基于数据驱动的火电厂关键辅机设备故障诊断技术  

Data-driven Fault Diagnosis Technology for Key Auxiliary Equipment in Thermal Power Plants

作　　者：肖琦 林杰 XIAO Qi;LIN Jie(National Energy Group Electric Power Safety Monitoring Center,Nanjing 210046,China;Guoneng Changyuan Jingmen Power Generation Co.,Ltd.,Jingmen 448000,China)

机构地区：[1]国家能源集团电力安全监察中心,江苏南京210046 [2]国能长源荆门发电有限公司,湖北荆门448000

出　　处：《电工技术》2025年第2期204-206,212,共4页Electric Engineering

摘　　要：随着信息技术和数据科学的发展,数据驱动的故障诊断技术成为研究热点。针对火电厂关键辅机设备的故障诊断问题,展开了基于数据驱动的故障诊断技术研究。通过对锅炉引风机振动信号的特征提取与选择分析,探讨了数据预处理、特征提取、特征选择等关键技术,以期提高故障诊断的准确性和效率,进而提升火电厂的运维水平和竞争力。With the development of information technology and data science,data-driven fault diagnosis technology has become a research hotspot.In this paper,a data-driven fault diagnosis technology is carried out for the fault diagnosis of key auxiliary equipment in thermal power plants.Based on the feature extraction and selection analysis of the vibration signal of the boiler induced draft fan,this paper discusses the key technologies such as data preprocessing,feature extraction,and feature selection,in order to improve the accuracy and efficiency of fault diagnosis,and then improve the operation and maintenance level and competitiveness of thermal power plants.

关 键 词：数据驱动 数据预处理 特征提取 特征选择 故障诊断 

分 类 号：TM621[电气工程—电力系统及自动化]