Wind Speed Measurement via Visual Recognition of Wind-Induced Waving Light Stick Target - Wei Zhou; Aliyu Kasimu; Yitong Wu; Mingzan Tang; Xifeng Liang; Chen Jiang (Applied Sciences, 2023)
Wind measurement in confined spaces is a challenge due to the influence of the dimensions of anemometers in intrusive flow-field measurements where the anemometer probes directly contact and influence the near-probe flow field. In this work, a new wind speed detection methodology is proposed based on wind-induced motion of a stick via vision-based recognition. The target’s displacement in pixel coordinates is mapped to its angular displacement in world coordinates to derive wind speed and direction information by applying the calibration coefficients. Simulation experiments were carried out to validate the model, the error of which was within an angular displacement of 4.0° and 3.0° for wind speed and direction detections, respectively. When applied to the measurement of wind speed in the inner equipment cabin of a stationary high-speed train, the error was within ±1.1 m/s in terms of average RMSE. Thus, the proposed method provides an accurate and economic option for monitoring 2D wind in a confined space.