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Wind turbine fault diagnosis based on Gaussian process classifiers applied to operational data
Yanting Li1; Shujun Liu1; Lianjie Shu2
2019-04-01
Source PublicationRenewable Energy
ISSN18790682 09601481
Volume134Pages:357-366
Abstract

Effective condition monitoring and fault diagnosis of wind turbines are crucial for avoiding serious damages to wind turbines. The supervisory control and data acquisition (SCADA) system of a wind turbine provides valuable insights into turbine performance. In order to make full use of such valuable information, this paper investigates fault diagnosis of wind turbines by using Gaussian process classifiers (GPC) to the operational data collected from the SCADA system. Both real-time and predictive fault diagnosis were considered. As an alternative to the support vector machine (SVM) technique, the GPC possesses the capability of providing probabilistic information about the fault types, which is valuable for making maintenance plan in real practice. The comparison results show that the GPC method is able to provide more accurate fault diagnosis results than the SVM technique on average.

KeywordConditional Monitoring Gaussian Process Classification Predictive Fault Diagnosis Support Vector Machine Wind Turbine
DOI10.1016/j.renene.2018.10.088
URLView the original
Language英语
WOS Research AreaScience & Technology - Other Topics ; Energy & Fuels
WOS SubjectGreen & Sustainable Science & Technology ; Energy & Fuels
WOS IDWOS:000456760900034
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Cited Times [WOS]:4   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
CollectionDEPARTMENT OF ACCOUNTING AND INFORMATION MANAGEMENT
Corresponding AuthorLianjie Shu
Affiliation1.Department of Industrial Engineering and Logistics Management,Shanghai Jiao Tong University,,ShangHai,China
2.Faculty of Business Administration,University of Macau,,Taipa,Macao
Corresponding Author AffilicationFaculty of Business Administration
Recommended Citation
GB/T 7714
Yanting Li,Shujun Liu,Lianjie Shu. Wind turbine fault diagnosis based on Gaussian process classifiers applied to operational data[J]. Renewable Energy,2019,134:357-366.
APA Yanting Li,Shujun Liu,&Lianjie Shu.(2019).Wind turbine fault diagnosis based on Gaussian process classifiers applied to operational data.Renewable Energy,134,357-366.
MLA Yanting Li,et al."Wind turbine fault diagnosis based on Gaussian process classifiers applied to operational data".Renewable Energy 134(2019):357-366.
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