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On Real-Time Fault Detection in Wind Turbines: Sensor Selection Algorithm and Detection Time Reduction Analysis

机译:风力发电机组实时故障检测:传感器选择算法与检测时间减少分析

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In this paper, we address the problem of real-time fault detection in wind turbines. Starting from a data-driven fault detection method, the contribution of this paper is twofold. First, a sensor selection algorithm is proposed with the goal to reduce the computational effort of the fault detection method. Second, an analysis is performed to reduce the data acquisition time needed by the fault detection method, that is, with the goal of reducing the fault detection time. The proposed methods are tested in a benchmark wind turbine where different actuator and sensor failures are simulated. The results demonstrate the performance and effectiveness of the proposed algorithms that dramatically reduce the number of sensors and the fault detection time.
机译:在本文中,我们解决了风力涡轮机中实时故障检测的问题。从数据驱动的故障检测方法开始,本文的贡献是双重的。首先,提出了一种传感器选择算法,其目的是减少故障检测方法的计算量。其次,进行分析以减少故障检测方法所需的数据获取时间,即,以减少故障检测时间为目标。所提出的方法在基准风力涡轮机中进行了测试,其中模拟了不同的执行器和传感器故障。结果证明了所提出算法的性能和有效性,该算法大大减少了传感器的数量和故障检测时间。

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