• Proceedings of the KIEE Conference
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• 2003.11c
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• pp.661-664
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• 2003

This paper presents a computer image processing system, which inspects the measurement of the ALC block on a real-time basis. The Image processing system was established with a CCD camera, an image grabber, and a personal computer without using assembled measurement equipment. The image obtained by the system was analyzed by a devised algorithm, specially designed for the enhanced measurement accuracy. From the experimental results, we could find that the required measurement accuracy specification is sufficiently satisfied using our proposed method.

• Journal of the Korean Society for Precision Engineering
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• v.25 no.5
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• pp.69-76
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• 2008

Inner diameter of bearing race is automatically measured by complete inspection system after grinding process. Contact type three points supporting method is widely applied to automatic inner diameter measurement because of its excellent stability. However, the geometric consideration regarding three points supporting method is not sufficient. In this study, the error equation from geometric error analysis of three points supporting method is found. The effect of factors in the error equation is also investigated. The error equation is linear for difference of diameter in sample and master on range of tolerance. An error becomes more and more larger, when the distance of two supporting balls or the diameter of supporting ball are increased. In the result, some considerations are proposed for measurement of inner diameter by the three points supporting method.

• Journal of the KSME
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• v.34 no.2
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• pp.112-117
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• 1994

최근의 전자기기는 반도체 기술의 급속한 발전에 따라 소형화, 고기능화 및 다양화 뿐만 아니라 경박단소화되는 추세에 있다. 이러한 시장의 요구에 대응하여 표면실장용 전자부품이 등장하여 그 사용이 점차증가하고 있고 여기에 발맞춰 국내 . 외 전자기기 제조업체가 제품내의 PCB를 SMD화하는 추세에 있다. 따라서 표면실장 부품의 조립을 위한 고밀도, 고정도의 실장기술의 개발이 요구되고 있다. 또한 부품 자동삽입 등 기존의 방법들로 조립된, 전자기기 내부에 사용 되는 PCB의 조립상태 및 각 부품의 특성들을 검사하기 위한 In-circuit Tester의 기술도 빠른 속도로 발전하여 자동화되어가고 있는 추세에 있다. 이에 따라 본 연구소에서는 '90년에 능 Mounter GCA-M2000 모델을 개발 완료하였고 현재 관련 사업부에서 양산중에 있으며, 아날로그 방식 및 디지털 방식의 In-circuit Tester 모델도 개발 완료하여 현재 양산 중에 있다. 이 지면을 빌어 소개할 기회를 갖고자 한다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.12
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• pp.1956-1959
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• 2021

AIS(Automatic Identification System) provides navigational information including identification, position, a ship's course and status to ground and other vessels. To obtain AIS Marine Equipment Approval Service, various requirements are required and meet the requirements International Standards. However, most of the requirements are to identify essential functions, response time, hardware requirements, and communication protocols of AIS. The requirements for the quality of SW are not sufficient or detailed, and the weight is relatively low. As role of SW grows and types become more diverse, AIS SW quality inspection is essential. In this paper, We apply eight-quality characteristics of ISO/IEC 25023 standard to improve SW coverage quality of AIS. Suggest additional AIS SW requirements based on the eight quality characteristics of ISO/IEC 25023 standard.

• Computers and Concrete
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• v.32 no.6
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• pp.615-623
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• 2023

Crack detection is an essential method to ensure the safety of dam concrete structures. Low-quality crack images of dam concrete structures limit the application of neural network methods in crack detection. This research proposes a modified attentional mechanism model to reduce the disturbance caused by uneven light, shadow, and water spots in crack images. Also, the focal loss function solves the small ratio of crack information. The dataset collects from the network, laboratory and actual inspection dataset of dam concrete structures. This research proposes a novel method for crack detection of dam concrete structures based on the U-Net neural network, namely AF-UNet. A mutual comparison of OTSU, Canny, region growing, DeepLab V3+, SegFormer, U-Net, and AF-UNet (proposed) verified the detection accuracy. A binocular camera detects cracks in the experimental scene. The smallest measurement width of the system is 0.27 mm. The potential goal is to achieve real-time detection and localization of cracks in dam concrete structures.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.38 no.3
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• pp.467-475
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• 2018

The purpose of this study is to propose the evaluation criteria of asphalt pavement condition in narrow regional road considering the traffic environment in order to reduce road budget of local governments. In general, narrow regional roads are considered relatively less important because they have low travel speed and low traffic volume of heavy-vehicle. Generally, automatic surveying equipment is used for investigations of pavement condition, but the operating costs are not efficient for the narrow regional roads because the cost is too high. This study presents the pavement condition evaluation index suitable for narrow regional roads. In this study, the pavement condition evaluation index is presented considering the traffic environment of narrow regional roads. The pavement condition were classified into three classes based on the crack measured by visual inspection, and the validity of the pavement condition evaluation index presented through the expert's questionnaire survey was examined. Pavement condition for the narrow regional roads was classified into three grades based on the index values calculated by visual inspection. Expert's surveys were conducted to evaluate the validity of the proposed pavement condition evaluation. The proposed evaluation index shows a high correlation with questionnaire survey result ($R^2=0.88$). The proposed evaluation index which is obtained through visual crack inspection under limited conditions can be applied to narrow regional roads. In addition, it is expected that it will be effective not only for road management but also for road management budget by more economical evaluation method of pavement condition.

• Design & Manufacturing
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• v.14 no.1
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• pp.8-14
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• 2020

In general, auto parts production assembly line is assembled and produced by automatic mounting by an automated robot. In such a production site, quality problems such as misalignment of parts (doors, trunks, roofs, etc.) to be assembled with the vehicle body or collision between assembly robots and components are often caused. In order to solve such a problem, the quality of parts is manually inspected by using mechanical jig devices outside the automated production line. Automotive inspection technology is the most commonly used field of vision, which includes surface inspection such as mounting hole spacing and defect detection, body panel dents and bends. It is used for guiding, providing location information to the robot controller to adjust the robot's path to improve process productivity and manufacturing flexibility. The most difficult weighing and measuring technology is to calibrate the surface analysis and position and characteristics between parts by storing images of the part to be measured that enters the camera's field of view mounted on the side or top of the part. The problem of the machine vision device applied to the automobile production line is that the lighting conditions inside the factory are severely changed due to various weather changes such as morning-evening, rainy days and sunny days through the exterior window of the assembly production plant. In addition, since the material of the vehicle body parts is a steel sheet, the reflection of light is very severe, which causes a problem in that the quality of the captured image is greatly changed even with a small light change. In this study, the distance between the car body and the door part and the door are acquired by the measuring device combining the laser slit light source and the LED pattern light source. The result is transferred to the joint robot for assembling parts at the optimum position between parts, and the assembly is done at the optimal position by changing the angle and step.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.5
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• pp.413-419
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• 2022

As the development of the underground space becomes active, safety accidents related to the underground are frequently occurring in recent years. In this regard, the Ministry of Land, Infrastructure and Transport is enforcing the 『Special Act on Underground Safety Management』 (enforced on January 1, 2018, hereafter referred to as the Underground Safety Act). Among the core contents of the Underground Safety Act, underground facilities(water supply, sewage, gas, power, communication, heating) buried underground, underground structures(subway, underpass, underpass, underground parking lot, underground shopping mall, common area), ground (Drilling, wells, geology) of 15 types of underground information can be checked at a glance on a three-dimensional basis by constructing an integrated underground spatial map and using it. The purpose of this study is to develop a program that can quickly inspect the three-dimensional model after creating a three-dimensional underground structure data among the underground spatial integration maps. To this end, we first investigated and reviewed the domestic and foreign status of technology that generates and automatically inspects 3D underground structure data. A quality inspection program was developed. Through this study, it is judged that it will be meaningful as a basic research for improving the quality of underground structures on the integrated map of underground space by automating more than 98% of the 3D model inspection process, which is currently being conducted manually.

• The KIPS Transactions:PartD
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• v.9D no.5
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• pp.915-924
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• 2002

Conventional Systems for parcel sorting consist of two sequences as loading the parcel into conveyor belt system and post-code input. Using bar code information, the parcels to be recorded and managed are recognized. This paper describes a 32 $\times$ 32 sized mini-block inspection to extract bar code Region of Interest (ROI) from the line Charged Coupled Device (CCD) camera capturing image of moving parcel at 2m/sec speed. Firstly, the Min-Max distribution of the mini-block has been applied to discard the background of parcel and region of conveying belts from the image. Secondly, the diagonal inspection has been used for the extraction of letters and bar code region. Five horizontal line scanning detects the number of edges and sizes and ROI has been acquired from the detection. The wrong detected area has been deleted by the comparison of group size from labeling processes. To correct excluded bar code region in mini-block processes and for analysis of bar code information, the extracted ROI 8 boundary points and decline distribution have been used with central axis line adjustment. The ROI extraction and central axis creation have become enable within 60～80msec, and the accuracy has been accomplished over 99.44 percentage.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.34 no.6
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• pp.619-627
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• 2016

Cells of a PV (photovoltaic) module can suffer defects due to various causes resulting in a loss of power output. As a malfunctioning cell has a higher temperature than adjacent normal cells, it can be easily detected with a thermal infrared sensor. A conventional method of PV cell inspection is to use a hand-held infrared sensor for visual inspection. The main disadvantages of this method, when applied to a large-scale PV power plant, are that it is time-consuming and costly. This paper presents an algorithm for automatically detecting defective PV panels using images captured with a thermal imaging camera from an UAV (unmanned aerial vehicle). The proposed algorithm uses statistical analysis of thermal intensity (surface temperature) characteristics of each PV module to verify the mean intensity and standard deviation of each panel as parameters for fault diagnosis. One of the characteristics of thermal infrared imaging is that the larger the distance between sensor and target, the lower the measured temperature of the object. Consequently, a global detection rule using the mean intensity of all panels in the fault detection algorithm is not applicable. Therefore, a local detection rule was applied to automatically detect defective panels using the mean intensity and standard deviation range of each panel by array. The performance of the proposed algorithm was tested on three sample images; this verified a detection accuracy of defective panels of 97% or higher. In addition, as the proposed algorithm can adjust the range of threshold values for judging malfunction at the array level, the local detection rule is considered better suited for highly sensitive fault detection compared to a global detection rule. In this study, we used a panel area extraction method that we previously developed; fault detection accuracy would be improved if panel area extraction from images was more precise. Furthermore, the proposed algorithm contributes to the development of a maintenance and repair system for large-scale PV power plants, in combination with a geo-referencing algorithm for accurate determination of panel locations using sensor-based orientation parameters and photogrammetry from ground control points.