基于智能方法的电机故障诊断技术综述  

Survey of motor fault diagnosis based on intelligent methods

作　　者：秦凯[1] 边莉[1] 张宁[1] 

机构地区：[1]黑龙江科技大学电气与控制工程学院,哈尔滨150022

出　　处：《工业仪表与自动化装置》2016年第1期19-22,共4页Industrial Instrumentation & Automation

摘　　要：随着人工智能技术的快速发展,越来越多的国内外学者不断提出了基于智能方法的电机故障诊断技术,主要包括专家系统、人工神经网络、粗糙集理论、贝叶斯网络、支持向量机等。该文对这些方法的理论概念、各自的优缺点和研究成果分别作了简单分析,最后探讨了电机故障诊断领域的发展趋势。With the rapid development of artificial intelligence technology,more and more scholars constantly proposed motor fault diagnosis technology based on intelligent methods,including expert systems,artificial neural network,rough set theory,Bayesian networks,support vector machines and so on.In this paper,theoretical concepts of these methods,their advantages and disadvantages,and the research results were made by a simple analysis,and finally discusses the development trends in the field of motor fault diagnosis.

关 键 词：电机故障诊断 智能方法 研究现状 发展趋势 

分 类 号：TM307[电气工程—电机]