基于ICEEMDAN方法和频率解调的行星齿轮箱故障电流信号特征分析  

Planetary gearbox fault diagnosis via current signature analysis based on ICEEMDAN and frequency demodulation

作　　者：管一臣 童攀 冯志鹏[1] GUAN Yichen;TONG Pan;FENG Zhipeng(School of Mechanical Engineering,University of Science and Technology Beijing,Beijing 100083,China)

机构地区：[1]北京科技大学机械工程学院

出　　处：《振动与冲击》2019年第24期41-47,共7页Journal of Vibration and Shock

基　　金：国家重点研发计划(2018YFC0810500);国家自然科学基金(51475038)

摘　　要：为了从电流信号中准确地提取行星齿轮箱故障特征,提出了基于改进自适应噪声完备集合经验模式分解和频率解调分析的故障诊断方法。通过改进自适应噪声完备集合经验模式分解将感应电机电流信号自适应地分解为一系列本质模式函数;根据故障频率调制供电频率的特性,以瞬时频率最接近供电频率为优选原则,优选出含有故障信息的本质模式函数作为敏感分量;并对敏感分量进行频率解调,通过频率解调谱诊断行星齿轮箱故障。齿轮箱试验分别采集太阳轮、行星轮以及齿圈三种局部故障状态的电机电流信号;信号分析结果表明该方法不仅可以减小定子电流噪声的影响,而且可以有效地提取复杂信号中的故障特征频率。In order to accurately extract gear fault feature of planetary gearboxes from current signals,a fault diagnosis method was proposed based on improved complete ensemble empirical mode decomposition with adaptive noise(ICEEMDAN)and frequency demodulation analysis.Firstly,the complex multi-component induction motor current signal was adaptively decomposed into a series of intrinsic mode functions(IMF)by ICEEMDAN.Then,based on the characteristics of fault frequency modulating supply frequency and the principle of the instantaneous frequency fluctuation around supply frequency,the IMF containing fault information was preferably selected as the sensitive component.Finally,the planetary gearbox fault was diagnosed according to the frequency demodulated spectrum of the sensitive components.The gearbox experiment collected the induction motor current signal with sun,planet and ring partial fault,respectively.The analysis result shows that this method can not only reduce the influence of the noise in stator current,but can also extract the fault frequency feature in complex signals effectively.

关 键 词：行星齿轮箱 故障诊断 频率解调 电机电流特征分析(MCSA) 

分 类 号：TH165.3[机械工程—机械制造及自动化]