With the deepening research on the rotor wind field of UAV operation, it has become a mainstream to quantify the UAV operation effect and study the distribution law of rotor wind field via the spatial parameters of the UAV-rice interaction wind field vortex.
At present, the point cloud segmentation algorithms involved in most wind field vortex spatial parameter extraction methods cannot adapt to the instantaneous changes and indistinct boundary of the vortex. As a result, there are problems such as inaccurate three-dimensional (3D) shape and boundary contour of the wind field vortex as well as large errors in the vortex’s spatial parameters.
To this end, this paper proposes an accurate method for establishing the UAV-rice interaction vortex 3D model and extracting vortex spatial parameters. Firstly, the original point cloud data of the wind filed vortex were collected in the image acquisition area. Secondly, DDC-UL processed the original point cloud data to develop the 3D point cloud image of the wind field vortex.
Thirdly, the 3D curved surface was reconstructed and spatial parameters were then extracted. Finally, the volume parameters and top surface area parameters of the UAV-rice interaction vortex were calculated and analyzed. The results show that the error rate of the 3D model of the UAV-rice interaction wind field vortex developed by the proposed method is kept within 2%, which is at least 13 percentage points lower than that of algorithms like PointNet.
The average error rates of the volume parameters and the top surface area parameters extracted by the proposed method are 1.4% and 4.12%, respectively. This method provides 3D data for studying the mechanism of rotor wind field in the crop canopy through the 3D vortex model and its spatial parameters.
Read more at: http://www.ijpaa.org/index.php/ijpaa/article/view/84
