关键词: 真空冶金, 模糊聚类, 智能, 故障诊断, 自学习

Abstract: An intelligent fault diagnosis model based on fuzzy clustering algorithm is put forward aiming at the high-duty vacuum metallurgical system of which the possible faults take place frequently and unwarnedly and need quick and exact fault diagnosis. The model is highly self-learning and self-organizing especially applicable for the fault diagnosis to heavy-duty and complicated vacuum systems. Describing the theory of fuzzy clustering algorithm, the paper presents the procedure of fuzzy fault diagnosis, with an actual diagnosis process given as an example to show the intelligent fault diagnosis for RH-KTB vacuum metallurgical system. Thus, effectiveness of the algorithm is proved through an analysis of the exemplification.