• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1996.06c
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• pp.823-833
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• 1996

An ultimate purpose of this study is to develop an automatic brown rice quality inspection system using image processing technique. In this study emphasis was put on developing an algorithm for discriminating the brown rice kernels depending on their external quality with a color image processing system equipped with an adaptor for magnifying the input image and optical fiber for oblique illumination. Primarily , geometrical and optical features of sample images were analyzed with unhulled paddy and various brown rice kernel samples such as sound, cracked, green-transparent , green-opaque, colored, white-opaque and brokens. Secondary, an algorithm for discrimination of the rice kernels in static state was developed on the basis of the geometrical and optical parameters screened by a statistical analysis(STEPWISE and DISCRIM Procedure, SAS ver.6). Brown rice samples could be discriminated by the algorithm developed in this study with an accuracy of 90% to 96% for the sound , cracked, colored, broken and unhulled , about 81% for the green-transparent and the white-opaque and about 75% for the green-opaque, respectively. A total computing time required for classification was about 100 seconds/1000 kernels with the PC 80486-DX2, 66MHz.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2021.05a
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• pp.295-296
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• 2021

With the recent diversification and complication of buildings, the functions of building are also developing. As much as the development of buildings, the machine or equipment used for them is also developing. Thus, all sorts of domestic/foreign industrial facilities and fire stations in the whole nation are using the electric shutter that could meet the insulation just like the exterior wall of general buildings, for bringing-in/storage and crime prevention/fire prevention. Currently, various types of electric shutters are used. Such wrong operation and poor management are causing many panel-falling accidents. This study researched the reduction of electric shutter panel-falling risk by reviewing the domestic/foreign laws and standards, and researching the new safety equipment. First, the causes for falling and accident types were drawn by analyzing the cases of electric shutter accidents. After that, a checklist as the measures for reducing the falling of electric shutter in building was suggested by analyzing the items for the inspection of electric shutter.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2022.11a
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• pp.223-224
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• 2022

The occurrence of defect, one of the major risk elements, gives rise to construction delays and additional costs. Although construction companies generally prefer to use a method of identifying and classifying the causes of defects, a system for predicting the rise of defects becomes important matter to reduce this harmful issue. However, the currently used methods are kinds of reactive systems that are focused on the defects which occurred already, and there are few studies on the occurrence of defects with prediction systems. This paper is about preliminary study on the development of judgemental algorithm that informs us whether additional works related to defect issue are needed or not. Among machine learning techniques, deep neural network was utilized as prediction model which is a major component of algorithm. It is the most suitable model to be applied to the algorithm when there are 8 hidden layers and the average number of nodes in each hidden layer is 70. Ultimately, the algorithm can identify and defects that may arise in later and contribute to minimize defect frequency.

• Computers and Concrete
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• v.32 no.5
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• pp.475-486
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• 2023

Nondestructive evaluation (NDE) is an important task of civil engineering structure monitoring and inspection, but minor damage such as small cracks in local structure is difficult to observe. If cracks continued expansion may cause partial or even overall damage to the structure. Therefore, monitoring and detecting the structure in the early stage of crack propagation is important. The crack detection technology based on machine vision has been widely studied, but there are still some problems such as bad recognition effect for small cracks. In this paper, we proposed a deep learning method based on sweep signals to evaluate concrete surface crack with a width less than 1 mm. Two convolutional neural networks (CNNs) are used to analyze the one-dimensional (1D) frequency sweep signal and the two-dimensional (2D) time-frequency image, respectively, and the probability value of average damage (ADPV) is proposed to evaluate the minor damage of structural. Finally, we use the standard deviation of energy ratio change (ERVSD) and infrared thermography (IRT) to compare with ADPV to verify the effectiveness of the method proposed in this paper. The experiment results show that the method proposed in this paper can effectively predict whether the concrete surface is damaged and the severity of damage.

• Smart Structures and Systems
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• v.33 no.2
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• pp.105-118
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• 2024

In order to realize tiny bridge crack discovery by UAV-based machine vision, a novel method combining deep learning and tensor voting is proposed. Firstly, the grid images of crack are detected and descripted based on SE-ResNet50 to generate feature points. Then, the probability significance map of crack image is calculated by tensor voting with feature points, which can define the direction and region of crack. Further, the crack detection anchor box is formed by non-maximum suppression from the probability significance map, which can improve the robustness of tiny crack detection. Finally, a case study is carried out to demonstrate the effectiveness of the proposed method in the Xiangjiang-River bridge inspection. Compared with the original tensor voting algorithm, the proposed method has higher accuracy in the situation of only 1-2 pixels width crack and the existence of edge blur, crack discontinuity, which is suitable for UAV-based bridge crack discovery.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.9
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• pp.351-358
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• 2016

An Electrical Point Machine (NS:New-type Switch), which is equipped and operated at railways in Korea, has been used since the 1960s after being imported from Japan. On the other hand, although the mechanical configuration has improved the position motor control circuit, the electrical connection has not been improved, so NS may have a problem, such as the interlocking system of automatic train operation. In addition, NS is the most vulnerable part in the railway system and a huge train accident may occur due to minor defects. The existing NS wiring set of the circuit controller should be checked only if fixed. Therefore, an excessive inspection time only by a Railroad Signal expert is required. In this paper, the improvement of electrical connection in a NS wiring set, such as the position motor control circuit, was developed and the prototype was installed at Seoul Metro in the distance to go section. The results can be used to help make appropriate adjustments. The improvement of the NS wiring set enhance the maintenance efficiency, passenger service and the stability of the signal system as well as reducing the maintenance cost.

• Journal of the Society of Disaster Information
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• v.17 no.2
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• pp.254-265
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• 2021

Purpose: Inspection and diagnosis on the performance and safety through domestic port facilities have been conducted for over 20 years. However, the long-term development strategies and directions for facility renewal and performance improvement using the diagnosis history and results are not working in realistically. In particular, in the case of port structures with a long service life, there are many problems in terms of safety and functionality due to increasing of the large-sized ships, of port use frequency, and the effects of natural disasters due to climate change. Method: In this study, the maintenance history data of the gravity type quay in element level were collected, defined as big data, and a predictive approximation model was derived to estimate the pattern of deterioration and aging of the facility of project level based on the data. In particular, we compared and proposed models suitable for the use of big data by examining the validity of the state-based deterioration pattern and deterioration approximation model generated through machine learning algorithms of GP and SGP techniques. Result: As a result of reviewing the suitability of the proposed technique, it was considered that the RMSE and R² in GP technique were 0.9854 and 0.0721, and the SGP technique was 0.7246 and 0.2518. Conclusion: This research through machine learning techniques is expected to play an important role in decision-making on investment in port facilities in the future if port facility data collection is continuously performed in the future.

• Journal of Dental Rehabilitation and Applied Science
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• v.27 no.1
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• pp.73-79
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• 2011

Purpose of this experiment is to evaluate the effect of titanium on the castability when the titanium is added to the Co-Cr alloy. Raw materials Cobalt, Chrome, Molybdenum, Silicon, Manganase, Carbon, Nitrogen, Titanium were weighted and prepared. $Biosil^F$ (Degudent, Germany) was the control group. To the experimental group, different weight percent of titanium was added from 1 wt% to 4 wt%. The wax pattern is $30{\times}40$ cm in size, rectangular in shape and has total of 160 grids. Centrifugal machine (Neutrodyne Easy Ti: Manfredy) was used for casting. For evaluation of the castability, the number of complete grids was counted by visual inspection and X-ray inspection. The test showed similar castability with the control group in the titanium addition of 1 wt% to 3 wt%. The titanium addition of 4 wt% showed poor result. With titanium lower than 4 wt%, the experiment metals showed proper castability with high expectation of successful clinical use.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.6
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• pp.482-489
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• 2020

This study conducted a prototype development and evaluation by performing die-casting mold design, mold manufacturing, and injection condition optimization based on flow and solidification analysis to meet the needs of the coupling parts produced by die casting. Through flow analysis, the injection conditions suitable for 100% filling in the cavity were found to be a molten metal temperature of 670 ℃, injection speed of 1.164 m/s, and filling pressure of 6.324~18.77 MPa. In addition, solidification close to 100 % occurred in all four cavities when the solidification rate was 69.47 %. A defect inspection on the surface and inside the product revealed defects, such as poor molding and pores. In addition, the dimensions of the injected product were within the target tolerance and showed good results. Through the feedback of the results of flow and solidification analysis, it was possible to optimize the mold design, and the injection optimization conditions were confirmed to be a total cycle time of approximately 6.5 seconds. Good quality carrier parts with an average surface hardness of approximately 45 mm from the gate measured at 97.48(Hv) could be produced.

• Journal of the Korea institute for structural maintenance and inspection
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• v.21 no.4
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• pp.69-79
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• 2017

The purpose of this study is to reconsider the rating method for the floor impact sound insulation performance in current criterion. Although there are some arguments about proper standard heavy impact source with reproducibility of actual impact source in residence building, bang machine is adopted as the only standard heavy impact source in domestic criterion. To inspect the rating methods of evaluation criteria, this study conducted vibration test for both of standard heavy impact sources and actual impact sources. Using the test results, the floor impact sound insulation performance levels were assessed by each of several criteria. In addition, low frequency noise beyond current criteria was evaluated. Consequently, the floor impact sound levels have different performance levels according to adopted criteria, and measured floor impact sounds are bound to annoy the neighbors in the low frequency range. Current criteria does not consider the spectrum characteristics of floor impact sound according to impact sources and low frequency noise. This may cause the difference between the floor impact sound insulation performance level and human perception. Thus current criterion needs to be complemented to reflect the spectrum characteristics of floor impact sound levels according to impact sources and sound pressure levels in low frequency range.