基于SSA改进VMD的轴承复合故障诊断方法研究  

Research on bearing compound fault diagnosis method based on SSA improved VMD

作　　者：张烨 周进节[1] 杨雨竹 Zhang Ye;Zhou Jinjie;Yang Yuzhu(School of Mechanical Engineering,North University of China,Shanxi Taiyuan,030051,China)

机构地区：[1]中北大学机械工程学院,山西太原030051

出　　处：《机械设计与制造工程》2023年第3期97-103,共7页Machine Design and Manufacturing Engineering

摘　　要：关乎整个设备正常运行的滚动轴承极易发生故障,且常是多故障并存,导致轴承复合故障诊断困难。VMD算法对诊断滚动轴承复合故障具有良好的频带分割、抗模态混叠和抑制噪声的优点。但当VMD控制参数[K,α]选取不当时,会造成频带分解失效、轴承复合故障分离不彻底。为此提出基于樽海鞘群算法(SSA)改进VMD的分离诊断方法。采用SSA自适应选取[K,α]对信号进行VMD,通过包络熵和峭度综合筛选敏感IMF,对敏感IMF进行Autogram共振频带提取,采用包络解调提取各自的故障特征频率。通过仿真信号和实测信号验证分析,可知基于SSA优化VMD算法对复合轴承故障有很好的分离诊断能力。Rolling bearings,which are related to the normal operation of the whole equipment,are prone to failure,and often multiple failures coexist,leading to the difficulty of bearing composite fault diagnosis.The VMD algorithm has the advantages of good frequency band segmentation,anti-mode aliasing and noise suppression for the diagnosis of rolling bearing compound faults.However,when the VMD control parameter[K,α]is not selected properly,the problems of frequency band decomposition failure and incomplete bearing compound fault separation can be caused.Therefore,an improved VMD separation and diagnosis method based on salp swarm algorithm(SSA)is proposed.SSA adaptive selection[K,α]is used to carry out VMD for the signal,sensitive IMF is screened by envelope entropy and kurtosis,Autogram resonance band extraction is carried out for sensitive IMF,and envelope demodulation is used to extract the respective fault characteristic frequencies.Through the verification and analysis of simulation signals and measured signals,it is concluded that the optimized VMD algorithm based on SSA has a good separation and diagnosis ability for composite bearing faults.

关 键 词：轴承复合故障 变模态分解 控制参数 樽海鞘群算法 共振频带 包络解调 

分 类 号：TP2[自动化与计算机技术—检测技术与自动化装置]