• Journal of Mechanical Science and Technology
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• v.20 no.4
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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.

• Journal of the Korean Society for Nondestructive Testing
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• v.33 no.1
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• pp.26-33
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• 2013

BMI nozzles in bottom head of the nuclear vessel are one of major components in nuclear power plants. The BMI nozzles have high possibility to generate PWSCC(primary water stress corrosion crack) according to recent foreign case although operation temperature is lower then the upper head of the nuclear vessel. Thus, nondestructive inspection of the BMI nozzles is required. But, inspection of BMI nozzles is not easy since the BMI nozzles placed in high radiated area and inside the nozzles filled with boric acid. Thus, in this study, a TOFD transducer for inspection of BMI and automated scanner system with water were developed. Also, validation of performance of the developed transducer and system are performed using specimens with artificial defects.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.304-311
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• 2022

Construction inspection is a crucial stage that ensures that all contractual requirements of a construction project are verified. The construction inspection capabilities among state highway agencies have been greatly affected due to budget reduction. As a result, efficient inspection practices such as risk-based inspection are required to optimize the use of limited resources without compromising inspection quality. Automated prioritization of textual requirements according to their criticality would be extremely helpful since contractual requirements are typically presented in an unstructured natural language in voluminous text documents. The current study introduces a novel model for predicting the risk level of requirements using machine learning (ML) algorithms. The ML algorithms tested in this study included naïve Bayes, support vector machines, logistic regression, and random forest. The training data includes sequences of requirement texts which were labeled with risk levels (such as very low, low, medium, high, very high) using the fuzzy logic systems. The fuzzy model treats the three risk factors (severity, probability, detectability) as fuzzy input variables, and implements the fuzzy inference rules to determine the labels of requirements. The performance of the model was examined on labeled dataset created by fuzzy inference rules and three different membership functions. The developed requirement risk prediction model yielded a precision, recall, and f-score of 78.18%, 77.75%, and 75.82%, respectively. The proposed model is expected to provide construction inspectors with a means for the automated prioritization of voluminous requirements by their importance, thus help to maximize the effectiveness of inspection activities under resource constraints.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.8
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• pp.2043-2050
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• 2014

As most the scanning systems developed until now provide radiation scan plane images of the inspected objects, there has been a limitation in judging exactly the shape of the objects inside a logistics container exactly with only 2-D radiation image information. As a radiation image is just the density information of the scanned object, the direct application of general stereo image processing techniques is inefficient. So we propose that a new volume-based 3-D reconstruction algorithm. Experimental results show the proposed new volume based reconstruction technique can provide more efficient visualization for X-ray inspection. For validation of the proposed shape reconstruction algorithm using volume, 15 samples were scanned and reconstructed to restore the shape using an X-ray stereo inspection system. Reconstruction results of the objects show a high degree of accuracy compared to the width (2.56%), height (6.15%) and depth (7.12%) of the measured value for a real object respectively. In addition, using a K-Mean clustering algorithm a detection efficiency of 97% is achieved. The results of the reconstructed shape information using the volume based shape reconstruction algorithm provide the depth information of the inspected object with stereo X-ray inspection. Depth information used as an identifier for an automated search is possible and additional studies will proceed to retrieve an X-ray inspection system that can greatly improve the efficiency of an inspection.

• 한국정보디스플레이학회:학술대회논문집
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• 2007.08a
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• pp.286-289
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• 2007

We have developed an automated circuit defect inspection and repair method that can be used to improve the yield ratio of TFT-LCD. The method focuses on correcting resist patterns after the development process to ensure shape regularity. We built a prototype system and confirmed that the method is valid.

• IE interfaces
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• v.11 no.3
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• pp.15-22
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• 1998

A new improved algorithm in edge location to subpixel accuracy using decent-based weight to spatial information is proposed in this paper and applied to automated visual inspection(AVI) system. An application of the new edge operator as an edge detector is also provided and compared with Tabatabai and Lyvers edge detectors. The existing algorithms located edger to subpixel accuracy using least-square or moment-based methods. The algorithms also use only spatial information or grey-level values to locate edges. However, the proposed algorithm consider the weighted sum of grey-levels values of each edge pattern. The results show that the proposed algorithm is relatively less biased and has smaller standard deviation than the edge operations developed by Tabatabai and Lyvers in the presence of noise.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.23 no.3
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• pp.331-340
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• 2005

Digital map is very important digital geographic information which is the base for various fields such as building and using the geographic information system (GIS), planing the regional development, and etc. Therefore, it needs high accuracy. Then we offer the advanced technique which minimizes errors on digital maps, using the automated inspection through the whole figures. In addition this new technique raises the economical efficiency as well as accuracy applying the automated error detection method which can recognize, search and classify errors automatically.

• The Journal of Korean Institute for Practical Engineering Education
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• v.4 no.2
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• pp.91-97
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• 2012

The automated visual inspection system (machine vision system) for quality assurance is an important factory automation equipment in the manufacturing industries, such as display, semiconductor, etc. The world market of the machine vision components is expected 18 billon dollars in 2015. Therefore, there is a lot of demand for the machine vision engineers. However, there are no technical training courses for machine vision technologies in vocational schools, colleges and universities. In this paper, we propose a technical training program for the machine vision technology. The total time of training is 30 to 60 hours and the training program can operate flexibly by student's major, a priori knowledge and education level.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.6
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• pp.1-15
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• 2009

In this paper, we have proposed an automated system that accurately measures the thickness and unbalanced wear of brake shoes, and the distance between brake shoes and wheels for travelling rolling stock. The images of brake shoes are captured automatically while rolling stock is passing by an inspection station. And in order to measure the thickness, etc. the locations of brake shoes are first determined because the locations are not the same in the captured image. Toward this goal, shadow regions between the brake shoes and wheels are utilized that are common in all captured images. The boundary of the shadow regions is modeled by an second order polynomial, and constrained curve fitting method is adopted to detect a curve (the initial curve) that passes through the regions. Then, three curves that correspond to the front, back of brake shoes and wheels, and a line that passes through the vertical surface of brake shoes are detected using the initial curve and intensity change information. Finally, the thickness, etc. are calculated using the detected curves and line, and experimental results showed that the brake shoe thickness was measured with an accuracy of 0.654mm.

• International Journal of Safety
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• v.8 no.2
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• pp.31-36
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• 2009

In accordance with the development of recent computer technology, railway signaling software became more complex for the intellectualization. Therefore the importance and dependency of railway signaling system on the computer software is getting more increased further, and the testing for the safety and reliability of railway signaling system software became more important. It is started to become influential as very important issue for the reliability and safety of vital embedded software like railway signaling system. The software coding which can have an effect on the safety at the coding level of software shall not be included preferentially, for the safety of software, and must be checked. This thesis suggested an automated testing tool for coding rules on this railway signaling system software, and presented its applied result for railway signaling system software. The testing items in the implemented tool had referred to the international standards in relation to the software for railway system and MISRA-C standards. This automated testing tool for railway signaling system can be utilized at the assessment stage for railway signaling system software also, and it is anticipated that it can be utilized usefully at the software development stage also.