基于非线性小波变换的汽油机爆震强度识别  

Knock Intensity Identification for a Gasoline Engine Based on Nonlinear Wavelet Transform

作　　者：李宁[1] 周瑞[2] 

机构地区：[1]上海第二工业大学智能制造与控制工程学院,上海201209 [2]中国舰船研究设计中心,上海201108

出　　处：《内燃机学报》2018年第1期83-89,共7页Transactions of Csice

基　　金：国家自然科学基金资助项目(51305250);上海市教委创新资助项目(14YZ153)

摘　　要：为提高利用振动信号检测汽油机爆震强度的精度,提出了一种基于非线性小波变换的爆震强度识别方法.首先,采用非线性小波变换对振动信号进行分解,提取出爆震特征.然后,在包含爆震特征的小波细节分量上计算一组能够表征爆震强度的时域统计特征参数.最后,将这些统计特征参数输入到人工智能分类器进行爆震强度识别.对某汽油机进行了爆震台架试验,并对提出的方法进行了验证.结果表明:非线性小波变换可以清晰地从缸盖振动信号中检测出微弱的爆震冲击特征;同时,采用支持向量机能够获得更优的爆震强度识别精度和泛化性能.To increase knock diagnosis accuracy by the vibration signal measured from engine cylinder head, a knock intensity identification method based on nonlinear wavelet transform （NWT） was proposed. First, the vibration signals were decomposed by the NWT to extract the oscillations induced by knocking combustion. Then, a series of parame- ters with temporal statistical characteristics were calculated from the resultant sub-band wavelet details that contain knocking information. Finally, these temporal statistical parameters were fed into the classifiers to identify the knock conditions. Knocking combustion experiments were carried out on a gasoline engine and the proposed method was tested. Experiment results show that the NWT enables the detection of weak impacts induced by knocking combustion. At the same time, a better knock intensity identification performance can be achieved by using support vector machine （SVM）.

关 键 词：汽油机 爆震 非线性小波变换 支持向量机 

分 类 号：TK411.22[动力工程及工程热物理—动力机械及工程]