Application of PCA and SVM in Fault Diagnosis of Mine Hoist

摘要

This paper studies the application of principal component analysis (PCA) and support vector machines (SVM) in fault diagnosis of mine hoist system. In this paper, the PCA is used for feature extraction and data reduction from original features of gearbox. With the features reduced from gearbox and the features from hydraulic system and wire rope, the training of multi-class SVM is carried out using the multi-class optimization algorithm based on one class and is applied to perform the faults identification. The results show that this method using PCA has the better performance of classification process than that without PCA.