A Novel Fault Diagnosis Method for Gear Transmission Systems Using Combined Detection Technologies

Abstract

This study focuses on the condition monitoring and fault diagnosis of gear transmission systems. Since the gear transmission systems have been used in very wide applications, such as the aerospace engineering, manufacturing industry, marine engineering, etc., it is crucial to monitor the working condition of the gear transmission systems. For this purpose, a new method has been proposed in this study to investigate the condition monitoring and fault diagnosis of gear transmission systems. In the new method, the oil analysis and vibration analysis have been integrated to collect the fault signals of the gears. Then an intelligent classifier based on the Support Vector Machine (SVM) is adopted to diagnose the fault types of the gears. To verify the proposed approach, the fault experiments have been carried out in a gear fault simulator. The analysis results show that the lubricant information and vibration information can be well used for the accurate fault detection of the gears. The fault diagnosis rate reaches up to 91.7%. Hence, the proposed method can be used in practice for the condition monitoring and fault diagnosis of gear transmission systems.