Repair techniques of dies with laser based on image morphological processing

ZHANG Weijie; LIU Lijun; ZHANG Hongxing

doi:10.7510/jgjs.issn.1001-3806.2016.02.008

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.

Repair techniques of dies with laser based on image morphological processing

Corresponding author: LIU Lijun, 888liulijun@163.com;

1. College of Mechanical Engineering, Taiyuan University of Science and Technology, Taiyuan 030024, China;

2. College of Mechanical and Energy Engineering, Ningbo Institute of Technology, Zhejiang University, Ningbo 315100, China;

3. College of Materials Science and Engineering, Harbin University of Science and Technology, Harbin 150080, China

Received Date: 2014-12-09

Accepted Date: 2015-01-15

Available Online: 2016-03-25

Abstract: 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.

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Reference (16)

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Repair techniques of dies with laser based on image morphological processing

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