Title :
Method of fault diagnosis for cold storage system based on probabilistic rough set and SVM
Author :
Ya-li, Liu ; Feng-Hao, Yu ; Sheng-Dong, Chen ; Ming, Mao
Author_Institution :
Dept. of Electr., Naval Petty Officer Acad., Bengbu, China
Abstract :
Proposed a method of fault diagnosis for cold storage system, the method based on probabilistic rough set and support vector machine(SVM). Simplify the uncertain information by using probabilistic rough set of Bayes decision making. Design a multi-level classifier of SVM to fault diagnosis. Research the typical fault set of cold storage system with the proposed method. The results show the accuracy ability of fault diagnosis with the proposed method.
Keywords :
Bayes methods; cold storage; decision making; fault diagnosis; probability; production engineering computing; rough set theory; support vector machines; Bayes decision making; SVM; cold storage system; fault diagnosis method; probabilistic rough set; support vector machine; Data analysis; Decision making; Extraterrestrial measurements; Fault diagnosis; Fuzzy systems; Information analysis; Safety; Stability; Support vector machine classification; Support vector machines; SVM; fault diagnosis; probabilistic rough set;
Conference_Titel :
Information Management and Engineering (ICIME), 2010 The 2nd IEEE International Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4244-5263-7
Electronic_ISBN :
978-1-4244-5265-1
DOI :
10.1109/ICIME.2010.5477747
