Vehicle Fault Diagnosis Technology Based on Multi-Information Fusion

摘要：

　　An information fusion fault diagnosis approach is proposed for vehicle fault diagnosis in this paper.It is based on RBF neural network for data level fusion diagnosis and D-S evidence theory for decision level fusion diagnosis.Using for coolant temperature sensor,oxygen sensor,manifold absolutely pressure sensor ageing fault,the results show that with the increase of input source number,fusion diagnosis precision is improved; And with RBF neural network diagnosis as a source of evidence for decision fusion,the precision of the fusion diagnosis is improved up to 90%,and the reliability of the final diagnosis results is also increased.

关键词： vehicle fault diagnosis information fusion intelligent diagnosis RBF neural network D-S evidence theory

作者: Cao Kai Li Kai Fan Zhirong Wu Xiaolu Yue Yi”e

作者单位: Dongfeng Motor Corporation Technical Center

会议类型: 国内会议

会议名称: 2015中国汽车工程学会年会

会议地点: 上海

会议语种:英文

页码: 814-817

在线出版日期: 2015-10-01（万方平台首次上网日期，不代表论文的发表时间）