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| Intelligent Identification Technology for Acoustic Fatigue Damage of Aircraft Structural Wall Panels |
| Received:August 08, 2024 Revised:August 26, 2024 |
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| DOI：10.7643/issn.1672-9242.2024.09.017 |
| KeyWord:noise fatigue damage compound material GBDT intelligent recognition model test verification structural wall panels |
| Author | Institution |
| XING Xiaoming |
Shenyang Branch of Tianjin Aerospace Relia Technology Co., Ltd., Shenyang , China |
| CHEN Guoyi |
Shenyang Branch of Tianjin Aerospace Relia Technology Co., Ltd., Shenyang , China |
| CHEN Zhongming |
Shenyang Aircraft Design and Research Institute, Shenyang , China |
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| Abstract: |
| The work aims to study the damage fatigue problem of aircraft structure panels, and improve the intelligent recognition ability of acoustic fatigue damage. In this paper, an efficient intelligent recognition model based on gradient boosting decision tree (GBDT) was constructed to identify the acoustic fatigue damage of aircraft structural panels. This method relies on the powerful performance of the GBDT model. It can effectively deal with complex nonlinear relationships, and continuously optimize the recognition results through iterative learning. In the experiment, based on the measured noise data of a composite structure panel, the time, speed and label data sets were constructed for model verification. The verification results showed that the intelligent recognition accuracy of noise fatigue damage based on GBDT was 76.8%. The results show that the intelligent recognition method of acoustic fatigue damage based on GBDT has good recognition ability, and can effectively monitor the acoustic fatigue damage of aircraft structure panels in practical application, which verifies the effectiveness and practicability of the method. |
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