支持向量机在提升机故障诊断中的应用研究

Study and application of support vector machines in fault diagnosis of hoist

鉴于支持向量机的优越性及提升机的故障特点,提出将支持向量机应用到提升机的故障智能诊断中。该方法专门针对小样本集合设计,能够在小样本情况下获得较大的推广能力,而且模型简单。首先对采集的故障信号采取信息融合方式进行特征提取,以获得特征向量。在此基础上通过多类分类支持向量机对提升机故障进行分类,建立故障诊断模型。试验结果表明,该方法具有较高的诊断精度,取得了比较令人满意的结果。

In view of the superiority of support vector machines and the characteristics of the fault hoist. A novel.fault diagnosis method based on support vector machines is presented in this paper. The method is special designed for small sample set, and commendable generaliza- tion ability can be obtained. Firstly feature information is extracted via information combination method, then support vector machines is adopted to realize patter recognition and correlation. Finally, on the basis of this, the fault diagnosis model is established through the SVM multi-classification. The method ensures the higher accuracy in the diagnosis. The results are satisfactory and prove this method is effective and commendable.