The Fault Diagnosis and Monitoring of Rotating Machines by Thermography

Abstract

The thermography is a convenient and versatile diagnosis method for many types of physical asset such as electric equipments, buildings, and mechanical equipments. However, the interpretation of measurements is just by experts until now. This paper describes an intelligent system for rotating machine fault diagnosis based on statistical feature of thermal images through automated algorithm that can detect and classify those defects. It will be evaluated by experimental dataset. By this, the expert system for condition monitoring and diagnosis will be more effective and the scope of discrimination by Expert system will be better with combining the result of automated diagnosis of vibration data.