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Sensor-Based Structural Health Monitoring and Control Group
01/27/2011 NASA Grant URC NCC NNX08BA44A 1
Research Team Members:Prof Helen Boussalis (CSULA)
Prof Sami F Masri (USC)Jessica Alvarenga (CSULA)Armen Derkevorkian (USC)
Outline
• Background
• Objective
• Theory
• Modeling of 2D Beam and 3D Wing
• Future Work
• Timeline
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Background
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Helios Wing
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Ultra-lightweight, unmanned, solar-powered flying wing aircraft
Long wingspan and high flexibility
Experienced large deformations during flight
Wing tip deflections could reach 40ft
Midair breakup at 3000ft altitude
Helios Wing In-flight breakup
In-flight Deformation Monitoring
• Need to develop method to monitor deformations of highly flexible
structures during flight
• As wingtip deflections approach limitations, emergency maneuvers
may be initiated
Ground-based pilots
Flight control system
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Existing Methods of Inflight Monitoring
Electro-optical flight deflection detection
Requires onboard cameras and wing mounted targets
Heavy and requires lots of equipment
Strain gages
Requires a high number of sensors in order to observe higher deflection modes of
these flexible structures
The more strain sensing stations are used, the heavier the load on the wing
Too heavy and impractical for most weight conscious aircraft
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Newly Proposed Method
• Fiber Optic Sensors with Fiber-Bragg Gratings
Immune to E&M/RF interference and radiation
Light weight and small (thin fibers)
Ability to multiplex 100’s of sensors onto a single fiber
Potential for embedment into structures
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Laser Light
Reflected Light(IR)
ReflectorLoss Light
Application
• Validation of fiber optic sensor measurements and real-time wing shape sensing on NASA’s Ikhana Vehicle
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In-Flight Shape Detection Algorithms
• Deflection Shape Algorithms based on strain data
• Validation with classical beam theory, and finite element analysis (FEA)
• Promising results, with much room for improvement
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Structural Health Monitoring (SHM)
• Objectives System Identification Damage Detection
• Broad applications in civil, mechanical, and aerospace industries
• Special importance after natural disasters (earthquakes), during key flying missions (Helios)
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Structural Health Monitoring (SHM)
• Destructive Evaluation (DE) Physical Decomposition to locate damage
• Non-Destructive Evaluation (NDE) Based on vibration signatures (Acc, Vel, Dsp) Enables real-time monitoring Involves sophisticated algorithms
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Non-Destructive Evaluation (NDE)
• Parametric Techniques Involves major assumptions about the model Prior knowledge about the parameters
Advantages Well-Developed techniques, such as least-square, Kalman
Filter, Eigen Value Realization Algorithm (ERA) along with the Natural Excitation Technique (NExT), among others.
Track certain parameters in great detail which allows detecting changes “damages”
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Non-Destructive Evaluation (NDE)
• Non-Parametric Techniques No knowledge about the model is required “Black-Box” or “Unknown-Structures”
approach Applicability on linear and non-linear systems Well-developed algorithms such the neural
networks
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Objective
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Vision
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• Objectives: Develop and implement innovative methods for utilizing fiber-optic strain
sensors for structural health monitoring and control applications in aerospace
systems, with emphasis on using on-line aeroelastic shape estimation methods under
realistic flight conditions.
• Approach: Conduct analytical and experimental studies on a subset of challenging
research issues to develop and evaluate a variety of modeling, monitoring and control
strategies.
• Applicability: Results of the research will be useful in the monitoring and control of a
wide variety of current as well as future generations of aircraft and aerospace
structures.
Preliminary Tasks
Task 1: Development and validation of a NASTRAN model for a 2D beam and a 3D wing
Task 2: Computational studies with NASTRAN model for shape determination from strain
measurements under deterministic excitation
Task 3: Computational studies with NASTRAN model for shape determination from strain
measurements under stochastic aerodynamic loads
Task 4: Damage detection studies based on NASTRAN model to assess sensitivity of
strain measurements to damage type, severity, location, and orientation, under
uncertain conditions
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In-flight deformation shape sensing theory
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Development of Deflection Equations
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Classical Beam Theory
• Classical Beam Differential Equation:
M(x): bending moment
E: Young modulus
I: moment of inertia
• By relating the bending moment to the associated bending strain at the top or bottom fiber:
σ(x): bending stress
c: half-beam depth
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Cantilever Tubular Spar
Δl : spacing between sensing stations
c: half-beam depth
γi: torsion strain sensing station
xi: strain sensing station
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M: bending moment
ε: bending strain
θ: slope angle
y: deflection
Bending: Slope Equations
• Slope Equation from Classical Beam Theory:
• Noting that at the built-in end, tan θ0=0, gives:
• Final Equation
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θi+1
θi
θi-1
Bending:Deflection Equations
• Deflection equation from slope equation:
• Noting that at the built-in end, y0=tan θ 0=0.
• Final Equation
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θi+1
θi
θi-1
yi-1
yi
yi+1
2D Beam
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FEMAP Model
2D Beam Element
• 55 Nodes
• 40 Elements
• Aluminum
0.1 unit thickness
10 units in length
2unit deep
• Deterministic point load = 60 pounds
• Beam fixed in all 6 degree of freedom at root
• Deformation shows wing deflection
• Contour shows bending-strain measurements
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Calculation of Strain• Case 1: Strain sensing station located in
the middle of an element
• Case 2: Strain sensing station located at the juncture of two elements
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e
xi
e
xi
e
i- i+ δi: represents the displacement measurementse: represents the finite-element span-wise lengthxi:the i-th sensing station
Deformation of an infinitesimal rectangular material element [Sanpaz 2008]
2D Beam Results
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2D Beam Results
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2D Beam Results• Calculation of error:
e: errora: reference measurement (FEA)ã:analyzed measurement (Case1 and 2)|| . ||: norm
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3D Wing
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FEMAP Wing Model• 138 Nodes
• 284 Elements
• 6 deterministic point loads each 250 lbs
• Pressure distribution along upper and lower wing skins
• Varying half-beam depth and width along span
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3D Wing Details
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3D Wing Details
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Potential Placement of Fiber Sensors
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Wing Deflection
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Contour shows deflection values in y-direction
Future Work
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Future Tasks
• Validation of: Combined Bending and Torsion (CBT) Theory Perturbation Method Stepwise Method
• Modeling artificial damage in 3D model
• Error analysis and classification
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Timeline
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USC-CSULA-Dryden Team Timeline: November 2010 - January 2011
2010 2011
Student Name November December January
ArmenDerkevorkian
Learn NASTRAN/FEMAP Continue Simple Wing Element [3D]
Implement algorithm on strain data obtained from beam, simple wing, and UAV Elements as they become
available
Beam Element [2D] Simple Wing Element [3D]
Start Modeling the UAV Wing Element [3D]
Learn about obtaining deformation shapes from strain, as time allows
Begin Coding the algorithm for obtaining deformation shape
JessicaAlvarenga
Learn NASTRAN/FEMAP Continue Simple Wing Element [3D]
Implement algorithm on strain data obtained from beam, simple wing, and UAV Elements as they become
available
Beam Element [2D] Simple Wing Element [3D]
Start Modeling the UAV Wing Element [3D]
Learn about obtaining deformation shapes from strain, as time allows
Begin Coding the algorithm for obtaining deformation shape
Timeline
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USC-CSULA-Dryden Team Timeline: February 2011 – Month Year
Student Name February March April
ArmenDerkevorkian
• Modeling artificial damage on 3D Wing Element.
• Creating Damage Scenarios.• Implementing theory on
proposed damage conditions.• Error Analysis of results.
• Possible review of health monitoring techniques, including parametric and non-parametric methods.
• Application of Health-Monitoring algorithms on the computational models.
JessicaAlvarenga
• Modeling artificial damage on 3D Wing Element.
• Creating Damage Scenarios.• Implementing theory on
proposed damage conditions.• Error Analysis of results.
• Possible review of health monitoring techniques, including parametric and non-parametric methods.
• Application of Health-Monitoring algorithms on the computational models.
ReferencesEmmons, M., Karnani, S., Trono, S., Mohanchandra, K., Richards, W., and Carman, G. 2010. Strain
Measurement Validation Of Embedded Fiber Bragg Gratings. International Journal of Optomechatronics, 4(1):22-33.
Ko, W. and Richards, W. 2009. Method for real-time structure shape-sensing.
Ko, W., Richards, W., and Tran, V. 2007. Displacement Theories for In-Flight Deformed Shape Predictions of Aerospace Structures.
Sanpaz. 2008. Deformation of an infinitesimal rectangular material element. Wikepedia, Accessed January 27, 2011. http://en.wikipedia.org/wiki/File:2D_geometric_strain.png
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Questions?
Thank You
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