• 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.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.3
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• pp.451-457
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• 2018

We propose an automatic detection and classification system of sewer damage database based on artificial intelligence and deep learning. In order to optimize the performance, we implemented a robust system against various environmental variations such as illumination and shadow changes. In our proposed system, a crack detection and damage classification method using a deep learning based Convolutional Neural Network (CNN) is implemented. For optimal results, 9,941 CCTV images with $256{\times}256$ pixel resolution were used for machine learning on the damaged area based on the CNN model. As a result, the recognition rate of 98.76% was obtained. Total of 646 images of $720{\times}480$ pixel resolution were extracted from various sewage DB for performance evaluation. Proposed system presents the optimal recognition rate for the automatic detection and classification of damage in the sewer DB constructed in various environments.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.2
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• pp.1339-1347
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• 2015

This study discusses a remote control torch system equipped with a GMAW double wire reel. The welding machine is 30m away from the wire feeder at the industrial site and the feeder is three to five meters away from the torch. Accordingly, the welders cannot control the current and voltage that meets the welding condition during work when they are working at a place that prevents them from seeing the control panel, such as inside a vehicle or tank or at a far work site. They also have no choice but to stop working to change the wire reel when it is burned out completely. Such work suspension resulting from frequent moves to adjust the current and voltage as well as to replace the wire and subsequent cooling causes welding defects. This study produced a remote control torch equipped with a double wire reel by simplifying and streamlining the existing GMAW functions to reduce the troubling issue. The remote control torch equipped with a double wire reel and the existing $CO_2$ /MAG welding torch were applied as a V-groove butt in the vertical position using 6mm rolled steel for a SM50A welding structure. After welding, the condition of welded surface beads underwent a visual inspection and radiographic inspection to analyze the welding quality inside the welded part. This study also evaluated the reduction of welding defects, cost saving, the replacing performance against the existing commercial welders, and the effects on possible compatibility.

• Journal of the Korea institute for structural maintenance and inspection
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• v.23 no.1
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• pp.102-112
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• 2019

This paper studies impact fracture behavior under temperature variation and compressive flexural strength of cement composites using VAE(vinyl acetate ethylene) powder polymer and PVA(polyvinyl alcohol) fiber. Impact test were conducted in the temperature range selected for the $-35^{\circ}C$, $0^{\circ}C$ and $35^{\circ}C$. In this experimental study, impact test were carried out using a drop impact testing machine (Ceast 9350) to obtain such as displacement, time, and impact fracture energy of normal specimen and and cement composites specimen. As test results, the use of VAE powder polymer and PVA fiber were observed to enhance the flexural strength of mortar. The compressive strength of PVA fibers reinforced cement composites was slightly decreased at 28 days, but the flexural strength was observed to increase 24.4% of normal mortar strength. As a result of the drop impact tests, PVA fiber reinforced cement composites specimens showed microcracks due to energy dispersion and crack prevention with bridge effect of the fibers, and scabbing or perforation by impact was suppressed. On the other hand, the normal mortar and VAE powder polymer cement composites specimens were carried out to the perforation and macro crack. Most of normal mortar and the cement composites subjected to impact load on specimens shows mostly local brittle failure. The impact resistant performance of the specimen with PVA fiber was greatly improved due to the increase of flexure performance.