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Main Factors Affecting The Quality Of Bottle Images Intellectually Grapped On Beer Packaging Line

Posted on:2011-06-22Degree:MasterType:Thesis
Country:ChinaCandidate:W ChenFull Text:PDF
GTID:2178360308463617Subject:Mechanical engineering
Abstract/Summary:PDF Full Text Request
China's Brewing industry has been rapid developed in recent years. In 2008 , annualproduction of bear were more than 41,000,000 tons in china,which has consistently rankedfirst in the world Since 2002. Brewing industry, whose the intensity of competition is moreand more severe, forces the beer manufacturers urgently to improve the original productionlines to raise efficiency,quality and product competitiveness. The traditional bottle'defectDetection in manual method of visual inspection has become increasingly difficult to meet thehigh-speed, high precision production.The studis of Domestic beer bottle defect recognition system stay at an early stage. iDomestic well-known large-scale procurement of beer producers can only use importequipments,which is expensive and difficult to repair.To ensure product quality, combinationof inspection equipment and man'eyes is the helpless approach. manual Inspection isunstable.different man,different time and tiredness can lead to an uncertain results.With automatic image processing, analysis and automatic classification on the test results,machine vision system have lots of characters,such as high speed, high precision,non-contact,etc. they can be applied to detect beer bottles, effectively overcome the shortcomings ofmanual bottle inspection, improve Beer production automation and production efficiency. Atpresent the beer bottles production line automatic detection has become an important researchdirection.Empty Bottle Inspection Machine is a modern and important beer packaging line testingequipment. By using CCD camera, a reasonable use of light, image acquisition, positioning,processing algorithm, combining with the computer, gray value of defects or defections inthe region brightness value or the difference of image recognition, ultimately the Defectivebottles can be rejected.This study aim to improve the line detection rate of empty bottles, and focus on factorsthat influence the quality of bottom images of bottles obtained in beer filling productionline ,and lay the solid foundation for improvement of stability and equipment utilization ofBeer Production Line.
Keywords/Search Tags:Machine Vision, Beer Packaging, Image Acquisition, Industry conditions improve
PDF Full Text Request
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