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...
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| Main Authors: | , , , |
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| Other Authors: | |
| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2021
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/146694 |
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| Institution: | Nanyang Technological University |
| Language: | English |
| Summary: | 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. |
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