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Detecting mechanical faults in bearings and machinery has long been recognized as being important for preventing catastrophic failure and effective maintenance planning. The human senses of sound and touch were the first mechanisms used to detect machinery problems. Electronic sensors have since offered the ability to feel and listen to machinery with more precision, at more locations, and over more time than was ever before possible. Interpretation of the electronic signals delivered by sensors has provided the maintenance engineer with the diagnostic information necessary to pinpoint bearing faults, thus enabling a more efficient and predictable maintenance effort. However, skilled and trained personnel have been required to effectively interpret this diagnostic information. As electronic sensors have become more sophisticated, and also have the diagnostic techniques, leading to the ability of earlier detection of failures with less required skill. This project proposes an implementation of bearing fault monitoring system by using acoustic emission (AE). The signal is captured and analyzed by MATLAB software. Generally this project is carried Oft by detecting ultrasonic waves captured by AE sensor of tested bearing and interprets the data which mean either the bearing is healthy or havin~ defect. The benefit of having early detection of bearing fault will be able to save maintenance cost and fso human life.

Item Type: Final Year Project
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: 06 Nov 2013 10:55
Last Modified: 25 Jan 2017 09:42
URI: http://utpedia.utp.edu.my/id/eprint/10171

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