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Title: Intelligent health monitoring of power transmission systems
Author: Onsy, Ahmed Mahmoud Helmy
ISNI:       0000 0004 2742 5738
Awarding Body: University of Newcastle Upon Tyne
Current Institution: University of Newcastle upon Tyne
Date of Award: 2009
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Power transmissions are one of the most important parts of any mechanical system and in order to achieve the reliable operation of these systems, effective maintenance strategies must be used. Condition based maintenance strategies (CBM) are currently gaining in popularity due to their effectiveness in reducing maintenance costs; however, these require reliable monitoring techniques. Vibration, acoustic emission, and oil debris analysis have been studied to establish which can best support the operation of CBM in tracking the condition of the operating system, classifying faults, and predicting the onset of failure. These studies have shown it is necessary to adapt an intelligent approach to solving the problem. This study presents a novel approach to monitoring gear fatigue failures by combining (fusing) vibration, acoustic emission, and oil debris analysis using fuzzy logic. An 'intelligent health monitoring system' (lHMS) has been implemented on a back-to-back gearbox which can be adapted to monitor the behaviour of transmission systems in automotive, aircraft, wind turbine, and industrial machinery. The study describes the design and operation of the online IHMS, and demonstrates its ability in detecting transmission gear defects, thus preventing sudden unexpected failures. The results support the recent trend in using IHMSs in CBM strategies. KEY WORDS: Transmission, Intelligent Health Monitoring, Condition Based Maintenance, Acoustic Emission, Vibration, Oil Analysis, Fuzzy Logic, Sensors Fusion.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available