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Volume 43 Issue 3
Jun.  2022
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Liu Jie, Zhang Lin, Wang Yunsheng, Yan Xiao, Zhan Li, Ou Zhu. Degradation Trend Prediction of Nuclear-level Electric Valve Based on Hilbert-Huang Transform and BP Neural Network[J]. Nuclear Power Engineering, 2022, 43(3): 179-184. doi: 10.13832/j.jnpe.2022.03.0179
Citation: Liu Jie, Zhang Lin, Wang Yunsheng, Yan Xiao, Zhan Li, Ou Zhu. Degradation Trend Prediction of Nuclear-level Electric Valve Based on Hilbert-Huang Transform and BP Neural Network[J]. Nuclear Power Engineering, 2022, 43(3): 179-184. doi: 10.13832/j.jnpe.2022.03.0179

Degradation Trend Prediction of Nuclear-level Electric Valve Based on Hilbert-Huang Transform and BP Neural Network

doi: 10.13832/j.jnpe.2022.03.0179
  • Received Date: 2021-03-25
  • Accepted Date: 2021-05-06
  • Rev Recd Date: 2022-03-14
  • Publish Date: 2022-06-07
  • Due to the harsh service environment of nuclear-level electric valves, degradation and failure are easy to occur. Therefore, in order to accurately predict the performance degradation trend of nuclear-level electric valves, this study adopts a method based on Hilbert-Huang transform (HHT) and BP neural network (BPNN) combined method (HHT-BPNN) to predict the degradation state of nuclear-level electric valve. In this paper, the vibration signal of a nuclear-level electric valve reliability test is used to predict the degradation trend of the electric valve. The results show that the method can accurately predict the three degradation states of the nuclear-level electric valve, and the relative error is within the acceptable range. The analysis and research results show that HHT can effectively extract the degradation information of the signal, and BPNN can accurately predict the degradation trend of nuclear-level electric valves. The HHT-BPNN prediction method can effectively solve the difficulty of predicting the performance degradation of nuclear-level electric valves.

     

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