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Hongfeng Gao, Tiexin Xu, Renlong Li and Chaozhi Cai
Because the gearbox in transmission systems is prone to failure and the fault signal is not obvious, the fault end cannot be located. In this paper, a gearbox fault diagnosis method grounded on improved complete ensemble empirical mode decomposition with...
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Xiaojiao Gu, Yang Tian, Chi Li, Yonghe Wei and Dashuai Li
The fault diagnosis method proposed in this paper can be applied to the diagnosis of bearings in machine tool spindle systems.
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Qingyong Zhang, Changhuan Song and Yiqing Yuan
Vehicle gearboxes are subject to strong noise interference during operation, and the noise in the signal affects the accuracy of fault identification. Signal denoising and fault diagnosis processes are often conducted independently, overlooking their syn...
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Zhenyu Yin, Feiqing Zhang, Guangyuan Xu, Guangjie Han and Yuanguo Bi
Confronting the challenge of identifying unknown fault types in rolling bearing fault diagnosis, this study introduces a multi-scale bearing fault diagnosis method based on transfer learning. Initially, a multi-scale feature extraction network, MBDCNet, ...
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Zhuofan Xu, Jing Yan, Guoqing Sui, Yanze Wu, Meirong Qi, Zilong Zhang, Yingsan Geng and Jianhua Wang
High-voltage circuit breakers (HVCBs) handle the important tasks of controlling and safeguarding electricity networks. In the case of insufficient data samples, improving the accuracy of the traditional HVCB mechanical fault diagnosis method is difficult...
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