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Model-based fault detection of blade pitch system in floating wind turbines

机译:基于模型的浮式风力机叶片桨距系统故障检测

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摘要

This paper presents a model-based scheme for fault detection of a blade pitch system in floating wind turbines. A blade pitch system is one of the most critical components due to its effect on the operational safety and the dynamics of wind turbines. Faults in this system should be detected at the early stage to prevent failures. To detect faults of blade pitch actuators and sensors, an appropriate observer should be designed to estimate the states of the system. Residuals are generated by a Kalman filter and a threshold based on H optimization, and linear matrix inequality (LMI) is used for residual evaluation. The proposed method is demonstrated in a case study that bias and fixed output in pitch sensors and stuck in pitch actuators. The simulation results show that the proposed method detects different realistic fault scenarios of wind turbines under the stochastic external winds.
机译:本文提出了一种基于模型的浮动风力涡轮机叶片变桨系统故障检测方案。叶片变桨系统是最关键的组件之一,因为它对风力发电机的运行安全性和动力产生影响。应该尽早检测该系统中的故障以防止故障。为了检测叶片变桨致动器和传感器的故障,应设计适当的观察器以估计系统状态。残差由卡尔曼滤波器和基于H优化的阈值生成,并且线性矩阵不等式(LMI)用于残差评估。在案例研究中证明了所提出的方法,该算法在俯仰传感器中偏置并固定输出,并卡在俯仰致动器中。仿真结果表明,该方法能在随机外部风的作用下,检测出不同的风力发电机组实际故障情况。

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