Abstract: China is a country heavily dependent on coal, it is of great significance for coal quantitative statistics.But the coal heaps in large coal mining areas are so large and numerous that it is difficult to count them by traditional manual measurement.To solve the difficult problem of volume measurement of coal heap in large coal mine area, a volume measurement method based on Lidar and neural network is proposed in this paper.Firstly, 3D point cloud image of coal heap surface is drawn by means of Lidar scanning, then noise reduction and completeness of point cloud are carried out by combining Meshlab and Cloud Compare software to form a more complete and concise point cloud model, and data set is established.Subsequently, Point-Net neural network is trained to segment the point cloud data by using the trained network model, and finally volume calculation is carried out by using Matlab software.The simulation experiment show that this method has the advantages of high precision, fast speed and no contact measurement compared with traditional measurement, and can meet the volume measurement requirements of coal heap in large coal mine area.Compared with the true volume, the calculation result of this method is smaller because Point-Net neural network can not recognize all the coal pile point cloud data and can be improved by subsequent training of the neural network.