基于ICEEMDAN和VMD的行星齿轮箱故障特征提取  

Fault Feature Extraction of Planetary Gearbox Based on ICEEMDAN and VMD

作　　者：王莉静 李鸿江 李民生 贾政 WANG Lijing;LI Hongjiang;LI Minsheng;JIA Zheng(School of Control and Mechanical Engineering,Tianjin Chengjian University,Tianjin 300384,China)

机构地区：[1]天津城建大学控制与机械工程学院,天津300384

出　　处：《河北工程大学学报(自然科学版)》2025年第1期105-112,共8页Journal of Hebei University of Engineering:Natural Science Edition

基　　金：天津市自然科学基金资助项目(20YDTPJC00840);天津城建大学研究生教改项目(JG-ZD-2205);天津市研究生科研创新项目(2022SKYZ328)。

摘　　要：提出一种基于改进的自适应噪声完备集合经验模态分解(ICEEMDAN)和变分模态分解(VMD)方法的行星齿轮箱故障特征提取方法。利用ICEEMDAN对信号进行分解,根据分量包络峭度对信号进行筛选重构。基于最大包络谱峰度作为适应度函数,采用麻雀搜索算法对VMD进行参数自适应优化,将重构后的信号分解为多个模态分量。根据分量的包络谱峭度,选取最优分量进行包络解调分析,实现行星齿轮箱故障特征提取。最后,通过实验得到本文所提方法的一致性相关系数在0.4723~0.7936之间,远高于EEMD-WTD方法的0.0881~0.2863和以包络谱为分量选取指标的0.1427~0.2864。A planetary gearbox fault feature extraction method based on improved adaptive noise complete set empirical mode decomposition(ICEEMDAN)and variational mode decomposition(VMD)methods is proposed.The signal was decomposed using ICEEMDAN,and the signal was filtered and reconstructed based on the kurtosis of the component envelope.Based on the maximum envelope spectral kurtosis as the fitness function,the sparrow search algorithm is used to adaptively optimize the parameters of VMD,and the reconstructed signal is decomposed into multiple modal components.Based on the kurtosis of the envelope spectrum of the components,select the optimal component for envelope demodulation analysis to achieve feature extraction of planetary gearbox faults.Finally,the consistency correlation coefficient of the method proposed in this paper was found to be between 0.4723 and 0.7936 through experiments,which is much higher than the EEMD-WTD method’s 0.0881 to 0.2863 and the envelope spectrum selection index’s 0.1427 to 0.2864.

关 键 词：行星齿轮箱 故障诊断 改进的自适应噪声完备集合经验模态分解 变分模态分解 

分 类 号：TG333.17[金属学及工艺—金属压力加工]