Hu, R., Wang, J. orcid.org/0000-0003-4870-3744, Mills, A. et al. (2 more authors) (2019) Detection and classification of turn fault and high-resistance connection fault in inverter-fed permanent magnet machines based on high-frequency signals. In: Journal of Engineering. The 9th International Conference on Power Electronics, Machines and Drives (PEMD 2018), 17-19 Apr 2018, Liverpool, UK. Institution of Engineering and Technology (IET) , 4278 -4282.
Abstract
Winding turn fault and high-resistance connection (HRC) fault will lead to different consequences and require different mitigation actions. In this study, the differentiating features between a turn fault and HRC fault are analysed and compared in a three-phase surface-mounted permanent magnet machine fed by the inverter with pulse-width-modulation voltages. The resultant high-frequency components in both voltages and currents are utilised for the fault detection and classification based on the high-frequency impedance and ripple current, without requiring modifications to the machine or interface design. Extensive simulations show that this method is capable of fault detection and classification in both transient and steady-state operations.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2019 The Author(s). This is an open access article published by the IET under the Creative Commons Attribution -NonCommercial License (http://creativecommons.org/licenses/by-nc/3.0/) |
Keywords: | permanent magnet motors; invertors; permanent magnet machines; fault diagnosis; inverter-fed permanent magnet machines; resultant high-frequency components; different mitigation actions; winding turn fault; three-phase surface-mounted permanent magnet machine; high-frequency impedance; fault detection; pulse-width-modulation voltages; classification; ripple; HRC fault; different consequences; high-frequency signals; high-resistance connection fault |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Automatic Control and Systems Engineering (Sheffield) The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Electronic and Electrical Engineering (Sheffield) |
Funding Information: | Funder Grant number ROLLS-ROYCE PLC (UK) 4600177781 |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 03 Jul 2019 15:53 |
Last Modified: | 03 Jul 2019 16:15 |
Status: | Published |
Publisher: | Institution of Engineering and Technology (IET) |
Refereed: | Yes |
Identification Number: | 10.1049/joe.2018.8253 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:147873 |