Research of elevator fault diagnosis based on decision tree and rough set

With the development of urbanization, more and more attention has been put on the safety and reliability of elevators. The elevator faults influence the effectiveness of whole mechanical transmission system, even lead to serious injuries. It is vital that real-time monitoring of the elevator status and accurate fault diagnosis to satisfy the high safety demand. In this study, an intelligent fault diagnosis approach is proposed, which combine the decision tree with rough set theory. First, the basic knowledge of decision tree and rough set techniques is briefly introduced which consists of classifier selection and decision rules. Next, this paper discussed the developed decision strategy and reasoning process in detail. Finally, the elevator fault diagnosis system is constructed, the results indicates the presented method can provide quick location of faults and solutions to deal with the problem.