Support vector classification for fault diagnostics of an electrical machine
| Autor: | H. Hyotyniemi, Antero Arkkio, S. Poyhonen, Marian Negrea, Heikki N. Koivo |
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| Rok vydání: | 2003 |
| Předmět: |
Electric motor
Learning automata Computer science business.industry Stator Electrical engineering ComputerApplications_COMPUTERSINOTHERSYSTEMS Pattern recognition Fault (power engineering) Finite element method Power (physics) law.invention Magnetic field Support vector machine ComputingMethodologies_PATTERNRECOGNITION law Artificial intelligence business |
| Zdroj: | 6th International Conference on Signal Processing, 2002.. |
| Popis: | Support vector classification (SVC) is applied to fault diagnostics of an electrical machine. Numerical magnetic field analysis is used to provide virtual measurement data from healthy and faulty operation of an electrical machine. Power spectra estimates of the stator current of the motor are calculated with Welch's method, and SVC is applied to distinguish healthy spectrum from faulty spectra. Results are promising. Most of the faults can be classified correctly. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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