Materials Reports  2020, Vol. 34 Issue (Z1): 476-479 |
| METALS AND METAL MATRIX COMPOSITES |
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| Composite Structural Damage Diagnosis Method Based on Wavelet EnergySpectrum and Information Entropy |
| CAO Fei1, CHEN Jie1,2, LIN Zeli2
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1 AVIC Shanghai Institute of Aeronautical Measurement and Control Technology, Shanghai 201601, China;
2 Aviation Science and Technology Key Laboratory of Fault Diagnosis and Health Management Technology, Shanghai 201601, China |
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Abstract The large number of applications of composite materials on aircraft can effectively improve the overall operational efficiency of the aircraft. Aiming at the problem that the structural damage of aircraft composites can not be accurately diagnosed, a method for structural damage diagnosis of aircraft composites was proposed. Firstly, the method of acquiring wavelet energy spectrum was used to extract the wavelet energy spectrum of the collected composite structure damage test data, and obtain the wavelet energy spectrum of the damage signal. Secondly, the statistical analysis was used to statistically analyze the extracted wavelet energy spectrum. The covariance signal of the wavelet energy spectrum was obtained. Finally, based on the obtained covariance signal, the information entropy method was used to diagnose the structural damage of the composite. The experimental results of the damage data of a certain composite material were obtained. The results show that the method can diagnose the damage of composite structures and has certain reliability.
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Published: 01 July 2020
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| About author:: Fei Cao received his degree from Shanghai University of Electric Power in 2007. He is the engineer of Aviation Industry Measurement and Control Institute. And he has published 1 paper as the first author. His current main research directions are aircraft fault diagnosis and health management technology ; Jie Chen received his degree from Nanjing University of Aeronautics and Astronautics in 2013. He is the senior engineer of Aviation Industry Measurement and Control Institute. And he has published 4 papers as the first author. His current main research directions is aircraft fault diagnosis and health management technology, artificial intelligenc ; Zeli Lin received his degree from Shenyang University of Aeronautics and Astronautics in 2014. He is the se-nior engineer of Aviation Industry Measurement and Control Institute. And he has published 7 papers as the first author, and applied for 5 patents. His current main research directions are aircraft fault diagnosis and health management technology, big data analysis. |
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