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Condition monitoring fault diagnosis system for Offshore Wind Turbines

机译:海上风机状态监测与故障诊断系统

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Due to the technological development, the electronic power progress and economic stake, through the use of Wound Rotor Induction Motor (WRIM) has taken more and more places in different domains (transport, energy production, electric drive‥,) thanks to their robustness, efficiency and lower costs. Despite the performed work researches and the improvement that has been brought, these machines still remain the potential seats of failures both in stator and rotor levels. Consequently, WRIM faults detection is currently one of the centers of interest of several researches of both academic and industrial laboratories. In fact, this article addresses this problem by the use of Principal Components Analysis (PCA) for faults detection in Offshore Wind Turbine Generator (OWTG). An accurate analytic modeling of healthy and faulted OWTG is suggested to perform the data matrix needed for PCA method. Tests were achieved using a numeric simulator on Matlab/Simulink software. Analysis of OWTG simulation proves the efficiency of PCA method. Several simulation results will be presented and discussed.
机译:由于技术的发展,电子功率的进步和经济利益,通过使用绕线转子感应电动机(WRIM)的坚固性,它已在不同领域(运输,能源生产,电力驱动)中占据了越来越多的位置,效率和较低的成本。尽管进行了深入的工作研究并做出了改进,但这些机器仍然是定子和转子级故障的潜在根源。因此,WRIM故障检测目前是学术实验室和工业实验室的多项研究的关注中心之一。实际上,本文通过使用主成分分析(PCA)进行海上风力发电机(OWTG)故障检测来解决此问题。建议对健康和故障的OWTG进行精确的分析建模,以执行PCA方法所需的数据矩阵。使用Matlab / Simulink软件上的数字模拟器完成了测试。 OWTG仿真分析证明了PCA方法的有效性。一些仿真结果将被介绍和讨论。

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