Title :
A mixed expert system for fault diagnosis
Author :
Wang, Yuan-Hang ; Deng, Chao ; Xiong, Yao ; Wu, Jun
Author_Institution :
Country State Key Lab. of Digital Manuf. Equip. & Technol., Huazhong Univ. of Sci. & Technol., Wuhan, China
Abstract :
Because of the high structure complexity and variety of working condition, it is greatly difficult to fault diagnosis for heavy machines. This paper puts forward a method of fault diagnosis based on mixed expert system, which uses the rules and cases. The architecture and diagnosis flow of the system are both proposed. The knowledge database of fault diagnosis of heavy machine are mainly set up, including the rule database and case database which are respectively based on the “Structure Fault Tree” and breakdown maintenance record. Finally, the prototype system is designed.
Keywords :
expert systems; fault diagnosis; fault trees; machinery; maintenance engineering; mechanical engineering computing; prototypes; case database; diagnosis flow; fault diagnosis; heavy machines; knowledge database; maintenance record; mixed expert system; prototype system; rule database; structure fault tree; working condition; Book reviews; Heavy machine; expert system; fault diagnosis; structure fault tree;
Conference_Titel :
Industrial Engineering and Engineering Management (IE&EM), 2010 IEEE 17Th International Conference on
Conference_Location :
Xiamen
Print_ISBN :
978-1-4244-6483-8
DOI :
10.1109/ICIEEM.2010.5646475