基于模糊聚类算法的精炼过程真空系统故障诊断

Fault Diagnosis for Vacuum Metallurgical System by Way of Fuzzy Clustering

针对大型真空冶金系统(DVMS)的故障点多、故障征兆不明显且要求其故障诊断快速、准确的特点,提出了一种基于模糊聚类算法的智能诊断模型·该模型具有很强的自学习、自组织能力适用于大型复杂真空系统的故障诊断·在介绍了模糊聚类算法的理论同时,给出了模糊故障诊断的步骤·以RH KTB真空冶金系统的智能故障诊断为例给出了模糊诊断的实际过程·通过分析证实了该算法对大型复杂真空冶金系统智能故障诊断的有效性·

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.