基于振动信号熵谱的柴油发动机失火故障诊断  

Fault Diagnosis of Diesel Engine Misfire Based on Entropy Spectrum of Vibration Signal

作　　者：张帅 Zhang Shuai(Military Supplies and Energy Quality Supervision Centre,Beijing 100000,China)

机构地区：[1]军需能源质量监督总站,北京100000

出　　处：《内燃机与配件》2022年第8期95-98,共4页Internal Combustion Engine & Parts

摘　　要：利用振动信号对发动机进行失火故障诊断是一种重要手段,但振动信号的平稳性较差,很多故障诊断方法的实际应用效果不佳。为此,提出了基于振动信号熵谱的柴油发动机故障诊断的新方法。利用振动信号获取转速进行等角度重采样,再提取三阶最大熵谱,最后利用模糊c均值聚类得到失火故障类型。利用台架试验,采集不同失火状态下的发动机振动信号进行验证,结果表明:该方法可有效识别失火故障,在车辆不解体检测方面有很大的应用前景。It is an important method to diagnose engine misfire fault by using vibration signal,but the stability of vibration signals is poor,and many fault diagnosis methods are not effective in practical application.Therefore,a new method for diesel engine fault diagnosis based on entropy spectrum of vibration signal is proposed.The vibration signal is used to obtain the rotational speed for equal-angle resampling,and then the third-order maximum entropy spectrum is extracted,and finally,the misfire fault type is obtained by using fuzzy c-means clustering.The engine vibration signals under different misfire conditions were collected on the engine bench,and the results showed that the method can effectively identify misfire faults and has a great application prospect in the field of non-disassembly test.

关 键 词：柴油发动机 故障诊断 振动信号 最大熵谱 聚类分析 

分 类 号：TK428[动力工程及工程热物理—动力机械及工程]