Condition monitoring using image processing

Vibrations have been traditionally associated with trouble in machines. However vibrations are merely symptoms of good or bad mechanical behaviour. Today these symptoms are used to detect solve many mechanical problems in rotating machines. These machines play the most important role in any industry. Faults results in motor failure causing breakdown and great loss of production due to shutdown of industry. This in turn increases the running cost of machine with reduction in efficiency. Therefore, early detection of fault with diagnosis of its root cause is needed. This project is an approach for fault detection of rotating machine using orbit analysis of shaft and image processing. Several works have been focused on detecting early mechanical and electrical faults before damage appears in the motor. All the techniques are very effective their way. In this project, a new methodology is proposed for identifying if there is a fault in motor. Through image processing based on orbital analysis, different faults will be studied, generating characteristically different patterns that are used for fault detection.