基于三维点云重建的储柜烟叶体积与重量在线测量方法研究OA

[Background and Objective]Storage cabinets in the primary processing line currently generally lack an online accurate measurement function for the weight of irregular tobacco materials inside the cabinet,leading to material balance calculations relying on estimation and rough control of material distribution uniformity.To address this,this study developed an online measurement system for the volume and weight of tobacco lamina in storage cabinets based on 3D vision.[Methods]A 3D camera array mounted above the storage cabinet was used to capture point cloud data;the raw point cloud was denoised and simplified through statistical filtering and voxel grid filtering.Fast Point Feature Histograms(FPFH)combined with the Iterative Closest Point(ICP)algorithm were used to complete point cloud registration and 3D reconstruction.The stacking volume was calculated using a combination of triangulation and slicing methods.A dynamic density estimation model based on historical production big data was established to achieve weight estimation.[Results]In a 500 kg irregular tobacco material stacking test,the accuracy of the volume calculation reached 99.37%;the online weight measurement accuracy reached 98.60%,and the agreement with electronic scale data reached 99.89%.Through real-time regulation,the coefficient of variation of material spreading flatness was improved from 0.117 to 0.041.[Conclusion]This method effectively solves the problem of online accurate measurement of irregular tobacco materials in storage cabinets,providing reliable technical support for the intelligent upgrading of the primary processing line.