Broken Bar Fault Detection Using Taylor–Fourier Filters and Statistical Analysis
Broken rotor bars in induction motors make up one of the typical fault types that are challenging to detect. This type of damage can provoke adverse effects on the motors, such as mechanical and electrical stresses, together with an increase in electricity consumption, causing higher operative costs...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2022-12-01
|
| Series: | Entropy |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1099-4300/25/1/44 |
| _version_ | 1827626160333258752 |
|---|---|
| author | Sarahi Aguayo-Tapia Gerardo Avalos-Almazan Jose de Jesus Rangel-Magdaleno Mario R. A. Paternina |
| author_facet | Sarahi Aguayo-Tapia Gerardo Avalos-Almazan Jose de Jesus Rangel-Magdaleno Mario R. A. Paternina |
| author_sort | Sarahi Aguayo-Tapia |
| collection | DOAJ |
| description | Broken rotor bars in induction motors make up one of the typical fault types that are challenging to detect. This type of damage can provoke adverse effects on the motors, such as mechanical and electrical stresses, together with an increase in electricity consumption, causing higher operative costs and losses related to the maintenance times or even the motor replacement if the damage has led to a complete failure. To prevent such situations, diverse signal processing algorithms have been applied to incipient fault detection, using different variables to analyze, such as vibrations, current, or flux. To counteract the broken rotor bar damage, this paper focuses on a motor current signal analysis for early broken bar detection and classification by using the digital Taylor–Fourier transform (DTFT), whose implementation allows fine filtering and amplitude estimation with the final purpose of achieving an incipient fault detection. The detection is based on an analysis of variance followed by a Tukey test of the estimated amplitude. The proposed methodology is implemented in Matlab using the O-splines of the DTFT to reduce the computational load compared with other methods. The analysis is focused on groups of 50-test of current signals corresponding to different damage levels for a motor operating at 50% and 75% of its full load. |
| first_indexed | 2024-03-09T12:49:53Z |
| format | Article |
| id | doaj.art-4c21ad17bc85445ba3a51842758be4a1 |
| institution | Directory Open Access Journal |
| issn | 1099-4300 |
| language | English |
| last_indexed | 2024-03-09T12:49:53Z |
| publishDate | 2022-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Entropy |
| spelling | doaj.art-4c21ad17bc85445ba3a51842758be4a12023-11-30T22:07:27ZengMDPI AGEntropy1099-43002022-12-012514410.3390/e25010044Broken Bar Fault Detection Using Taylor–Fourier Filters and Statistical AnalysisSarahi Aguayo-Tapia0Gerardo Avalos-Almazan1Jose de Jesus Rangel-Magdaleno2Mario R. A. Paternina3Digital Systems Group, National Institute for Astrophysics, Optics and Electronics, Puebla 72840, MexicoDigital Systems Group, National Institute for Astrophysics, Optics and Electronics, Puebla 72840, MexicoDigital Systems Group, National Institute for Astrophysics, Optics and Electronics, Puebla 72840, MexicoDepartment of Electrical Engineering, National Autonomous University of Mexico, Mexico City 04510, MexicoBroken rotor bars in induction motors make up one of the typical fault types that are challenging to detect. This type of damage can provoke adverse effects on the motors, such as mechanical and electrical stresses, together with an increase in electricity consumption, causing higher operative costs and losses related to the maintenance times or even the motor replacement if the damage has led to a complete failure. To prevent such situations, diverse signal processing algorithms have been applied to incipient fault detection, using different variables to analyze, such as vibrations, current, or flux. To counteract the broken rotor bar damage, this paper focuses on a motor current signal analysis for early broken bar detection and classification by using the digital Taylor–Fourier transform (DTFT), whose implementation allows fine filtering and amplitude estimation with the final purpose of achieving an incipient fault detection. The detection is based on an analysis of variance followed by a Tukey test of the estimated amplitude. The proposed methodology is implemented in Matlab using the O-splines of the DTFT to reduce the computational load compared with other methods. The analysis is focused on groups of 50-test of current signals corresponding to different damage levels for a motor operating at 50% and 75% of its full load.https://www.mdpi.com/1099-4300/25/1/44induction motorbroken barstator currentfault detectionstatistical analysisdigital Taylor–Fourier transform |
| spellingShingle | Sarahi Aguayo-Tapia Gerardo Avalos-Almazan Jose de Jesus Rangel-Magdaleno Mario R. A. Paternina Broken Bar Fault Detection Using Taylor–Fourier Filters and Statistical Analysis Entropy induction motor broken bar stator current fault detection statistical analysis digital Taylor–Fourier transform |
| title | Broken Bar Fault Detection Using Taylor–Fourier Filters and Statistical Analysis |
| title_full | Broken Bar Fault Detection Using Taylor–Fourier Filters and Statistical Analysis |
| title_fullStr | Broken Bar Fault Detection Using Taylor–Fourier Filters and Statistical Analysis |
| title_full_unstemmed | Broken Bar Fault Detection Using Taylor–Fourier Filters and Statistical Analysis |
| title_short | Broken Bar Fault Detection Using Taylor–Fourier Filters and Statistical Analysis |
| title_sort | broken bar fault detection using taylor fourier filters and statistical analysis |
| topic | induction motor broken bar stator current fault detection statistical analysis digital Taylor–Fourier transform |
| url | https://www.mdpi.com/1099-4300/25/1/44 |
| work_keys_str_mv | AT sarahiaguayotapia brokenbarfaultdetectionusingtaylorfourierfiltersandstatisticalanalysis AT gerardoavalosalmazan brokenbarfaultdetectionusingtaylorfourierfiltersandstatisticalanalysis AT josedejesusrangelmagdaleno brokenbarfaultdetectionusingtaylorfourierfiltersandstatisticalanalysis AT mariorapaternina brokenbarfaultdetectionusingtaylorfourierfiltersandstatisticalanalysis |