Kumar, R. R. and Cirrincione, Giansalvo and Cirrincione, Maurizio and Tortella, A. and Andriollo, M. (2018) A Topological and Neural Based Technique for Classification of Faults in Induction Machines. [Conference Proceedings]
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Official URL: https://ieeexplore.ieee.org/document/8549509/autho...
Abstract
This paper presents a data driven approach where at first the most significant features of the three phase current signal are analyzed and then a Curvilinear Component based analysis (CCA), which is a nonlinear manifold learning technique, is performed to compress and interpret the feature behaviour. Finally, a multi-layer perceptron network is used to develop a classifier. The effectiveness of the developed model is verified experimentally with data provided on-line and in real-time.
| Item Type: | Conference Proceedings |
|---|---|
| Subjects: | T Technology > TA Engineering (General). Civil engineering (General) T Technology > TK Electrical engineering. Electronics Nuclear engineering |
| Divisions: | School of Information Technology, Engineering, Mathematics and Physics (STEMP) |
| Depositing User: | Fulori Nainoca - Waqairagata |
| Date Deposited: | 27 Jan 2021 12:03 |
| Last Modified: | 27 Jan 2021 12:03 |
| URI: | http://repository.usp.ac.fj/id/eprint/12579 |
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