Elevator Motor Fault Diagnosis using Bayesian Belief Fusion and Stator Current Signals

다국어 초록 (Multilingual Abstract)

Fault detection and diagnosis are critical for health operation of elevator system. Aim to realize a real-time and convenient diagnosis for satisfying the requirement of advanced maintenance of elevator system. This paper develops an intelligent fault diagnosis system of elevator motor using a new approach, decision fusion. First, the basic knowledge of fusion techniques are briefly introduced which consist of classifier selection and multi-classifier fusion. Then a new decision fusion system is presented. Next Bayesian belief fusion algorithms are employed in a real-world diagnosis experiment of a faulty elevator motor system. Based on the satisfied results shown in the experiment, a big potential in the real-world application is presented that are effective and cost saving only by analyzing stator current signals using proposed decision fusion system.

목차 (Table of Contents)

• Abstract
• 1. Introduction
• 2. Preliminary knowledge
• 3. Decision fusion system used in elevator motor fault diagnosis
• 4. Results and Discussion
• 5. Conclusions
• References
• Acknowledgment