# Wind Speed Measurement via Visual Recognition of Wind-Induced Waving Light Stick Target
## 5 Practical Application  
### Test Overview  
To demonstrate the applicability of the proposed method in practical cases, a wind tunnel test was implemented in the stationary equipment cabin of a high-speed train. Unlike the wind tunnel calibration test in Section 3.2, the Environmental Wind Tunnel  
Figure 23: Three-dimensional bar plot of absolute error between detected and expected results. (**a**) Yaw angle in bottom-front coupled view; (**b**) yaw angle in side-front coupled view; (**c**) wind direction in bottom-front coupled view; (**d**) wind direction in side-front coupled view.  
Figure 22: Comparison of curved face plot between detected and expected results. (**a**) Yaw angle in bottom-front coupled view; (**b**) yaw angle in side-front coupled view; (**c**) wind direction in bottom-front coupled view; (**d**) wind direction in side-front coupled view.  
(EWT) is a vertical closed circuit with an open test section (4 m \(\times\) 1 m at the inlet and 6.7 m in length). The key components of the wind tunnel consist of insulation layers, axial fan, and the rotary table with wheelset drive system, etc.  
In the wind tunnel test, the cabin was situated in the test section with its air inlet facing the tunnel airflow direction where filter screens are installed behind the inlet grills at the skirt plate to prevent dust accumulation in the cabin. Since the air filter can influence the flow characteristics inside the compartment, four 225 mm long light sticks were equally spaced at 30 mm, and aligned 165 mm away from the inlet grills, in an attempt to detect the wind speed behind the grills and air filters. This is also important to test the uniformity of the flow at different points with the same camera. Four T-shape tubes were fixed beside each stick and linked with a pressure transmission pipe to pressure sensors to test the wind speed based on the pitot method as the reference for the proposed method. Finally, a video camera was placed 58 mm away from the closest stick on the cabin wall in a side-front coupled view to observe the yaw angle of the four light sticks, the location of which are respectively denoted as TP1#, TP2#, TP3# and TP4#, shown in Figure 24. The camera has the same parameters as in the model validation section. Image sequences of the stick motion and corresponding wind pressure were simultaneously measured respectively by the camera and pitot T-tube. Thereafter, a video processing algorithm was implemented in MATLAB to identify each moving stick and determine their respective angular displacements.  
In the experiment, five wind tunnel speed cases were set from 0 m/s to 25 m/s at intervals of 5 m/s. When the tunnel wind is 0 m/s, the detected wind speed is the wind flow from the external environment driven by the blower inside the cabin. During the 6 tunnel wind stages, the motion of light sticks was recorded and extracted into 24 image frames per second to acquire the time history of their yaw angle variations. Dynamic pressures of the pitot T-tube were collected by IMC DAQ system at a sampling frequency of 256 Hz. The dynamic pressure data were processed with low-pass filtering at a frequency of 40 Hz, and then used to determine the corresponding wind speed data according to the Bernoulli equation:  
\[v_{\rm c}=\sqrt{2\rho\cdot P_{\rm d}} \tag{40}\]  
where \(v_{\rm c}\) is the wind speed (m/s), \(P_{\rm d}\) is the dynamic pressure (Pa), and \(\rho\) is the atmospheric density, 1.225 kg/m\({}^{3}\).  
Figure 24: Set-up for wind speed measurement in train cabin.