Incipient fault detection of industrial pilot plant machinery via acoustic emission

Elmaleeh, M.A.A. and Saad, N. and Awan, M. (2012) Incipient fault detection of industrial pilot plant machinery via acoustic emission. In: UNSPECIFIED.

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Abstract

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. © 2012 IEEE.

Item Type: Conference or Workshop Item (UNSPECIFIED)
Additional Information: cited By 1; Conference of 2012 8th International Symposium on Mechatronics and its Applications, ISMA 2012 ; Conference Date: 10 April 2012 Through 12 April 2012; Conference Code:91051
Uncontrolled Keywords: AE signals; Chemical process; Detection and diagnosis; Identification algorithms; Incipient fault detection; Machine failure; Monitoring system; Monitoring techniques; Plant machinery; Process plants; Real time measurements; Rotating machine; Time and frequency domains; Unplanned shutdowns, Algorithms; Condition monitoring; Failure (mechanical); Frequency domain analysis; Machinery; MATLAB; Motors; Pilot plants; Plant shutdowns; Time domain analysis, Acoustic emissions
Depositing User: Mr Ahmad Suhairi UTP
Date Deposited: 09 Nov 2023 15:51
Last Modified: 09 Nov 2023 15:51
URI: https://khub.utp.edu.my/scholars/id/eprint/2946

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