontal waves for defect identification over large areas of thick plates.

Wilcox, 2003, “A Rapid Signal Processing Technique to Remove the Effect of Dispersion from Guided Wave Signals”

Journal: Used the symmetric (So) mode Lamb wave and attempted to compensate for signal dilation due to dispersion.

Wilcox, 2003, “Omni-Direct ional Guided Wave Transducer Arrays for the Rapid Inspection of Large Areas of Plate Structures”

Journal: Incorporated a dispersion compensation technique and developed a guided wave compact phased transducer technique; holes and notches.

Wilcox et al, 2005, “Omnidirectional Guided Wave Inspection of Large Metallic Plate Structures Using an EMAT Array”

Journal: Extended the work to using an EMAT array for defect identification in large metallic structures.

Rajagopalan et al, 2006, “A Phase Reconstruction Algorithm for Lamb Wave Based Structural Health Monitoring of Anisotropic Multilayered Composite Plates”

Journal: Extended the work by Wilcox (2003b) to locate damage (medium sized through hole) using a single actuator and multiple sensors.

Chen et al, 2003, “Acoustic Emission in Monitoring Quality of Weld in Friction Stir Welding”

Conference: Used acoustic emission techniques for monitoring the quality of welds obtained through the friction stir welding process.

Lamarre and Moles, 2000, “Ultrasound Phased Array Inspection Technology for the Evaluation of Friction Stir Welds”

Conference: Identified defects in a friction stir weld using ultrasonic phased arrays.

Raghavan and Cessnik, 2007, “Guided-wave Based Structural Health Monitoring: A Review”

Journal: A detailed review paper on work involving the use of guided waves for nondestructive testing.

Kundu et al, 2001, “Importance of the Near Lamb Mode Imaging of Multilayered Composite Plates”

Journal: Showed that it was possible to detect internal defects in layers of mirror symmetry in the upper and lower halves of a plate.

Crawley and de Luis, 1987, “Use of Piezoelectric Actuators as Elements of Intelligent Structures”

Journal: Proposed a quasi-static induced strain actuation piezo actuator model that can be more effectively modeled to operate in a pinching mode.

Yang, J., and Chang, F., 2006, “Detection of Bolt Loosening in C-C Composite Thermal Protection Panels: I. Diagnostic Principle”

Journal: Used elastic waves to determine the preload in bolt connections of thermal protection panels.

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2. Alleyne, D.N., and Cawley, P., “The Interaction of Lamb Waves with Defects,” 1992a, IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control, Vol. 39, No. 3, pp. 381-397.

3. Alleyne, D.N., and Cawley, P., “Optimization of Lamb Wave Inspection Techniques,” 1992b, NDT and E International, Vol. 25, pp. 11–22.

4. Banerjee, S., Banerji, P., Berning, F., and Eberle, K., “Lamb Wave Propagation and Scattering in Layered Composite Plates,” 2003, Proc. of SPIE, Smart NDE for Health Monitoring of Structural and Biological Systems, 8th Annual International Symposium on NDE for Health Monitoring & Diagnostics, San Diego, California, Paper No. 5047-02.

5. Bar-Cohen, Y., “Emerging NDE Technologies and Challenges at the Beginning of the 3rd Millennium - Part I,” 2000, Materials Evaluation, Vol. 58, No. 1, pp. 17-30.

6. Bar-Cohen, Y., Mal, A., and Chang, Z., “Composite Material defects Characterization Using Leaky Lamb wave Dispersion Data,” 1998, Proc. of SPIE, NDE Techniques for Aging Infrastructure & Manufacturing, Conference NDE of Materials and Composites II, San Antonio, Texas, Vol. 3396, Paper No. 3396-25.

7. Bardouillet, P., “Application of Electronic Focusing and Scanning Systems to Ultrasonic Testing,” 1984, NDT International, Vol. 17, No. 2, pp. 81- 85.

8. Beard, M.D., “Guided Wave Inspection of Embedded Cylindrical Structures,” 2002, PhD Dissertation, University of London.

9. Chahbaz, A., Mustafa, V., and Hay, D.R., “Corrosion Detection in Aircraft Structures using Guided Lamb Waves,” 1996, http://www.ndt.net/article/tektrend/tektrend.htm, Vol. 1, No.11, Online Journal.

10. Chen, C., Kovacevic, R., and Jandgric, D., “Acoustic Emission in Monitoring Quality of Weld in Friction Stir Welding,” 2003, Proc. of the Fourth International Symposium on Friction Stir Welding, Park City, Utah, USA, 14-16 May 2003.

11. Crawley E.F. and de Luis J., “Use of Piezoelectric Actuators as Elements of Intelligent Structures,” 1987, AIAA Journal, Vol. 25, No. 10, pp.1373-1385, Oct 1987

12. Doebling, S.W., Farrar, C.R., Prime, M.B., and Shevitz, D.W., “Damage Identification and Health Monitoring of Structural and Mechanical Systems from Changes in Their Vibration Characteristics: A Literature Review,” 1996, Los Alamos National Laboratory Report LA-13070-MS.

13. Fromme, P., “Defect Detection in Plates Using Guided Waves,” 2001, Doctoral Dissertation, Swiss Federal Institute of Technology, Zurich. Eth: 14397.

14. Giurgiutiu, V. and Bao, J., “Embedded-Ultrasonics Structural Radar for In-Situ Structural Health Monitoring of Thin-Wall Structures,” 2004, Structural Health Monitoring – an International Journal, Vol. 3, Number 2, June 2004, pp. 121-140.

15. Giurgiutiu, V., “Lamb Wave Generation with Piezoelectric Wafer Active Sensors for Structural Health Monitoring,” 2003, Proc. of the SPIE 5056, pp. 111–122.

16. Giurgiutiu, V., and Bao, J., “Embedded Ultrasonic Structural Radar with Piezoelectric Wafer Active Sensors for the NDE of Thin-Wall Structures,” 2002, Proc. of ASME International Mechanical Engineering Congress, Nov. 17-22, New Orleans, LA, CDROM, paper # IMECE 2002-39017, p. 1-8.

17. Grisso, B.L., “Considerations of the Impedance Method, Wave Propagation, and Wireless Systems for Structural Health Monitoring,” 2004, MS Thesis, Virginia Polytechnic Institute and State University.

18. Ihn, J.-B., and Chang, F.-K., “Detection and Monitoring of Hidden Fatigue Crack Growth Using a Built-in Piezoelectric Sensor/Actuator Network: I. Diagnostics,” 2004, Smart Materials and Structures, Vol. 13, pp. 609-620.

19. Kessler, S. S., “Piezoelectric-Based In-Situ Damage Detection of Composite Materials for Structural Health Monitoring Systems,” 2002, Ph.D. Dissertation, Department of Aeronautics and Astronautics, Massachusetts Institute of Technology.

20. Kundu, T., Potel, C., and de Belleval, J.F., “Importance of the Near Lamb Mode Imaging of Multilayered Composite Plates,” 2001, Ultrasonics, vol. 39, pp. 283-290.

21. Lakshmanan, K.A., and Pines, D.J., “Modeling Damage in Rotorcraft Flexbeams using Wave Mechanics,” 1997, Smart Materials and Structures, Vol.6, pp. 383-392.

22. Lamarre, A., and Moles, M., “Ultrasound Phased Array Inspection Technology for the Evaluation of Friction Stir Welds,” 2000, Annual Conference of the British Institute of Non-Destructive Testing Proceedings, pp. 56-61.

23. Lamb. H., “On Waves in an Elastic Plate,” 1917, Proc. of the Royal Society, London, Vol. 93, pp.114–128.

24. Li, J., and Rose, J. L., “Implementing Guided Wave Mode Control by use of a Phased Transducer Array,” 2001, IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control, Vol. 48, No. 3, pp. 761-768.

25. Lin X. and Yuan F. G., “Diagnostic Lamb Waves in an Integrated Piezoelectric Sensor/Actuator Plate: Analytical and Experimental Studies,” 2001, Smart Materials and Structures, Vol. 10, pp. 907–913.

26. Lin, X., “Structural Health Monitoring using Geophysical Migration Technique with Built-in Piezoelectric Sensor/Actuator Arrays,” 2000, PhD Dissertation, North Carolina State University.

27. Liu, W., “Multiple Wave Scattering and Calculated Effective Stiffness and Wave Properties in Unidirectional Fiber-Reinforced Composites,” 1997, PhD. Dissertation, Engineering Mechanics, Virginia Polytechnic.

28. Lord-Rayleigh, “On the Free Vibrations of an Infinite Plate of Homogeneous Isotropic Matter,” 1889, Proc. of the London Mathematical Society, Vol. 20, pp.225–234.

29. Lowe, M.J.S., “Matrix Techniques for Modeling Ultrasonic Waves in Multilayered Media,” 1995, IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control, Vol. 42, pp.525–542.

30. Lui, G., and Qu, J., “Guided Circumferential Waves in a Circular Annulus,” 1998, Journal of Applied Mechanics, vol.65, pp.424-430.

31. MacLauchlan, D.T., Schlader, D.M., Clark, S.P., and Latham, W.M., “Phased Array EMATs for Flaw Sizing,” 1998, EPRI Phased Array Inspection Seminar 99-01, Portland, Maine.

32. McNab, A., and Campbell, M.J., “Ultrasonic Phased Arrays for Nondestructive Testing,” 1987, NDT International, Vol. 6, pp. 333-337.

33. Mustafa, V., Chahbaz, A., Hay, D.R., Brassard, M., and Dubois, S., “Imaging of Disbond in Adhesive Joints with Lamb Waves,” 1997, http://www.ndt.net/article/tektren2 /tektren2.htm, Vol. 2, No. 3, Online Journal.

34. Pavlakovic, B., “Leaky Guided Ultrasonic Waves in NDT,” 1998, Doctoral Dissertation, Imperial College, University of London.

35. Pavlakovic, B., and Lowe, M.J.S., “A General Purpose Approach to Calculating the Longitudinal and Flexural Modes of Multi-Layered, Embedded, Transversely Isotropic Cylinders,” 1999, Review of Progress in Quantitative Nondestructive Evaluation, D. O. Thompson and D. E. Chimenti, editors, Vol. 18A, pp. 239–246, New York: Plenum Press.

36. Pavlakovic, B., Lowe, M.J.S., Alleyne, D., and Cawley, P., “Disperse: A General Purpose Program for Creating Dispersion Curves,” 1997, Review of Progress in Quantitative Nondestructive Evaluation, D. O. Thompson and D. E. Chimenti, editors, Vol. 16A, pp. 185–192, New York: Plenum Press.

37. Pines, D.J., “The Use of Wave Propagation Models for Structural Damage Identification”, 1997, Structural Health Monitoring: Current Status and Perspectives, International Workshop on Structural Health Monitoring, Stanford CA, 1997, Chang, F.-K., ed., Boca Raton, Florida: CRC Press Inc., pp.664-677.

38. Prosser, W.H., Jackson, K.E., Kellas, S., Smith, B.T., McKeon, J., and Friedman, A., “Advanced, Waveform Based Acoustic Emission Detection of Matrix Cracking in Composites,” 1995, Materials Evaluation, Vol. 53, No. 9, pp. 1052-1058.

39. Purekar, A.S., and Pines, D.J., Damage Detection in Plate Structures Using Lamb Waves with Directional Filtering Sensor Arrays,” 2005, Proc. of the Fifth International Workshop on Structural Health Monitoring, Stanford, CA, pp. 1025-1032.

40. Purekar, A.S., and Pines D.J., “A Phased Sensor/Actuator Array for Detecting Damage in 2-D Structures,” 2002, AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conf. (No 2002-1547), p. 1-9.

41. Purekar, A.S., and Pines, D.J., “Interrogation of Beam and Plate Structures Using Phased Array Concepts,” 2001, Proc. of the 12th International Conference on Adaptive Structures and Technologies (ICAST), University of Maryland, MD, pp. 275-288.

42. Purekar, A.S., Pines, D.J., Sundararaman, S., and Adams, D.E., “Directional Piezoelectric Phased Array Filters for Detecting Damage in Isotropic Plates,” 2004, Smart Materials and Structures, Vol. 13, pp. 838-850.

43. Raghavan, A., and Cesnik, C.E.S., “Piezoelectric-Actuator Excited-Wavefield Solutions for Guided-Wave Structural Health Monitoring,” 2005, Proc. of the SPIE 5765, p. 1-11.

44. Rajagopalan, J., Balasubramanian, K., and Krishnamurthy, C.V., “A Phase Reconstruction Algorithm for Lamb Wave Based Structural Health Monitoring of Anisotropic Multilayered Composite Plates,” 2006, Journal of the Acoustical Society of America, Vol. 119, No. 2, pp. 872-878.

45. Rizzo, P., and di Scalea, F.L., “Ultrasonic Inspection of Multi-wire Steel Strands with the Aid of the Wavelet Transform,” 2005, Smart Materials and Structures, Vol. 14, pp. 685-695.

46. Rose, J.L., “Ultrasonic Waves in Solid Media,” 1999, London: Cambridge University Press.

47. Saravanos, D.A., and Heyliger, P.R., “Coupled Layerwise Analysis of Composite Beams with Embedded Piezoelectric Sensors and Actuators,” 1995, Journal of Intelligent Material Systems and Structures, Vol.6, pp. 350-363.

48. Schmerr Jr., L.W., “Fundamentals of Ultrasonic Nondestructive Evaluation: A Modeling Approach,” 1999, New York: Plenum Press.

49. Shah, S. P., Popovics, J. S., Subramaniam, K. V., and Aldea, C., “New Directions in Concrete Health Monitoring Technology,” 2000, Journal of Engineering Mechanics, Vol. 126, No. 7, pp. 754-760.

50. Sohn, H., Farrar, C.R., Hemez, F.M., Shunk, D.D., Stinemates, D.W., and Nadler, B.R., 2001, “A Review of Structural Health Monitoring Literature: 1996-2001,” Los Alamos National Laboratory Report LA-13976-MS.

51. Sohn, H., Wait, J.R., Park, G., and Farrar, C.R., “Multi-Scale Structural Health Monitoring for Composite Structures,” 2004, Proc. of the Second European Workshop on Structural Health Monitoring, July 7-9, Munich, Germany, pp. 721-729.

52. Sundararaman, S., “Structural Diagnostics through Beamforming of Phased Arrays: Characterizing Damage in Steel and Composite Plates,” 2003, MS Thesis, Purdue University.

53. Sundararaman, S., Adams, D.E., and Jata, K.V., “Structural Health Monitoring Studies of a Friction Stir Welded Al-Li Plate for Cryotank Application,” 2004b, Materials Damage Prognosis, Edited by TMS (The Minerals, Metals and Materials Society).

54. Sundararaman, S., Adams, D.E., and Rigas, E., “Biologically Inspired Structural Diagnostics through Beamforming with Phased Transducer Arrays,” 2005a, International Journal of Engineering Science, May 2005, pp. 756-778.

55. Sundararaman, S., Adams, D.E., and Rigas, E.J., “Structural Damage Identification in Homogeneous and Heterogeneous Structures Using Beamforming,” 2005b, Structural Health Monitoring-an International Journal, pp. 171-190.

56. Sundararaman, S., and Adams, D.E., “Phased Transducer Arrays for Structural Diagnostics Through Beamforming,” 2002, Proc. of the American Society for Composites (ASC) 17th Technical Conference, W. Lafayette, IN, C.T. Sun and H. Kim eds., CD-ROM, Paper 177.

57. Sundararaman, S., Haroon, M., Adams, D.E., and Jata, K.V., “Incipient Damage Identification Using Elastic Wave Propagation through a Friction Stir Welded Al-Li Interface for Cryogenic Tank Applications,” 2004a, Proc. of the Second European Workshop of Structural Health Monitoring, Munich, Germany, DESTech Publications Inc., PA, USA, pp. 525-532.

58. Tua, P.S., Quek, S.T., and Wang, Q., “Detection of Cracks in Plates using Piezo-actuated Lamb Waves,” 2004, Smart Materials and Structures, Vol. 13, pp. 643-660.

59. Tucker, B.J., “Ultrasonic Waves in Wood-based Composite Panels,” 2001, PhD Dissertation, Department of Civil and Environmental Engineering, Washington State University.

60. Viktorov, I.A., “Rayleigh and Lamb Waves: Physical Theory and Applications,” 1967, New York: Plenum Press.

61. Wang, L., “Elastic Wave Propagation in Composites and Least-Squares Damage Localization Technique,” 2004, MS Thesis, North Carolina State University, Rayleigh.

62. Wang, L., and Yuan, F.G., “Damage Identification in a Composite Plate using Prestack Reverse-time Migration Technique,” 2005, Structural Health Monitoring – an International Journal, Vol. 4, No. 3, pp. 195-217.

63. Wevers, M., “Listening to the Sound of Materials: Acoustic Emission for the Analysis of Material Behavior,” 1997, NDT&E International, Vol. 30, No. 2, pp. 99-106.

64. Wilcox, P., Lowe, M., and Cawley, P., “Omnidirectional Guided Wave Inspection of Large Metallic Plate Structures Using an EMAT Array,” 2005, IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control, Vol. 52, No. 4, pp. 653-665.

65. Wilcox, P., Lowe, M., Cawley, P., “Lamb and SH Wave Transducer Arrays for the Inspection of Large Areas of Thick Plates,” 2000, Review of Progress in Quantitative Nondestructive Evaluation, ed. D.O. Thomson and D.E. Chimenti, CP509, Vol. 18A, pp. 1049-1056.

66. Wilcox, P.D., “Lamb Wave Inspection of Large Structures using Permanently Attached Transducers,” 1998, PhD Dissertation, Imperial College of Science Technology and Medicine, University of London.

67. Wilcox, P.D., “A Rapid Signal Processing Technique to Remove the Effect of Dispersion from Guided Wave Signals,” 2003, IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control, Vol. 50, No. 4, pp. 419-427.

68. Wilcox, P.D., “Omni-Direct ional Guided Wave Transducer Arrays for the Rapid Inspection of Large Areas of Plate Structures,” 2003, IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control, Vol. 50, No. 4, pp. 699-709.

69. Wilcox, P.D., Dalton, R.P., Lowe, M.J.S., and Cawley, P., “Mode Selection and Transduction for Structural Monitoring Using Lamb Waves,” 1999, Structural Health Monitoring 2000, 2nd International Workshop on Structural Health Monitoring, Stanford, CA, Chang, F.-K., ed., Boca Raton, FL: CRC Press Inc., pp. 703-712.

70. Wilcox, P.D., Lowe, M., and Cawley, P., “The Effect of Dispersion on Long-range Inspection using Ultrasonic Guided Waves,” 2001, NDT&E International, Vol. 34, pp. 1-9.

71. Worlton, D.C., “Experimental Confirmation of Lamb Waves at Megacycle Frequencies,” 1961, Journal of Applied Physics, Vol. 32, pp. 967-971.

72. Yu, L., and Giurgiutiu, V., “Improvement of Damage Detection with the Embedded Ultrasonics Structural Radar for Structural Health Monitoring,” 2005, Proc. of the Fifth International Workshop on Structural Health Monitoring, ed. Fu-kuo Chang, pp. 1081-1090.

73. Yang, J., and Chang, F., “Detection of Bolt Loosening in C-C Composite Thermal Protection Panels: I. Diagnostic principle,” 2006, Smart Materials and Structures 15, pp. 581-590.

Table B.14 – References on temporal data analysis.

Reference

Summary

Samuel and Pines, 2005, “A Review of Vibration-Based Techniques for Helicopter Transmission Diagnostics”

Journal: A detailed review paper on statistical techniques in conjunction with signal processing for helicopter transmission diagnostics.

Staszewski and Worden, 2004, “Signal Processing for Damage Detection”

Book Chapter: Includes a summary of data analysis methods for damage identification with illustrations of data compression and denoising.

Box et al, 1994, “Time Series Analysis: Forecasting and Control”

Book: Detailed account of time series analysis methods including different auto-regressive and moving average models.

Castillo et al, 2005, “Extreme Value and Related Models with Applications in Engineering and Science”

Book: Implementation and mathematical background for extreme value and reliability models.

Montgomery, 2001, “Design and Analysis of Experiments”

Book: Illustrates methods of combining and analyzing data using experimental design and hypothesis testing.

McLachlan, 1992, “Discriminant Analysis and Statistical Pattern Recognition”

Book: Seminal work in using temporal/transformed temporal data for feature extraction and discrimination using pattern recognition.

Webb, 2002, “Statistical Pattern Recognition”

Book: Includes basic and advanced statistical tools used for feature extraction and data/feature discrimination using pattern recognition.

Sohn et al, 2000, “Structural Health Monitoring using Statistical Process Control”

Conference: Experimental investigation of statistical process control to identify damage during a vibration experiment.

Todd and Nichols, 2002, “Structural Damage Assessment Using Chaotic Dynamic Interrogation”

Conference: Used a single factor analysis-of-variance (ANOVA) with Bonferroni confidence interval generation to as a damage sensitive feature.

Monaco et al, 2000, “Experimental and Numerical Activities on Damage Detection Using Magnetostrictive Actuators and Statistical Analysis”

Journal: Used a t-test to determine the effectiveness of damage indices obtained from changes in the frequency response functions.

Worden et al, 2003, “Extreme Value Statistics for Damage Detection in Mechanical Structures”

Report: Detailed report on unsupervised learning methods based on extreme value statistical analysis using statistical process control.

George et al, 2000, “Identifying Damage Sensitive Features using Nonlinear Time Series and Bispectral Analysis”

Conference: Multivariate analysis method that compares groups of data by a weighted linear combination known as the canonical variate analysis.

Kantz and Schreiber, 1997, “Nonlinear Time Series Analysis”

Book: Detailed review on nonlinear time series analysis methods.

Yu and Giurgiutiu, 2005, “Advanced Signal Processing for Enhanced Damage Detection with Piezoelectric Wafer Active Sensors”

Journal: Detailed literature review of recent works using temporal and frequency domain methods.

1. Box, G., Jenkins, G.M., and Reinsel, G., “Time Series Analysis: Forecasting and Control,” 1994, Third Edition, Prentice-Hall, New Jersey.

2. Castillo, E., Hadi, A.S., Balakrishnan, N., Sarabia, J.M., “Extreme Value and Related Models with Applications in Engineering and Science,” 2005, John Wiley and Sons Inc., New Jersey.

3. George, D., Hunter, N., Farrar, C.R., Deen, R., “Identifying Damage Sensitive Features using Nonlinear Time Series and Bispectral Analysis,” 2000, Proc. of the 18th International Modal Analysis Conference, San Antonio, Texas, p. 1-7.

4. Kantz, H., Schreiber, T., “Nonlinear Time Series Analysis,” 1997, Cambridge Nonlinear Science Series 7, Cambridge University Press, Cambridge, UK.

5. McLachlan, G.J., “Discriminant Analysis and Statistical Pattern Recognition,” 1992, John Wiley and Sons, New York.

6. Monaco, E., Franco, F., and Lecce, L., “Experimental and Numerical Activities on Damage Detection Using Magnetostrictive Actuators and Statistical Analysis,” 2000, Journal of Intelligent Materials and Structures, Vol. 11, pp. 567-578.

7. Montgomery, D.C., “Design and Analysis of Experiments,” 2001, Fifth Edition, John Wiley and Sons, New York.

8. Samuel, P.D., and Pines, D.J., “A Review of Vibration-Based Techniques for Helicopter Transmission Diagnostics,” 2005, Journal of Sound and Vibration, Vol. 282, pp. 475-508.

9. Sohn, H., Czarnecki, J.A., and Farrar, C.R., “Structural Health Monitoring Using Statistical Process Control,” 2000, Journal of Structural Engineering, Nov. 2000, pp. 1356-1363.

10. Staszewski W. and Worden K., “Signal Processing for Damage Detection,” 2004, Health Monitoring of Aerospace Structures, eds. Staszewski W., Boller C. and Tomlinson G., John Wiley & Sons, UK, pp. 163-206.

11. Todd, M.D., and Nichols, J.M., “Structural Damage Assessment Using Chaotic Dynamic Interrogation,” 2002, Proc. of 2002 ASME International Mechanical Engineering Conference and Exposition, v. 71, pp. 613-620.

12. Webb A., “Statistical Pattern Recognition,” 2002, Second Edition, John Wiley and Sons, West Sussex, UK.

13. Worden, K., Allen, D.W., Sohn, H., Stinemates, D.W., and Farrar, C.R., “Extreme Value Statistics for Damage Detection in Mechanical Structures,” 2003, Los Alamos National Laboratory Report LA-13903-MS.

14. Yu, L., and Giurgiutiu, V., “Advanced Signal Processing for Enhanced Damage Detection with Piezoelectric Wafer Active Sensors,” 2005, Smart Systems and Structures, Vol. 1, No.2, pp. 185-215.

Table B.15 – References on time-frequency data analysis.

Reference

Summary

Staszewski, W.J., 1998, “Wavelet Based Compression and Feature Selection for Vibration Analysis”

Journal: Used wavelet analysis to extract features from vibration time series to detect damage.

Prosser et al, 1999, “Time-Frequency Analysis of the Dispersion of Lamb Modes”

Journal: Lamb mode signals were processed using a pseudo Wigner Ville distribution for determining material properties (i.e., dispersion).

Cao, X., 2002, “Adaptability and Comparison of the Wavelet-based with Traditional Equivalent Linearization Method and Potential Application for Damage Detection.”

Thesis: Presented background for time-frequency analysis and compared a wavelet based equivalent linearization method with traditional method.

Yuan et al, 2004, “A New Damage Signature for Composite Structural Health Monitoring.”

Journal: Introduced a damage signature based on wavelet analysis to determine the presence and extent of damage.

Peng et al, 2005, “A Comparison Study of Improved Hilbert-Huang Transform and Wavelet Transform: Application to Fault Diagnosis for Roller Bearing”

Journal: Compared the results obtained by processing data using the Hilbert Huang transform (HHT) and wavelet analysis.

Shinde, 2004, “A Wavelet Packet Based Sifting Process and Its Application in Structural Health Monitoring”

Thesis: Extended the HHT by using wavelet packet principles; also included details and background about obtaining the HHT and wavelet transform.

Cohen, 1995, “Time-Frequency Analysis”

Book: Outline and mathematical background for time-frequency methods used for signal analysis.

Auger et al, 1996, “Time Frequency Toolbox – For Use with MATLAB: Tutorial”

Online Report: Review article and tutorial in the use of time, frequency and time-frequency analysis (including wavelet analysis) with MATLAB(.

Huang et al, 1998, “The Empirical Mode Decomposition Method and the Hilbert Spectrum for Non-linear and Non-stationary Time Series Analysis”

Journal: Detailed literature review of time frequency analysis and extends the Hilbert transform by implementing empirical mode decomposition.

Daubechies, I., 1992, “Ten Lectures in Wavelets”

Daubechies, I., 1990, “The Wavelet Transform, Time-Frequency Localization and Signal Analysis”

Journal & Book: Seminal works on wavelet analysis; used quadrature mirror filters associated with the scaling function and the mother wavelet function.

Donoho, D.L., 1995, “De-noising by Soft-Thresholding”

Journal: Presented a soft thresholding method for denoising data using the wavelet transform.

Jensen and la Cour-Harbo, 2001, “Ripples in Mathematics: The Discrete Wavelet Transform”

Book: Review, background and implementation of time-frequency analysis (wavelet transforms).

Mallat, 1999, “A Wavelet Tour of Signal Processing”

Book: Review, background and implementation of time-frequency analysis (wavelet transforms).

1. Auger, F., Flandrin, P., Goncalves, P., and Lemoine, O., “Time Frequency Toolbox – For Use with MATLAB: Tutorial,” 1996, Web: Matlab File Exchange.

2. Cao, X., “Adaptability and Comparison of the Wavelet-based with Traditional Equivalent Linearization Method and Potential Application for Damage Detection,” 2002, MS Thesis (Advisor: Mohammad N. Noori), North Carolina State University.

3. Cohen, L., “Time-Frequency Analysis,” Prentice Hall, Englewood Cliffs, NJ, 1995.

4. Daubechies, I., “Ten Lectures in Wavelets,” 1992, CBMS-NSF Regional Conference Series in Mathematics, Society for Industrial and Applied Math (SIAM), Philadelphia, PA.

5. Daubechies, I., “The Wavelet Transform, Time-Frequency Localization and Signal Analysis,” 1990, IEEE Transactions on Information Theory, Vol. 36, No. 5, pp. 961-1005.

6. Donoho, D.L., “De-noising by Soft-Thresholding,” 1995, IEEE Transactions on Information Theory, Vol. 41, No.3, pp. 613-627.

7. Huang, N.E., Shen, Z., Long, S.R., Wu, M.C., Shih, H.H., Zheng, Q., Yen, N.-C., Tung, C.C., Liu, H.H., “The Empirical Mode Decomposition Method and the Hilbert Spectrum for Non-linear and Non-stationary Time Series Analysis”, 1998, Proc. of the Royal Society London, Vol. 454, pp. 903-995.

8. Ihn, J.-B., and Chang, F.-K., “Detection and Monitoring of Hidden Fatigue Crack Growth Using a Built-in Piezoelectric Sensor/Actuator Network: I. Diagnostics,” 2004, Smart Materials and Structures, Vol. 13, pp. 609-620.

9. Jensen, A., la Cour-Harbo, A., “Ripples in Mathematics: The Discrete Wavelet Transform,” 2001, Springer International, New Delhi.

10. Mallat, S., “A Wavelet Tour of Signal Processing,” 1999, Second Edition, Academic Press.

11. Peng, Z.K., Tse, P.W., Chu, F.L., “A Comparison Study of Improved Hilbert-Huang Transform and Wavelet Transform: Application to Fault Diagnosis for Roller Bearing,” 2005, Mechanical Systems and Signal Processing, Vol. 19, pp. 974-988.

12. Prosser W.H., Seale M.D. and Smith B.T., “Time-Frequency Analysis of the Dispersion of Lamb Modes,” 1999, Journal of the Acoustical Society of America, Vol. 105, No. 5, pp. 2669-2676.

13. Raghavan, A., and Cesnik, C.E.S., “Piezoelectric-Actuator Excited-Wavefield Solutions for Guided-Wave Structural Health Monitoring,” 2005, Proc. of the SPIE 5765, p. 1-11.

14. Rizzo, P., and di Scalea, F.L., “Ultrasonic Inspection of Multi-wire Steel Strands with the Aid of the Wavelet Transform,” 2005, Smart Materials and Structures, Vol. 14, pp. 685-695.

15. Shinde, A.D., “A Wavelet Packet Based Sifting Process and Its Application in Structural Health Monitoring,” 2004, MS Thesis, Worcester Polytechnic Institute.

16. Staszewski, W.J., “Wavelet Based Compression and Feature Selection for Vibration Analysis,” 1998, Journal of Sound and Vibration, v. 211(5), p. 735-760.

17. Yuan, S., Wang, L., and Wang, X., “A New Damage Signature for Composite Structural Health Monitoring,” 2004, Proc. of the 2nd European Workshop on Structural Health Monitoring, Munich, Germany, July 7-9, 2004, p. 1-8.

18. Hou, Z., Noori S. and Amand, St. R., “A Wavelet-Based Approach for Structural Damage Detection”, 2000, ASCE Journal of Engineering Mechanics, 126, pp. 667-683.

Table B.16 – References on triangulation for damage location.

Reference

Summary

White et al, 2005, “Modeling and Material Damage Identification of a Sandwich Plate Using MDOF Modal Parameter Estimation and the Method of Virtual Forces”

Conference: Developed a distributed sensor array technique for detecting and locating damage.

Sundararaman, 2003, “Structural Diagnostics through Beamforming of Phased Arrays: Characterizing Damage in Steel and Composite Plates”

Thesis: Outlined a phased array directional filtering algorithm for damage localization in steel and woven composite structures.

1. Sundararaman, S., “Struct

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