摘要
开展机械设备的故障诊断对保障设备的稳定运行和企业的安全生产具有重要意义。故障诊断的准确率在很大程度上受所提取特征质量、诊断模型参数的影响,因此采用优化算法进行特征优选、寻找模型最优参数是提高诊断准确率的关键。介绍了3种经典智能优化算法和3种新型智能优化算法的原理、基本运算过程及应用现状;总结了算法的优缺点,提出了改进算法;重点分析了各算法在机械故障诊断中的具体作用,并对未来智能优化算法在故障诊断领域的研究方向进行了展望。
The fault diagnosis of mechanical equipment is of great significance to ensure the stable operation of equipment and the safe production of enterprises.The accuracy of fault diagnosis is greatly affected by the quality of extracted features and the parameters of diagnosis model,so it is the key to improve the diagnosis accuracy to optimize the features and find the optimal parameters of the model through optimization algorithms.The principle,basic operation process and application status of three classical intelligent optimization algorithms and three new intelligent optimization algorithms are introduced.The advantages and disadvantages of the algorithms are summarized,and the improved algorithms are proposed.The specific functions of each algorithm in mechanical fault diagnosis are analyzed emphatically.The research directions of intelligent optimization algorithms in the field of fault diagnosis are prospected.
作者
洪晓翠
段礼祥
杨晓光
黄谦
HONG Xiao-cui;DUAN Li-xiang;YANG Xiao-guang;HUANG Qian(College of Safety and Ocean Engineering,China University of Petroleum,Beijing 102249,China;CNPC Engineering Technology R&D Company Ltd.,Beijing 102206,China;China Oilfield Services Ltd.,Sanhe 065201,China)
出处
《测控技术》
2021年第7期1-8,共8页
Measurement & Control Technology
基金
国家自然科学基金资助项目(51674277)
中石油重大工程专项课题(2018E-2101)。
关键词
智能优化算法
机械故障诊断
特征选择
参数优化
综述
intelligent optimization algorithm
mechanical fault diagnosis
feature selection
parameter optimization
review
