基于SSA-IWT-EMD的滚动轴承故障诊断方法  

Fault diagnosis method of rolling bearings based on SSA-IWT-EMD

作　　者：雷春丽[1] 焦孟萱 樊高峰 刘世超 薛林林 李建华[1] LEI Chunli;JIAO Mengxuan;FAN Gaofeng;LIU Shichao;XUE Linlin;LI Jianhua(School of Mechanical and Electrical Engineering,Lanzhou University of Technology,Lanzhou 730050,China;Ineos Sinopec Tianjin Petrochemicals Limited,Tianjin 300280,China;Yunnan Wenshan Aluminum Co.,Ltd.,Wenshan 663000,China)

机构地区：[1]兰州理工大学机电工程学院,兰州730050 [2]中石化英力士(天津)石化有限公司,天津300280 [3]云南文山铝业有限公司,文山663000

出　　处：《北京航空航天大学学报》2025年第4期1152-1162,共11页Journal of Beijing University of Aeronautics and Astronautics

基　　金：国家自然科学基金(51465035);甘肃省自然科学基金(20JR5RA466);兰州理工大学红柳一流学科建设项目。

摘　　要：针对小波阈值降噪不充分及经验模态分解(EMD)特征频率提取不明显的问题,提出一种基于麻雀搜索算法-改进小波阈值-EMD(SSA-IWT-EMD)的滚动轴承故障诊断方法。引入2个调节因子,提出一种IWT函数,克服了传统软硬阈值的缺点,并运用SSA对其各参数进行全局寻优,实现滚动轴承信号降噪。提出一种综合指标P对EMD产生的分量进行选取重构,突出信号的故障特征信息。采用包络谱分析实现轴承的故障诊断。仿真和实测结果验证了所提方法的有效性;同时与单一指标选取分量的方法及文献方法进行对比,说明了综合指标P和所提方法具有更强的降噪能力及特征提取能力,包络谱幅值及倍频成分更明显,可以更好地实现对滚动轴承的故障诊断。Wavelet threshold denoising is insufficient,and feature frequency extraction of empirical mode decomposition(EMD)is unclear.To address these issues,a fault diagnosis method of rolling bearings based on sparrow search algorithm-improved wavelet threshold-EMD(SSA-IWT-EMD)was proposed.Firstly,two adjustment factors were introduced,and an IWT function was presented to overcome the shortcomings of traditional soft and hard thresholds.The SSA was used to globally optimize the parameters of the IWT to reduce the noise of rolling bearing signals.Secondly,a comprehensive index P was put forward to select and reconstruct the components generated by EMD,so as to highlight the fault feature information of the signals.Finally,the fault diagnosis of bearings was realized by envelope spectrum analysis.The simulation and experimental results verified the effectiveness of the proposed method.At the same time,the comparison with the single index component selection method and the literature method indicated that the comprehensive index P and the method proposed in this paper had stronger denoising ability and feature extraction ability,and the envelope spectrum amplitude and frequency doubling component were more obvious,which could better realize the fault diagnosis of rolling bearings.

关 键 词：滚动轴承 改进阈值 综合指标 经验模态分解 故障诊断 

分 类 号：TH133.33[机械工程—机械制造及自动化]