热力发电2023，Vol.52Issue(12)：180-189,10.DOI:10.19666/j.rlfd.202303041
基于WPT-Transformer的磨煤机故障预警研究
Research on fault early warning of coal mill based on WPT and Transformer
摘要
Abstract
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.关键词
故障预警/磨煤机/小波包降噪/自注意力机制/时间序列预测Key words
fault early warning/coal mill/wavelet packet de-noising/self-attention mechanism/time series prediction引用本文复制引用
杨婷婷,李浩千,陈晓峰,罗海玉..基于WPT-Transformer的磨煤机故障预警研究[J].热力发电,2023,52(12):180-189,10.基金项目
中国华能集团有限公司总部科技项目(HNKJ20-H88) Science and Technology Project of China Huaneng Group Co.,Ltd.(HNKJ20-H88) （HNKJ20-H88）
