A REVIEW OF VIBRATION MACHINE DIAGNOSTICS BY USING ARTIFICIAL INTELLIGENCE METHODS
In the industry, gears and rolling bearings failures are one of the foremost causes of breakdown in rotating machines, reducing availability time of the production and resulting in costly systems downtime. Therefore, there are growing demands for vibration condition based monitoring of gears and bea...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Universidad Privada Boliviana
2016-09-01
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| Series: | Investigación & Desarrollo |
| Subjects: | |
| Online Access: | http://www.upb.edu/revista-investigacion-desarrollo/index.php/id/article/view/16 |
| _version_ | 1818541513977626624 |
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| author | Grover Zurita Vinicio Sánchez Diego Cabrera |
| author_facet | Grover Zurita Vinicio Sánchez Diego Cabrera |
| author_sort | Grover Zurita |
| collection | DOAJ |
| description | In the industry, gears and rolling bearings failures are one of the foremost causes of breakdown in rotating machines, reducing availability time of the production and resulting in costly systems downtime. Therefore, there are growing demands for vibration condition based monitoring of gears and bearings, and any method in order to improve the effectiveness, reliability, and accuracy of the bearing faults diagnosis ought to be evaluated. In order to perform machine diagnosis efficiently, researchers have extensively investigated different advanced digital signal processing techniques and artificial intelligence methods to accurately extract fault characteristics from vibration signals. The main goal of this article is to present the state-of-the-art development in vibration analysis for machine diagnosis based on artificial intelligence methods. |
| first_indexed | 2024-12-11T22:10:17Z |
| format | Article |
| id | doaj.art-a8e4fefdf4dd4ef48786e3423f187835 |
| institution | Directory Open Access Journal |
| issn | 1814-6333 2518-4431 |
| language | English |
| last_indexed | 2024-12-11T22:10:17Z |
| publishDate | 2016-09-01 |
| publisher | Universidad Privada Boliviana |
| record_format | Article |
| series | Investigación & Desarrollo |
| spelling | doaj.art-a8e4fefdf4dd4ef48786e3423f1878352022-12-22T00:48:48ZengUniversidad Privada BolivianaInvestigación & Desarrollo1814-63332518-44312016-09-0111614A REVIEW OF VIBRATION MACHINE DIAGNOSTICS BY USING ARTIFICIAL INTELLIGENCE METHODSGrover Zurita0Vinicio Sánchez1Diego Cabrera2Universidad Privada BolivianaCuenca-EcuadorCuenca-EcuadorIn the industry, gears and rolling bearings failures are one of the foremost causes of breakdown in rotating machines, reducing availability time of the production and resulting in costly systems downtime. Therefore, there are growing demands for vibration condition based monitoring of gears and bearings, and any method in order to improve the effectiveness, reliability, and accuracy of the bearing faults diagnosis ought to be evaluated. In order to perform machine diagnosis efficiently, researchers have extensively investigated different advanced digital signal processing techniques and artificial intelligence methods to accurately extract fault characteristics from vibration signals. The main goal of this article is to present the state-of-the-art development in vibration analysis for machine diagnosis based on artificial intelligence methods.http://www.upb.edu/revista-investigacion-desarrollo/index.php/id/article/view/16Artificial Intelligence Method, Machine Learning Method, Random Forest, Deep Learning |
| spellingShingle | Grover Zurita Vinicio Sánchez Diego Cabrera A REVIEW OF VIBRATION MACHINE DIAGNOSTICS BY USING ARTIFICIAL INTELLIGENCE METHODS Investigación & Desarrollo Artificial Intelligence Method, Machine Learning Method, Random Forest, Deep Learning |
| title | A REVIEW OF VIBRATION MACHINE DIAGNOSTICS BY USING ARTIFICIAL INTELLIGENCE METHODS |
| title_full | A REVIEW OF VIBRATION MACHINE DIAGNOSTICS BY USING ARTIFICIAL INTELLIGENCE METHODS |
| title_fullStr | A REVIEW OF VIBRATION MACHINE DIAGNOSTICS BY USING ARTIFICIAL INTELLIGENCE METHODS |
| title_full_unstemmed | A REVIEW OF VIBRATION MACHINE DIAGNOSTICS BY USING ARTIFICIAL INTELLIGENCE METHODS |
| title_short | A REVIEW OF VIBRATION MACHINE DIAGNOSTICS BY USING ARTIFICIAL INTELLIGENCE METHODS |
| title_sort | review of vibration machine diagnostics by using artificial intelligence methods |
| topic | Artificial Intelligence Method, Machine Learning Method, Random Forest, Deep Learning |
| url | http://www.upb.edu/revista-investigacion-desarrollo/index.php/id/article/view/16 |
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