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Exterior Vision Inspection Method of Injection Molding Automotive Parts

사출성형 자동차부품의 외관 비전검사 방법

  • Kim, HoYeon (Department of Computer Science & Engineering, Korea University of Technology and Education) ;
  • Cho, Jae-Soo (Department of Computer Science & Engineering, Korea University of Technology and Education)
  • Received : 2019.01.14
  • Accepted : 2019.02.19
  • Published : 2019.02.28

Abstract

In this paper, we propose a visual inspection method of automotive parts for injection molding to improve the appearance quality and productivity of automotive parts. Exterior inspection of existing injection molding automobile parts was generally done by manual sampling inspection by human. First, we applied the edge-tolerance vision inspection algorithm ([1] - [4]) for vision inspection of electronic components (TFT-LCD and PCB) And we propose a new visual inspection method to overcome the problem. In the proposed visual inspection, the inspection images of the parts to be inspected are aligned on the basis of the reference image of good quality. Then, after partial adaptive binarization, the binary block matching algorithm is used to compare the good binary image and the test binary image. We verified the effectiveness of the edge-tolerance vision check algorithm and the proposed appearance vision test method through various comparative experiments using actual developed equipment.

본 논문에서는 사출성형 자동차부품의 외관 품질과 생산성을 높이기 위하여 사출성형 자동차부품의 외관 비전검사 방법을 제안한다. 일반적으로 기존 사출성형 자동차부품의 외관검사는 사람에 의한 매뉴얼 샘플링 검사로 진행된다. 먼저 전자부품(TFT-LCD 및 PCB 등) 비전검사에 활용되는 Edge-Tolerance 비전검사 알고리즘([1]-[4])을 사출성형 부품 외관검사에 적용하고, 그 문제점을 파악하였다. 그리고 그 문제점을 극복하는 새로운 외관 비전검사 방법을 제안한다. 제안된 외관비전검사는 양품 기준영상을 기준으로 검사하고자 하는 부품의 검사영상을 정렬한 후, 부분적인 적응적 이진화 후, 이진블록매칭 알고리즘을 이용하여 양품 이진영상과 검사이진영상을 블록단위로 비교함으로써 불량부분을 검출한다. Edge-Tolerance 비전검사 알고리즘과 제안된 외관비전검사 방법을 실제 개발된 장비를 이용하여 다양한 비교 실험을 통하여 그 효용성을 검증하였다.

Keywords

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Fig. 1 ACV TL auto part(Throtle Valve, www.sdauto.co.kr)

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Fig. 2 Various appearance defects of ACV TL parts

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Fig. 3 The image reference vision inspection approach

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Fig. 4 Experimental example for edge-tolerance vision algorithm[1-3] (a problem that a non-defective area is also detected as defective area)

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Fig. 5 The block diagram of proposed geometry vision inspection for injection molded parts

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Fig. 6 Concept diagram of injection molding automotive parts vision inspection equipment

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Fig. 7 Vision inspection equipment of ACV TL injection molding automotive parts

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Fig. 8 UI screen image for vision inspection application program

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Fig. 9 Example of detection of defective terminal protrusion during inspection process

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Fig. 10 Experimental results using the proposed vision inspection method (defect detection examples)

Table. 1 Comparison of existing edge-tolerance algorithm and Proposed method

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