Title :
Base on Hybrid Reasoning Mechanism Fans of Coal Fault Diagnosis Expert System
Author :
Meng, Li ; Cong, Wang ; Xinli, Bai
Author_Institution :
China Univ. of Min. & Technol., Beijing
Abstract :
It is necessary to guarantee that timely diagnosis of fans of coal fault is for mine safety production in enterprises. To establish fans of coal fault diagnosis expert system is a kind of effective way for improving fans fault diagnosis. The roughness set is applied to fans fault expert system for knowledge; this way can improve the objectivity of mining knowledge, which to establish effectively fans fault diagnosis rules. The reasoning machine adopts the mixed reasoning mechanism which is based rules and examples, consequently achieved the function of expert system to self-learning and self-improvement. After fans of coal fault diagnosis expert system is put in to use, the operation and maintenance of fans is significantly improved.
Keywords :
case-based reasoning; coal; condition monitoring; diagnostic expert systems; fans; fault diagnosis; mining industry; safety; case-based reasoning; coal mine production; expert system; fans; fault diagnosis; hybrid reasoning mechanism; mine safety; mining knowledge; roughness set; self improvement; self learning; Diagnostic expert systems; Displacement measurement; Fans; Fault diagnosis; Frequency measurement; Product safety; Production; Sensor systems; Velocity measurement; Vibration measurement; Expert System; Fan of Coal; Fault Diagnosis;
Conference_Titel :
Electronic Measurement and Instruments, 2007. ICEMI '07. 8th International Conference on
Conference_Location :
Xi´an
Print_ISBN :
978-1-4244-1136-8
Electronic_ISBN :
978-1-4244-1136-8
DOI :
10.1109/ICEMI.2007.4350972
