• Journal of the Korea institute for structural maintenance and inspection
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• v.24 no.4
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• pp.38-47
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• 2020

A parametric study for analytical correction using measurement results was performed to minimize errors in the predictions of column shortening in RC tall building. The parameters of the column shortening analytical correction are the execution standard of analytical correction, the value of the analytical correction, and the measurement location, and the analytical correction models with the parameters were applied to the construction sequence analysis of a 41-story RC building to compare and analyze the correction effect according to the parameter. The reduction ratio of the error value for each floor was compared with the number of corrections and the total corrected value, and it was confirmed that the error tended to be minimized when the execution standard of analytical correction was performed based on a regular interval, when the analysis correction value was corrected by the error value, and when the measurement position was measured every floor. From this, it was confirmed that the most appropriate analytical correction model can be derived by applying multiple analytical correction models to the actual analysis model.

• Journal of the Earthquake Engineering Society of Korea
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• v.28 no.4
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• pp.183-191
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• 2024

Accurate seismic vulnerability assessment requires high quality and large amounts of ground motion data. Ground motion data generated from time series contains not only the seismic waves but also the background noise. Therefore, it is crucial to determine the high-pass cut-off frequency to reduce the background noise. Traditional methods for determining the high-pass filter frequency are based on human inspection, such as comparing the noise and the signal Fourier Amplitude Spectrum (FAS), f² trend line fitting, and inspection of the displacement curve after filtering. However, these methods are subject to human error and unsuitable for automating the process. This study used a deep learning approach to determine the high-pass filter frequency. We used the Mel-spectrogram for feature extraction and mixup technique to overcome the lack of data. We selected convolutional neural network (CNN) models such as ResNet, DenseNet, and EfficientNet for transfer learning. Additionally, we chose ViT and DeiT for transformer-based models. The results showed that ResNet had the highest performance with R² (the coefficient of determination) at 0.977 and the lowest mean absolute error (MAE) and RMSE (root mean square error) at 0.006 and 0.074, respectively. When applied to a seismic event and compared to the traditional methods, the determination of the high-pass filter frequency through the deep learning method showed a difference of 0.1 Hz, which demonstrates that it can be used as a replacement for traditional methods. We anticipate that this study will pave the way for automating ground motion processing, which could be applied to the system to handle large amounts of data efficiently.

• The KIPS Transactions:PartA
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• v.11A no.4
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• pp.235-242
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• 2004

When manufacturing information and communication device that consists of lots of part, it is important to improve the quality of the produced system by inspecting the system accurately and exclude the defected part. In case of LCD which is recently in a great demand, the inspection process of the nut which bonds the back frame to protect the LCD panel has to be done by human labor. It highly required an automatic inspection system which can inspect the nut without wasting human resources. In this paper, we describe the process of developing a system which automatically inspect the status of nuts inserted during the manufacturing of LCD. The nut inspection vision system developed measures the number of nut's spiral, the distance between pitches, the width of a pitch, and the inside diameter of nut. We have adopted lens with high magnifying power and calibration tool and intended to produce automatic lighting for maintaining a stable environment for a high precision system. We also developed the algorithms for analyzing the nut. We apply the system to real factory field and verify that it is better than the man power in terms of error rate.

• Journal of the Institute of Convergence Signal Processing
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• v.21 no.1
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• pp.38-48
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• 2020

In order to inspect the existing or newly constructed ship's hull, a professional diver directly inspects the ship's bottom of the water. However, since it is a work done by people, there are many dangers such as human casualties and crashes. To solve this problem, it is necessary to develop underwater drones for ship inspection for visual inspection. The technology applied to underwater drones, the use and manufacturing process of each component, and the method of manufacture such as firmware development were described, and the difference was compared by measuring the drone's own driving ability and driving ability using crawler under water, and the location tracking device test confirmed the error from the actual location. It is estimated that the use of underwater drones produced through this research will prevent human casualties and achieve economic effects and stability.

• Journal of the Korea Institute of Building Construction
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• v.23 no.3
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• pp.273-284
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• 2023

This study is centered on the combined use of LiDAR(Light Detection and Ranging) and AR(Augmented Reality) technologies during vertical and horizontal frame measurements in construction projects. The intention is to enhance the quality control procedure, elevate accuracy, and curtail manual labor along with time expenditure. Present methods for accuracy inspection in frame construction often grapple with reliability concerns due to subjective interpretation and the scope for human error. This research recommends the application of LiDAR and AR technologies to counter these issues and augment the efficiency of the inspection process, along with facilitating the dissemination of results. The suggested technique involves the collection of 3D point cloud data of the frame utilizing LiDAR and leveraging this data for checks on construction accuracy. Furthermore, the inspection outcomes are fed into a BIM (Building Information Modeling) model, and the results are visualized via AR. Upon juxtaposing this methodology with the current approach, it is evident that it offers benefits in terms of objective inspection, speed, precise result sharing, and potential enhancements to the overall quality and productivity of construction projects.

• Journal of the Ergonomics Society of Korea
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• v.30 no.1
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• pp.19-28
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• 2011

Objective: The aim of this study is to reclassify human errors and to develop hands-on tools to apply the new classification for preventing human error accidents in highway construction site. Background: The main cause of accidents in highway construction was reported as the carelessness of workers. However, such diagnosis could not help us operationally prevent accidents in real workplace. Method: The accidents in highway construction were reanalyzed and the causes of human error were reclassified in order to educate and improve the awareness of human error in highway construction. Field survey and interview with safety managers and workers were conducted to find the causal relationship between the actual accidents and the human errors. Results: The most frequently observed human errors in highway construction were classified into six categories such as mis-perception, distraction, memory fail, slip, cognition error and mis-judgment. In order to provide hands-on tools to increase the awareness of human error in construction field, the human error checklist and card sorting diary were developed. Especially, the card sorting diary was designed to increase the ability in human error inspection of safety manager at construction site. Moreover, posters were developed based on actual accident cases. Conclusion: We suggested that the improved awareness and analytical report on checklist, card sorting diary and posters for construction field could collectively prevent the accident. Application: The classification of human error, hands-on tools and posters can be directly applicable on highway construction site. This analytical and collective approach preventing human error-related accident could be extended to other construction workplaces.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.7
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• pp.3444-3449
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• 2013

The control module controlling points has become high-tech. but the introduction of relevant company's inspection intervals and methods, and the adoption of the way which is used in relay interlock system became the cause of a failure by excessive and incorrect maintenance. The Human error in failure recovery process can cause vital accidents including train derailment, the points monitoring system could prevent this problem by monitoring points' operation condition in real time. After conducting the changed inspection intervals that applied the results of the criticality of each failure type, MTBF, MTTR, availability, maintainer's opinion, the work became simplified, and, the failure did not occur for 4 consecutive years in contrast to the previous annual average of 11 failures.

• Journal of the Korean Society for Precision Engineering
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• v.30 no.5
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• pp.513-519
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• 2013

Line scan camera has been widely used in the area of inspection of glass, film, fabric, iron, PCB and etc. due to the high resolution and the high speed. We developed the line scan based vision system to inspect tangled and cut-off status of yarn in the manufacturing process. The original image is binarized with a proper threshold, and the gap distances in the yarn are measured in real time, so finally the status of the process is decided by the maximum value of the gap distance. All procedures are executed in real time by realization of multi-processed threads. By implementation of this system, the error of the yarn in manufacturing process can be precedently monitored and the loss of the yarn is decreased efficiently.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.3
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• pp.353-362
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• 1999

This paper presents a shape reconstruction method for automatic inspection of the solder joints on PCBs using X-ray. Shape reconstruction from X-ray radiographic image has been very important since X-ray equipment was used for improving the reliability of inspection result. For this purpose there have been lots of previous works using tomography, which reconstructs the correct shape, laminography or tomosynthesis, which are very fast algorithm. Latter two methods show outstanding performance in cross-sectional image reconstruction of lead type component, but they are also known to show some fatal limitations to some kinds of components such as BGA, because of shadow effect. Although conventional tomography does not have any shadow effect, the shape of PCB prohibits it from being applied to shape reconstruction of solder joints on PCB. This paper shows that tomography using Iterative Reconstruction Technique(IRT) can be applied to this difficult problem without any limitations. This makes conventional radiographic instrument used for shape reconstruction without shadow effect. This means that the new method makes cost down and shadow-free shape reconstruction. To verify the effectiveness of IRT, we develop three dimensional model of BGA solder ball, make projection model to obtain X-ray projection data. and perform a simulation study of shape reconstruction. To compare the performance of IRT with that of conventional laminography or tomosynthesis, reconstruction data are reorganized and error analysis between the original model are also performed.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.7
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• pp.1551-1556
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• 2010

In this paper, we propose a new inspection method that applies fuzzy reasoning method considering the difference of brightness and intensity of illumination by bend together. In the preprocessing phase, we compensate the degree of semiconductor images with bilinear interpolation and moment-rotation. Then we use fuzzy reasoning method with the difference of brightness from error region by pattern matching and the difference of intensity of illumination from bends. Then the result is difuzzified and applied to the final inspection process. In experiment which uses 30 real world semiconductors with strait shots and side shots, the proposed method successfully discard the false positive identified by conventional brightness comparison only method without any loss of misidentification.