• Journal of electromagnetic engineering and science
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• v.15 no.2
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• pp.104-110
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• 2015

As civil infrastructures continue to deteriorate, the demand for structural health monitoring (SHM) has increased. Despite its outstanding capability for damage identification, many conventional SHM techniques are restricted to huge structures because of their wired system for data and power transmission. Although wireless data transmission using radio-frequency techniques has emerged vis-$\grave{a}$-vis wireless sensors in SHM, the power supply issue is still unsolved. Normal batteries cannot support civil infrastructure for no longer than a few decades. In this study, we develop a magnetic resonance-based wireless power transmission system, and its performance is validated in three different mediums: air, unreinforced concrete, and reinforced concrete. The effect of concrete and steel rebars is analyzed.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2001.10a
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• pp.101-108
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• 2001

In the previous study, an improved QRD (QR Decomposition)-ILS(Iterative Least-Squares) method is proposed to estimate the structural parameters at the element level using response data alone without using any information of excitation measurements for the assessment of local damages and deterioration in complex and large structural systems. But for a complex and large structural system, where response measurement at every dynamic degree of freedom(DDOF) is not possible, the absence of some observation points of responses and its effect on the proposed SI method must be studied In the paper, a QRD-ILS technique that utilizes the known intact stiffness information estimated based on the visual inspection, field measurements and/or NDT tests is proposed to identify local damages of fracture critical members using measured responses only at limited DDOFs. A numerical example is used to illustrate the application of this technique. The results indicate that the proposed SI technique is very simple but efficient, since no input information are required with only limited observations.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2011.04a
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• pp.676-679
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• 2011

인공신경망(Artificial Neural Network)을 이용하여 RC Mock-up 구조물의 손상위치 및 손상정도를 단계적으로 추정하였다. 대상 구조물은 가진실험을 통하여 구조물의 응답을 취득하고 구조물식별기법(Structural System Identification)을 통하여 구조물의 동특성을 찾았다. 유한요소해석프로그램을 사용하여 동특성이 계측치와 가장 유사한 기본해석모델을 만든 후 이 기본해석모델을 이용하여 학습데이터를 생성하였다. 기존 인공신경망을 이용한 손상탐지를 개선하고자 본 연구에서는 인공신경망 학습데이터를 분석하였고 효과적인 손상탐지를 위하여 학습데이터를 가공하였다. 가공된 학습데이터를 사용하여 단계별 손상탐지를 실시하였고 기존 손상탐지 방법보다 좋은 결과를 유도하였다.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2003.05a
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• pp.430-433
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• 2003

This paper presents a system identification (SI) scheme in time domain using measured acceleration data. The error function is defined as the time integral of the least square errors between the measured acceleration and the calculated acceleration by a mathematical model. Damping parameters as well as stiffness properties of a structure are considered as system parameters. The structural damping is modeled by the Rayleigh damping in SI. The regularization technique is applied to alleviate the ill-posed characteristics of inverse problems. The validity of the proposed method is demonstrated by an experimental study on a shear building model.

• Journal of the Korean Society of Safety
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• v.26 no.5
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• pp.54-58
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• 2011

Emergency preparedness plan(EPP) is the systematic management of activities that involve a material degree of risk of loss or other damage to the surroundings(people, property and environment), and the boundary of accident recovery plan(ARP). The main purpose of the program is to provide a safety management system to each facility in order to enable to prevent accident and to control accident immediately. The EPP includes not only typical safety-related documentations such as material safety data sheet(MSDS), standard operation procedure(SOP), emergency response plan(ERP). EPP is established basis of the preliminary safety analysis involving risk identification, assessment and prevention plans. The program is also helpful for government or related agencies to control a number of accidents in small-scale companies in the whole country.

• Earthquakes and Structures
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• v.12 no.4
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• pp.437-448
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• 2017

Soft or extreme soft storeys in multi-storied buildings cause localized damage (and even collapse) during strong earthquake shaking. The presence of such soft or extremely soft storey is identified through provisions of vertical stiffness irregularity in seismic design codes. Identification of the irregularity in a building requires estimation of lateral translational stiffness of each storey. Estimation of lateral translational stiffness can be an arduous task. A simple procedure is presented to estimate storey stiffness using only properties of fundamental lateral translational mode of oscillation (namely natural period and associated mode shape), which are readily available to designers at the end of analysis stage. In addition, simplified analytical expressions are provided towards identifying stiffness irregularity. Results of linear elastic time-history analyses indicate that the proposed procedure captures the irregularity in storey stiffness in both low- and mid-rise buildings.

• Smart Structures and Systems
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• v.24 no.6
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• pp.683-692
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• 2019

Traditional damage detection methods for nonlinear structures are often based on simplified models, such as the mass-spring-damper and shear-building models, which are insufficient for predicting the vibration responses of a real structure. Conventional global nonlinear finite element model updating methods are computationally intensive and time consuming. Thus, they cannot be applied to practical structures. A decentralized approach for identifying the nonlinear material parameters is proposed in this study. With this technique, a structure is divided into several small zones on the basis of its structural configuration. The unknown material parameters and measured vibration responses are then divided into several subsets accordingly. The structural parameters of each subset are then updated using the vibration responses of the subset with the Newton-successive-over-relaxation (SOR) method. A reinforced concrete and steel frame structure subjected to earthquake loading is used to verify the effectiveness and accuracy of the proposed method. The parameters in the material constitutive model, such as compressive strength, initial tangent stiffness and yielding stress, are identified accurately and efficiently compared with the global nonlinear model updating approach.

• Korea Trade Review
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• v.44 no.4
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• pp.153-168
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• 2019

The logistics industry is changing with the diversification of demand and related technology development. Thus, the transportation system is also changing to social problems and environmental damage, and the importance of rail freight is increasing with changes in the international logistics environment. This study analyzes railway freight competition structure using freight volume and suggests improving the competitiveness of railroad freight. To achieve the research purpose, this study was conducted using the Hirshmann-Herfindahl Index(HHI) and Location Quotients(LQ) method. As a result, the concentration trend of railway trends has increased from 0.213 to 0.238 during the last 9 years, and LQ analysis has enabled the identification of local competition lines by item. The study result confirmed that policy measures on railway freight system, railway infrastructure construction and railway operation are necessary to enhance railway competitiveness.

• Journal of Korean Medical classics
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• v.34 no.1
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• pp.89-102
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• 2021

Objectives : This paper aims to examine situations that were conceived as incurable at the time of publication of the 『Huangdineijing』. Methods : The texts of the 『Huangdineijing』 were searched for contents which included 'cannot be cured.' Next, the verses were examined within their context, after which those that specifically indicated 'incurability' were selected. These were categorized according to content, then organized to better show the situations that were seen as incurable to the authors of the 『Huangdineijing』. Results : The conditions deemed incurable in the 『Huangdineijing』 were bloody and purulent stool, ascites, tumors, some purulent inflammation, some infectious diseases with fever, wasting thirst, chronic kidney disorder, some diseases of the connective tissue, epilepsy, cardiac infarction, and cerebrovascular diseases. Internal damage due to acupuncture and poor patient attitude could also contribute to incurability. Conclusions : The authors of the 『Huangdineijing』 were unable to cure some conditions that are currently being cured by Korean Medicine.

• Journal of Drive and Control
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• v.20 no.4
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• pp.54-63
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• 2023

High and intermittent loading cycles induce fatigue damage to transmission components, resulting in premature gearbox failure. To identify gearbox defects, numerous vibration-based diagnostics techniques, using several artificial intelligence (AI) algorithms, have recently been presented. In this paper, an optimized deep belief network (DBN) model for gearbox problem diagnosis was designed based on time-frequency visual pattern identification. To optimize the hyperparameters of the model, a particle swarm optimization (PSO) approach was integrated into the DBN. The proposed model was tested on two gearbox datasets: a wind turbine gearbox and an experimental gearbox. The optimized DBN model demonstrated strong and robust performance in classification accuracy. In addition, the accuracy of the generated datasets was compared using traditional ML and DL algorithms. Furthermore, the proposed model was evaluated on different partitions of the dataset. The results showed that, even with a small amount of sample data, the optimized DBN model achieved high accuracy in diagnosis.