The wind power industry continues to experience rapid growth worldwide. However, the fluctuations in wind speed and direction complicate the wind turbine control process and hinder the integration of wind power into the electrical grid. To maximize wind utilization, we propose to precisely measure the wind in a three-dimensional (3D) space, thus facilitating the process of wind turbine control. Natural wind is regarded as a 3D vector, whose direction and magnitude correspond to the wind's direction and speed. A semi-conical ultrasonic sensor array is proposed to simultaneously measure the wind speed and direction in a 3D space. As the ultrasonic signal transmitted between the sensors is influenced by the wind and environment noise, a Multiple Signal Classification algorithm is adopted to estimate the wind information from the received signal. The estimate's accuracy is evaluated in terms of root mean square error and mean absolute error. The robustness of the proposed method is evaluated by the type A evaluation of standard uncertainty under a varying signal-to-noise ratio. Simulation results validate the accuracy and anti-noise performance of the proposed method, whose estimated wind speed and direction errors converge to zero when the SNR is over 15 dB.

中文翻译：

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基于超声波传感器阵列和多信号分类的三维风测量。

全球风电行业继续快速增长。然而，风速和风向的波动使风力涡轮机的控制过程复杂化，并且阻碍了将风能集成到电网中。为了最大程度地利用风，我们建议在三维（3D）空间中精确测量风，从而简化风力涡轮机的控制过程。自然风被视为3D向量，其方向和大小与风的方向和速度相对应。提出了一种半锥形超声传感器阵列，以同时测量3D空间中的风速和风向。由于传感器之间传输的超声波信号受到风和环境噪声的影响，因此采用多信号分类算法从接收到的信号中估计风信息。根据均方根误差和绝对绝对误差来评估估计的准确性。在信噪比变化的情况下，通过标准不确定度的A类评估来评估所提出方法的鲁棒性。仿真结果验证了该方法的准确性和抗噪性能。当信噪比超过15 dB时，该方法的估计风速和方向误差收敛为零。