SCADA data based condition monitoring of wind turbines

作     者：Ke-Sheng Wang Vishal S.Sharma Zhen-You Zhang 

作者机构：Department of Production and Quality Engineering NorwegianUniversity and Science and Technology Trondheim Norway Department of'Industrial and Production Engineering Dr. B .R.Ambedkar National Institute of Technology Jalandhar PunjabIndia 

出 版 物：《Advances in Manufacturing》 (先进制造进展（英文版）)

年 卷 期：2014年第2卷第1期

页      面：61-69页

核心收录：

学科分类：080802[工学-电力系统及其自动化] 0808[工学-电气工程] 08[工学] 0835[工学-软件工程] 0802[工学-机械工程] 080201[工学-机械制造及其自动化] 

主　　题：SCADA data Data-driven approaches Artificial intelligence (AI) Diagnosis and prognosis ofwind turbines Central monitoring system (CMS) 

摘      要：Wind turbines（WTs） are quite expensive pieces of equipment in power industry. Maintenance and repair is a critical activity which also consumes lots of time and effort, hence making it a costly affair. Carefully planning the maintenance based upon condition of the equipment would make the process reasonable. Mostly the WTs are equipped with some kind of condition monitoring device/system, which provides the information about the device to the central data base i.e., supervisory control and data acquisition（SCADA） data base. These devices/systems make use of data processing techniques/methods in order to detect and predict faults. The information provided by condition monitoring equipments keeps on recoding in the SCADA data base. This paper dwells upon the techniques/methods/algorithms developed, to carry out diagnosis and prognosis of the faults, based upon SCADA *** data driven approaching for SCADA data interpretation has been reviewed and an artificial intelligence（AI） based framework for fault diagnosis and prognosis of WTs using SCADA data is proposed.