• Journal of Institute of Control, Robotics and Systems
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• v.10 no.8
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• pp.726-733
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• 2004

This paper presents a method to segment object ID(identification) marks on poor quality images under uncontrolled lighting conditions of automated inspection process. The method is based on dynamic programming using multiple templates and normalized gray-level correlation (NGC) method. If the lighting condition is not good and hence, we can not control the image quality, target image to be inspected presents poor quality ID marks and it is not easy to identify and recognize the ID characters. Conventional several methods to segment the interesting ID mark regions fail on the bad quality images. In this paper, we propose a multiple template method, which uses combinational relation of multiple templates from model templates to match several characters of the inspection images. To increase the computation speed to segment the ID mark regions, we introduce the dynamic programming based algorithm. Experimental results using images from real factory automation(FA) environment are presented.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2023.11a
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• pp.165-166
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• 2023

Construction inspection and monitoring are key activities in construction projects. Automation of inspection tasks improves the limitations and inefficiencies of manual construction inspections, enabling systematic and consistent construction inspections. In this paper, an RTSP (Real-Time Streaming Protocol) system is used to remotely manage and supervise the construction site without having to visit the construction site by deploying a robot on site on behalf of four construction stakeholders (owner, supervisor, constructor, and designer). I would like to propose. The proposed system can contribute to identifying and monitoring the process process and work results at the construction site in real time.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.43-48
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• 1992

The automation system oriented as one of the second year automation projects for the small and medium sized enterprises(SME) was developed for the improvement of the production rate and cut the required manpower in the field of the relay which is one of the small electric components used in various industrial fields. The objectives of this study are not only improving the international competition of the relay itself but also partially solving the technical and financial problems featured by common bottlenecks of the SME for efficient assembly automation. For the purpose of these objectives, several topics are studied as followings. - Analyzing the adjustment process and determining the specification of the automation system. - Determining the layout for the automation system to meet the determined specification. - Detail design of the automation system for relay adjustment and inspection. - Control system design - Automation system development and performance test.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1992.04a
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• pp.374-379
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• 1992

The automation system oriented as one of the second year automation projects for the small and medium sized enterprises(SME) was developed for the improvement of the production rate and cut the required manpower in the field of the relay which is one of the small electric components used in various industrial fields. The objectives of this study are not only improving the international competition of the relay itself but also partially solving the technical and financial porblems featured by common bottlenecks of the SME for effecient assembly automation. For the purpose of these objectives, several topics are studied as followings. -. Analyzing the adjustment process and determining the specification of the automation system. -. Determining the layout for the automation system to meet the determined specification. -. Detail design ofthe automation system for relay adjusment and inspection. -. Control system design. -. Automation system development and performance test.

• Journal of Information Processing Systems
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• v.19 no.6
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• pp.791-802
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• 2023

The manual inspection of photovoltaic (PV) panels to meet the requirements of inspection work for large-scale PV power plants is challenging. We present a hot spot detection and positioning method to detect hot spots in batches and locate their latitudes and longitudes. First, a network based on the YOLOv3 architecture was utilized to identify hot spots. The innovation is to modify the RU_1 unit in the YOLOv3 model for hot spot detection in the far field of view and add a neural network residual unit for fusion. In addition, because of the misidentification problem in the infrared images of the solar PV panels, the DeepLab v3+ model was adopted to segment the PV panels to filter out the misidentification caused by bright spots on the ground. Finally, the latitude and longitude of the hot spot are calculated according to the geometric positioning method utilizing known information such as the drone's yaw angle, shooting height, and lens field-of-view. The experimental results indicate that the hot spot recognition rate accuracy is above 98%. When keeping the drone 25 m off the ground, the hot spot positioning error is at the decimeter level.

• IE interfaces
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• v.10 no.1
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• pp.209-222
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• 1997

The paper provides a methodology to obtain the automaticity indicator of a factory and the sequence of enabling technologies of factory automation. The automaticity indicator is the measure of the current automation status of a factory and can be used as a crucial criteria for the future automation schedule and investment. Although most industries have their own computation methods which usually consider the number of workers in the shop floor, this research covers five evaluation items of automation, such as, production facility, material transfer system, inspection and test system, information system, and flexibility. The detailed evaluation models are developed for each item. Automation sequencing prioritizes the enabling technologies of factory automation on the basis of several criteria which consist of two phases. The first phase includes the automation indicator and the second phase includes six sub-criteria such as production rate, quality, number of workers, capital investment, development duration, development difficulty. For this evaluation, AHP(Analytical Hierarchy Process) is introduced to prevent the decision maker's subject intention. As results of the automaticity indicator and automation sequence, the manager can save time and cost in building constructive and transparent automation plans.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2019.05a
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• pp.157-158
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• 2019

Reinforcing bars are an important material for tensile strength of structures. For this reason, the inspection of the reinforcing bars confirming the layout and omission is very important for the safety of the structures. However, the current method of inspecting of the reinforcing bars through photographs of specific areas is difficult to identify condition all reinforcing bars. And It is also difficult to confirm after completion of a building. Therefore, reinforcing bar inspection using 3D scanner is required for automation of rebar inspection and database construction. For this purpose, this study test application of automated inspection method for rebar inspection using 3D scanner and discuss the effect of this method.

• Nuclear industry
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• v.5 no.12 s.34
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• pp.60-71
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• 1985

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.4
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• pp.157-163
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• 2022

Recently, with the development of automation in the industrial field, research on anomaly detection is being actively conducted. An application for anomaly detection used in factory automation is camera-based defect inspection. Vision camera inspection shows high performance and efficiency in factory automation, but it is difficult to overcome the instability of lighting and environmental conditions. Although camera inspection using deep learning can solve the problem of vision camera inspection with much higher performance, it is difficult to apply to actual industrial fields because it requires a huge amount of normal and abnormal data for learning. Therefore, in this study, we propose a network that overcomes the problem of collecting abnormal data with 72 geometric transformation deep learning methods using only normal data and adds an outlier exposure method for performance improvement. By applying and verifying this to the MVTec data set, which is a database for auto-mobile parts data and outlier detection, it is shown that it can be applied in actual industrial sites.

• IEMEK Journal of Embedded Systems and Applications
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• v.17 no.6
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• pp.337-346
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• 2022

This paper addresses the problem of vision-based ear loops ansd attachment inspection in mask production lines. This paper focuses on connections with ear loops and mask filter by an efficient combined approach. The proposed method used a template matching, shape detection and summation of histogram with preprocessing. We had a parameter for detecting defects heuristically. If the shape vertices are lower than the parameters our proposed method will find defective mask automatically. After finding normal masks in mask ear loops attachment status inspection algorithm our proposed method conducts attachment amount inspection. Our experimental results showed that the precision is 1 and the recall is 0.99 in the mask attachment status inspection and attachment amount inspection.