Brushless synchronous generator turn-to-turn short circuit fault detection using multilayer neural network
Stator winding short circuit is one of the faults that occur frequently in electrical machines. Therefore, fault detection and elimination in electric drive systems is necessary for safety-critical applications in order not to cause catastrophic failure to the machine in a short time. This paper rev...
| Main Authors: | , , , |
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| Other Authors: | |
| Format: | Conference Paper |
| Language: | English |
| Published: |
2021
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/146694 |
| _version_ | 1811695518031544320 |
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| author | Tun, Pyae Phyo Kumar, Padmanabhan Sampath Pratama, Ryan Arya Liu, Shuyong |
| author2 | 2018 Asian Conference on Energy, Power and Transportation Electrification (ACEPT) |
| author_facet | 2018 Asian Conference on Energy, Power and Transportation Electrification (ACEPT) Tun, Pyae Phyo Kumar, Padmanabhan Sampath Pratama, Ryan Arya Liu, Shuyong |
| author_sort | Tun, Pyae Phyo |
| collection | NTU |
| description | Stator winding short circuit is one of the faults that occur frequently in electrical machines. Therefore, fault detection and elimination in electric drive systems is necessary for safety-critical applications in order not to cause catastrophic failure to the machine in a short time. This paper reviews recent fault detection and diagnosis techniques that use signal analysis, model-based techniques and artificial intelligence machine diagnosis methods. Then, feedforward neural network will be trained, tested and validated whether or not this artificial neural network can classified healthy and different severity inter-turn short circuit levels by using per unit RMS 3 phases current and voltage quantities as well as fundamental and third harmonic components of current and voltage. |
| first_indexed | 2024-10-01T07:24:44Z |
| format | Conference Paper |
| id | ntu-10356/146694 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T07:24:44Z |
| publishDate | 2021 |
| record_format | dspace |
| spelling | ntu-10356/1466942021-03-06T20:11:28Z Brushless synchronous generator turn-to-turn short circuit fault detection using multilayer neural network Tun, Pyae Phyo Kumar, Padmanabhan Sampath Pratama, Ryan Arya Liu, Shuyong 2018 Asian Conference on Energy, Power and Transportation Electrification (ACEPT) Rolls-royce Singapore Pte Ltd Energy Research Institute @ NTU (ERI@N) Rolls-Royce@NTU Corporate Lab Engineering::Electrical and electronic engineering Brushless Synchronous Generator Power Generation Stator winding short circuit is one of the faults that occur frequently in electrical machines. Therefore, fault detection and elimination in electric drive systems is necessary for safety-critical applications in order not to cause catastrophic failure to the machine in a short time. This paper reviews recent fault detection and diagnosis techniques that use signal analysis, model-based techniques and artificial intelligence machine diagnosis methods. Then, feedforward neural network will be trained, tested and validated whether or not this artificial neural network can classified healthy and different severity inter-turn short circuit levels by using per unit RMS 3 phases current and voltage quantities as well as fundamental and third harmonic components of current and voltage. Accepted version 2021-03-05T04:58:42Z 2021-03-05T04:58:42Z 2019 Conference Paper Tun, P. P., Kumar, P. S., Pratama, R. A., Liu, S. (2019). Brushless synchronous generator turn-to-turn short circuit fault detection using multilayer neural network. Proceeding of 2018 Asian Conference on Energy, Power and Transportation Electrification (ACEPT). doi:10.1109/ACEPT.2018.8610686 9781538681367 https://hdl.handle.net/10356/146694 10.1109/ACEPT.2018.8610686 2-s2.0-85062075659 en © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at: https://doi.org/10.1109/ACEPT.2018.8610686. application/pdf |
| spellingShingle | Engineering::Electrical and electronic engineering Brushless Synchronous Generator Power Generation Tun, Pyae Phyo Kumar, Padmanabhan Sampath Pratama, Ryan Arya Liu, Shuyong Brushless synchronous generator turn-to-turn short circuit fault detection using multilayer neural network |
| title | Brushless synchronous generator turn-to-turn short circuit fault detection using multilayer neural network |
| title_full | Brushless synchronous generator turn-to-turn short circuit fault detection using multilayer neural network |
| title_fullStr | Brushless synchronous generator turn-to-turn short circuit fault detection using multilayer neural network |
| title_full_unstemmed | Brushless synchronous generator turn-to-turn short circuit fault detection using multilayer neural network |
| title_short | Brushless synchronous generator turn-to-turn short circuit fault detection using multilayer neural network |
| title_sort | brushless synchronous generator turn to turn short circuit fault detection using multilayer neural network |
| topic | Engineering::Electrical and electronic engineering Brushless Synchronous Generator Power Generation |
| url | https://hdl.handle.net/10356/146694 |
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