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Non-Destructive Testing for Damage Detection in Composite Materials

EMILIO DI LORENZO, QUIRINO LORENZO BERNABEI, BART PEETERS

Abstract


One of the trends in the automotive, aerospace and energy industries is the use of lightweight structures (e.g. 3D printed structures, composite materials) in order to reduce the weight and improve the system performance. These industries have the need to estimate the presence of defects (e.g. Flat Bottom Holes (FBH) or Delamination in case of composite) both in-service and at the end of the production line. This work tries to find a solution to these problems. Two types of materials have been analyzed: Carbon Fiber Reinforced Plate (CFRP) and Glass Plate (GP). Due to the low weight of the structure it is not a good option to perform the measurements with classical sensors such as accelerometers and the tests have been performed in a less invasive way by using non-contact measurements. In the specific case, the OptoMET scanning Laser Doppler Vibrometry (LDV) measures the surface velocities and piezo-patch sensors (PZTs) excite the specimens in a very large frequency band (up to 40kHz). The algorithm for identifying the defects is based on the Local Defect Resonance (LDR) concept, which looks to the high frequency vibrations to get a localized resonant activation of the defect. To do that, an automated procedure able to analyze both time data with a time-frequency analysis and frequency data through modal analysis have been developed. The techniques have been validated in a lab environment and afterwards on real industrial components. Several defects with different sizes and locations have been identified. All techniques work also if more defects are located within the analyzed region. Future steps foresee the use of innovative modal parameter estimation techniques in the loop and the use of machine learning algorithms.


DOI
10.12783/shm2019/32245

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