In chemical processes, fault diagnosis is relatively difficult due to the incomplete prior-knowledge and unpredictable production changes. To solve the problem, a case-based extension fault diagnosis (CEFD) method is ...In chemical processes, fault diagnosis is relatively difficult due to the incomplete prior-knowledge and unpredictable production changes. To solve the problem, a case-based extension fault diagnosis (CEFD) method is proposed combining with extension theory, in which the basic-element model is used for the unified and deep fault description, the distance concept is applied to quantify the correlation degree between the new fault and the original fault cases, and the extension transformation is used to expand and obtain the solution of unknown faults. With the application in Tennessee Eastman process, the result indicates that CEFD method has a flexible fault representation, objective fault retrieve performance and good ability for fault study, providing a new way for diagnosing production faults accurately.展开更多
A mechinery fault diagnosis expert system based on case-based reasoning (CBR) technology was established. The process of the CBR fault diagnosis is analyzed from three main aspects: expression and memory, retrieving a...A mechinery fault diagnosis expert system based on case-based reasoning (CBR) technology was established. The process of the CBR fault diagnosis is analyzed from three main aspects: expression and memory, retrieving and matching, and modification and maintenance of a case. The results indicate that the CBR method is flexible and simple to implement, and it has strong self-studying ability. Using a large enough number of case reasoning sets, it can accumulate the experience of problem solving, avoid the difficulty of knowledge acquisition, shorten the course of solving problems, improve efficiency of reasoning, and save the time of developing.展开更多
基金Supported by the National Natural Science Foundation of China （61104131）.
文摘In chemical processes, fault diagnosis is relatively difficult due to the incomplete prior-knowledge and unpredictable production changes. To solve the problem, a case-based extension fault diagnosis (CEFD) method is proposed combining with extension theory, in which the basic-element model is used for the unified and deep fault description, the distance concept is applied to quantify the correlation degree between the new fault and the original fault cases, and the extension transformation is used to expand and obtain the solution of unknown faults. With the application in Tennessee Eastman process, the result indicates that CEFD method has a flexible fault representation, objective fault retrieve performance and good ability for fault study, providing a new way for diagnosing production faults accurately.
基金Funded by Scientific Research Foundation of PLA General Equipment Department (No.20020214).
文摘A mechinery fault diagnosis expert system based on case-based reasoning (CBR) technology was established. The process of the CBR fault diagnosis is analyzed from three main aspects: expression and memory, retrieving and matching, and modification and maintenance of a case. The results indicate that the CBR method is flexible and simple to implement, and it has strong self-studying ability. Using a large enough number of case reasoning sets, it can accumulate the experience of problem solving, avoid the difficulty of knowledge acquisition, shorten the course of solving problems, improve efficiency of reasoning, and save the time of developing.
