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基于神经网络的水电机组智能故障诊断系统
引用本文:陈林刚,韩凤琴,桂中华.基于神经网络的水电机组智能故障诊断系统[J].电网技术,2006,30(1):40-43.
作者姓名:陈林刚  韩凤琴  桂中华
作者单位:华南理工大学,电力学院,广东省,广州市,510640
摘    要:针对现有水电机组状态监测系统功能不完善、不够智能化的缺点,开发了基于神经网络的水电机组智能故障诊断系统,该系统由状态监测和故障诊断两个模块构成,包括数据采集、数据分析、通信和智能故障诊断4部分。与传统故障诊断系统相比具有BP神经网络组成的专家系统,因此具有自学习、自适应和智能化等特点。实验结果表明,此系统的诊断结果准确可靠,具有良好的实用价值。

关 键 词:NULL
文章编号:1000-3673(2006)01-0040-04
收稿时间:2005-08-29
修稿时间:2005-08-29

A Neural Network Based Intelligent Fault Diagnosis System for Hydroelectric Generating Sets
CHEN Lin-gang,HAN Feng-qin,GUI Zhong-hua.A Neural Network Based Intelligent Fault Diagnosis System for Hydroelectric Generating Sets[J].Power System Technology,2006,30(1):40-43.
Authors:CHEN Lin-gang  HAN Feng-qin  GUI Zhong-hua
Affiliation:College of Electrical Engineering, South China University of Technology, Guangzhou 510640, Guangdong Province, China
Abstract:To improve the functions and intelligent extent of existing monitoring system for hydroelectric generating sets,a neural network based intelligent fault diagnosis system for hydroelectric generating sets is developed,which is composed of two modules,namely state monitoring module and fault diagnosis module,and four parts,i.e.,data acquisition,data analysis,communication and intelligent fault diagnosis,is included.Because an expert system based on BP neural network is configured,so the developed diagnosis system possesses the features such as self-study,adaptability and intelligence.Tests show that the diagnosis results by this system are accurate,reliable and practicable.
Keywords:Hydroelectric generating sets  State monitoring  Fault diagnosis  Back-propagation neural network  Expert system
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