A New MLP Approach for the Detection of the Incipient Bearing Damage
In this study, it is aimed to track the aging trend of the incipient bearing damage in an induction motor which is subjected to an accelerated aging process. For this purpose, a new Multilayer perceptron (MLP) neural network approach is introduced. The input signals are extracted from power spectr...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Stefan cel Mare University of Suceava
2010-08-01
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| Series: | Advances in Electrical and Computer Engineering |
| Subjects: | |
| Online Access: | http://dx.doi.org/10.4316/AECE.2010.03006 |
| _version_ | 1818394482009178112 |
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| author | SEKER, S. KARATOPRAK, E. SENGULER, T. |
| author_facet | SEKER, S. KARATOPRAK, E. SENGULER, T. |
| author_sort | SEKER, S. |
| collection | DOAJ |
| description | In this study, it is aimed to track the aging trend of the incipient bearing damage in an induction motor which is subjected to an accelerated aging process. For this purpose, a new Multilayer perceptron (MLP) neural network approach is introduced. The input signals are extracted from power spectral densities (PSD) of the vibration signals taken from a 5-HP induction motor. Principal component analysis (PCA) has been applied to select the best possible feature vectors as a dimensionality reduction purpose. Variance and entropy values are used as the targets of the MLP network. The healthy motor condition was modelled by the MLP network considering all load conditions. The results showed that the incipient bearing damage was clearly extracted by the oscillations of the MLP output error. |
| first_indexed | 2024-12-14T06:01:54Z |
| format | Article |
| id | doaj.art-15cf6ae2223d478a8f7ab89432c5ee41 |
| institution | Directory Open Access Journal |
| issn | 1582-7445 1844-7600 |
| language | English |
| last_indexed | 2024-12-14T06:01:54Z |
| publishDate | 2010-08-01 |
| publisher | Stefan cel Mare University of Suceava |
| record_format | Article |
| series | Advances in Electrical and Computer Engineering |
| spelling | doaj.art-15cf6ae2223d478a8f7ab89432c5ee412022-12-21T23:14:23ZengStefan cel Mare University of SuceavaAdvances in Electrical and Computer Engineering1582-74451844-76002010-08-01103343910.4316/AECE.2010.03006A New MLP Approach for the Detection of the Incipient Bearing DamageSEKER, S.KARATOPRAK, E.SENGULER, T.In this study, it is aimed to track the aging trend of the incipient bearing damage in an induction motor which is subjected to an accelerated aging process. For this purpose, a new Multilayer perceptron (MLP) neural network approach is introduced. The input signals are extracted from power spectral densities (PSD) of the vibration signals taken from a 5-HP induction motor. Principal component analysis (PCA) has been applied to select the best possible feature vectors as a dimensionality reduction purpose. Variance and entropy values are used as the targets of the MLP network. The healthy motor condition was modelled by the MLP network considering all load conditions. The results showed that the incipient bearing damage was clearly extracted by the oscillations of the MLP output error.http://dx.doi.org/10.4316/AECE.2010.03006bearing damagevibration analysisMLP neural networksfeature extractioncondition monitoring |
| spellingShingle | SEKER, S. KARATOPRAK, E. SENGULER, T. A New MLP Approach for the Detection of the Incipient Bearing Damage Advances in Electrical and Computer Engineering bearing damage vibration analysis MLP neural networks feature extraction condition monitoring |
| title | A New MLP Approach for the Detection of the Incipient Bearing Damage |
| title_full | A New MLP Approach for the Detection of the Incipient Bearing Damage |
| title_fullStr | A New MLP Approach for the Detection of the Incipient Bearing Damage |
| title_full_unstemmed | A New MLP Approach for the Detection of the Incipient Bearing Damage |
| title_short | A New MLP Approach for the Detection of the Incipient Bearing Damage |
| title_sort | new mlp approach for the detection of the incipient bearing damage |
| topic | bearing damage vibration analysis MLP neural networks feature extraction condition monitoring |
| url | http://dx.doi.org/10.4316/AECE.2010.03006 |
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