AE11.pdf

Before passing the acoustic emission test data

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Before passing the acoustic emission test data through the neural network, there was a problem noted with some of the hits recorded in the in-flight system files. This problem was associated with two of the recorded acoustic emission test parameters: duration and energy. The duration was pegged, meaning that acoustic emission test signals longer than the software could record were being partially captured. These very long duration signals also had correspondingly high energies. These signals were probably caused by aerodynamic fluttering of the two side doors attached to the top of the cowling by the hinge line parallel to the transducer positions. In this case, the signals did not overwhelm the system; fatigue cracking and plastic deformation were successfully differentiated. These pegged signals were a good test of the in-flight monitoring system’s ability to work in noisy conditions. Despite the extra noise picked up by the acoustic emission transducers, fatigue cracking was successfully recorded and distinguished from the noise. Conclusions The results reported here demonstrate the practicality of an acoustic emission in-flight crack monitoring system. The system is able to extract very small acoustic emission fatigue crack signals from a great deal of noise that accompanies an aircraft in flight. Results Several particular observations are summarized as follows. 1. Distinct separation of fatigue cracking, plastic deformation and rubbing gave the neural network a very clean data set on which to train. 2. From the in-flight data, the neural network indicated that fatigue cracking was occurring, as expected, on the right side of the cowling between channels 1 and 2 and that it was also occurring unexpectedly between channels 3 and 4 on the left side. 375 Aerospace Applications of Acoustic Emission Testing F IGURE 19. Photograph of cowling crack: (a) channels 1 and 2, expected crack side; (b) channels 3 and 4, unexpected crack side. (a) (b)
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3. Further testing of the engine cowling verified that a second fatigue crack was indeed growing between channels 3 and 4, verifying the neural network results from in-flight data. 4. Fatigue cracking occurred predominantly when the aircraft was on the ground, both before takeoff and after landing. These findings demonstrate the ability of an acoustic emission test system to identify and monitor fatigue crack growth in an in-flight environment using conventional acoustic emission test hardware. Recommendations 1. Thermal analysis of the engine cowling may be useful because these tests point to the possibility that thermal loading may play a significant role in the fatigue of an engine cowling. 2. To keep high duration files from overwhelming the system, the threshold setting can be raised before data acquisition. A threshold such as 50 dB or higher could prevent this problem.
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  • Fall '19
  • Fighter aircraft, Nondestructive testing, Acoustic Emission, Acoustic Emission Testing

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