Study On The Secondary Identification Method Of Coal Gangue Based On Multi-parameter Fusion

Accurate identification of coal gangue is the first step to ensure the efficient sorting of robots.However,in actual production,the traditional image recognition rate of coal gangue is low or cannot be recognized due to environmental pollution,which seriously restricts the sorting efficiency of coal gangue sorting robots.Aiming at this problem,this paper puts forward a secondary identification method of coal gangue based on image recognition,considering the coal gangue density difference,in order to reduce the false detection rate of coal gangue.In this paper,the quality difference of coal and gangue in different coal mines with the same volume is analyzed.In addition,a secondary identification scheme of coal and gangue based on binocular vision is designed.Through studying the existing irregular object volume calculation methods,a three-dimensional reconstruction scheme based on binocular vision is determined.Moreover,Combined with the sorting process and mechanical structure of the coal gangue sorting robot,a dynamic weighing scheme is formulated to obtain an accurate secondary coal gangue identification result.Aiming at the problem that the binocular camera cannot capture the whole target picture,the point cloud data outline characteristics are analyzed.The point cloud data is completed by turning over the point cloud and filling the supporting surface.The Poisson reconstruction method is used to complete the three-dimensional reconstruction and calculate the coal gangue volume,and combined with the gangue density to calculate the target detection quality.The experiment proves that the volume of coal gangue obtained by point cloud turnover method is more accurate,and the error is about 4%.Aiming at the problem that the dynamic coal gangue quality fluctuation caused by the manipulator speed and acceleration in its movement,considering the influence of the end effector’s grabbing stage on the dynamic weighing results,the grabbing process of the manipulator is analyzed.Select the stage of steady-state measurement of gangue quality.Then,establishe a dynamic weighing model.The model is solved by the the coal gangue sorting robot system parameters.Complete the dynamic weighing experiment on the robot platform of coal gangue sorting,compare the real quality with the weighing quality,and analyze the quality measurement error.The experiment results show that the maximum error is 5.74%,while the minimum error is 1.71%.Furthermore,the measurement time of dynamic quality is within 0.15s,which meets the requirement of working condition.According to the research of coal gangue volume detection method and coal gangue dynamic weighing method,the three-dimensional reconstruction volume detection method and dynamic quality acquisition method based on binocular vision are applyed to the coal gangue secondary identification.Develop the secondary identification program of coal gangue,design the experimental scheme of secondary identification,and test it based on the coal gangue sorting robot platform.This research can provide a theoretical basis for improving the accuracy of coal gangue image recognition.