A novel intelligent fault diagnosis method using entropy-based rough sets and its application

Fault diagnosis is a complex problem that concerns effective decision-making. Carrying out timely system diagnosis whenever a failure symptom is detected would help to reduce system maintenance time and improve the overall productivity. However, with the increased complexity of equipments, the task of fault diagnosis has become increasingly difficult and its complexity almost unmanageable using traditional techniques. In this paper, a new fault diagnostic rule acquisition method is proposed based on rough sets theory, and an intelligent fault diagnosis system is designed. The results of a fault diagnosis example show that the proposed method is correct and effective, and can avoid the fault diagnosis dimensional disaster problem.