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Explicit speed-integrated LSTM network for non-stationary gearbox vibration representation and fault detection under varying speed conditions

Author

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  • Chen, Yuejian
  • Liu, Xuemei
  • Rao, Meng
  • Qin, Yong
  • Wang, Zhipeng
  • Ji, Yuanjin

Abstract

Condition monitoring of the gearbox plays a crucial role in implementing proactive maintenance strategies and minimizing the economic loss of unexpected failures. Gearboxes often operate under variable speed conditions, which makes the collected vibration monitoring signals non-stationary. Existing works did not explore the scientific structures that incorporate speed signals into the long short-term memory (LSTM) networks, and thus leave room for improvement at varying speed conditions. To this end, this paper proposes novel explicit speed-integrated LSTM (SI-LSTM) models to enhance the representation accuracy of non-stationary vibration signals and improve gearbox fault detection capability. The SI-LSTM models with three variants are designed to account for the effects of speed variations on vibration signals. In SI-LSTM model 1, the vibration and speed signals are directly merged and input into the LSTM network. In SI-LSTM model 2, the speed signal is integrated into the network before the final LSTM layer. SI-LSTM model 3 is designed with a dedicated LSTM layer for speed signal, and the state outputs of both speed and vibration LSTMs are then merged and input into a final LSTM layer. Comprehensive experiments are conducted on a helical fixed axis gearbox dataset and a planetary gearbox dataset, and finally SI-LSTM model 3 is the best recommended structure. Spectral analysis is used to demonstrate the effectiveness of SI-LSTM model 3. The performance are also compared with four state-of-the-art methods, and the SI-LSTM model 3 achieves the highest AUCs of 0.9998 and 0.9676 and the best vibration representation accuracy on fixed-axis and planetary gearbox datasets, respectively.

Suggested Citation

  • Chen, Yuejian & Liu, Xuemei & Rao, Meng & Qin, Yong & Wang, Zhipeng & Ji, Yuanjin, 2025. "Explicit speed-integrated LSTM network for non-stationary gearbox vibration representation and fault detection under varying speed conditions," Reliability Engineering and System Safety, Elsevier, vol. 254(PA).
  • Handle: RePEc:eee:reensy:v:254:y:2025:i:pa:s0951832024006677
    DOI: 10.1016/j.ress.2024.110596
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    2. Li Lin & Xuelei Meng & Kewei Song & Liping Feng & Zheng Han & Ximan Xia, 2025. "Train Planning for Through Operation Between Intercity and High-Speed Railways: Enhancing Sustainability Through Integrated Transport Solutions," Sustainability, MDPI, vol. 17(3), pages 1-34, January.

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