• 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.

• Proceedings of the Korea Concrete Institute Conference
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• 2001.11a
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• pp.1097-1102
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• 2001

Seismic safety of continuous span concrete bridge can be enhanced by distributing a large seismic lateral load to each supporting pier. A new viscoelastic device called Shock Transmission Unit(STU), which is a simple cylinder-piston assembly packed with a so-called silicone putty compound, enables the lateral seismic load to be transmitted to the pier by installation of the device to movable bearings of the bridge. The seismic safety of concrete bridges having the STU depends on not only safety of the bridges globally but also safety of anchor systems which anchors the STU to concrete pier. An experimental investigation is performed to study the behavior of cast-in-place anchor and post-installed anchor subjected to shear load statically and cyclically according to different edge distance, embedment length, and anchor spacing. Finally, the experimental results are compared with results by design methods of ACI and CCD, and results by FEM analysis.

• Proceedings of the KIEE Conference
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• 2006.04b
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• pp.281-283
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• 2006

This paper presents two new circuit topologies of DC bus lineside active edge resonant snubber assisted soft-switching PWM full-bridge DC-DC converter acceptable for either utility AC 200V-rms or AC 400V-rms input voltage source. All the active power switches in the full-bridge arms and DC busline can achieve ZCS turn-on and ZVS turn-off commutations and the total turn-off switching power losses of all active switches can be reduced for high-frequency switching action. The effectiveness of these new DC-DC converters topologies is proved for low voltage and large current high efficiency DC-DC power supplies as TIG arc welding machine from a practical point of view.

• The Transactions of the Korean Institute of Power Electronics
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• v.12 no.3
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• pp.241-247
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• 2007

This paper presents a new Leading edge modulation Buck converter operating in discontinuous conduction mode (DCM) for the pulse voltage input. In the slave output of the LLC half-bridge multi-resonant converter, to regulate the direct chopper's output voltage, its PWM switch is controlled by the leading edge modulation. The principles of this proposed LEM control method and the fast dynamics in inductor current based on the converter impulse response are studied. The theoretical results are verified through an experimental prototype of the 100W 60inch PDP Address power module.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.12
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• pp.357-362
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• 2023

Bridges are important transportation infrastructure, but they are subject to damage and cracking due to various environmental factors and constant traffic loads, which accelerate their aging. With many bridges now older than their original construction, there is a need for systems to ensure safety and diagnose deterioration. Bridges are already utilizing structural health monitoring (SHM) technology to monitor the condition of bridges in real time or periodically. Along with this technology, the development of intelligent bridge monitoring technology utilizing artificial intelligence and Internet of Things technology is underway. In this paper, we study an edge system technique for predicting bridge safety using fast Fourier transform and dimensionality reduction algorithm for maintenance of aging bridges. In particular, unlike previous studies, we investigate whether it is possible to form a dataset using sensor data collected from actual bridges and check the safety of bridges.

• Smart Structures and Systems
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• v.33 no.6
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• pp.399-414
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• 2024

This study discusses the long-term deformation monitoring and shape sensing of bridge girder surfaces with an automated extraction scheme for point clouds in the Region Of Interest (ROI), invariant to the position of a Light Detection And Ranging system (LiDAR). Advanced smart construction necessitates continuous monitoring of the deformation and shape of bridge girders during the construction phase. An automated scheme is proposed for reconstructing geometric model of ROI in the presence of noisy non-stationary background. The proposed scheme involves (i) denoising irrelevant background point clouds using dimensions from the design model, (ii) extracting the outer boundaries of the bridge girder by transforming and processing the point cloud data in a two-dimensional image space, (iii) extracting topology of pre-defined targets using the modified Otsu method, (iv) registering the point clouds to a common reference frame or design coordinate using extracted predefined targets placed outside ROI, and (v) defining the bounding box in the point clouds using corresponding dimensional information of the bridge girder and abutments from the design model. The surface-fitted reconstructed geometric model in the ROI is superposed consistently over a long period to monitor bridge shape and derive deflection during the construction phase, which is highly correlated. The proposed scheme of combining 2D-3D with the design model overcomes the sensitivity of 3D point cloud registration to initial match, which often leads to a local extremum.

• Steel and Composite Structures
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• v.35 no.6
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• pp.799-813
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• 2020

Fatigue cracks of rib-to-deck (RD) joints have been frequently observed in the orthotropic steel decks (OSD) using conventional U-ribs (CU). Thickened edge U-rib (TEU) is proposed to enhance the fatigue strength of RD joints, and its effectiveness has been proved through fatigue tests. In-depth full-scale tests are further carried out to investigate both the fatigue strength and fractography of RD joints. Based on the test result, the mean fatigue strength of TEU specimens is 21% and 17% higher than that of CU specimens in terms of nominal and hot spot stress, respectively. Meanwhile, the development of fatigue cracks has been measured using the strain gauges installed along the welded joint. It is found that such the crack remains almost in semi-elliptical shape during the initiation and propagation. For the further application of TEUs, the design curve under the specific survival rate is required for the RD joints using TEUs. Since the fatigue strength of welded joints is highly scattered, the design curves derived by using the limited test data only are not reliable enough to be used as the reference. On this ground, an experiment-numerical hybrid approach is employed. Basing on the fatigue test, a probabilistic assessment model has been established to predict the fatigue strength of RD joints. In the model, the randomness in material properties, initial flaws and local geometries has been taken into consideration. The multiple-site initiation and coalescence of fatigue cracks are also considered to improve the accuracy. Validation of the model has been rigorously conducted using the test data. By extending the validated model, large-scale databases of fatigue life could be generated in a short period. Through the regression analysis on the generated database, design curves of the RD joint have been derived under the 95% survival rate. As the result, FAT 85 and FAT 110 curves with the power index m of 2.89 are recommended in the fatigue evaluation on the RD joint using TEUs in terms of nominal stress and hot spot stress respectively. Meanwhile, FAT 70 and FAT 90 curves with m of 2.92 are suggested in the evaluation on the RD joint using CUs in terms of nominal stress and hot spot stress, respectively.

• Journal of the Korea institute for structural maintenance and inspection
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• v.28 no.3
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• pp.66-73
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• 2024

Stay-cable is one of the most important load carrying members in cable-stayed bridges. Monitoring structural integrity of stay-cables is crucial for evaluating the structural condition of the cable-stayed bridge. For stay-cables, tension and damping ratio are estimated based on modal properties as a measure of structural integrity. Since the monitoring system continuously measures the vibration for the long-term period, data acquisition systems should be stable and power-efficiency as the hardware system. In addition, massive signals from the data acquisition systems are continuously generated, so that automated analysis system should be indispensable. In order to fulfill these purpose simultaneously, this study presents an autonomous cable monitoring system based on domain-knowledge using IoT for continuous cable monitoring systems of cable-stayed bridges. An IoT system was developed to provide effective and power-efficient data acquisition and on-board processing capability for Edge-computing. Automated peak-picking algorithm using domain knowledge was embedded to the IoT system in order to analyze massive data from continuous monitoring automatically and reliably. To evaluate its operational performance in real fields, the developed autonomous monitoring system has been installed on a cable-stayed bridge in Korea. The operational performance are confirmed and validated by comparing with the existing system in terms of data transmission rates, accuracy and efficiency of tension estimation.

• Journal of the Korean Institute of Telematics and Electronics
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• v.25 no.3
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• pp.307-314
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• 1988

The thin, square-diaphragm silicon pressure sensor utilizing shear piezoresistance effect was designed and fabricated and its characteristics were examined. The sensor has only one diffused resistor, whereas conventional full-bridge sensor has four. Sensitivity is somewhat lower but temperature compensation is easier than the latter. The proposed sensor was fabricated with only one p-type diffused resistor of the dimension of 113x85\ulcorner\ulcornerlocated near the center of the edge of the diaphragm. The resistor was at 45\ulcornerwith the edge of the diaphragm. The sensitivity of the sensor was 36\ulcorner/V\ulcornermHg and was linear in the pressure range from 0 to 300 mmHg. The temperature coefficient without temperature compensation was 55 ppm/\ulcorner and it was decreased to about 0.17 mmHg/\ulcorner with compensation in the range from 10 to 60\ulcorner.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.179-185
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• 2005

This paper presents a novel circuit topology of a high efficiency single-phase power conditioner. This power conditioner is composed of time-sharing sinewave absolute pulse width modulated boost chopper with a bypass diode in the first power processing stage and time-sharing sinewave pulse width modulated full-bridge inverter in the second power processing stage operated by time-sharing dual mode pulse pattern control scheme. The unique operating principle of the two power processing stage with time-sharing dual mode sinewave modulation scheme is described with a design example. This paper proposes also a sinewave tracking voltage controlled soft switching PWM boost chopper with a passive auxiliary edge-resonant snubber. The new conceptual operating principle of this novel power conditioner related to new energy utilization system is presented and discussed through the experimental results.