电气技术2025，Vol.26Issue(3)：59-64,84,7.
基于Transformer语义迁移的定子热故障诊断
Transformer-based semantic transfer for stator thermal fault diagnosis
姚驰宇 1桂晶 1李泼 1王伟 1陈聪2
作者信息
- 1. 淮南平圩发电有限责任公司,安徽 淮南 232089
- 2. 中电华创电力技术研究有限公司,上海 200086||中电华创(苏州)电力技术研究有限公司,江苏 苏州 215123
- 折叠
摘要
Abstract
The stator cooling water system of a turbine generator must maintain optimal operating conditions to ensure the reliability and safety of the generator.Typically,thermal faults are detected using methods such as shutdown maintenance or temperature difference thresholds,but these methods cannot effectively detect faults in real time while the generator is in operation.To more accurately identify stator thermal faults,this paper proposes a temperature prediction algorithm based on the Transformer architecture.Using the predicted temperatures from multiple measurement points,the future temperature difference is estimated,and a diagnosis model for stator thermal faults is established.To address the issue of limited fault operation data samples,this paper utilizes Gaussian processes with different kernel functions to generate various types of time series,which are then combined with the original data,significantly expanding the training sample space.Finally,experiments are conducted using existing test data.The results indicate that the predictive algorithm proposed in this paper outperforms traditional autoregressive integrated moving average(ARIMA)and long short term memory(LSTM)algorithms.Moreover,the diagnostic model based on this predictive algorithm achieves an accuracy rate of 91.9%in identifying operational states,while also maintaining high precision and recall rates,ensuring low false alarm and missed alarm rates.关键词
定子热故障/出水温度/Transformer/高斯过程Key words
stator thermal faults/outlet-water temperature/Transformer/Gaussian process引用本文复制引用
姚驰宇,桂晶,李泼,王伟,陈聪..基于Transformer语义迁移的定子热故障诊断[J].电气技术,2025,26(3):59-64,84,7.
