Data-driven design of robust fault detection system for wind turbines
In this paper, a robust data-driven fault detection approach is proposed with application to a wind turbine benchmark. The main challenges of the wind turbine fault detection lie in its nonlinearity, unknown disturbances as well as significant measurement noise. To overcome these difficulties, a dat...
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| Published in | Mechatronics (Oxford) Vol. 24; no. 4; pp. 298 - 306 |
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| Main Authors | , , |
| Format | Journal Article |
| Language | English |
| Published |
Elsevier Ltd
01.06.2014
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| Subjects | |
| Online Access | Get full text |
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| Abstract | In this paper, a robust data-driven fault detection approach is proposed with application to a wind turbine benchmark. The main challenges of the wind turbine fault detection lie in its nonlinearity, unknown disturbances as well as significant measurement noise. To overcome these difficulties, a data-driven fault detection scheme is proposed with robust residual generators directly constructed from available process data. A performance index and an optimization criterion are proposed to achieve the robustness of the residual signals related to the disturbances. For the residual evaluation, a proper evaluation approach as well as a suitable decision logic is given to make a correct final decision. The effectiveness of the proposed approach is finally illustrated by simulations on the wind turbine benchmark model. |
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| AbstractList | In this paper, a robust data-driven fault detection approach is proposed with application to a wind turbine benchmark. The main challenges of the wind turbine fault detection lie in its nonlinearity, unknown disturbances as well as significant measurement noise. To overcome these difficulties, a data-driven fault detection scheme is proposed with robust residual generators directly constructed from available process data. A performance index and an optimization criterion are proposed to achieve the robustness of the residual signals related to the disturbances. For the residual evaluation, a proper evaluation approach as well as a suitable decision logic is given to make a correct final decision. The effectiveness of the proposed approach is finally illustrated by simulations on the wind turbine benchmark model. |
| Author | Wang, Guang Yin, Shen Karimi, Hamid Reza |
| Author_xml | – sequence: 1 givenname: Shen surname: Yin fullname: Yin, Shen email: shen.yin2011@googlemail.com organization: Research Institute of Intelligent Control and Systems, Harbin Institute of Technology, 150001 Harbin, China – sequence: 2 givenname: Guang surname: Wang fullname: Wang, Guang email: guang.wang@hit.edu.cn organization: Research Institute of Intelligent Control and Systems, Harbin Institute of Technology, 150001 Harbin, China – sequence: 3 givenname: Hamid Reza surname: Karimi fullname: Karimi, Hamid Reza email: hamid.r.karimi@uia.no organization: Department of Engineering, Faculty of Engineering and Science, University of Agder, N-4898 Grimstad, Norway |
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| Snippet | In this paper, a robust data-driven fault detection approach is proposed with application to a wind turbine benchmark. The main challenges of the wind turbine... |
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| SubjectTerms | Benchmarking Data-driven Design engineering Disturbances Fault detection Optimization Optimization criterion Performance index Performance indices Robustness Wind turbine Wind turbines |
| Title | Data-driven design of robust fault detection system for wind turbines |
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