电厂化学仪表设备状态监测与故障诊断  

State Monitoring and Fault Diagnosis of Chemical Instrumentation for Power Plants

作　　者：印亮亮 Yin Liangliang(Beijing Guodian Power Co.,Ltd.Dalian Development Zone CHP Plant,Dalian Liaoning 116600)

机构地区：[1]北京国电电力有限公司大连开发区热电厂,辽宁大连116600

出　　处：《中国仪器仪表》2025年第1期93-95,共3页China Instrumentation

摘　　要：随着电力系统自动化水平提高,化学仪表设备在电厂中作用日益重要,其稳定可靠运行对生产安全经济运行至关重要。但仪表设备也面临各种故障风险,一旦发生将导致严重的后果。本文针对电厂化学仪表状态监测与故障诊断问题,系统阐述了相关理论方法。首先介绍了化学仪表分类及应用领域,分析了常见故障模式和影响因素;接着重点论述了基于模型、知识、数据驱动的故障诊断方法,并探讨了故障诊断系统总体设计框架;最后,对大数据分析、智能化诊断、预测性维护等前沿技术应用进行了展望。该研究对提高化学仪表可靠性和安全性具有重要意义。With the increasing level of automation in power systems,chemical instrumentation plays an increasingly important role in power plants,and its stable and reliable operation is crucial for ensuring safe and economical production.However,instrumentation also faces various fault risks,and the occurrence of faults will have serious consequences.This paper systematically expounds on the relevant theories and methods for state monitoring and fault diagnosis of chemical instrumentation in power plants.Firstly,the classification and application fields of chemical instrumentation are introduced,and the common fault modes and influencing factors are analyzed.Then,the model-based,knowledge-based,and data-driven fault diagnosis methods are discussed in detail,and the overall design framework of the fault diagnosis system is explored.Finally,the application of cutting-edge technologies such as big data analysis,intelligent diagnosis,and predictive maintenance is prospected.This research is of great significance for improving the reliability and safety of chemical instrumentation.

关 键 词：化学仪表设备 状态监测 故障诊断 电厂 故障模式 诊断方法 

分 类 号：TM62[电气工程—电力系统及自动化]