Abstract: The present invention discloses a plant point cloud acquisition, registration, and optimization method based on a time of flight (TOF) camera, which includes the following steps: (1) placing a to-be-tested plant on a turntable, adjusting a view angle of the TOF camera, and aligning the TOF camera with the to-be-tested plant; (2) turning on the turntable so that it rotates automatically, and enabling the TOF camera to acquire point cloud data of the to-be-tested plant at intervals; (3) performing real-time preprocessing on each frame of point cloud data acquired by the TOF camera; (4) performing registration and optimization on every two adjacent frames of point cloud data, and then integrating the data to obtain complete plant point cloud data; and (5) using statistical filtering to remove the discrete noise in the plant point cloud data obtained in the registration and optimization process to obtain final point cloud data.

Abstract: The present invention discloses a plant point cloud acquisition, registration, and optimization method based on a time of flight (TOF) camera, which includes the following steps: (1) placing a to-be-tested plant on a turntable, adjusting a view angle of the TOF camera, and aligning the TOF camera with the to-be-tested plant; (2) turning on the turntable so that it rotates automatically, and enabling the TOF camera to acquire point cloud data of the to-be-tested plant at intervals; (3) performing real-time preprocessing on each frame of point cloud data acquired by the TOF camera; (4) performing registration and optimization on every two adjacent frames of point cloud data, and then integrating the data to obtain complete plant point cloud data; and (5) using statistical filtering to remove the discrete noise in the plant point cloud data obtained in the registration and optimization process to obtain final point cloud data.

Abstract: A temperature adjusting device is included with a sand and dust environmental testing system. The sand and dust environmental testing system includes: a circulating air duct, including a contraction section, a test section and a separation section etc.; a main blower; U-type separators and guide vanes, respectively configured at four corners of the circulating air duct. The temperature adjusting device includes: heat exchange pipes distributed in the U-type separators; four groups of guide vanes. Three groups of the guide vanes are configured with heat exchange medium holes and the other group of the guide vanes is equipped with heating device. An electric heater is accommodated in the second contraction section. An intelligent temperature control includes: building a neural network system structure; blended learning training of neural network parameters; PI control; and amplitude limitation processing.