摘要
针对行星齿轮箱实际工况中存在多种频率耦合无法直接提取故障特征频率的问题,提出一种基于樽海鞘群算法优化变分模态分解(SSA-VMD)结合2.5维谱的故障诊断方法。运用SSA优化VMD的参数;运用自相关系数对分解信号进行重构,降低噪声的干扰;最后运用2.5维谱对重构信号中的频率耦合进行解耦运算。搭建行星齿轮箱磨损故障全生命周期实验台采集振动信号,运用提出的方法解耦出参与耦合的故障频率成分,揭示了行星齿轮箱磨损故障演化规律。研究结果表明:随着磨损故障程度的加深,磨损故障特征频率明显增多。
Aiming at the problem of not directly extracting the fault from multiple frequency couplings in the actual working conditions of the planetary gearbox,a fault diagnosis method based on salp swarm algorithm optimized variational mode decomposition(SSA-VMD)combined with 2.5D spectrum was proposed.The SSA was used to optimize the parameters of VMD;the decomposed signal was reconstructed to reduce noise interference by the autocorrelation coefficient;and finally the 2.5D spectrum was used to decouple the frequency coupling in the reconstructed signal.A planetary gearbox wear fault full life cycle test bench was set up to collect vibration signals,the proposed method was used to decouple the frequency components of the faults participating in the coupling,and the evolutionary law of the wear fault of the planetary gearbox was revealed.The research results show that with the deepening of the degree of wear faults,the frequency of wear faults characteristic increases significantly.
作者
毕浩程
蒋章雷
吴国新
刘秀丽
王红军
栾忠权
BI Haocheng;JIANG Zhanglei;WU Guoxin;LIU Xiuli;WANG Hongjun;LUAN Zhongquan(The Ministry of Education Key Laboratory of Modern Measurement and Control Technology,Beijing Information Science&Technology University,Beijing 100192,China)
出处
《机床与液压》
北大核心
2023年第6期181-187,共7页
Machine Tool & Hydraulics
基金
国家自然科学基金面上项目(61973041,51975058)
北京信息科技大学“勤信人才”培育计划项目(QXTCP C202120)。
关键词
变分模态分解
樽海鞘群算法
2.5维谱
行星齿轮箱
故障诊断
Variational mode decomposition(VMD)
Salp swarm algorithm(SSA)
2.5D spectrum
Planetary gearbox
Fault diagnosis
作者简介
毕浩程(1997-),男,硕士研究生,研究方向为机械设备状态监测与故障诊断。E-mail:1661309931@qq.com;通信作者:蒋章雷,男,博士,副研究员,研究方向为机电装备状态监测与故障诊断、工业互联网与智能制造。E-mail:Jiang_Z hanglei@126.com。
