Vibration Fault Diagnosis of Helicopter Accessory Gearbox Under Multi-operating Conditions

被引：0

作者：

Wan A. ^{[1
]}

Gong Z. ^{[1
]}

Wang J. ^{[2
]}

Shan T. ^{[2
]}

He J. ^{[1
]}

机构：

[1] Department of Mechanical Engineering, Zhejiang University City College, Hangzhou

[2] Aviation Key Laboratory of Science and Technology on Fault Diagnosis Health Management, Shanghai

来源：

Zhendong Ceshi Yu Zhenduan/Journal of Vibration, Measurement and Diagnosis | 2024年 / 44卷 / 02期

关键词：

accessory gear box; multi-scale convolution network; variational modal decomposition; vibration fault diagnosis;

D O I：

10.16450/j.cnki.issn.1004-6801.2024.02.006

中图分类号：

学科分类号：

摘要：

Aiming at the problems of difficulty in fault feature extraction and low recognition accuracy of helicopter accessory gearbox under limited variable working conditions, a fault diagnosis method is proposed combining variational mode decomposition (VMD) and multi-scale convolution neural network (MCNN). Firstly, the helicopter accessory gearbox is tested on the ground and sampled, and the original signal is preprocessed by filtering and noise reduction. Secondly, the VMD decomposition signal is used as several intrinsic mode functions (IMF) to reconstruct and normalize the decomposition modes according to the frequency characteristics of the gear meshing ground, so as to enhance the weak high-frequency fault characteristics. Finally, each component of the reconstructed signal is regarded as a different scale, and multi-scale features are extracted and fused by MCNN. The identified fault category is given by softmax classifier. The test results show that the proposed method can effectively enhance the signal fault characteristics, excavate the difference and identity of signals under multiple working conditions. In the vibration fault diagnosis of helicopter accessory gearbox, the average accuracy rate is 97.25%. © 2024 Nanjing University of Aeronautics an Astronautics. All rights reserved.

引用

页码：246 / 252

页数：6

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