Abstract: In the conventional binocular vision system, the commonly used speeded up robust features and scale-invariant feature transform matching algorithms have high requirements for image quality. When applied to scenes with relatively single color and texture such as coal, it is prone to failure. It needs to consume a lot of computing resources, which is difficult to ensure real-time performance. When using LiDAR for coal quantity measurement, the effective field of view is relatively small. The corresponding measurement points are few and the scanning frequency is low. When the belt conveyor runs at a faster speed, the precision will be significantly reduced. In order to solve the above problems, a coal flow measurement method based on binocular structured light vision is proposed. The linear structured light is introduced into the binocular vision system. By using the constraint of linear structured light, the image feature point matching is simplified into matching between left and right image lines. On the basis of ensuring the parallelism of the optical axis of the binocular system camera, corresponding row matching is used to calculate three-dimensional coordinate points. The sampling frequency and resolution is improved. The precision of coal flow measurement is improved. The dependence of the measurement system on lighting and environment is reduced. Point cloud acquisition: It uses the line structured light to highlight the coal material section curve, and extracts the image coordinates of the coal material section center line. It uses the binocular camera to obtain the left and right coal material section line structured light images. It establishes binocular structured light 3D reconstruction model. The left and right image center line coordinates form a matching point pair to participate in the calculation of the coal material section 3D coordinates, so as to achieve real-time acquisition of point clouds. Coal flow calculation: The point cloud of coal material is obtained by combining the point cloud of no-load belt section and the point cloud of loaded belt section. The infinitesimal method is used to sample the 3D point cloud of coal material. The volume of coal material in unit time is calculated by the uniform meshing method and the triangle meshing method, respectively. The coal flow measurement of belt conveyor is realized. The experimental results show that the average relative error of coal volume measured by the uniform meshing method is 6.758%. The average relative error of coal volume measured by the triangle meshing method is 2.791%. The measurement precision of the triangle meshing method is higher than that of the uniform meshing method. The industrial test results show that compared with the electronic belt weigher, the maximum absolute error of the coal flow measurement method based on binocular structured light vision is 87.855 t/h. The average absolute error is 25.902 t/h, the maximum relative error is 2.876%, and the average relative error is 0.847%. The results meet the requirements of non-contact coal flow measurement in coal mines.