一种基于广义S变换增强的柴油机失火故障特征提取方法

doi:10.3969/j.issn.1001-2222.2017.02.012

车用发动机 ›› 2017, Vol. 0 ›› Issue (2) : 67-71. DOI: 10.3969/j.issn.1001-2222.2017.02.012

栏目

一种基于广义S变换增强的柴油机失火故障特征提取方法

贾翔宇1,2，贾继德3，梅检民3，张帅1，吴春志1

作者信息 +

Identification Method of HEV Driving Condition Based on Wavelet Filtering and PSO Algorithm

GUO Hailong1,2，ZHANG Yongdong1,2， ZHANG Shengbin1

Author information +

文章历史 +

摘要

为有效提取柴油机缸盖振动信号失火故障特征，提出一种基于广义S变换增强的柴油机失火故障特征提取方法。首先根据柴油机燃烧过程与配气相位的关系对信号进行等角度重采样，然后利用广义S变换对信号进行消噪处理，并按工作循环将信号的周期性瞬态特征进行同步增强。通过仿真信号验证和某柴油机缸盖振动信号的实例应用，结果表明，此方法能有效地提取柴油机缸盖振动信号的失火故障特征，实现失火故障的准确诊断。

Abstract

The recognition method of driving condition for the parallel series HEV based on wavelet filtering and PSO algorithm was put forward to identify the realtime road slope and vehicle load changes effectively so that the driver could adjust his driving behavior in time through the control strategy of driving system. The identification model of vehicle driving condition was established and the optimization objective function was determined by the least square method. Then the recognition
principle of driving condition based on wavelet filtering and PSO algorithm was studied. Finally, the recognition test of driving condition with the method was
conducted. The wavelet filtering, the recognition of driving road slope and vehicle load and the wavelet refiltering of vehicle test data were further conducted. The results show that the absolute average value of relative error for vehicle load and road slope is 2.71% and 3.85% respectively. Therefore, the proposed method is feasible.

导出引用

贾翔宇1，贾继德，梅检民，张帅，吴春志. 一种基于广义S变换增强的柴油机失火故障特征提取方法[J]. 车用发动机. 2017, 0(2): 67-71 https://doi.org/10.3969/j.issn.1001-2222.2017.02.012

GUO Hailong，ZHANG Yongdong， ZHANG Shengbin. Identification Method of HEV Driving Condition Based on Wavelet Filtering and PSO Algorithm[J]. Vehicle Engine. 2017, 0(2): 67-71 https://doi.org/10.3969/j.issn.1001-2222.2017.02.012