Research And Design Of Black Tungsten Ore Intelligent Sorting System Based On Machine Vision

China's tungsten resources are abundant,and it has a huge advantage in resource storage.Among them,the value of black tungsten mining is high.At present,the main sorting method of domestic black tungsten ore is traditional manual sorting method.However,the manual sorting method has the disadvantages of low efficiency and low precision,and people are subjective and cannot form objective and unified standards,which is easy to cause waste of resources..In recent years,machine vision technology has developed rapidly.Compared with manual sorting methods,it has the advantages of fast production rate,high efficiency and stable function.It has strong advantages in the application of tungsten ore industry.The use of machine vision detection instead of manual sorting can not only eliminate the existence of human subjective factors,but also form an objective and uniform sorting standard to maximize the production efficiency of tungsten ore and the accuracy of ore sorting.This paper takes the black tungsten ore as the research object,analyzes the ore sorting demand,researches and designs a black tungsten ore intelligent sorting system based on machine vision,instead of the traditional manual sorting method,realizes the gangue and waste rock in the black tungsten ore.Automated separation.The main research contents of the thesis are as follows:Firstly,from the background and significance of the subject,the necessity of research on the intelligent sorting system of the black tungsten ore is analyzed.At the same time,the concept of machine vision is introduced,and the system composition,industrial application and development status of machine vision,and black tungsten ore at home and abroad are introduced.The current research status of the selection,and ultimately the overall framework of this paper.Secondly,the overall structure of the black tungsten ore intelligent sorting system is designed,mainly mechanical structure,machine vision module and electrical control module.According to the actual industrial demand,the mechanical structure of the system is designed from the aspects of ore transmission,visual imaging and ore sorting,and then the machine vision module is designed,including camera selection and imaging methods,to ensure high quality ore images,and finally to ensure the system.Each functional module coordinates its work and designs an electrical control module that includes an electrical component framework and its control flow.Furthermore,the color characteristics of the black tungsten ore image are analyzed,and the black tungsten ore detection algorithm is studied,which mainly includes ore segmentation and ore identification and judgment.In this paper,the genetic neural network algorithm is used to realize the segmentation of the black tungsten ore image,and the segmentation image is adopted.The connected domain analysis method locates the location of the gangue and classifies the gangue and waste rock by acquiring features(area area,aspect ratio,etc.)Finally,design the black tungsten ore intelligent sorting system software platform,use C Sharp language to realize software development in Microsoft Visual Studio 2015 platform,and finally,summarize the research content for the above paper design,and according to the shortcomings in the design The next step is to improve the development of the systemThe technical indicators of the black tungsten ore intelligent sorting system designed in this paper:Ore sorting output reaches 40T,which is 33%higher than the manual beneficiation method,the ratio of gangue to stone in the waste rock is PT(weight ratio),and the ratio of waste rock in the gangue The PN(weight ratio)and the gangue rejection ratio PGT(the number of gangue rejections)are in line with the technical specifications of industrial applications.