摘要
随着现代机械装备复杂性、综合化、智能化程度的不断提高,在机械装备故障预测与健康管理(Prognostics Health Management,PHM)中,对机械装备进行智能故障诊断是一个必要环节,是保证后续健康状态评估和故障预测可靠性的基础。综述了近年来国内外学者在机械装备智能故障诊断研究方面的探究成效,回顾了传统故障诊断方法研究成果,介绍了现代智能故障诊断方法研究现状,展望了机械装备智能故障诊断发展趋势。分析表明,随着机械装备逐步向多功能化、智能化、绿色化方向发展,机械装备智能故障诊断技术将迎来新的挑战;融合智能感知、深度学习、强化学习等人工智能的智能故障诊断技术有望成为机械装备状态监测与故障诊断的一把利器,为机械装备智能故障诊断与预测提供新的探索路径,在科学研究和工程应用中具有广阔的应用前景。
With the continuous improvement of modern mechanical equipment to the degree of complexity,integration and intelligence,in the prognostics and health management of mechanical equipment,intelligent fault diagnosis is a necessary link.It is the basis for ensuring the reliability of subsequent health assessment and failure prediction.In this article,the research achievements of domestic and foreign scholars in the research of intelligent fault diagnosis of mechanical equipment were reviewed in recent years.The research results of traditional fault diagnosis methods were presented.And the research status of modern intelligent fault diagnosis methods was introduced.Moreover,the development trend for intelligent fault diagnosis of mechanical equipment is prospected.The analysis indicates that with the development of mechanical equipment to multi-functional,intelligent and green,the intelligent fault diagnosis technology of mechanical equipment will face new challenges.The intelligent fault diagnosis technology that integrates artificial intelligence such as intelligent perception,deep learning,and reinforcement learning is expected to become a powerful tool for condition monitoring and fault diagnosis of mechanical equipment.It can provide a new exploration path for the intelligent fault diagnosis and prediction of mechanical equipment,and has a broad application prospects in scientific research and engineering application.
作者
李洪
刘培邦
汤胜楠
朱勇
周岭
Li Hong;Liu Peibang;Tang Shengnan;Zhu Yong;Zhou Ling(Fujian Fuqing Nuclear Power Co.,Ltd.,Fuqing 350318,China;China Nuclear Power Operation Technology Co.,Ltd.,Wuhan 430000,China;National Research Center of Pumps,Jiangsu University,Zhenjiang 212013,China)
出处
《电子技术应用》
2021年第S01期380-389,共10页
Application of Electronic Technique
关键词
机械装备
智能故障诊断
人工智能
研究现状
发展趋势
mechanical equipment
intelligent fault diagnosis
artificial intelligence
research status
development trend
作者简介
李洪(1987-),男,本科,高级工程师,主要研究方向:核电厂数字化仪控;刘培邦(1982-),男,硕士研究生,高级工程师,主要研究方向:核电厂仪控系统仿真验证;通信作者:汤胜楠(1988-),女,博士研究生,工程师,主要研究方向:智能信息处理与故障诊断,E-mail:tangsn6635@126.com。
