基于图像形态学激光模具裂纹修复技术研究  

Repair techniques of dies with laser based on image morphological processing

作　　者：张伟杰[1,2] 刘立君[2,3] 张红兴[1,2] 

机构地区：[1]太原科技大学机械工程学院,太原030024 [2]浙江大学宁波理工学院机电与能源工程学院,宁波315100 [3]哈尔滨理工大学材料科学与工程学院,哈尔滨150080

出　　处：《激光技术》2016年第2期189-194,共6页Laser Technology

基　　金：浙江省自然科学基金资助项目(Y1110262);宁波市自然科学基金资助项目(2014A610078);哈尔滨市科技创新人才专项基金资助项目(2012RFXXG75);黑龙江省自然科学基金资助项目(E201240);国家自然科学基金资助项目(51275468);浙江省零件轧制成形技术研究重点实验室开放基金资助项目(ZKL-PR-200303)

摘　　要：为了探究小功率激光模具自动修复技术,利用同轴视觉采集系统采集模具的裂纹图像,结合数字图像形态学细化处理识别裂纹位置信息,建立了数字图像处理流程,得到裂纹的轨迹信息,将裂纹轨迹信息矢量化后,经曲线拟合生成数控代码,导入到数控系统完成激光模具修复。裂纹图像经图像去噪增强、形态学细化等处理后,能够有效地得到裂纹中心线,将裂纹位图矢量化后转为DXF文件格式,通过CAM软件生成数控加工代码。结果表明,该方法加工精度达到0.0368mm,满足模具修复的精度要求;通过图像形态学细化处理技术可以实现激光模具自动修复。这对激光加工设备实现自动化和智能化提供了理论支持和技术基础。In order to repair dies automatically with low-power laser, crack images were taken by a coaxial vision acquisition system. Crack position information was acquired combining with digital image morphological thinning processing technology. Digital images processing were established and crack trajectory information was obtained. And then, dies were repaired by computer numerical control （CNC） system from numerical control （ NC ） code generated from curve fitting vector image. Crack center line was effectively obtained after image denoising, enhancement and morphological thinning treatments. NC codes were generated with the help of CAM software after crack bitmaps were converted to DXF file format. The results show that repair precision of dies can reach 0. 0368mm and meet the repair demands of dies. Dies can be repaired automatically by means of image morphological thinning processing. It is theoretical support and technical foundation for automation and intelligence of laser processing equipment.

关 键 词：激光技术 激光模具修复 图像形态学处理 数控代码 UG NX后处理 

分 类 号：TN249[电子电信—物理电子学] TN957.52