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Multi-Vision Detection Method For Wood Panel Defect

Posted on:2016-12-26Degree:MasterType:Thesis
Country:ChinaCandidate:S S LvFull Text:PDF
GTID:2348330485452042Subject:Mechanical engineering
Abstract/Summary:PDF Full Text Request
Block board is one of the leading varieties for decoration. What is outstanding board looks like? The first point is the surface should be smoothly and drying without any defects, such as no hard knot, no replace no dropped gum and so on. What's more, the thickness of the middle board should be same without overlap or gaps, making sure that the core board joining closely, and there is no cracks on neither of the ends.The inner spliced board is over 60% of the board's volume. So it is the key point to the block board's quality. The standard of its thickness:the thickness of the block board plus the machining allowances of the board when it planed. The standard of its width:in a general way, the width is 1.5 to 2 times of the thickness, it is better not go over the standard. The width of core board to wsome high quality block board is less than 20mm. When the width goes over the standard and its moisture content changes, it could be out of shape. The longer of the core board, the greater bending of the lengthwise. There is a question, the lower of the Utilization. The standard of its material:no resinous wood is allowed, no rotten timber is allowed, and any other defects of the wood.So far, most manufacturing enterprises rest on manual vision inspection to check the defects of the board. About the quality control, enterprises rely on the labors'experiences. It easy to find that checking in this way is inefficiently. And it is uncontrollable for labors to check the boards in same. Focus on this phenomenon; I design a system for checking defects after the board joining.The research content including:This paper used multiple linear CCD camera taking photos to save time.This paper designed a system for checking defects.This paper designed a software system based on Visual C++ 6.0 from taking photos to label the defects.This paper used linear CCD camera lens distortion correction, gray scale images were collected uneven distribution correction. Improve the system accuracy.By contrast to the experimental collected Block board and real images and analysis concluded that the error, verify the usefulness of the system.
Keywords/Search Tags:vision measurement, image stitching, calibration, wood-based panels, surface defect detection
PDF Full Text Request
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