Classification of induction machine faults by K-nearest neighbor
New diagnosis method of induction motor faults based on classification of the current waveforms is presented in this paper. This method is composed of two sequential processes: a feature extraction and a rule decision. The diagnosis is realized the detection of different faults - bearing fault, stat...
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| Published in | 2011 7th International Conference on Electrical and Electronics Engineering (ELECO) pp. I-363 - I-366 |
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| Main Authors | , , , |
| Format | Conference Proceeding |
| Language | English |
| Published |
IEEE
01.12.2011
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| Subjects | |
| Online Access | Get full text |
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| Abstract | New diagnosis method of induction motor faults based on classification of the current waveforms is presented in this paper. This method is composed of two sequential processes: a feature extraction and a rule decision. The diagnosis is realized the detection of different faults - bearing fault, stator fault and rotor fault. K-nearest neighbor (K-NN) is used as decision criterion. The flexibility of this method allows an accurate classification independent from the level of load. This method is validated on a 5.5-kW induction motor test bench. |
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| AbstractList | New diagnosis method of induction motor faults based on classification of the current waveforms is presented in this paper. This method is composed of two sequential processes: a feature extraction and a rule decision. The diagnosis is realized the detection of different faults - bearing fault, stator fault and rotor fault. K-nearest neighbor (K-NN) is used as decision criterion. The flexibility of this method allows an accurate classification independent from the level of load. This method is validated on a 5.5-kW induction motor test bench. |
| Author | Bouguerne, A. Medoued, A. Boukadoum, A. Lebaroud, A. |
| Author_xml | – sequence: 1 givenname: A. surname: Bouguerne fullname: Bouguerne, A. organization: Electr. Eng. Dept., Univ. Mentouri Constantine, Constantine, Algeria – sequence: 2 givenname: A. surname: Lebaroud fullname: Lebaroud, A. email: lebaroud@yahoo.fr organization: Electr. Eng. Dept., Skikda Univ., Skikda, Algeria – sequence: 3 givenname: A. surname: Medoued fullname: Medoued, A. organization: Electr. Eng. Dept., Skikda Univ., Skikda, Algeria – sequence: 4 givenname: A. surname: Boukadoum fullname: Boukadoum, A. organization: Electr. Eng. Dept., Skikda Univ., Skikda, Algeria |
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| Snippet | New diagnosis method of induction motor faults based on classification of the current waveforms is presented in this paper. This method is composed of two... |
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| SubjectTerms | Euclidean distance Feature extraction Gravity Kernel Stators Support vector machine classification Vectors |
| Title | Classification of induction machine faults by K-nearest neighbor |
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