Static and dynamic testing of the full scale helicopter rotor blades
M. Luczak1, B. Peeters1, K. Dziedziech1, 1 LMS International, Test Division; Test Technology R&D Interleuvenlaan 68, B-3001 Leuven, Belgium email: [email protected]
Abstract This paper presents the experimental investigations done on the main and tail rotor composite material blades of the medium size helicopter. For the dynamic testing accelerometers, innovative optical Fiber Bragg Grating and classical strain sensors were used. Dynamic tests covered the modal analysis and dynamic strain measurements. Static measurement discrepancies of strain values between optical and electrical signal sensors are provided and assessed. In modal testing the Modal Assurance Criterion is most commonly used to compare test-to-test results. In the static test there is apparently no such criterion therefore the evaluation of the strain differences was made with different approaches. Different dynamic test setups and excitation configurations were studied to account for the test-to-test and blade-to-blade variability observed.
1 Introduction
The paper discusses detailed comprehensive experimental campaign done on the rotor blades coming from Polish helicopters Mi-2 and PZL-W3 “SOKOL”. The research was done in the context of the first stage of EU funded Marie Curie PROND project oriented for testing, modeling and updating the non-deterministic FE models of the composite material blades. The study includes the following elements:
• static tests made on the tail rotor blade with the application of electrical and fiber optic strain gauges,
• dynamic strain measurement on the tail rotor blade,
• the comparison of the test results focusing on the discrepancies in between two applied strain sensing techniques,
• experimental modal analysis executed with the piezoceramic accelerometers, microflown and lased vibrometer sensors,
• the comparison of the modal test results from the various measurement techniques,
Three blades from main rotor from PZL Swidnik W-3 helicopter, presented on Figure 2, were investigated in the second part of this research. Blades are made of Glass Fiber Reinforced Plastics. Dimension of the investigated blades are: Length ≈ 7300 [mm], Width ≈ 520 [mm], Approximate weight of the structure is 70 [kg]. In the blades structure spar is reinforced with the use of glass roving material and honeycomb elements are made from nomex or glass epoxy.
During the measurement the blade was fixed to steel cylinder (weight approximately 1 ton) by using two screws with elastic gaskets between the blade and the cylinder. The rubber layers were necessary to decrease the natural frequencies of the blade (restrictions in maximum measured frequency by FOS&S interrogator- up to 50 Hz). This approach let bring down the frequency of the first mode from 23 Hz (blade fixed directly to cylinder) to 12 Hz (with elastic layer between both parts). More important is that
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the setup remained linear according to series of tests made for different (0 up to 5) numbers of rubber layers. Figure 3 presents the overview of the measurement setup during the modal test prepared with FOS&S (with traditional and fibre optics strain gauges, accelerometers were used to get reference modal output). All 5 electrical strain gauges were installed, following a standard installation procedure using the MBond 200 GA-2 adhesive approach. All 5 optical strain gauges were installed using the FOS&S strain gauge installation kit with included installation procedure.
Figure 3: The test setup build with use of LMS and FOS&S hardware and software.
The second objects of the investigation are three blades from the main rotor of a PZL Swidnik W-3 helicopter presented in Figure 4 .Main rotor blades were supported in the edgewise direction with two elastic cords.
Figure 4: Test Setup of Blade from Main Rotor from Helicopter PZL Swidnik W-3.
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During the measurement campaign the following hardware and software were used:
• LMS SCADAS Mobile equipped with VB8 and V8 modules- 16 acquisition channels.
• PC with LMS Test.Lab 8B software. LMS Test. Lab provides a powerful, high-speed multi-channel vibration control system.
• 5 Vishay general purpose strain gauges (CEA-06-500UW-350) to measure the strains on the surface of the blade, the input mode was fixed as the ¼ bridge
• 5 FOS&S fibre optics strain gauges (SG-01) to measure the strains on the surface of the blade
• FBG-Scan 700 interrogator- dynamic, high accuracy measurement device for Fibre Bragg Grating (FBG) sensors
• Laptop with FOS&S ILLumiSense Strain v1.2 software
• 5 PCB Accelerometers Model 333B32
• PCB impedance head model 288D01
• Electromagnetic shaker with stinger and amplifier,
• Microflown probes: PU-mini NT0712-44 and USP-mini UT0608-01,
4 Static and dynamic strain measurement with electrical and optical sensors
4.1 STATIC STRAIN MEASUREMENT
The series of static tests were made on the blade. As the load was used the steel block with the mass of 4,5 kg. Results were obtained as the strain levels at measurement points described in Table 1 as Strain 1÷5 on the blade surface. During the static test with use of the traditional and fibre optics strain gauges the same experimental equipment as in case of dynamic test was used. The results from three series of static tests are presented in Table 1. Load center means that the run was made for the 4,5 kg mass attached in the middle of the blade at the tip. Load trailing edge means that the run was measured with the mass attached at the tip of the blade on the trailing edge side. Load leading edge - loading mass was mounted at the tip of the blade at leading edge side. The percent differences between both types of strain gauges readings are calculated and presented in Table 1.
Table 1: Strains levels obtained during static test with use of traditional and fiber optics strain gauges
It was found that strain output data from both optical and electrical signals correspond quite well. Differences between measured strains with both techniques were within 15%. These differences can be explained by the fact that both strain sensor lines have been installed next to each other at the same rotor blade side. Electrical strain gauges have been installed on a thicker part of the blade, resulting in higher strains (measurement point further away from the blade’s neutral axis in bending).
4.2 DYNAMIC STRAIN MEASUREMENT
Synchronization options for fiber optic signals with electrical signals require to be further elaborated. The importance of synchronization is first explained here: to study a system’s behavior, it is indeed very important that multiple channels / heterogeneous sensors are synchronously measured. Advanced data processing often involves the calculation of cross-correlations and/or transfer functions between different output channels. If these channels are not synchronously measured, the derived measurement functions will be erroneous. An example of potential errors is included here. Helicopter tail rotor blade was excited by a shaker and the force injected by the shaker into the structure was measured using a force cell. The structural response was measured using 2 systems. One set of sensors was measured using the same data acquisition system that also measured the force and in which synchronization between channels was very carefully dealt with and another set of sensors was measured using an independent acquisition unit. In an attempt to post-synchronize both units, the cross-correlation between 2 signals from nearby sensors was calculated. The time lag at maximum correlation value determines the time shift between both signals. Figure 5 Left compares both signals after time-shifting. The same time shift was applied to align the force signal with signals from the 2nd set. When the empirical frequency response function (FRF) is processed, the result looks very noisy above 30 Hz. This is exactly due to a slight difference in the sampling clocks. In other words, a very small sampling clock difference can have a dramatic effect on the quality of the FRF. Therefore, as a second post-processing attempt, data from the 2nd unit was not only time-shifted but also re-sampled to the clock of the first DACQ system (Figure 5 Right). In this way, a new and improved FRF could be computed. In order to compare classical electrical with optical strain gauge measurements, measured with 2 independent DACQ units, the synchronization post-processing as outlined above has been applied for the helicopter rotor blade strain output data. Figure 6 compares the Discrete Fourier Transforms (DFT) of both synchronized strain measurements. The examples above have indicated that it is possible to align data measured with different DACQ units, each running on its own clock, using dedicated data post-processing tools. It is however obvious that the use of such post-processing is not ideal and even not suited for certain applications. Therefore, a further integration between optical fibre strain measurements and more classical instrumentation is pursued. The optical signal conditioning is rather specific, but relevant here is that finally the strain data will be available as digital signals with a certain sampling frequency.
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Figure 5: Left: Time series comparison between signals from 2 different DACQ units after time-shifting. Right: re-sampled time histories: optical (blue, FOS&S) versus electrical strain gauge
(green, LMS).
Figure 6: Fourier transform of sine sweep data: comparison between optical (blue, FOS&S) and
electrical strain gauge (green, LMS).
5 Experimental modal analysis with use of contact and non-contact sensing techniques
5.1 GEOMETRY DEFINITION
A dense grid of measurement points is defined all over the blade surface, in order to successfully identify the dynamic properties of this rather big structure. Measurement points are set with a distance of 0.25 [m] one from each other in the spanwise (Z) direction and 0.1 [m] in the edgewise direction (Y) (Figure 4). Geometry definition for blade is presented on Figure 7. It consists of 78 points, 77 of which are acquisition locations and the remaining 1 is the driving point.
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Figure 7: Cartesian Coordinate System for Piezoelectric, Microflown and Laser Sensors.
5.2 EXPERIMENTAL MODAL MODELS
Based on the experimental data collection, modal models were estimated. This is a very important step in the assessment of the test data variability because it preserves the gross errors to be included into an analysis. Control of the collected data quality and evaluation of the estimated models by means of coherence functions synthesis and AutoMAC criterion is done. The estimated modal models are compared for the contact and non-contact measurement. For the piezoelectric sensors the measurement was done in “sets” which means not all the points were measured at the same time. As a consequence a number of partial modal models were estimated for each of the set. Next the partial models were merged into a global model by means of multi-run modal analysis. Modal models have to be validated to provide confident information about the structural dynamics of an object.
5.3 MEASUREMENT ERRORS DISCUSSION
All measurements are prone to systematic errors. A systematic error is any biasing effect in the methods of observation or instruments used which introduces error into an experiment and is such that it always affects the results of an experiment in the same direction. When accelerometers are used to record the system’s response, 8 sets of sensor locations are measured, in order to cover the whole grid of measurement points, using a maximum number of 10 sensors/set. The mass of a single sensor is 0.005 [kg]. Weighted mass of all sensors and wiring system is 0.06 [kg]. This distributed mass is moved along the 8 blade regions, which are characterized by a different flexibility. Additional mass always causes local structural modification which results in natural frequencies shift. Frequency shift due to mass loading for the driving point FRFs is presented on Figure 8, for the second natural mode (second flapwise mode, around 10.2Hz).
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8.05 Hz
-70.00
-10.00
dBg/N
Figure 8: FRF plot for the impedance head for all the measured sets for a selected point
Measuring in sets poses another engineering practice problem. Moving sensors from one location to another requires decoupling the shakers from the structure, since it is not possible to provide a required quality of the sensor-structure wax connection, keeping the shakers coupled. Re-coupling the shakers also alters the connection’s dynamic characteristic which consequently contributes to the measured signal. In other words the physical, real life conditions of the test realization make each set of measurements to be in fact a measurement of a slightly different assembly of the structure, sensors, wiring system and shaker fastening. Therefore contact measurements suffer from more than just mass loading effect. Laser and microflown measurements are free of these systematic errors since no mass and no de-coupling/coupling of the shakers is performed. Laser measurement is affected by another type of error. Velocity measurement is realised along the optical axis of the beam. In situations in which a velocity vector (which is normal to the surface of the blade) is not in line with the optical axis of the LVD, the correction factor, equal to the cosine of the difference angle, has to be applied. LMS (CADA-X) software, used for the LVD tests, has a built-in algorithm of correction of such errors for flat surfaces. Since the surface of the blades is curved it was divided into 3 regions (assumed to be flat with a satisfactory approximation) along the spanwise direction, in order to minimize this effect. Therefore for each of these sets a slightly difference velocity field was obtained (Figure 9). The Microflown probe measurements were also not completely error free. Direct result of the sensing principle of the microflown probes is a non-correct measurement of the low frequency modes.
Figure 9: Error of the Curvature Correction in Laser Measurement
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5.4 MEASUREMENT RESULTS
Vibration measure of the blades done was different for all three techniques. Therefore it is difficult to present the direct comparison of the acquired response signal for the particular point. Signal from a microflown probes is a subject of post processing. For this sensor there is no single frequency independent sensitivity value. The calibration of the signal data is being computed afterwards and is multiplied by frequency dependent curve. Measurement results shown on the Figure 10 clearly confirm the mass loading effect of the piezoceramic sensors.
0.00 81.36Hz
-80.00
0.00
dB( g/N
)
0.00
1.00
Ampl
itude
F FRF Drvp:1:+X/Drvp:1:-XF FRF Drvp:1:+X/Drvp:1:-XF FRF Drvp:1:-X/Drvp:1:+X
Figure 10: Mass influence within investigated frequency range for driving point. Piezoceramic accelerometers measurement (red) and Microflown probes (green) measurements are the upper
curves, the Laser vibrometer measurement (blue) is the lower curve.
Driving points FRFs for both contactless measurement techniques have higher resonant frequency values than piezoceramic sensors FRFs towards increasing frequency range which is mass influence area.
5.5 MODAL MODELS COMPARISON
The data presented in previous section was used for the estimation of the modal models. Table 2 presents a part of the comparison of the natural frequency and damping ratio values for the identified modes. Data for these models were acquired by means of contact and non-contact techniques.
Table 2: Experimental natural frequencies and damping.
Within the bandwidth of interest there are all modes (except the first one using the microflown sensor) successfully identified for all modal models. Visual inspection of the mode shapes is presented in Error! Reference source not found.Table 3
Accelerometers Microflown Laser
Flapwise 2nd
Torsion 1st
Table 3: Mode shapes.
Discussed systematic errors do not influence the correctness of the model estimation which can be observed in MAC matrix plots in Table 4.
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Acceleration (A) vs LASER (B) Acceleration (A) vs Microflown (B) Laser (A) vs Microflown (B)
Table 4: MAC Criterion for modal vectors comparison.
MAC matrix comparison also confirms that both contactless measurement models coincide better than contact, piezoceramic accelerometer model. Another relevant comparison method for these models is a correlation plot shown on Figure 11. For contact and non-contact models the correlation plot of damping ratio and frequency is being drawn. Damping ratios for the torsional modes (see Table 2) are clearly demonstrating the significantly higher value with respect to the translational modes. This concerns all the considered models. A new observation comes from the comparison between the microflown and laser measurement models. Both are non-contact techniques, therefore the same values of estimated damping ratio could be expected for both models. This is not a case and what is more, the higher is the frequency of the mode the larger the difference becomes (see the trend line of the difference on the bottom part of Figure 11).
Contact (accelerometers) vs non-contact (microflown and laser)
Accelerometers Microflown Laser (microflown-laser) Linear ((microflown-laser)) Figure 11: Assessment of the laser vibrometer, microflown probes and piezoceramic measurement
on modal parameters. It is also assessment of acceleration and velocity measurement.
The explanation for this could be looked into the plots of measured (Figure 8 ,Table 4) and reported data. Both reported laser and microflown measured velocity signals comparisons are done for the constant
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distance of a probe from a surface. Due to the curvature of a large blade surface it is difficult to maintain exactly the same distance between the probe and the surface all over the measurements. Therefore this variability also contributes to the final modal model quality and especially the damping ratio is affected. Both abovementioned reasons result in increasing differences of estimated mode shapes (see Table 4) and damping ratios (Figure 11) .
6 Conclusions
This paper presents some aspects of the multidisciplinary and interdisciplinary research oriented for the test data variability due to the applied measurement technique both in static and dynamic domains. It presents an extensive test campaign led on the composite material main rotor helicopter blades. Test setups included different measurement techniques of contact and non-contact type. Experimental test data examples were shown and used for modal models estimation. Measurement systematic errors were identified and examined. Estimated modal models were compared by means of natural frequency, damping ratio and mode shape. Common observation from displayed comparisons is that the accuracy of the results is frequency dependent. The discrepancy between models grows in frequency. However all three measurement techniques lead to a correct experimental modal models. One has to be aware of proper choice of the measurement technique and its impact on test data, modal model estimated afterwards and the needed time-effort.
Acknowledgements
This research was supported by Marie Curie European Reintegration Grants within the 7th European Community Framework Programme. The authors of this work gratefully acknowledge support for this research under the project No. 239191 “PROND” provided by the EU. Calculations were performed in the Academic Supercomputing Center TASK, Gdansk, Poland.
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