• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2004년도 추계학술대회 논문집
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• pp.993-997
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• 2004

A data error inspection algorithm for wireless digital data communication was developed. Original data converted By wireless digital data error inspection algorithm. Wireless digital data is high possibility to get distortion and lose by noise and barrier on wireless. If the data check damaged and lost at receiver, can't make it clear and can't judge whether this data is right or not. Therefore, by wireless transmission data need the data error inspection algorithm in order to decrease the data distortion and lose and to monitoring the transmission data as real time. This study consists of RF station for wireless transmission, Water Level Meter station for water level measurement and Error inspection algorithm for error check of transmission data. This study is also that investigation and search for error inspection algorithm in order to wireless digital data transmission in condition of the least data's damage and lose. Designed transmitter and receiver with one - chip micro process to protect to swell the volume of circuit. Had designed RF transmitter - receiver station simply by means of ATMEL one - chip micro processing the systems. Used 10mW of the best RF power and 448MHz-449MHz on frequency band which is open to public touse free within the limited power.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2008년도 학술대회 논문집 정보 및 제어부문
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• pp.145-146
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• 2008

The appearance inspection of various electronic products and parts has been executed by the eyesight of human. But inspection by eyesight cannot bring about uniform inspection result. Because the appearance inspection result by eyesight of human is changed by condition of physical and spirit of the checker. So machine vision inspection system is currently used to many appearance inspection fields instead of the checker. However the inspection result of machine vision is changed by the illumination of workplace. Therefore we proposed histogram specification in this paper for machine vision inspection accuracy. As a result of histogram specification algorithm, we could increase the exactness of visual inspection and prevent system error from physical and spirit condition of human. More specifically, average inspection error rate was 7.5[%] in existing inspection method but we could see 0.6[%] error rate after applying the algorithm which is presented in this paper.

• 대한임베디드공학회논문지
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• 제18권3호
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• pp.117-124
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• 2023

In the machine vision inspection equipment, diameter measurement is important process in inspection of cylindrical object. However, machine vision inspection equipment requires complex algorithm processing such as camera distortion correction and perspective distortion correction, and the increase in processing time and cost required for precise diameter measurement. In this paper, we proposed the algorithm for diameter measurement of cylindrical object using the laser displacement sensor. In order to fit circle for given four input outer points, grid search algorithms using root-mean-square error and mean-absolute error are applied and compared. To solve the limitations of the grid search algorithm, we finally apply the singular-value-decomposition based circle fitting algorithm. In order to compare the performance of the algorithms, we generated the pseudo data of the outer points of the cylindrical object and applied each algorithm. As a result of the experiment, the grid search using root-mean-square error confirmed stable measurement results, but it was confirmed that real-time processing was difficult as the execution time was 10.8059 second. The execution time of mean-absolute error algorithm was greatly improved as 0.3639 second, but there was no weight according to the distance, so the result of algorithm is abnormal. On the other hand, the singular-value-decomposition method was not affected by the grid and could not only obtain precise detection results, but also confirmed a very good execution time of 0.6 millisecond.

• Corrosion Science and Technology
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• 제18권6호
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• pp.253-257
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• 2019

A deep learning based real-time painting surface inspection algorithm is proposed herein, designed for developing an autonomous inspection drone. The painting surface inspection is usually conducted manually. However, the manual inspection has a limitation in obtaining accurate data for correct judgement on the surface because of human error and deviation of individual inspection experiences. The best method to replace manual surface inspection is the vision-based inspection method with a camera, using various image processing algorithms. Nevertheless, the visual inspection is difficult to apply to surface inspection due to diverse appearances of material, hue, and lightning effects. To overcome technical limitations, a deep learning-based pattern recognition algorithm is proposed, which is specialized for painting surface inspections. The proposed algorithm functions in real time on the embedded board mounted on an autonomous inspection drone. The inspection results data are stored in the database and used for training the deep learning algorithm to improve performance. The various experiments for pre-inspection of painting processes are performed to verify real-time performance of the proposed deep learning algorithm.

• Journal of Mechanical Science and Technology
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• 제20권4호
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• pp.437-446
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• 2006

Laser vision inspection systems are becoming popular for automated inspection of manufactured components. The performance of such systems can be enhanced by improving accuracy of the hardware and robustness of the software used in the system. This paper presents a new approach for enhancing the capability of a laser vision system by applying hardware compensation and using efficient analysis software. A 3D geometrical model is developed to study and compensate for possible distortions in installation of gantry robot on which the vision system is mounted. Appropriate compensation is applied to the inspection data obtained from the laser vision system based on the parameters in 3D model. The present laser vision system is used for dimensional inspection of car chassis sub frame and lower arm assembly module. An algorithm based on simplex search techniques is used for analyzing the compensated inspection data. The details of 3D model, parameters used for compensation and the measurement data obtained from the system are presented in this paper. The details of search algorithm used for analyzing the measurement data and the results obtained are also presented in the paper. It is observed from the results that, by applying compensation and using appropriate algorithms for analyzing, the error in evaluation of the inspection data can be significantly minimized, thus reducing the risk of rejecting good parts.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2004년도 추계학술대회 논문집
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• pp.323-326
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• 2004

In this study, the inspection path which is considered to free collision is generated by offset surface. When the inspection is executed, the consideration of machine dynamic error increases a precision. Dynamic error is measured on CNC machine bed changing of weight work price. Offset surface is safety space about collision. Because the danger of probe-collision is excluded in Offset surface, it is possible to rapid feed of probe and reduced inspection time. The Program which is possible to simulate using CAIP and is confirmed through actual experiment.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2002년도 하계종합학술대회 논문집(5)
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• pp.211-214
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• 2002

Under a continuous manufacturing process, two dimension inspection system causes problems as blurring effect and low resolution and requires position calibration between frames. One dimension inspection system is, therefore, being researched as a substitution. In this paper, we implement mechanism of switching memory and processing data for reasonable one dimension inspection system. Redundant weft image and noise was suggested to be reduced by new method using modified morphological process and masked erosion process. From resulting image, line data and possible error information were obtained and constructed as a structure. Finally, error detecting algorithm was performed with this data structure. Processing time of error detecting was 0.625ms per line in applied system and experiment showed 94.7% of error detecting ability. This method is 20% faster in speed and 2.7% higher in error detecting ability comparing with the present method.

• 한국정밀공학회지
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• 제15권7호
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• pp.26-35
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• 1998

This paper presents a visual inspection algorithm looking for solder joint defects of IC chips on PCBs (Printed Circuit Boards). In this algorithm, seven features are proposed in order to categorize the solder joints into four classes such as normal, insufficient, excess, and no solder, and optimal back-propagation network is determined by error evaluation which depend on the number of neurons in hidden and out-put layers and selection of the features. In the end, a good accuracy of classification performance, an optimal determination of network structure and the effectiveness of chosen seven features are examined by experiment using proposed inspection algorithm.

• 한국산학기술학회논문지
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• 제17권7호
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• pp.14-22
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• 2016

신관은 다양한 부품과 복잡성으로 인해 육안 검사 시 휴먼에러가 발생할 수 있으며 부품 누락, 장전된 신관 등이 제품에 혼입될 경우 탄약이 폭발할 가능성을 내재하고 있다. 본 논문에서는 신관 검사 시 휴먼에러를 방지하기 위한 탄약 자동화검사 알고리즘을 제안한다. 탄약 자동화검사 알고리즘은 다음과 같은 세 단계로 구성된다. 첫 번째로 검사 이미지 입력 및 전처리 단계로써 검사 대상 이미지를 입력하고, 이미지 회전 알고리즘을 적용하여 이미지를 회전한 후 이진화 알고리즘을 사용하여 이미지를 컴퓨터 계산에 적합하도록 이진화한다. 두 번째로 장전 및 비장전 여부를 검사하는 단계로써 Masked Template Matching 알고리즘 등을 활용하여 탄약의 장전여부를 판단한다. 세 번째로 부품검사 단계로써 이미지 탐색 알고리즘 등을 활용하여 부품 위치나 부품 누락 여부에 대해서 판단한다. 본 탄약 자동화검사 알고리즘을 신관 검사에 적용한 결과 부품 누락, 장전 여부 등을 오류 없이 효율적으로 검출함으로써 40mm 고속유탄 신관의 신뢰성 및 안전성 향상에 기여할 것으로 판단된다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2006년 학술대회 논문집 정보 및 제어부문
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• pp.431-433
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• 2006

The goal of this paper is improvement of vision inspection accuracy by using histogram specification operation. The histogram is composed of horizontal axis of image intensity value and vertical axis of pixel number in image. In appearance vision inspection, the histogram of reference image and input image are different because of minutely lighting distinction. The minutely lighting distinction is main reason of vision inspection error in many cases. Therefore we made an effort for elevation of vision inspection accuracy by making the identical histogram of reference image and input image. As a result of this area separation histogram specification algorithm, we could increase the exactness of vision inspection and prevent system error from physical and spirit condition of human. Also this system has been developed only using PC, CCD Camera and Visual C++ for universal workplace.