Vibration based Fault Diagnosis Techniques for Rotating Mechanical Components: Review Paper

Abstract

A rotating mechanical components in machineries like bearings, gears, pulleys, belt drives etc. are major components in any rotating machinery. The failure of these components leads to downtime of machines and reduction in production. Significant economic losses will be caused due to an unexpected failure of these components. Belt drives are widely employed in various industrial equipment. Finding the early fault symptoms in the belt drive is very important. This can be achieved by various methods. For detecting faults and monitoring the condition of a belt drive, the vibration signal can be used as one of the parameter. Thus, vibration signal can be used as a procedure for predictive maintenance and it is used for machinery maintenance decisions. The changes in vibration signals due to fault can be detected by employing signal processing methods. It can be used to evaluate the health status of the machinery. The nature and severity of the problem can be determined by analysing the vibration signal and hence the failure can be predicted. Signature of the fault in the machine is carried by the vibration signal. It is possible to have early fault detection by analysing these vibration signals. Different signal processing techniques are used for processing these signals. The various techniques used for fault diagnosis based on vibration analysis method are discussed in this paper. The application of the artificial intelligence techniques such as Artificial Neural Network (ANN), fuzzy sets and other emerging technologies are discussed.