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刘立君, 张伟杰, 于义涛, 胡雄武, 张红兴. 小功率激光模具自动修复CCD标定技术[J]. 焊接学报, 2015, 36(12): 1-4.
引用本文: 刘立君, 张伟杰, 于义涛, 胡雄武, 张红兴. 小功率激光模具自动修复CCD标定技术[J]. 焊接学报, 2015, 36(12): 1-4.
LIU Lijun, ZHANG Weijie, HU Xiongwu, ZHANG Hongxing. CCD calibration technology for low-power laser automatic repair of dies[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2015, 36(12): 1-4.
Citation: LIU Lijun, ZHANG Weijie, HU Xiongwu, ZHANG Hongxing. CCD calibration technology for low-power laser automatic repair of dies[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2015, 36(12): 1-4.

小功率激光模具自动修复CCD标定技术

CCD calibration technology for low-power laser automatic repair of dies

  • 摘要: 针对模具修复过程中的质量控制问题引入视觉传感技术. 为得到准确的模具修复中的视觉特征信息,对模具修复试验装置的成像系统进行了分析,建立成像模型,分析亚像素角点提取算法,制作符合试验装置要求的标定板,对利用改进的张正友法对试验装置进行了标定,求得成像系统的内参数和外参数. 结果表明,成像系统标定误差为0.712 305像素,即标定误差为0.012 4 mm,利用标定后的试验装置修复模具;修复结果表明标定方法实用可靠,满足小功率激光模具自动修复的精度要求.

     

    Abstract: Aim at the quality control problems during the process, visual sensing technology was introduced. In order to obtain the visual feature information accurately, the imaging system was analyzed, imaging model was put forward, and the sub-pixel corner extraction algorithm was compared. External parameters and extrinsic parameters was obtained by improved calibration algorithm of Zhang using color optimized calibration target. Results show that calibration error is 0.712 305 pixel, it namely that 0.123 mm. Two dies was repaired after the calibration, which could meet the accuracy requirement and this method was practical and reliable.

     

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