Wind speed and direction measurement method based on intelligent optimization algorithm

Area of Science:

• Sensor Technology
• Acoustic Measurement
• Computational Fluid Dynamics

Background:

• Accurate wind speed and direction measurement is crucial for various applications.
• Current ultrasonic array algorithms face computational challenges due to spectrum peak search.
• This limits the development and application of ultrasonic array wind parameter measurement.

Purpose of the Study:

• To develop an intelligent optimization algorithm for rapid and accurate wind speed and direction measurement using a co-prime arc ultrasonic array.
• To overcome the computational burden associated with traditional spectrum peak search methods.
• To enhance the efficiency and applicability of ultrasonic array wind measurement technology.

Main Methods:

• Utilized a co-prime arc ultrasonic array configuration.
• Employed particle swarm optimization (PSO) with the spatial-spectral function of the propagator method as the fitness function.
• Applied the artificial bee colony (ABC) algorithm to further reduce computational complexity for wind parameter estimation.

Main Results:

• Successfully formulated wind parameter estimation as a function optimization problem, enabling fast and accurate measurements.
• Demonstrated significant reduction in computational time complexity, up to 90%, compared to conventional methods.
• Validated the performance, speed, and feasibility through simulations and hardware experiments.

Conclusions:

• The proposed intelligent optimization algorithms effectively address the computational limitations of existing ultrasonic array wind measurement techniques.
• This approach offers a feasible and efficient solution for rapid and accurate wind speed and direction determination.
• The validated method holds promise for advancing ultrasonic array wind parameter measurement technology.