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Comparative analysis of feature selection and classification techniques for robust broken rotor bar diagnosis in induction motors using current and vibration signals
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| Published in: | Autonomous Intelligent Systems |
|---|---|
| Format: | Online Article RSS Article |
| Published: |
2025
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| Subjects: | |
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| _version_ | 1868553686305734657 |
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| collection | WordPress RSS FRELIP Feed Integration |
| container_title | Autonomous Intelligent Systems |
| description | |
| discipline_display | Artificial Intelligence |
| discipline_facet | Artificial Intelligence |
| format | Online Article RSS Article |
| genre | Journal Article |
| id | rss_article:83246 |
| institution | FRELIP |
| journal_source_facet | Autonomous Intelligent Systems |
| last_indexed | 2026-06-20T21:40:56.151Z |
| publishDate | 2025 |
| publishDateSort | 2025 |
| record_format | rss_article |
| spellingShingle | Comparative analysis of feature selection and classification techniques for robust broken rotor bar diagnosis in induction motors using current and vibration signals Artificial Intelligence General Artificial Intelligence |
| sub_discipline_display | General |
| sub_discipline_facet | General |
| subject_display | Artificial Intelligence General Artificial Intelligence |
| subject_facet | Artificial Intelligence General Artificial Intelligence |
| title | Comparative analysis of feature selection and classification techniques for robust broken rotor bar diagnosis in induction motors using current and vibration signals |
| title_alt | Análisis comparativo de técnicas de selección de características y clasificación para diagnóstico robusto de barras rotas en motores de inducción usando señales de corriente y vibración Analyse comparative des techniques de sélection de caractéristiques et de classification pour le diagnostic robuste de barres rotoriques cassées dans les moteurs à induction utilisant des signaux de courant et de vibration Análise comparativa de técnicas de seleção de características e classificação para diagnóstico robusto de barras rotóricas quebradas em motores de indução usando sinais de corrente e vibração |
| title_auth | Comparative analysis of feature selection and classification techniques for robust broken rotor bar diagnosis in induction motors using current and vibration signals |
| title_es_txt | Análisis comparativo de técnicas de selección de características y clasificación para diagnóstico robusto de barras rotas en motores de inducción usando señales de corriente y vibración |
| title_fr_txt | Analyse comparative des techniques de sélection de caractéristiques et de classification pour le diagnostic robuste de barres rotoriques cassées dans les moteurs à induction utilisant des signaux de courant et de vibration |
| title_full | Comparative analysis of feature selection and classification techniques for robust broken rotor bar diagnosis in induction motors using current and vibration signals |
| title_fullStr | Comparative analysis of feature selection and classification techniques for robust broken rotor bar diagnosis in induction motors using current and vibration signals |
| title_full_unstemmed | Comparative analysis of feature selection and classification techniques for robust broken rotor bar diagnosis in induction motors using current and vibration signals |
| title_pt_txt | Análise comparativa de técnicas de seleção de características e classificação para diagnóstico robusto de barras rotóricas quebradas em motores de indução usando sinais de corrente e vibração |
| title_short | Comparative analysis of feature selection and classification techniques for robust broken rotor bar diagnosis in induction motors using current and vibration signals |
| title_sort | comparative analysis of feature selection and classification techniques for robust broken rotor bar diagnosis in induction motors using current and vibration signals |
| topic | Artificial Intelligence General Artificial Intelligence |
| url | https://link.springer.com/article/10.1007/s43684-025-00113-0 |