Title :
Extraction method of decision rules for fault diagnosis from incomplete data based on rough set
Author :
Huang, Wentao ; Zhao, Xuezeng ; Wang, Weijie ; Dai, Lizhou
Author_Institution :
Sch. of Mech. & Electr. Eng., Harbin Inst. of Technol., China
Abstract :
Extracting rules from incomplete data are usually more difficult than extracting rules from complete data in mechanical fault diagnosis. In order to extract simple and effective diagnostic rules from incomplete data, a method to directly extract decision rules for fault diagnosis from incomplete data based on rough set is proposed in this paper. The method realizes an object-oriented reduction approach in an incomplete fault diagnosis decision table using the defined object-oriented discernibility function, and then simple and understandable decision rules are extracted directly from an incomplete fault diagnosis decision table using the obtained all object-oriented reductions. The application of the proposed method is demonstrated by a mechanical fault diagnosis example with incomplete information.
Keywords :
decision tables; fault diagnosis; knowledge acquisition; object-oriented methods; rough set theory; decision rule extraction; decision table; diagnostic rules; fault diagnosis; incomplete data; object oriented discernibility function; object oriented reduction; rough set; Data mining; Fault diagnosis;
Conference_Titel :
Intelligent Control and Automation, 2004. WCICA 2004. Fifth World Congress on
Print_ISBN :
0-7803-8273-0
DOI :
10.1109/WCICA.2004.1342327