一种滚动轴承故障状态诊断方法  

A method for diagnosing fault status of rolling bearings

作　　者：崔奔 郭盼盼 张文斌[2] Cui Ben;Guo Panpan;Zhang Wenbin(School of Mechanical and Electrical Engineering,Kunming University of Science and Technology,Kunming 650500,China;Key Laboratory of Mechanical Performance Analysis and Optimization of Plateau in Yunnan Province,College of Engineering,Honghe University,Mengzi 661199,China)

机构地区：[1]昆明理工大学机电工程学院,昆明650500 [2]红河学院工学院云南省高校高原机械性能分析与优化省重点实验室,蒙自661199

出　　处：《电子测量技术》2023年第7期60-66,共7页Electronic Measurement Technology

基　　金：国家自然科学基金(51769007);云南省地方本科高校基础研究联合专项重点项目(202001BA070001-002);云南省高校重点实验室建设计划(2018ZD022)项目资助。

摘　　要：针对滚动轴承故障受噪声污染大,故障特征不明显,导致的故障诊断困难问题,提出了一种新的滚动轴承故障诊断方法。首先利用基尼指数对滚动轴承进行健康状态评估,并对状态异常的振动信号采用最优参数最大相关峭度解卷积进行降噪预处理以突出冲击成分,计算预处理信号的层次熵组成特征矩阵,最后采用布谷鸟算法优化支持向量机相关参数,并完成滚动轴承故障状态的智能诊断。通过实验分析验证了所提方法的可行性,且具有较高的准确率。Aiming at the problem of fault diagnosis caused by noise pollution and the vague of fault characteristic frequency.A new method for fault diagnosis of rolling bearings is proposed.Firstly,the Gini Index(GI) is used to evaluate the health status of rolling bearings,and the vibration signal with abnormal state is used for noise reduction preprocessing using the optimal parameter Maximum Correlated Kurtosis Deconvolution(MCKD) to highlight impact component.Then,calculate the hierarchical entropy(HE)of the preprocessed signal to form a feature matrix.Finally,the cuckoo search algorithm is used to optimize the relevant parameters of the support vector machine,and the intelligent diagnosis of the fault state of the rolling bearing is completed.The feasibility of the proposed method is verified by experimental analysis,and it has a high accuracy.

关 键 词：基尼指数 最大相关峭度解卷积 布谷鸟算法 支持向量机 滚动轴承 故障诊断 

分 类 号：TN911.7[电子电信—通信与信息系统]