Open AccessMonitoring of Wind Turbines: A Bio-Inspired Fault Tolerant Approach
Author(s) -
Peng Li,
Yongduan Song,
Wei Liu,
Ming Qin
Publication year - 2011
Publication title -
measurement + control/measurement and control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.286
H-Index - 21
eISSN - 2051-8730
pISSN - 0020-2940
DOI - 10.1177/002029401104400403
Subject(s) - scada , turbine , wind power , process (computing) , offshore wind power , data acquisition , computer science , fault detection and isolation , fault (geology) , engineering , control engineering , real time computing , reliability engineering , artificial intelligence , mechanical engineering , seismology , geology , electrical engineering , actuator , operating system
With increasing capacity and offshore application of wind turbines the on-line monitoring module plays a vital role in maintaining safe, reliable and cost-effective operation of wind conversion systems. In this work a novel monitoring structure for large-scale wind turbines is introduced and analyzed. The salient features of the proposed monitoring structure lie in three aspects. First, a double-sensor structure with individual pitch control module is adopted to ensure more reliable pitch load distribution and data acquisition. Second, a bio-inspired data process method with state estimation and prediction module is introduced to pre-process the large amount of data from various sensors, so as to improve the data utilization efficiency of SCADA (Supervisory Control and Data Acquisition) system. Third, a fault tolerant scheme with switched control strategies is used for different modes, and thus optimizes the wind turbine operation performance. Numerical simulations demonstrate the data process flow briefly.