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Research on fault early warning of coal mill based on WPT and Transformer
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Tingting YANG1, Haoqian LI1, Xiaofeng CHEN2, Haiyu LUO1
Thermal Power Generation | 2023, 52(12) : 180 - 189
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Thermal Power Generation | 2023, 52(12): 180-189
• Power generation technology forum •
Research on fault early warning of coal mill based on WPT and Transformer
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Tingting YANG1, Haoqian LI1, Xiaofeng CHEN2, Haiyu LUO1
Affiliations
  • 1.School of Control and Computer Engineering, North China Electric Power University, Beijing 102206, China
  • 2.North China Electric Power Research Institute Co., Ltd., Beijing 100045, China
Published: 2023-12-25 doi: 10.19666/j.rlfd.202303041
Outline
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The fault early warning of the coal mill is of great significance to the safe operation of thermal power unit, but the operation of the coal mill has many interference noises and a high degree of coupling, which makes the fault early warning more difficult. Based on this, this paper proposes a fault warning method based on wavelet packet transform (WPT) and Transformer. Firstly, the signal is denoised by the wavelet packet analysis method with adaptive threshold value. Then, the characteristic parameters related to the fault measurement point are selected as input to establish a Transformer coal pulverized prediction model based on the self-attention mechanism. Finally, the kernel density estimation method is used to analyze the prediction deviation and determine the warning threshold. Taking a 660 MW medium-speed coal mill as the research object and using actual data for verification, the experimental results show that the prediction accuracy of the proposed method is higher than that of CNN, LSTM, and CNN+LSTM models, and it can provide early warning of coal mill failures.

fault early warning  /  coal mill  /  wavelet packet de-noising  /  self-attention mechanism  /  time series prediction
Tingting YANG, Haoqian LI, Xiaofeng CHEN, Haiyu LUO. Research on fault early warning of coal mill based on WPT and Transformer[J]. Thermal Power Generation, 2023 , 52 (12) : 180 -189 . DOI: 10.19666/j.rlfd.202303041
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  • Science and Technology Project of China Huaneng Group Co., Ltd.(HNKJ20-H88)
Appendix
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Year 2023 volume 52 Issue 12
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104
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Article Info
doi: 10.19666/j.rlfd.202303041
  • Receive Date：2023-03-17
  • Online Date：2026-01-26
  • Published：2023-12-25
Article Data
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History
  • Received：2023-03-17
Funding
Science and Technology Project of China Huaneng Group Co., Ltd.(HNKJ20-H88)
Affiliations
    1.School of Control and Computer Engineering, North China Electric Power University, Beijing 102206, China
    2.North China Electric Power Research Institute Co., Ltd., Beijing 100045, China
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