RUL prediction of rolling bearing based on adaptive VMD and DD-cCycleGAN

YU Jun1,2, ZHAO Kun1, ZHANG Shuai3, DENG Si’er4

Journal of Vibration and Shock ›› 2024, Vol. 43 ›› Issue (13) : 45-52.

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Journal of Vibration and Shock ›› 2024, Vol. 43 ›› Issue (13) : 45-52.

RUL prediction of rolling bearing based on adaptive VMD and DD-cCycleGAN

  • YU Jun1,2, ZHAO Kun1, ZHANG Shuai3, DENG Si’er4
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Abstract

In order to accurately predict the remaining useful life (RUL) of rolling bearings under strong noise interference and small samples, a RUL prediction method of rolling bearings based on adaptive variational mode decomposition (VMD) and double-discriminator conditional CycleGAN (DD-cCycleGAN) is put forward. Combining chimp optimization algorithm (ChOA) with VMD, an adaptive VMD algorithm based on ChOA is presented, which selects effective mode components for reconstruction and reduces interference from strong background noise. A DD-cCycleGAN is developed to generate new samples which not only retain sample information from the source domain, but also resemble samples from the target domain. A long short-term memory (LSTM) network is trained by using the reconstructed samples of training samples and the generated new samples. The LSTM network after training is used to predict the RUL of rolling bearings in test samples. The effectiveness of this method was verified by using the XJTU-SY rolling bearing accelerated life test dataset. The experimental results show that this method possesses strong noise resistance and high accuracy in the bearing RUL prediction.

Key words

rolling bearing / remaining useful life prediction / adaptive variational mode decomposition / double-discriminator conditional CycleGAN / chimp optimization algorithm

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YU Jun1,2, ZHAO Kun1, ZHANG Shuai3, DENG Si’er4. RUL prediction of rolling bearing based on adaptive VMD and DD-cCycleGAN[J]. Journal of Vibration and Shock, 2024, 43(13): 45-52

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