کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6765105 | 1431588 | 2018 | 27 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Condition monitoring and fault detection in wind turbines based on cointegration analysis of SCADA data
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی انرژی
انرژی های تجدید پذیر، توسعه پایدار و محیط زیست
پیش نمایش صفحه اول مقاله
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چکیده انگلیسی
This paper presents a new methodology - based on cointegration analysis of Supervisory Control And Data Acquisition (SCADA) data - for condition monitoring and fault diagnosis of wind turbines. Analysis of cointegration residuals - obtained from cointegration process of wind turbine data - is used for operational condition monitoring and automated fault and/or abnormal condition detection. The proposed method is validated using the experimental data acquired from a wind turbine drivetrain with a nominal power of 2Â MW under varying environmental and operational conditions. A two-stage cointegration-based procedure is performed on six process parameters of the wind turbine, where data trends have nonlinear characteristics. The method is tested using two case studies with known faults. The results demonstrate that the proposed method can effectively analyse nonlinear data trends, continuously monitor the wind turbine and reliably detect abnormal problems.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Renewable Energy - Volume 116, Part B, February 2018, Pages 107-122
Journal: Renewable Energy - Volume 116, Part B, February 2018, Pages 107-122
نویسندگان
Phong B. Dao, Wieslaw J. Staszewski, Tomasz Barszcz, Tadeusz Uhl,