Wireless Health Monitoring System for Rotor Eccentricity Faults Detection in Induction Machine
Condition monitoring and fault detection of induction machines become an important area of research. Many techniques have been applied in this field including vibration, thermal, chemical and acoustic emission monitoring, but Motor Current Signature Analysis monitoring techniques usually are applied...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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VSB-Technical University of Ostrava
2017-01-01
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| Series: | Advances in Electrical and Electronic Engineering |
| Subjects: | |
| Online Access: | http://advances.utc.sk/index.php/AEEE/article/view/2193 |
| _version_ | 1827947514337165312 |
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| author | Ilias Ouachtouk Soumia El Hani Khalid Dahi |
| author_facet | Ilias Ouachtouk Soumia El Hani Khalid Dahi |
| author_sort | Ilias Ouachtouk |
| collection | DOAJ |
| description | Condition monitoring and fault detection of induction machines become an important area of research. Many techniques have been applied in this field including vibration, thermal, chemical and acoustic emission monitoring, but Motor Current Signature Analysis monitoring techniques usually are applied to detect the various classes of induction machine faults such as rotor, short winding, eccentricity and bearing fault etc. This paper presents a wireless system detection for rotor eccentricity faults in induction machine based on LabVIEW platform. Moreover, it is demonstrated that eccentricity fault generates a series of low frequency components in the form of sidebands around the fundamental frequency and its harmonic. In addition, the amplitudes of those components increase in proportion to the load and fault severity. The Power Spectral Density techniques and Short Time Frequency Transform spectrogram of current signals are used to detect the presence of those fault signatures. |
| first_indexed | 2024-04-09T12:41:09Z |
| format | Article |
| id | doaj.art-c0c5f8056b70467c8cbacd90fd461687 |
| institution | Directory Open Access Journal |
| issn | 1336-1376 1804-3119 |
| language | English |
| last_indexed | 2024-04-09T12:41:09Z |
| publishDate | 2017-01-01 |
| publisher | VSB-Technical University of Ostrava |
| record_format | Article |
| series | Advances in Electrical and Electronic Engineering |
| spelling | doaj.art-c0c5f8056b70467c8cbacd90fd4616872023-05-14T20:50:11ZengVSB-Technical University of OstravaAdvances in Electrical and Electronic Engineering1336-13761804-31192017-01-0115337638210.15598/aeee.v15i3.2193909Wireless Health Monitoring System for Rotor Eccentricity Faults Detection in Induction MachineIlias Ouachtouk0Soumia El Hani1Khalid Dahi2Electrical Laboratory Researche, Ecole Normale Superieure de Enseignement Technique, Mohammed V University, Avenue des Nations Unies, Agdal, Rabat, MoroccoElectrical Laboratory Researche, Ecole Normale Superieure de Enseignement Technique, Mohammed V University, Avenue des Nations Unies, Agdal, Rabat, MoroccoElectrical Laboratory Researche, Ecole Normale Superieure de Enseignement Technique, Mohammed V University, Avenue des Nations Unies, Agdal, Rabat, MoroccoCondition monitoring and fault detection of induction machines become an important area of research. Many techniques have been applied in this field including vibration, thermal, chemical and acoustic emission monitoring, but Motor Current Signature Analysis monitoring techniques usually are applied to detect the various classes of induction machine faults such as rotor, short winding, eccentricity and bearing fault etc. This paper presents a wireless system detection for rotor eccentricity faults in induction machine based on LabVIEW platform. Moreover, it is demonstrated that eccentricity fault generates a series of low frequency components in the form of sidebands around the fundamental frequency and its harmonic. In addition, the amplitudes of those components increase in proportion to the load and fault severity. The Power Spectral Density techniques and Short Time Frequency Transform spectrogram of current signals are used to detect the presence of those fault signatures.http://advances.utc.sk/index.php/AEEE/article/view/2193eccentricitycondition monitoringinduction machinestator current signaturewireless system. |
| spellingShingle | Ilias Ouachtouk Soumia El Hani Khalid Dahi Wireless Health Monitoring System for Rotor Eccentricity Faults Detection in Induction Machine Advances in Electrical and Electronic Engineering eccentricity condition monitoring induction machine stator current signature wireless system. |
| title | Wireless Health Monitoring System for Rotor Eccentricity Faults Detection in Induction Machine |
| title_full | Wireless Health Monitoring System for Rotor Eccentricity Faults Detection in Induction Machine |
| title_fullStr | Wireless Health Monitoring System for Rotor Eccentricity Faults Detection in Induction Machine |
| title_full_unstemmed | Wireless Health Monitoring System for Rotor Eccentricity Faults Detection in Induction Machine |
| title_short | Wireless Health Monitoring System for Rotor Eccentricity Faults Detection in Induction Machine |
| title_sort | wireless health monitoring system for rotor eccentricity faults detection in induction machine |
| topic | eccentricity condition monitoring induction machine stator current signature wireless system. |
| url | http://advances.utc.sk/index.php/AEEE/article/view/2193 |
| work_keys_str_mv | AT iliasouachtouk wirelesshealthmonitoringsystemforrotoreccentricityfaultsdetectionininductionmachine AT soumiaelhani wirelesshealthmonitoringsystemforrotoreccentricityfaultsdetectionininductionmachine AT khaliddahi wirelesshealthmonitoringsystemforrotoreccentricityfaultsdetectionininductionmachine |