Incipient fault detection of industrial pilot plant machinery via acoustic emission

Numerous condition monitoring techniques and identification algorithms for detection and diagnosis of faults in industrial plants have been proposed for the past few years. Motors are one of the common used elements in almost all plant machinery. They cause the machine failure upon getting faulty. Therefore advance and effective condition monitoring techniques are required to monitor and detect the motor 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 motors used in chemical process pilot plant. A real time measurement system is developed. It utilizes MatLAB to process and analyze the data to provide valuable information regarding the process being monitored.