电站风烟系统设备故障智能在线预警与诊断系统研究与应用  

Research and Application of Intelligent Online Early Warning and Diagnosis System for Equipment Faults of Power Station Air and Gas System

作　　者：张春晖 李栋华 王念 ZHANG Chunhui;LI Donghua;WANG Nian(Shanghai Oriental Maritime Affairs Engineering Technology Co.,Ltd.,Shanghai 200011,China)

机构地区：[1]上海市东方海事工程技术有限公司,上海200011

出　　处：《电力大数据》2025年第2期74-82,共9页Power Systems and Big Data

摘　　要：在当今电力行业数字化与智能化的转型浪潮中,对火电机组低成本运营以及精细化管理的要求也越来越高。该文分析了建设电站智能风烟系统的必要性,并详细设计了一个智能风烟系统一体化云平台;基于机器学习和统计学方法,对电站风烟系统设备故障智能在线预警与诊断方法进行了研究与应用,为电站智能风烟系统的建设提供了有益的参考。In today's wave of accelerated transformation of the power industry towards digitalization and intelligence,the demands for low-cost operation and refined management of thermal power units are becoming higher and higher.This paper analyzes the necessity of constructing an intelligent air and gas system for power plants and designs an integrated cloud platform for such a system in detail.At the same time,an online intelligent early warning and diagnosis system for equipment faults of power station air and gas system is studied and applied based on machine learning and statistical methods,which provides a useful reference for the construction of intelligent air and gas system of power stations.

关 键 词：智能风烟系统 故障诊断 故障预警 大数据 

分 类 号：TM621[电气工程—电力系统及自动化]