摘要
为解决发电厂电动机运行异常识别的技术难题,通过分析短路、断条、轴承故障等异常类型的通信信号特征,提出基于通信信号的发电厂电动机运行异常识别方法。实验验证表明,该方法在正常工况、匝间短路工况、转子断条工况和轴承故障工况4种典型工况下的识别准确率分别达到98.3%、96.8%、97.5%和95.6%,明显优于传统方法,为发电厂电动机状态监测提供了有效的技术手段。
In order to solve the technical problem of identifying abnormal operation of power plant motors,a communication signal based method for identifying abnormal operation of power plant motors is proposed by analyzing the communication signal characteristics of abnormal types such as short circuits,broken bars,and bearing faults.Experimental verification shows that this method achieves recognition accuracy of 98.3%,96.8%,97.5%,and 95.6%respectively under four typical working conditions:normal working conditions,inter turn short circuit working conditions,rotor bar breakage working conditions,and bearing fault working conditions.It is significantly better than traditional methods and provides an effective technical means for monitoring the status of electric motors in power plants.
作者
曾繁威
ZENG Fanwei(National Energy Penglai Power Generation Co.,Ltd.,Yantai 264000,China)
出处
《通信电源技术》
2025年第19期219-221,共3页
Telecom Power Technology
关键词
通信信号
电动机异常识别
小波包分解
communication signals
abnormal recognition of electric motors
wavelet packet decomposition
