• 한국광학회:학술대회논문집
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• 한국광학회 2006년도 하계학술발표회 논문집
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• pp.469-471
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• 2006

This paper describes a efficient insepction method of PCB PADs for AFVI. The methods for PCB inspection have been tried to detect the defects in PCB PADs, but their low detection rate results from pattern variations that are originating from etching, printing and handling processes. The adaptive inspection method has been newly proposed to extract minute defects based on dynamic segments and filters. The vertexes are extracted from CAM master images of PCB and then a lot of segments are constructed in master data. The proposed method moves these segments to optimal directions of a PAD contour and so adaptively matches segments to PAD contours of inspected images, irrespectively of various pattern variations. It makes a fast, accurate and reliable inspection of PCB patterns. Experimental results show that proposed methods are found to be effective for flexible defects detection.

• 반도체디스플레이기술학회지
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• 제10권1호
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• pp.113-118
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• 2011

This paper proposes computer visual inspection algorithms for PCB defects which are found in a manufacturing process. The proposed method can detect open circuit and short circuit on bare PCB without using any reference images. It performs adaptive threshold processing for the ROI (Region of Interest) of a target image, median filtering to remove noises, and then analyzes connected components of the binary image. In this paper, the connected components of circuit pattern are defined as 6 types. The proposed method classifies the connected components of the target image into 6 types, and determines an unclassified component as a defect of the circuit. The analysis of the original target image detects open circuits, while the analysis of the complement image finds short circuits. The machine vision inspection system is implemented using C language in an embedded Linux system for a high-speed real-time image processing. Experiment results show that the proposed algorithms are quite successful.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 학술대회 논문집 정보 및 제어부문
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• pp.273-275
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• 2005

Active thermography is being used since several years for remote non-destructive testing. It provides thermal images for remote detection and imaging of damages. Also, it is based on propagation and reflection of thermal waves which are launched from the surface into the inspected component by absorption of modulated radiation. For energy deposition, it use external heat sources (e.g., halogen lamp or convective heating) or internal heat generation (e.g., microwaves, eddy current, or elastic wave). Among the external heat sources, the ultrasound is generally used for energy deposition because of defect selective heating up. The heat source generating a thermal wave is provided by the defect itself due to the attenuation of amplitude modulated ultrasound. A defect causes locally enhanced losses and consequently selective heating up. Therefore amplitude modulation of the injected ultrasonic wave turns a defect into a thermal wave transmitter whose signal is detected at the surface by thermal infrared camera. This way ultrasound thermography(UT) allows for selective defect detection which enhances the probability of defect detection in the presence of complicated intact structures. In this paper the applicability of UT for fast defect detection is described. Examples are presented showing the detection of defects in PCB material. Measurements were performed on various kinds of typical defects in PCB materials (both Cu metal and non-metal epoxy). The obtained thermal image reveals area of defect in row of thick epoxy material and PCB.

• 한국멀티미디어학회논문지
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• 제24권8호
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• pp.988-999
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• 2021

AOI (Automatic Optical Inspection) of PCB (Printed Circuit Board) is a very important step to guarantee the product performance. The process of registering components called teaching mode is first perform, and AOI is then carried out in a testing mode that checks defects, such as recognizing and comparing the component mounted on the PCB to the stored components. Since most of registration of the components on the PCB is done manually, it takes a lot of time and there are many problems caused by mistakes or misjudgement. In this paper, A components classifier is proposed using YOLO (You Only Look Once) v2's object detection model that can automatically register components in teaching modes to reduce dramatically time and mistakes. The network of YOLO is modified to classify small objects, and the number of anchor boxes was increased from 9 to 15 to classify various types and sizes. Experimental results show that the proposed method has a good performance with 99.86% accuracy.

• 한국멀티미디어학회논문지
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• 제12권3호
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• pp.397-408
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• 2009

영상 학습은 컴퓨터를 이용한 자동 시각 검사에서 매우 중요하고 어려운 문제이다. 최근 생산되는 인쇄회로 기판(PCB : Printed Circuit Board)은 부품의 크기가 작아지고 회로 패턴이 점점 복잡해져서 신제품의 개발 주기가 짧고 다양한 제품들을 검사해야 하는 분야에서 어렵고 복잡한 학습 과정은 큰 문제가 되고 있다. 본 논문은 CAD(Gerber: 거버)파일을 이용하여 PCB 자동 시각 검사의 기준이 되는 참조 영상을 생성하였다. Gerber 파일로 생성된 참조 영상은 결함이 없는 PCB 패턴을 보장한다. 시스템의 구현과 실험을 통하여 Gerber 파일을 이용하여 PCB 자동 시각 검사 시스템의 학습 과정을 손쉽게 할 수 있는 방안을 제시하였다.

• 한국정밀공학회지
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• 제23권3호
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• pp.102-109
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• 2006

Several methods for PCB pattern inspection have been tried to detect fine detects in pad contours, but their low detection accuracy results from pattern variations originating from etching, printing and handling processes. The adaptive inspection algorithm has been newly proposed to extract minute defects based on movable segments. With gerber master images of PCB, vertex extractions of a pad boundary are made and then a lot of segments are constructed in master data. The pad boundary is composed of segment units. The proposed method moves these segments to optimal directions of a pad boundary and so adaptively matches segments to pad contours of inspected images, irrespectively of various pattern variations. It makes a fast, accurate and reliable inspection of PCB patterns. Its performances are also evaluated with several images.

• 한국콘텐츠학회논문지
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• 제17권7호
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• pp.182-192
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• 2017

제조 산업은 국가 경제 성장의 원동력으로 그 중요성이 부각되고 있다. 이에 따라 제조 공정상에서 생성되는 제조 데이터 분석의 중요성 또한 조명 받고 있다. 본 논문에서는 PCB(Printed Circuit Board) 제조 공정에서 발생한 로그 데이터를 분석하여 PCB 상에서 빈번하게 발생하는 고장 영역에 대해서 작업자가 고장 영역을 직접 눈으로 볼 수 있도록 시각화하는 방법을 제안한다. 우선 고장 영역을 파악하기 위해서 PCB 공정 데이터 집합에 K-means, DB-SCAN 클러스터링 알고리즘을 적용하여 군집화 하였고, 두 알고리즘 중 더 정확한 고장 영역을 도출하는지 비교하였다. 또한 MVC(Model-View-Controller) 구조 시스템을 개발하여 실제 PCB 이미지 상에 클러스터링 결과를 출력하는 것으로 실제 고장영역을 눈으로 확인할 수 있도록 시각화하였다.

• 대한전기학회논문지:시스템및제어부문D
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• 제55권2호
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• pp.68-71
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• 2006

Active thermography has been used for several years in the field of remote non-destructive testing. It provides thermal images for remote detection and imaging of damages. Also, it is based on propagation and reflection of thermal waves which are launched from the surface into the inspected component by absorption of modulated radiation. For energy deposition, it use external heat sources (e.g., halogen lamp or convective heating) or internal heat generation (e.g., microwaves, eddy current, or elastic wave). Among the external heat sources, the ultrasound is generally used for energy deposition because of defect selective heating up. The heat source generating a thermal wave is provided by the defect itself due to the attenuation of amplitude modulated ultrasound. A defect causes locally enhanced losses and consequently selective heating up. Therefore amplitude modulation of the injected ultrasonic wave turns a defect into a thermal wave transmitter whose signal is detected at the surface by thermal infrared camera. This way ultrasound thermography(UT) allows for selective defect detection which enhances the probability of defect detection in the presence of complicated intact structures. In this paper the applicability of UT for fast defect detection is described. Examples are presented showing the detection of defects in PCB material. Measurements are performed on various kinds of typical defects in PCB materials (both Cu metal and non-metal epoxy). The obtained thermal image reveals area of defect in row of thick epoxy material and PCB.

• 정보학연구
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• 제3권4호
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• pp.13-21
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• 2000

본 논문은 PCB를 설계할 때 내부회로환경에서 테스트 정보교환을 위한 방법이 채택되는 최근의 동향을 분석해 본 것이다. PCB의 공정전체에서 설계단계가 테스트성을 개선할 수 있는 잠재력이 가장 크다. PCB는 수많은 노드가 갈수록 복잡해지므로 테스트하기가 점점 어려워지고 있다. 더 짧은 기간에 보다 신뢰성 있는 제품을 내어놓기 위해서는 PCB 테스트 성능을 개선하기 위한 정보교환이 쉬어야한다. 오늘날 가장 낮은 비용으로 결함들을 정확히 발견, 진단 및 수리하기 위하여 두세 가지 종류의 PCB 테스터들을 결합시키고 있다. 가장 효과적인 방법의 하나로 AXI는 ICT와의 결합하여 테스트의 정보를 주고받는 시스템을 많이 사용한다. 테스트를 고려한 설계(DFT)기술은 PCB와 부품들을 철저하고 신속하게 테스트하도록 해주어 PCB의 품질을 효과적으로 개선하고 테스트 개발 시간과 비용을 크게 줄이는 방법이다. 또 실질적이고 정량화가 가능하도록 하며 테스트의 반복, 진단 및 처리 속도를 개선하여 개발 주기를 단축시킬 수 있고 잠재적인 제조 결함들을 효과적으로 발견해내 고신뢰성의 PCB를 생산해 낼 수 있다.

• 한국전자통신학회논문지
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• 제11권5호
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• pp.465-472
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• 2016

본 논문에서는 PCB(: Printed Circuit Board) 패턴 검출을 위하여 Camera Link(Medium)을 지원하는 FPGA 기반 패턴 매칭 시스템을 구현하였다. 최근 생산되고 있는 PCB 패턴은 고집적화 시스템을 위해 점점 미세해지고 복잡해지고 있다. PCB 생산 공정의 비전 자동화를 위하여 고속 처리가 가능한 FPGA 기반 시스템을 제작하였고, 패턴 검출을 위해 사용되는 비전 라이브러리를 IP(: Intellectual property)로 구현하였다. 구현한 IP는 Camera Link IP, 패턴 매칭 IP, VGA IP, 에지 검출 IP, 메모리 IP이다.