基于形态分量分析的变工况齿轮箱故障诊断研究

Study on the Fault Diagnose of Gearbox Under Varied Working Condition based on Morphological Component Analysis

齿轮箱变工况运行时表现为转速和负载的变化,其振动信号是非线性的多分量信号,变工况齿轮箱故障诊断是研究难点。首先使用数字微分的阶次跟踪方法对原始振动信号按计算得到等角度重采样时刻插值,将非平稳的振动信号转化为角域平稳信号;然后使用形态分量分析(MCA)方法从角域信号中分离出冲击、简谐分量与噪声成分,提取齿轮箱非线性、多分量信号中的故障特征;再对冲击分量做角域平均突出故障特征,最后进行瞬时功率谱分析识别齿轮是否有故障。实验分析表明,使用此方法能根据瞬时功率谱分布的阶次和角度范围识别故障,适用于变工况下的故障齿轮检测。

The operation of gearbox is under a varied working condition with the change of speed and load,and the vibration signal is non-linear and multi-components,so it＇ s difficult to realization of gearbox fault diagnose in varied working condition. Firstly,The original vibration signal interpolated by uniform angle re-sampling time through order tracking based on numerical differentiation,which transforms non-stationary vibration signals into angle domain stationary signal. Subsequently,the shock component,harmonic component and noise component are separated from angular domain stationary signal through morphological component analysis（MCA）,which can extract the fault feature from non-linear and multi-component signal in gearbox.Then,the angle domain averaging of shock component highlight the fault characteristic. Finally,by using instantaneous power spectrum（IPS） to identify failure of gearbox. The experimental results show that,using this method,the distribution of IPS in domain of angle and order can identify gear faults,and further testing the method also apply to gearbox fault diagnose under the condition of variable condition.