HOC与EMD结合的齿轮损伤检测研究

Gear damage detection based on higher order cumulant combined with empirical mode decomposition

结合高阶累积量(HOC)与经验模态分解(EMD)方法的各自优点,提出了一种新的HOC与EMD相结合齿轮损伤故障检测方法。将采集到的齿轮系统信号先通过经验模态分解方法分解成3层不同频段信号,将各频率段的特征信号进行粗略分离,再对每一层信号进行高阶累积量谱分析,抑制了系统噪声,突出信号的损伤与故障特征。据此分别对在4级转速300 r/min、900 r/min、1200 r/min、1500r/min下采集到的各自6种信号:无故障信号、齿根短裂纹故障信号、齿根长裂纹故障信号、分度圆短裂纹故障信号、分度圆长裂纹故障信号、齿面磨损故障信号等进行了分析。研究表明,该方法不但能有效地区分和诊断低速和高速不同运转状态下的各种齿轮故障,而且也能识别某些故障的故障损伤程度。

Combining higher order cumulant（HOC） with Empirical Mode Decomposition（EMD）,a new gear damage detection method is proposed,which possesses both the benefits of HOC and EMD.To restrain system noise and protrude fault features of the signals,the acquired signal is decomposed to three-layer signals that have respectively different frequency bands,and then higher order cumulant analysis is performed on every layer signal.At four kinds of speed： 300 r/min,900 r/min,1 200 r/min and 1 500 r/min,six kinds of signals are acquired and analyzed,which include signal without fault,signal with tooth root short crack,signal with tooth root long crack,signal with pitch line short crack,signal with pitch line long crack and signal with tooth face attrition.Study results show that this method not only can be used to identify various faults in low speed state and high speed state,but also can be used to identify the damage level of some faults.