基于Daubechies小波分析的汽车电控发动机失火故障诊断信息提取

采用Daubechies （dbN）小波分析方法,对汽车电控发动机的瞬时转速信号进行降噪处理与分析.应用Matlab中的一维小波分析函数,对汽车电控发动机瞬时转速信号进行不同阶数和层数的拟合效果分析,并确定出使原始转速信号失真较小的拟合消失矩阶数（10阶）和层数（3层）;基于发动机瞬时转速的平均值M、瞬时转速的标准差Sd、变异系数作为特征值以及发动机转速数据频率分布图的特点,对电控发动机产生失火状态的故障识别的明显性进行比较.研究结果表明,常用的发动机失火故障的诊断仅是利用断缸法识别转速的变化,而采用dbN小波分析方法可以有效的提取明显表征电控发动机失火故障状态的变异系数及发动机转速数值主频分布特点等信息,可进一步增强对失火故障的识别程度和诊断的准确性.

Diagnosis Information Extraction of Misfire Fault of Vehicle Electronically Controlled Engine Based on Daubechies Wavelet

This paper proposed using Daubechies（dbN） wavelet transform method to reduce noise processing and analyze instanta- neous speed data of vehicle electronically controlled engine. Based on one-dimensional wavelet analysis function in Matlab software, combined with the fitting effect of instantaneous speed data in different orders and layers, we determined that signal distortion was smallest when the number of order and layer was 10 and 3, respectively. Identification of cylinder of misfire diagnosis for vehicle elec- tronically controlled engine was achieved based on 3 types of feature value, i. e. , mean value M, standard deviation Sd, variation coefficient ~p and engine speed frequency distribution characteristics of the data. The results show that commonly used engine misfire fault diagnosis method was only identified using the broken cylinder speed, while using dhN wavelet analysis method can effectively ex- tract the obvious characterization electronically controlled engine misfire condition numerical coefficient of variation and frequency dis- tribution of engine speed and other information, which can further enhance the degree of recognition and diagnostic accuracy.