The invention provides a
train carriage bulk material leveling method and
system based on a material leveling
machine and a medium, and relates to the technical field of bulk material loading, and the method comprises the following steps: S1, carrying out real-time synchronous scanning on a
train carriage through a plurality of
laser radar scanners, and obtaining real-time
point cloud data of the
carriage; s2, extracting key feature
point cloud data through a 3D sparse
convolutional neural network based on the real-time
point cloud data of the carriage; and S3,
processing the key feature point
cloud data through point cloud voxelization, and projecting on a plane to generate a two-dimensional
distribution diagram. According to the method, multi-
laser radar real-time synchronous scanning is combined with the 3D sparse
convolutional neural network, two-dimensional mapping is performed through voxelization
processing, and the moving position required by the leveling
machine in the next step is tracked and predicted according to the two-dimensional image, so that the point
cloud data processing efficiency is remarkably improved; the problem of insufficient real-time performance caused by large data volume in a traditional method is effectively solved, and meanwhile the requirements for high real-time performance and high precision of material leveling operation are met.