Title :
Research on Health Diagnosis Method Based on Fuzzy Sets and Information Fusion
Author :
Wang, Xin ; Ma, Qing-lin
Author_Institution :
Sch. of Electr. Eng. & Autom., Henan Polytech. Univ., Jiaozuo, China
Abstract :
This paper presents a new online health diagnosis method of the mine hoister based on the multi-sensor information fusion and fuzzy sets. A calculating method of the mass function for this system based on the fuzzy set was given. The correlation coefficients are replaced by the membership function using the fuzzy theory. The mass functions are obtained according to the object types. This method is suitable for the online health diagnosis systems. By using the Dempster-Shafer (D-S) evidential theory, the information fusion is carried out. In the end, we used the above methods in the health diagnosis system of the mine hoister. The diagnosis result indicates that these methods can improve the accuracy and reliability of health diagnosis of the mine hoister effectively.
Keywords :
fuzzy set theory; inference mechanisms; medical computing; sensor fusion; uncertainty handling; Dempster-Shafer evidential theory; fuzzy sets; membership function; mine hoister; multisensor information fusion; online health diagnosis method; Artificial intelligence; Automation; Computational intelligence; Fault diagnosis; Fuzzy sets; Fuzzy systems; Gold; Mining industry; Sensor fusion; Sensor systems; D-S evidential theory; Information fusion; fuzzy sets; health diagnosis;
Conference_Titel :
Artificial Intelligence and Computational Intelligence, 2009. AICI '09. International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-3835-8
Electronic_ISBN :
978-0-7695-3816-7
DOI :
10.1109/AICI.2009.183