基于安全聚类算法的挖掘机故障诊断研究

Research on Excavator Fault Diagnosis Based on Safety Cluster Algorithm

对挖掘机迅速、准确进行监测,有效进行挖掘机故障实时诊断在大型工程中成为一种迫切要求。文章提出一种安全性和相关性相结合的安全聚类算法,并在聚类过程中生成一棵安全二叉树,利用支持向量机和二叉树对挖掘机故障实时监测。实践证明这种方法不仅保证了故障诊断的正确率,而且可以让引起严重后果的故障得到优先诊断。

Quickly and accurately monitoring the excavators, the effective implementation of real- time fault diagnosis of excavators become an urgent requirement. This paper presents a safety combined with the relevant clustering algorithm, and in the proeess of clustering, generates a safety - binary tree. Making use of support vector machines and binary tree to achieve excavator real - time monitoring. Practice has proved that this meth- od not only guarantees the accuracy of fault diagnosis, and can cause more serious consequences of the failure diagnosis can be given priority.