摘要
总结了国内外旋转机械系统故障诊断的研究现状及存在的问题,介绍了机械系统故障数据采集和状态监测的常用方法,探讨了模糊理论、神经网络、遗传算法等在诊断决策算法研究中的应用前景,最后指出要发展完善信号提取及处理技术,加强人工智能理论的研究及应用,提高网络集成化水平,进而向与容错控制相结合的方向发展。
The current research situation and existing questions of fault diagnosis of rotary machinery system are summarized. The common methods of data acquisition and condition monitoring for mechanical system fault are introduced. It is discussed that the application prospect about fuzzy theory, neural network, genetic algorithm, etc, which is applied in algorithm research of diagnosis decision. And finally the development direction is pointed out that is developing and perfecting the signal extrac- tion and processing technology, enhancing the research and application of artificial intelligence theory; raising integration level of the network, and then to unify with the fault-tolerant control.
出处
《矿山机械》
北大核心
2008年第12期6-9,共4页
Mining & Processing Equipment
关键词
旋转机械
故障诊断
人工智能
发展综述
Rotary machinery
Fault diagnosis
Artifical intelligence
Development summary
作者简介
车立志，男，1983年生，山东淄博人，在读硕士研究生，控制理论与控制工程专业，主要研究方向：计算机控制与仿真、智能故障诊断。
