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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_ | 1864030189463273473 |
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| collection | WordPress RSS FRELIP Feed Integration |
| container_title | Autonomous Intelligent Systems |
| description | |
| discipline_display | Engineering & Technology |
| discipline_facet | Engineering & Technology |
| format | Online Article RSS Article |
| genre | Journal Article |
| id | rss_article:42847 |
| institution | FRELIP |
| journal_source_facet | Autonomous Intelligent Systems |
| 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 Computer Science & IT Engineering & Technology |
| sub_discipline_display | Computer Science & IT |
| sub_discipline_facet | Computer Science & IT |
| subject_display | — — — — — — Artificial Intelligence Computer Science & IT Engineering & Technology — — — — — — Artificial Intelligence Computer Science & IT Engineering & Technology |
| subject_facet | — — — — — — Artificial Intelligence Computer Science & IT Engineering & Technology |
| title | Comparative analysis of feature selection and classification techniques for robust broken rotor bar diagnosis in induction motors using current and vibration signals |
| 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_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_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 Computer Science & IT Engineering & Technology |
| url | https://link.springer.com/article/10.1007/s43684-025-00113-0 |