Novel Condition Monitoring Method for Wind Turbines Based on the Adaptive Multivariate Control Charts and SCADA Data
المؤلفون المشاركون
Han, Qinkai
Wang, Zhentang
Hu, Tao
المصدر
العدد
المجلد 2020، العدد 2020 (31 ديسمبر/كانون الأول 2020)، ص ص. 1-16، 16ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2020-09-15
دولة النشر
مصر
عدد الصفحات
16
التخصصات الرئيسية
الملخص EN
A novel condition monitoring method based on the adaptive multivariate control charts and the supervisory control and data acquisition (SCADA) system is developed.
Two types of control charts are adopted: one is the adaptive exponential weighted moving average (AEWMA) control chart for abnormal state detection, and the other is the multivariate exponential weighted moving average (MEWMA) control chart for anomaly location determination.
Optimization procedures for these control charts are implemented to achieve minimum out-of-control average running length.
Multivariate regression analysis is utilized to obtain the normal condition prediction model of wind turbine with fault-free SCADA data.
After comparing the regression accuracy of several popular algorithms in the MRA, the random forest is adopted for feature selection and regression prediction.
Various tests on the wind turbine with normal and abnormal states are conducted.
The performance and robustness of various control charts are compared comprehensively.
Compared with conventional control charts, the AEWMA control chart is more sensitive to the abnormal state and thus has a more effective anomaly identification ability and better robustness.
It is shown that the MEWMA control chart combined with the out-of-limit number index can effectively locate and identify the abnormal component.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Han, Qinkai& Wang, Zhentang& Hu, Tao. 2020. Novel Condition Monitoring Method for Wind Turbines Based on the Adaptive Multivariate Control Charts and SCADA Data. Shock and Vibration،Vol. 2020, no. 2020, pp.1-16.
https://search.emarefa.net/detail/BIM-1213037
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Han, Qinkai…[et al.]. Novel Condition Monitoring Method for Wind Turbines Based on the Adaptive Multivariate Control Charts and SCADA Data. Shock and Vibration No. 2020 (2020), pp.1-16.
https://search.emarefa.net/detail/BIM-1213037
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Han, Qinkai& Wang, Zhentang& Hu, Tao. Novel Condition Monitoring Method for Wind Turbines Based on the Adaptive Multivariate Control Charts and SCADA Data. Shock and Vibration. 2020. Vol. 2020, no. 2020, pp.1-16.
https://search.emarefa.net/detail/BIM-1213037
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1213037
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر