The present application relates to the technical field of
intelligent control of
coal unloading
machine, in particular to an intelligent
coal unloading
control system and method, in the present application, the environmental fusion
perception unit fuses the
coal pile point cloud data of the three-dimensional
laser scanner and the texture information of the RGB-D camera, constructs a real-time digital twin model through hierarchical semantic segmentation, maps the coal
pile surface morphology,
spatial distribution and residual coal
layer thickness in the stage of cleaning, the autonomous decision planning unit adopts a hierarchical optimization strategy, uses a
heuristic space segmentation
algorithm in the global layer to divide the coal unloading grid and plan the grab bucket, generates a spiral progressive cleaning trajectory of the adaptive
cutting point based on the curvature gradient of the coal
pile in the local layer, the dynamic posture adjustment unit collects the digging torque data, combines the coal pile thickness to build a coal quality
hardness classification model, dynamically corrects the grab bucket
cutting angle, digging depth and swing amplitude, and the closed-loop vibration suppression
control unit generates a vibration suppression
signal using the active damping controller of
Lyapunov stability theory to achieve optimal
energy consumption of the grab bucket.