基于时序分析的气阀机构故障诊断研究

Study of Fault Diagnosis for Valve Train Based on Time-Sequence Analysis

通过模拟柴油机气阀机构的两种常见的主要故障:气阀漏气和气门间隙异常。采集气缸盖表面的振动信号,应用时序分析方法进行缸盖振动信号的AR谱估计,再从其AR谱中提取出可用于实际诊断的故障特征参数,最后利用欧氏距离判别函数进行故障状态识别。结果表明该方法是可行的,便于实现气阀机构故障的在线实时监测与诊断。

By simulating two kinds of main fault of a valve train, which are the gas leak and abnormal lash, the vibration signals of a cylinder head have been measured. Based on the time-sequence analysis method, the AR spectrums of cylinder head vibration signals are computed. Some parameters extracted from the AR spectrum are used for diagnosis. At last, the Euclidean distance is used to diagnose the valve train faults. The results show that the method is feasible and effective on achieving the on-line motoring and the diagnosis of valve train faults.