Development of acoustic emission diagnostic system for condition monitoring of rotating machines

Numerous condition monitoring (CM) techniques and identification algorithms for detection and diagnosis of rotating machinery faults have been proposed for the past few years. Bearing are the common used elements in almost all rotating machinery. It causes the machine failure upon getting faulty. Therefore advance and effective inspection techniques are required to monitor and detect the bearing problems at incipient stages. This avoids catastrophic machine failure and costly unplanned shutdown. In this paper the acoustic emission (AE) monitoring system is established. It discusses a method based on time and frequency domain analysis of AE signals acquired from bearings assembly. A real time measurement system is developed. It utilizes LabVIEW to process and analyze the data to provide valuable information regarding the process being monitored. ©2008 IEEE.