Study on Hybrid System for Fault Diagnosis Based on ANN-CBR Approach
This paper studies on the case indexing and retrieval algorithm based on artificial neural network in case-based reasoning fault diagnosis system. The cases that include certain fault are saved in a same subset case base and indexed by an artificial neural network classifier. When a new case comes, the neural network classifier quickly obtains a subset of objective cases. Then, optimal objective case can be obtained in the subset by case-based reasoning. Thus the matching and calculating between the new case and all of the existing cases are avoided, the speed and efficiency of case-based reasoning fault diagnosis system are enhanced.
fault diagnosis case based reasoning neural network hybrid system indexing
LI Yan ZHENG Silong
Ordnance Engineering College, Shijiazhuang, 050003 P.R.China
国际会议
北京
英文
2007-08-05（万方平台首次上网日期，不代表论文的发表时间）