高功率密度柴油机气门间隙故障信号提取

摘要

为有效地从实测的高功率密度柴油机机体表面振动信号中提取气门间隙故障特征,设计开发了高功率密度柴油机械振动信号收集装置,提出使用聚合经验模态分解(EEMD)结合相关系数法对高功率密度柴油机故障信号进行预处理.然后,运用信息熵进行特征提取.通过试验表明,聚合经验模态分解原始信号可以得到更加有效的特征参数.%To extract the characteristics of valve clearance fault from the high power density diesel engine surface vibration signals,we have designed a high power density diesel mechanical vibration signal collec-tion device,and make the use of Ensemble Empirical Mode Decomposition(EEMD) combined with corre-lation coefficient method for pretreatment of high power density diesel engine signals. Then, the Fractal Fuzzy Entropy is used to extract the feature. Experiments indicated that the diagnosed results of all samples conform to actualities. And the method can get the feature parameter effectively.