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Prediction of Vibration Trend of Hydroelectric Unit Based on WOA-VMD-TCN
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Pu WANG1, Lian-tao JI2, Long-xiang CHEN1, Xiu-yan JING1, Cheng-jian YUAN3, Chao-shun LI3
Water Resources and Power | 2023, 41(6) : 175 - 179
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Water Resources and Power | 2023, 41(6): 175-179
• ELECTROMECHANICS AND CONTROL ENGINEERING •
Prediction of Vibration Trend of Hydroelectric Unit Based on WOA-VMD-TCN
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Pu WANG1, Lian-tao JI2, Long-xiang CHEN1, Xiu-yan JING1, Cheng-jian YUAN3, Chao-shun LI3
Affiliations
  • 1.State Grid Corporation of China, Beijing 100031, China
  • 2.China Electric Power Research Institute, Beijing 100192, China
  • 3.School of Civil and Hydraulic Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
Published: 2023-06-25 doi: 10.20040/j.cnki.1000-7709.2023.20221389
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Prediction of the vibration trend of hydropower units is an important measure to ensure the normal operation of the unit. However, due to the complexity and non-stationarity of the vibration signal of the unit, accurate prediction becomes a difficult problem. To this end, this paper proposes a combined trend prediction model based on adaptive variational modal decomposition and temporal convolutional network (TCN). Firstly, the Whale Swarm Algorithm (WOA) was used to optimize the parameters of Variational Mode Decomposition (VMD) to avoid the drawbacks of blindly selecting parameters, and to achieve adaptive decomposition of vibration signals. And then each decomposed component signal was normalized to establish TCN for trend prediction. Finally the original vibration signal prediction was obtained by superimposing the results. The proposed model was demonstrated and tested with the actual operation data of a domestic power station. The results show that the proposed model has high prediction accuracy and can be used in engineering practice.

vibration signal  /  whale swarm algorithm  /  VMD  /  trend prediction  /  TCN
Pu WANG, Lian-tao JI, Long-xiang CHEN, Xiu-yan JING, Cheng-jian YUAN, Chao-shun LI. Prediction of Vibration Trend of Hydroelectric Unit Based on WOA-VMD-TCN[J]. Water Resources and Power, 2023 , 41 (6) : 175 -179 . DOI: 10.20040/j.cnki.1000-7709.2023.20221389
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Article Info
doi: 10.20040/j.cnki.1000-7709.2023.20221389
  • Receive Date：2022-07-08
  • Online Date：2026-01-28
  • Published：2023-06-25
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  • Received：2022-07-08
  • Revised：2022-08-16
Funding
Affiliations
    1.State Grid Corporation of China, Beijing 100031, China
    2.China Electric Power Research Institute, Beijing 100192, China
    3.School of Civil and Hydraulic Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
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https://castjournals.cast.org.cn/joweb/sdnykx/EN/10.20040/j.cnki.1000-7709.2023.20221389
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小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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