Fault Diagnosis of Engine Misfire Based on Genetic Optimized Support Vector Machine

摘要：

In this paper an intelligent algorithm for com men misfire fault of automobile engines is proposed, in which the support vector machine(SVM) is used to extract the volume fractions of the automobile emission and to improve the accuracy of fault diagnosis, the genetic algorithms(GA) is adopted to optimize the parameters of SVM algorithm. Simulation results demonstrate GA-SVM algorithm can obtain satisfied classification result, the diagnosis speed and accuracy by GA-SVM algorithm are better than traditional SVM algorithm. The result shows that the GA-SVM algorithm has a very high accuracy for small sample fault diagnosis, thus the proposed algorithm is suitable for mechanical fault diagnosis of misfire fault of automobile engines.

关键词： component Misfire Fault diagnosis Support vector machine Genetic algorithms

作者: DiLu Wenjuan Dou

作者单位: College of Electrical and Electronic Engineering Harbin University of Science and Technology Harbin,P.R.China

会议类型: 国际会议

会议名称: The 6th International Forum on Strategic Technology(IFOST 2011)(第六届国际战略技术论坛)

会议地点: 哈尔滨

会议语种:英文

页码: 250-253

在线出版日期: 2011-08-22（万方平台首次上网日期，不代表论文的发表时间）