Lubrication Oil Condition Monitoring and Remaining Useful Life Prediction With Particle Filtering
In order to reduce the costs of wind energy, it is necessary to improve the wind turbine availability and reduce the operational and maintenance costs. The reliability and availability of a functioning wind turbine depend largely on the protective properties of the lubrication oil for its drive trai...
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| Format: | Article |
| Language: | English |
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The Prognostics and Health Management Society
2013-01-01
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| Series: | International Journal of Prognostics and Health Management |
| Subjects: | |
| Online Access: | http://www.phmsociety.org/sites/phmsociety.org/files/phm_submission/2013/ijphm_13_020.pdf |
| _version_ | 1818923879014334464 |
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| author | Yongzhi Qu David He Jae M. Yoon Junda Zhu Eric Bechhoefer |
| author_facet | Yongzhi Qu David He Jae M. Yoon Junda Zhu Eric Bechhoefer |
| author_sort | Yongzhi Qu |
| collection | DOAJ |
| description | In order to reduce the costs of wind energy, it is necessary to improve the wind turbine availability and reduce the operational and maintenance costs. The reliability and availability of a functioning wind turbine depend largely on the protective properties of the lubrication oil for its drive train subassemblies such as gearbox and means for lubrication oil condition monitoring and degradation detection. The wind industry currently uses lubrication oil analysis for detecting gearbox and bearing wear but cannot detect the functional failures of the lubrication oils. The main purpose of lubrication oil condition monitoring and degradation detection is to determine whether the oils have deteriorated to such a degree that they no longer fulfill their functions. This paper describes a research on developing online lubrication oil health condition monitoring and remaining useful life prediction with particle filtering technique using commercially available online sensors. The paper first presents a survey on current state-of-the-art online lubrication oil condition monitoring solutions and their characteristics along with the classification and evaluation of each technique. It is then followed by an investigation on wind turbine gearbox lubrication oil health condition monitoring and degradation detection using online viscosity and dielectric constant sensors. In particular, the lubricant performance evaluation and remaining useful life prediction of degraded lubrication oil with viscosity and dielectric constant data using particle filtering are presented. A simulation case study is provided to demonstrate the effectiveness of the developed technique. |
| first_indexed | 2024-12-20T02:16:26Z |
| format | Article |
| id | doaj.art-a8eb5ada3e14430386830c350e81a6e7 |
| institution | Directory Open Access Journal |
| issn | 2153-2648 |
| language | English |
| last_indexed | 2024-12-20T02:16:26Z |
| publishDate | 2013-01-01 |
| publisher | The Prognostics and Health Management Society |
| record_format | Article |
| series | International Journal of Prognostics and Health Management |
| spelling | doaj.art-a8eb5ada3e14430386830c350e81a6e72022-12-21T19:56:55ZengThe Prognostics and Health Management SocietyInternational Journal of Prognostics and Health Management2153-26482013-01-014Sp2124138Lubrication Oil Condition Monitoring and Remaining Useful Life Prediction With Particle FilteringYongzhi QuDavid HeJae M. YoonJunda ZhuEric BechhoeferIn order to reduce the costs of wind energy, it is necessary to improve the wind turbine availability and reduce the operational and maintenance costs. The reliability and availability of a functioning wind turbine depend largely on the protective properties of the lubrication oil for its drive train subassemblies such as gearbox and means for lubrication oil condition monitoring and degradation detection. The wind industry currently uses lubrication oil analysis for detecting gearbox and bearing wear but cannot detect the functional failures of the lubrication oils. The main purpose of lubrication oil condition monitoring and degradation detection is to determine whether the oils have deteriorated to such a degree that they no longer fulfill their functions. This paper describes a research on developing online lubrication oil health condition monitoring and remaining useful life prediction with particle filtering technique using commercially available online sensors. The paper first presents a survey on current state-of-the-art online lubrication oil condition monitoring solutions and their characteristics along with the classification and evaluation of each technique. It is then followed by an investigation on wind turbine gearbox lubrication oil health condition monitoring and degradation detection using online viscosity and dielectric constant sensors. In particular, the lubricant performance evaluation and remaining useful life prediction of degraded lubrication oil with viscosity and dielectric constant data using particle filtering are presented. A simulation case study is provided to demonstrate the effectiveness of the developed technique.http://www.phmsociety.org/sites/phmsociety.org/files/phm_submission/2013/ijphm_13_020.pdflubrication oilon-line condition monitoringRemaining Useful Life Estimation |
| spellingShingle | Yongzhi Qu David He Jae M. Yoon Junda Zhu Eric Bechhoefer Lubrication Oil Condition Monitoring and Remaining Useful Life Prediction With Particle Filtering International Journal of Prognostics and Health Management lubrication oil on-line condition monitoring Remaining Useful Life Estimation |
| title | Lubrication Oil Condition Monitoring and Remaining Useful Life Prediction With Particle Filtering |
| title_full | Lubrication Oil Condition Monitoring and Remaining Useful Life Prediction With Particle Filtering |
| title_fullStr | Lubrication Oil Condition Monitoring and Remaining Useful Life Prediction With Particle Filtering |
| title_full_unstemmed | Lubrication Oil Condition Monitoring and Remaining Useful Life Prediction With Particle Filtering |
| title_short | Lubrication Oil Condition Monitoring and Remaining Useful Life Prediction With Particle Filtering |
| title_sort | lubrication oil condition monitoring and remaining useful life prediction with particle filtering |
| topic | lubrication oil on-line condition monitoring Remaining Useful Life Estimation |
| url | http://www.phmsociety.org/sites/phmsociety.org/files/phm_submission/2013/ijphm_13_020.pdf |
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