Wind speed and direction measurement method based on intelligent optimization algorithm

Accurate and rapid measurement of wind speed and direction is an important research topic. However, the current measurement algorithms based on ultrasonic arrays are constrained by the large computational effort caused by the spectrum peak search, which hinders the development and application of ultrasonic array wind parameter measurement technology. To overcome this problem, this study applies an intelligent optimization algorithm for measuring wind speed and direction based on a co-prime arc ultrasonic array, which avoids the problem of a large number of calculations in the spectrum peak search. First, the spatial-spectral function of the propagator method algorithm is employed as the fitness function of the particle swarm optimization algorithm. Then, the wind parameter estimation problem is formulated as a function optimization problem, which realizes the fast and accurate measurement of wind speed and direction. Then, the artificial bee colony algorithm is used to measure wind speed and direction, further reducing the calculation amount of the wind parameter measurement. The performance and speed of the proposed method are verified by the design simulation and comparison experiments, reducing the time complexity by up to 90%. In addition, the feasibility of the proposed method is validated in hardware experiments.