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作 者:周娟利[1] 王城宇 赵栓峰[3] Zhou Juanli;Wang Chengyu;Zhao Shuanfeng(College of Aeronautical Materials Engineering,Xi'an Aeronautical Polytechnic Institute,Xi'an 710089,China;Hebei Key Laboratory of Electric Machinery Health Maintenance&Failure Prevention,North China Electric Power University,Baoding 071003,China;College of Mechanical Engineering,Xi'an University of Science and Technology,Xi'an 710054,China)
机构地区:[1]西安航空职业技术学院航空材料工程学院,陕西西安710089 [2]华北电力大学河北省电力机械装备健康维护与失效预防重点实验室,河北保定071003 [3]西安科技大学机械工程学院,陕西西安710054
出 处:《机械传动》2024年第9期160-166,共7页Journal of Mechanical Transmission
基 金:陕西省科技厅表面非晶态合金激光3D打印制备技术研究(S2020-JC-YB-2124);西安航空职业技术学院2023年教育教学改革研究项目(23XHJG05)。
摘 要:针对齿轮箱滚动轴承在故障诊断过程中,存在采样数据过大、故障特征提取效果不佳的问题,提出了一种基于最大相关峭度解卷积(Maximum Correlation Kurtosis Deconvolution,MCKD)的正则化正交匹配追踪(Regularized Orthogonal Matching Pursuit,ROMP)算法,用于轴承微弱故障信号的诊断。首先,为实现MCKD和ROMP算法中参数的自适应选择,引入改进的灰狼优化(Improved Grey Wolf Optimization,IGWO)算法;然后,利用IGWO对原始信号进行MCKD降噪处理;最后,利用IGWO-ROMP实现对信号的重构,通过对信号进行包络分析,实现对轴承故障的诊断。仿真信号和实验验证结果表明,该方法能够有效地提取轴承微弱故障成分。为轴承微弱故障信号的诊断提供了一种新思路。In response to the issue of excessive sampling data and poor fault feature extraction performance in the fault diagnosis process of gearbox rolling bearings,a regularized orthogonal matching pursuit(ROMP)algorithm was proposed based on the maximum correlation kurtosis deconvolution(MCKD)for the diagnosis of bearing weak fault signals.Firstly,to achieve adaptive selection of parameters in the MCKD and ROMP algorithms,an improved grey wolf optimization(IGWO)algorithm was introduced.Then,the IGWO was used to denoise the original signal through MCKD processing.Finally,IGWO-ROMP was utilized to reconstruct the signal and diagnose bearing faults through envelope analysis of the signal.Verified by simulation signals and experimental results,this method can effectively extract bearing weak fault components,providing a new approach for the diagnosis of bearing weak fault signals.
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