Research Of Key Components And System Of Automatic Tobacco Leaf Grading

At present,large amount of human and financial resources are needed of tobacco leaf classification,and the classification result is subjective and easily suffered by many factors,which leads to unscientific, no objective and low efficient tobacco leaf classification.For this,this paper designed an automatic tobacco leaf classification system for tobacco leaves in central of Guizhou area,this system mainly consists of transport device for tobacco leaves,dispersion device for bundles of tobacco leaves,pave device for fold tobacco leaves,capture and identify device for tobacco leaves and the grade sorting device for tobacco leaves.After analyzes,the structural features and its working principle for those key components of the pave device and capture and identify device for tobacco leaves are determined.This paper designed the key parts of main devices,and took a qualitative and quantitative analysis for those main parameters which is influential to working effect of key parts.According to the biological and mechanical characters of tobacco leaf,single tobacco leaves’ movement process and stress distribution were analyzed when it passed through each part,and the main factors affecting single tobacco leaf paved smooth and automatically identified were reached,then got the best parameter combination. The following are main research parts:(1) According to the mechanical and biological characters analysis,for the longitudinal fold tobacco leaves,this paper designed a tobacco leaf roller paving mechanism based on the friction effect:The roller is composed by roll shaft and brushes row with the surface and divided into two layers,each layer contains 10 root rollers and divided into two groups averagely, each group connects with a same synchronous belt,a same pulley and a speed reduce,driven by motor respectively,the mechanism paves leaf flat by the speed difference between roller pairs.After analysis,the key parts’ structure and parameters of roller brush,bracket of pave device and drive system were determined,then tested the paving effect by changing roller spacing, roller speed of two layers and speed difference the three parameters respectively,the result shows, it is feasible to pave the fold tobacco leaf smooth, and when the roller space is 15 cm, roller speed of two layers are 25 r/min,10 r/min and speed difference is 20 r/min, it will get the best pave effect. The method of realizing tobacco leaf transported and paved smooth by two layers roller brush with speed difference is innovative put forward in this paper.(2) Taking central part tobacco leaves as the research object,this paper designed an image acquisition system:used CCD camera and adopted the led light, based on artificial light intensity,pictures were captured under twelve different light intensities,then according to the color vectors got under RGB, HSI and HSV three models,this paper analyzed how light intensity influence color vectors and sensibility,and got the suitable color vectors and light intensity for grading tobacco leaf.The result shows,the sensitive degree of different color vectors to light intensity is:SHSI,SHSV>R,I,V>G,B,HHSI,HHSV,and as the light intensity improves,the obvious degree of changed gray values of each color vectoris:R,G,B,I,V>HHSI,HHSV>SHSI,SHSV; Color vectors R,G,B,I and HHSV,V with bigger difference between grades can be used as discriminant operator of tobacco leaf grade;Light intensity between 2500 lux-3200 lux should be used to automatic identification of tobacco leaf grade.To the design of picture captured hardware system and selection of grade discriminant features,the research provides a scientific basis for it of light intensity to color vector and grade identification(3) Based on an artificial intelligence recognition method of BP neural network,this paper established an automatic identification model for central tobacco leaves,and analyzed how color vectors influence the leaf grade under RGB、HIS and HSV three color models,color vectors with bigger difference between tobacco leaf grades were selected as neural network input factors, and the corresponding tobacco leaf grade were selected as output factors.After constantly trained and predicted,the average identification accuracy reached to eighty nine point one seven percent,it is feasible to realize the prediction of tobacco leaf grade.(4) This paper designed a grade sorting device for tobacco leaf with Solidworks software.After analysis,the key parts’ structure and parameters of control system,bracket of grade sorting device, tobacco leaf grade container,transport system and execute system,it is feasible to realize automatically sorting the tobacco leaves by designed grad sorting device.