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Acoustic Emission Techniques for Condition Monitoring and Diagnosis of Rotating Machines

ADAM ELMALEEH, MOHAMMED ABDALLA (2009) Acoustic Emission Techniques for Condition Monitoring and Diagnosis of Rotating Machines. PhD thesis, Universiti Teknologi PETRONAS.

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Detection of abnormalities and defects in rotating machines is of prime importance for industry and equipment. It avoids the occurrence of unplanned down time of machines that causes serious damage and costly downtime. Several condition monitoring techniques have been applied to improve the plant reliability and reduce the downtime. Generally, bearing represents the commonly used part in all rotating machines and equipment. Various rotating machine problems are encountered during plant and equipment operation. These include overload, unbalance, misalignment and over speed. Any of these problems can cause the bearings to deteriorate. It is therefore necessary to detect and diagnose the bearing faults in order to avoid serious problems which could lead to catastrophic machine failure. This thesis explores the effectiveness of acoustic emission (AE) technique for incipient detection of faults related to bearings. To understand the pattern of acoustic signals a series of measurements are performed in an experimental test rig which is developed to examine the bearings health condition. Initially a number of experiments are conducted for a collection of healthy bearings. Each bearing is tested at various motor speeds and loads. Consequently, significant amounts of acoustic data are recorded as reference. Measurements are extended for poorly lubricated and seeded defect bearings which are created by electrical discharge machine. Comparison of the results indicated that the amplitudes of AE signals provide valuable information regarding bearings health condition. On the other hand, fast Fourier transforms implemented for the acquired time domain signals have significantly distinguished between the normal, onset, and defective bearings. The study shows the importance of couplant grease in the transmission ability of the high frequency acoustic signals. The AE technique is implemented 111 an industrial plant to monitor and diagnose the operating condition of the rotating machinery. A couple of AE measurements are conducted on motors and pumps used in chemical process plant. The results obtained discriminate between the machines working at normal conditions and that start to deteriorate. Statistical methods are used to recapitulate the data obtained to demonstrate the significance and valuable characteristics of acoustic signals. In this regards, the statistical analyses are carried out for the time domain acoustic data acquired from the experimental test rig. The results clearly differentiate between normal and defective bearings.

Item Type: Thesis (PhD)
Academic Subject : Academic Department - Electrical And Electronics - Instrumentation and Control - Modeling and Optimization - Acoustic Emission for condition monitoring
Subject: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions: Engineering > Electrical and Electronic
Depositing User: Users 2053 not found.
Date Deposited: 29 Oct 2013 10:49
Last Modified: 25 Jan 2017 09:44
URI: http://utpedia.utp.edu.my/id/eprint/10020

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