Tsyokhla, Igor (2017) Health Monitoring Techniques for High Availability Drives. PhD thesis, University of Sheffield.
Abstract
The growing number and need for high availability drives in the modern world places high importance on reliability and operational availability. Part of the solution to the increased requirements on availability involves monitoring degradation associated with machine failure, diagnosing the mode of failure and predicting into the future to a possible time to failure. Broad multi-disciplinary knowledge is required to understand drive ageing and implement monitoring systems. This research reviews the failure modes associated with high availability drives, in particular with regards to low voltage random wound permanent magnet inverter driven machines. The main failure modes are presented, with analysis of available literature regarding machine failure. Gaps in literature are identified and the most common failure modes of the low voltage machine, bearing and winding damage are presented. Currently the area of least understanding in the field of drive health monitoring involves the measurement and analysis of winding insulation failure. The modes of insulation failure are investigated in detail and a new model for ground-wall insulation is developed. Methods to measure insulation ground-wall insulation have been reviewed, and a new method has been developed to monitor the ground-wall insulation health, during machine operation, using common-mode current inherent in inverter driven machines during operation. To expand the knowledge of insulation failure, the novel insulation health monitoring method is used to monitor four stators during an accelerated ageing test, representing monitoring of insulation of real machine lifetimes. The results are analysed and additional testing is presented in order to develop the monitoring system for standard industry drives. The major conclusion from results indicates that insulation degradation progression follows a deterministic trend, with clearly defined threshold of failure, allowing prognosis of lifetime based on monitored parameters. Future work recommendations are made to expand on the findings during the course of research.
Metadata
Supervisors: | Jiabin, Wang and Zi-Qiang, Zhu |
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Awarding institution: | University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Electronic and Electrical Engineering (Sheffield) |
Identification Number/EthosID: | uk.bl.ethos.736536 |
Depositing User: | Mr Igor Tsyokhla |
Date Deposited: | 01 Mar 2018 09:45 |
Last Modified: | 25 Sep 2019 20:03 |
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