• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.33 no.2
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• pp.215-229
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• 2023

Objectives: To validate the effectiveness of a real-time chemical exposure monitoring system developed by KOSHA (Korea Occupational Safety and Health Agency), we applied the system to a workplace in the electronics industry for 153 days. Methods: The monitoring system consisted of a PID chemical sensor, a LTE communication equipment, and a web-based platform. To monitor chemical exposure, four sets of sensors were placed in two manufacturing tasks - inspection and jig cleaning - which used TCE as a degreasing agent. We reviewed previous reports of work environment measurements and conducted a new work environment measurement on one day during the period. The PID sensor systems detected the chemical exposure levels in the workplace every second and transmitted it to the platform. Daily average and maximum chemical exposure levels were also recorded. Results: We compared the results from the real-time monitoring system and the work environment measurement by traditional methods. Generally, the data from the real-time monitoring system showed a higher level because the sensors were closer to the chemical source. We found that 28% of jig cleaning task data exceeded the STEL. Peak exposure levels of sensor data were useful for understanding the characteristics of the task's chemical use. Limitations and implications were reviewed for the adoption of the system for preventing poisoning caused by chemical substances. Conclusions: We found that the real-time chemical exposure monitoring system was an efficient tool for preventing occupational diseases caused by chemical exposure, such as acute poisoning. Further research is needed to improve the reliability and applicability of the system. We also believe that forming a social consensus around the system is essential.

• Journal of Digital Convergence
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• v.17 no.5
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• pp.217-223
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• 2019

A study in predicting defects of spot welding in real time in automotive field is essential for cost reduction and high quality production. Welding quality is determined by shear strength and the size of the nugget, and results depend on different independent variables. In order to develop the real-time prediction system, multiple regression analyses were conducted and the two dependent variables were obtained with sufficient statistical results with three independent variables, however, the quality prediction by the regression formula could not ensure accuracy. In this study, a multi-layer neural network circuit was constructed. The neural network by 10 dynamic resistance variables was constructed with three hidden layers to obtain execution functions and weighting matrix. In this case, the neural network was established with three independent variables based on regression analysis, as there could be difficulties in real-time control due to too many input variables. As a result, all test data were divided into poor, partial, and modalities. Therefore, a real-time welding quality determination system by three independent variables obtained by multiple regression analysis was completed.

• Journal of the Korea institute for structural maintenance and inspection
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• v.24 no.5
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• pp.150-157
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• 2020

In this study, an algorithm was developed to validate the seismic acceleration measurement data of the seismic acceleration measurement system using measurement data from public buildings currently in operation. Through the results of the study, an algorithm was developed to detect errors and abnormalities in the measurement data itself and the process of generating real-time data (MMA/sec) and event measurement data (MiniSEED), which are the main data generated by the system, and the basic data for determining the direction of inspection through measurement data analysis. It is expected that this will be used as a guideline to determine whether or not the seismic acceleration measurement system, which was managed as receiving/not receiving, is inspected and abnormal types of conditions.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.40 no.4
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• pp.206-213
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• 2003

In this paper, we propose a design method of automatic thickness measurement and defect inspection system, which measures the thickness of the autoclaved lightweight concrete block and inspects the defect 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. For the realization of proposed algorithm, the preprocessing method that can be applied to overcome uneven lighting environment, threshold decision method, unit length decision method in uneven condition with rocking objects, and the curvature calibration method of camera using a constructed grid are developed. From the experimental results, we have found that the required measurement accuracy specification is sufficiently satisfied using our proposed method.

• Journal of the Korean Society of Industry Convergence
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• v.24 no.6_2
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• pp.729-735
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• 2021

Recently Artificial Intelligence(AI) has been developed and used in various fields. Especially AI recognition technology can perceive and distinguish images so it should plays a significant role in quality inspection process. For stability of autonomous driving technology, semiconductors inside automobiles must be protected from external electromagnetic wave(EM wave). As a shield film, a thin polymeric material with hole shaped micro-patterns created by a laser processing could be used for the protection. The shielding efficiency of the film can be increased by the hole structure with appropriate pitch and size. However, since the sensitivity of micro-machining for some parameters, the shape of every single hole can not be same, even it is possible to make defective patterns during process. And it is absolutely time consuming way to inspect all patterns by just using optical microscope. In this paper, we introduce a AI inspection system which is based on web site AI tool. And we evaluate the usefulness of AI model by calculate Area Under ROC curve(Receiver Operating Characteristics). The AI system can classify the micro-patterns into normal or abnormal ones displaying the text of the result on real-time images and save them as image files respectively. Furthermore, pressing the running button, the Hardware of robot arm with two Arduino motors move the film on the optical microscopy stage in order for raster scanning. So this AI system can inspect the entire micro-patterns of a film automatically. If our system could collect much more identified data, it is believed that this system should be a more precise and accurate process for the efficiency of the AI inspection. Also this one could be applied to image-based inspection process of other products.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.7
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• pp.1303-1310
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• 2016

The track circuit carries out a train detection using a electrical closed loop, and incidentally it detects the rail rupture using the track circuit current flowing rail. However, in the case of the axle counter or the Radio based train control system, it requires a new way for detecting the rail rupture because of not using the track circuit. To solve this problem, it periodically checks non-steady state of rail by the track inspection car. but real-time detection of the rail rupture is impossible. Therefore, this paper analyzed feasibility to realize a real-time detection of rail rupture by using the return current.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2006.05a
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• pp.353-354
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• 2006

The automatic inspection system is developed for the formed end part of automotive fuel pipe. The developed system has functions of outer diameter and formed end length measurement by LVDT(linear variable differential transformer) together with burr cleaning of automotive fuel pipe. The measured data are managed and controlled in real time by embedded SPC(statistical process control) program. The system is composed of mechanical part, electronic part and developed software system. These three parts operate automatically by mutual communication with each other. The developed system showed good results in finding inferior goods and efficiency improvement of the fuel pipe production line. It also eliminated the unreliable manual inspection processes and improved the confidence of product quality.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2508-2513
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• 2003

This paper presents a nuclear steam generator tube inspection/maintenance robot system. The robot assists in automatic non-destructive testing and the repair of nuclear steam generator tubes welded into a thick tube sheet that caps a hemispherical or quarter-sphere plenum which is a high-radiation area. For easy carriage and installation, the robot system consists of three separable parts: a manipulator, a water-chamber entering and leaving device for the manipulator and a manipulator base pose adjusting device. A software program to control and manage the robotic system has been developed on the NT based OS to increase the usability. The software program provides a robot installation function, a robot calibration function, a managing and arranging function for the eddy-current test, a real time 3-D graphic simulation function which offers remote reality to operators and so on. The image information acquired from the camera attached to the end-effecter is used to calibrate the end-effecter pose error and the time-delayed control algorithm is applied to calculate the optimal PID gain of the position controller. The developed robotic system has been tested in the Ulchin NPP type steam generator mockup in a laboratory.

• Journal of the Korea Convergence Society
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• v.8 no.3
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• pp.191-197
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• 2017

This development is for non-destructive machine using X-Ray source about detecting outline faults of below middle size products. The differentiation is product of research and development unspecialized small and medium-sized products using X-Ray light sources can check real time if the surface of an external fault of radiation dose reference, within the leakage. The speed control is possible by software solution. In addition, we're working on possibly block doors for worker safety and equipment at the same time that inner drive can be identified in the image. These principles, as a key enabler of the current inspection system such as the container is small to medium-sized parts - a long way from utilization level is possible. This research will give rise to major effects for other various non-destructive market industries except car-industry. The most important fact is that this developed non-destructive machine is controlled below $0.2micro-S{\mu}v$.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.16 no.1
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• pp.9-18
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• 2007

There have been continuous efforts for automation of joint tracking system. This automation process is mainly used to do in root pass of gas metal arc welding in the field of heavy industry and shipbuilding etc. For automation, it is important using of vision sensor. Welding robot with vision sensor is used for weld seam tracking on welding fabrication. Recently, it is used to on post-weld inspection for weld quality evaluation. For real time seam tracking, it is very important role in vision process technique. Vision process is included in filtering and thinning, segmentation processing, feature extraction and recognition. In this paper, it has shown performance comparison results of seam tracking for real time root pass on gas metal arc welding. It can be concluded better segment splitting method than iterative averaging technique in the performance results of seam tracking.