• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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• pp.48-51
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• 1997

This paper presents the algorithm of FIC inspection in chip mounter. When device is mounted on the PCB, it is impossible to get zero defects since there are many problems which can not be predicted. Of these problems, devices with bent corner leads due to mis-handling and which are not placed at a given point measured along the axis are principal problem in SMT(Surface Mounting Technology). In this paper, we proposed a new algorithm based on the Radon transform which uses a projection to inspect the FIC(Flat Integrated Circuit) device and compared this method with other algorithms. We measured the position error and applied this algorithm to our image processing board which is characterized by line scan camera. We compared speed and accuracy in our board.

• Structural Engineering and Mechanics
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• 제87권3호
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• pp.211-219
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• 2023

The structural health of a pipeline is usually assessed by visual inspection. In addition to the fact that this method is expensive and time consuming, inspection of the whole structure is not possible due to limited access to some points. Therefore, adopting a damage detection method without the mentioned limitations is important in order to increase the safety of the structure. In recent years, vibration-based methods have been used to detect damage. These methods detect structural defects based on the fact that the dynamic responses of the structure will change due to damage existence. Therefore, the location and extent of damage, before and after the damage, are determined. In this study, fuzzy genetic algorithm has been used to monitor the structural health of the pipeline to create a fuzzy automated system and all kinds of possible failure scenarios that can occur for the structure. For this purpose, the results of an experimental model have been used. Its numerical model is generated in ABAQUS software and the results of the analysis are used in the fuzzy genetic algorithm. Results show that the system is more accurate in detecting high-intensity damages, and the use of higher frequency modes helps to increase accuracy. Moreover, the system considers the damage in symmetric regions with the same degree of membership. To deal with the uncertainties, some error values are added, which are observed to be negligible up to 10% of the error.

• Journal of Biosystems Engineering
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• 제23권6호
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• pp.621-628
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• 1998

In order to develop an inspection algorithm for an automatic eggshell inspection system, acoustic impulse response with neural network method was studied. An improved error backpropagation algorithm was selected as a loaming rule of neural network, and three layer network was chosen for the neural network architecture. Acoustic signals in time domain and theirs power spectrum were studied as the input to the neural network. The classification feasibility and success rate were investigated in terms of statistical analysis and neural network approach. As a result, the success rate was 95% with the statistical model having five independent variables. Among the neural network models studied, the power spectrum of acoustic signal as the input with 64 input neurons and the two impact data showed the success rate of 95.5% which was slightly higher than of statistical analysis.

• 한국산학기술학회논문지
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• 제14권6호
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• pp.2624-2630
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• 2013

LED 칩 패키징에서 다이 본딩은 분할된 칩을 리드 프레임에 고정시켜 칩이 이후 공정을 견딜 수 있도록 충분한 강도를 제공하는 중요한 공정이다. 다이본딩 공정 중에서, 측정 단계는 정확한 에폭시 토출 위치 지정과 충분한 강도를 가지고 접합할 수 있도록 다이가 정확한 위치에 놓여있는지 상태를 결정하는데 있어 매우 중요하다. 본 연구에서는 LED 다이 본딩을 위한 머신 비전 기반의 측정 시스템을 개발하였다. 제안된 시스템에서 에폭시 토출과 어태칭 상태 검출을 위해 각각 2개의 카메라를 사용하였다. 제안된 측정 시스템에 새로운 비전 알고리즘을 적용하였고, 실험을 통해 본 알고리즘의 효율을 검증하였다. 비전 알고리즘을 이용하여 측정된 위치 오차는 $X:-29{\mu}m$, $Y:-32{\mu}m$, 회전오차는 3도 이내 인 것을 확인할 수 있었다. 결론적으로 제안된 머신 비전 기반의 측정 시스템을 통해 개발된 다이 본딩 시스템의 향상된 성능을 확인하였다.

• 한국구조물진단유지관리공학회 논문집
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• 제11권4호
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• pp.129-137
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• 2007

본 논문에서는 교량상을 이동하는 차량의 차축하중을 교량의 동적거동을 계측하여 추정하는 알고리듬을 제안하였으며, 교량을 보로 모델하여 알고리듬을 적용하였다. 가속도는 교량에서 직접 계측하였으며, 변위는 가속도와 같은 위치에 부착한 변형률을 변환하여 계산하는 식을 제안하였다. 절점하중벡터는 속도별로 준비해둔 절점하중변환행렬 데이터베이스를 사용하여 구하였다. 개발된 알고리듬을 수치예제와 실내모형실험을 통해 검증하였다. 수치예제에서는 계측오차와 속도 및 위치오차가 하중식별에 미치는 영향을 분석하였다.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2003년도 춘계학술대회 논문집
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• pp.434-437
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• 2003

Evaluation or the patterning accuracy of e-beam lithography machines requires a high precision inspection system that is capable of measuring the true xy-locations of fiducial marks generated by the e-beam machine under test. Fiducial marks are fabricated on a single photo mask over the entire working area in the form of equally spaced two-dimensional grids. In performing the evaluation, the principles of self-calibration enable to determine the deviations of fiducial marks from their nominal xy-locations precisely, not being affected by the motion errors of the inspection system itself. It is. however, the fact that only repeatable motion errors can be eliminated, while random motion errors encountered in probing the locations of fiducial marks are not removed. Even worse, a random error occurring from the measurement of a single mark propagates and affects in determining locations of other marks, which phenomenon in fact limits the ultimate calibration accuracy of e-beam machines. In this paper, we describe an uncertainty analysis that has been made to investigate how random errors affect the final result of self-calibration of e-beam machines when one uses an optical inspection system equipped with high-resolution microscope objectives and a precision xy-stages. The guide of uncertainty analysis recommended by the International Organization for Standardization is faithfully followed along with necessary sensitivity analysis. The uncertainty analysis reveals that among the dominant components of the patterning accuracy of e-beam lithography, the rotationally symmetrical component is most significantly affected by random errors, whose propagation becomes more severe in a cascading manner as the number of fiducial marks increases

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2001년도 춘계학술대회 논문집(한국공작기계학회)
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• pp.376-381
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• 2001

This paper presents a methodology of machining error compensation by using Artificial Neural Network(ANN) model based on the inspection database of On-Machine-Measurement(OMM) system. First, the geometric errors of the machining center and the probing errors are significantly reduced through compensation processes. Then, we acquire machining error distributions from a specimen workpiece. In order to efficiently analyze the machining errors, we define two characteristic machining error parameters. These can be modeled by using an ANN model, which allows us to determine the machining errors in the domain of considered cutting conditions. Based on this ANN model, we try to correct the tool path in order to effectively reduce the errors by using an iterative algorithm. The iterative algorithm allows us to integrate changes of the cutting conditions according to the corrected tool path. Experimentation is carried out in order to validate the approaches proposed in this paper.

• 한국기계가공학회지
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• 제3권4호
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• pp.7-12
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• 2004

Inspection and analysis are essential process to determine whether a completed product is in given specification or not. Analysis of products with very complicated shape is difficult to carry out direct comparison between inspected coordinate and designed coordinates. So process called as matching or registrations is needed to solve this problem. By defining error between two coordinates and minimizing the error, registration is done. Registration consists of translation, rotation and scale transformations. Error must be defined to express feature of inspected product. In this paper, registration algorithm is developed to determine pose of sub-frame at assembly with body of automobile by defining error between two coordinates considering geometric feature of sub-frame.

• 디지털산업정보학회논문지
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• 제5권1호
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• pp.99-105
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• 2009

Recently the research is much interested in about the inspection system using by computer vision system. In this paper, we deal with shape inspection technique for moving to be long and narrow object on conveyor belt. first, we are acquired for moving object on conveyor belt. then the object segmentation is using by color information for background and object. the object position be calculated by horizontal and a vertical histogram. second, we are checked for two hole in front part, widths and top/bottom side information in middle part, and finally checking for two holes in rear part. The performance of our proposed model is evaluated by experiments, within error of 1㎜, and can be checking to 17 object /min.

• 전기학회논문지
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• 제57권2호
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• pp.307-313
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• 2008

In this paper, we propose a novel defects inspection algorithm for TFT-LCD panels. We first compensate the distorted image caused by the camera distortion and the uneven illumination environment using the least squares method and the bezier surface. We find a starting point of each pattern for restricting each pattern. A clean image is compared to each pattern to find defects using modified PCSR-G algorithm. The simulation example shows that our algorithm not only inspects the defects well, but also is robust to the 1-pixel error.