Vibration signal analysis using histogram features and support vector machine for gear box fault diagnosis

Abstract

This paper discusses about the extraction of histogram features from the vibration signal of the different conditions of the gear box under investigation, and the application of machine learning method, support vector machine in machine condition monitoring and diagnostics. This paper aims at using classification methods for fault diagnosis of the gear box under investigation. In this paper fault diagnostics of spur bevel gear box is treated as a pattern classification problem. The major steps in pattern classification are feature extraction, and classification. This work investigates the use histogram features and support vector machine for classification. The results show that the developed method can reliably diagnose different conditions of the gear box.