SAS与EPS集成系统传感器和ECU的故障诊断方法

摘要

In order to solve the problem of the on-line fault diagnosis on automotive Semi-Active Suspension ( SAS) and Electric Power Steering ( EPS) integrated system, Wavelet analysis method is proposed and applied to the fault diagnosis of sensors and ECU on SAS and EPS integrated system.According to the sudden change characteristics of voltage signals for sensors and ECU under the failure status, the sudden change information could be detected with singularity detection principle of Wavelet analysis.In order to make the detection more accurately, the voltage signals de-noise was carried out first with the wavelet threshold method, then, the denoised volt-age signals were detected.At last, the fault diagnosis trial studies of torque sensors and ECU in the system were carried out as exam-ples.The results prove that Wavelet analysis method can effectively restrain the noise of signal and precisely detect the fault information on time.It has great engineering significance to the safe operation and fault diagnosis of the integrated control system of vehicle.%为解决汽车半主动悬架(Semi-Active Suspension,SAS)与电动助力转向(Electric Power Steering,EPS)集成系统在线故障诊断的问题,提出将小波分析方法应用到SAS与EPS集成系统传感器和ECU的故障诊断中.首先根据故障状态下传感器和ECU输出电压信号的突变特性,利用小波分析奇异性检测原理检测出突变信息.随后为能更精确地检测出突变信息,先使用小波阈值法对电压信号消噪,再对消噪后的电压信号进行检测.最后以SAS与EPS集成系统中扭矩传感器和ECU故障诊断为例进行试验研究.结果表明,小波分析方法能有效抑制信号噪声,并准确检测出故障和故障发生时刻,对集成控制系统的安全运行及故障诊断具有重要的工程应用意义.