Study of Automobile Electric Controlled System Fault Diagnosis Based on Classification Pattern Recognition

摘要：

The analysis of data flow from electric controlled system of On-Board Diagnosis shows that sensor and actuator fault could be separated obviously, and then use Neural Network and D-S evidence information fusing method for final recognition. The result shows that, the method based on classification fault recognition could not only promote the precision, but also could promote the efficiency on some degree.

关键词： Electric controlled system Neural Network Fusing Data flow Classification Pattern recognition

作者: Zhang Lili Chu Jiangwei Zou bencun

作者单位: Department of traffic college Northeast forestry university,CHINA

会议类型: 国际会议

会议名称: 2010 IEEE信息与自动化国际会议(ICIA 2010)

会议地点: 哈尔滨

会议语种:英文

页码: 1-6

在线出版日期: 2010-06-20（万方平台首次上网日期，不代表论文的发表时间）