• Journal of the Korea institute for structural maintenance and inspection
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• v.19 no.3
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• pp.149-160
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• 2015

This study reports the interfacial bond strength between Ultra High Performance Concrete (UHPC) and Normal Strength Concrete (NSC). While previous studies have focused on the interfacial strength between NSC substrate and UHPC overlay, this study use precast UHPC for enhanced constructability and replacement of formwork. The factors affecting the interface strength are comprehensively reviewed. It can be classified into: interface shape, degree of hardening and moisture condition of UHPC before combining with NSC, and curing condition of composite materials. Conducted experiments verify the effects of each factor on the interface strength and, accordingly show different failure modes. In particular, a new failure mode of the failure of a part of UHPC was firstly found in the case of sample with rough interface between UHPC and NSC. The other factors of the degree of hardening and the moisture and curing conditions of UHPC were discussed. This research will provide a valuable foundation to utilize the UHPC as a composite material.

• Journal of the Korea institute for structural maintenance and inspection
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• v.18 no.1
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• pp.68-74
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• 2014

Recently, concrete facility as advanced water treatment facilities is extending in the water treatment facilities according to raise awareness of pure drinking water and delicious water. For this reason, it is increased to the necessity need to make the standard and the development of waterproofing and anti-corrosion materials for concrete structures applied water treatment tank. So, related research has become active recently. However, as the limit of research focused on durability improvement of top coating material, it is insufficient to study on the adhesion strength between the concrete surface and primer. Therefore, there is to confirm the adhesion of between concrete surface and the three primers used as anti-corrosion waterproofing materials, and to investigate the properties of adhesion strength according to the condition such as dry condition, wet condition, and water pressure condition of the concrete surface in this study.

• Journal of the Korea institute for structural maintenance and inspection
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• v.23 no.4
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• pp.31-36
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• 2019

Concrete is a material generally used to build structures and it is exposed to various environment conditions. In particular, a medium such as water lets noxious factors flow into concrete, causing a lot of damage. Therefore, different kinds of materials are being developed to increase the durability of concrete. Among such materials, silane and siloxane compound are known to have a high utilization as an absorption inhibitor. However, if aged or deteriorated reinforced concrete is treated with those compounds, they easily come off the concrete and lose their function since the basic material is weak. This study conducted an experiment to provide concrete with both an absorption-inhibiting effect and surface strengthening by using melamine-formaldehyde resins that are surface-treated with siloxane compound. In addition, a study on the porosity and surface hardness characteristics of a concrete was conducted to check the absorption-inhibiting effect and surface strengthening.

• Proceedings of the KSR Conference
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• 2011.10a
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• pp.1664-1666
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• 2011

오늘날 고성능의 소형 센서 및 무선통신 기술의 발달로 유비쿼터스 컴퓨팅의 실현이 가능하게 되었다. 미래의 스마트한 디바이스뿐만 아니라 무선통신이 가능한 USN(Ubiquito us Sensor network) 기술은 주변 현황을 인식하고 필요한 정보를 처리하여 현장건설 등에 피이드백 시킴으로써 보다 나은 건설 진행과정에 관한 파악과 설계변경 및 계획 등에 필요한 정보를 제공할 수 있다. 본 연구는 TinyOS 기반에서 운용되는 무선 통신에 의한 USN 기술과 그래픽 기반의 LabView 프로그래밍 기술을 융합하여 정보를 처리할 수 있는 일련의 인터페이스 방법을 구현하였다. 송수신된 데이터 처리 결과는 TinyOS 기반으로 동작하는 PC에 그래프 등으로 나타나도록 하였으며, 무선통신용 USN 기술과 융합된 그래픽 처리 기반의 마이크로프로세서 시스템의 장점과 편리성으로 건설현장의 진행과정파악 및 변경 등에 필요한 정보를 제공하며 건설현장 정보의 피이드백을 가능하도록 하였다. 그 결과, 철도건설 현장관리에서의 USN과 구조물의 정밀진단 및 관리에 매우 유용함을 입증하였다.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.23 no.1
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• pp.116-124
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• 2009

This paper proposes a new Artificial-Intelligent(AI) Power Quality(PQ) diagnosis algorithm using Discrete Wavelet Transform(DWT), Fast Fourier Transform(FFT), Root-Mean-Square(RMS) value. The developed algorithm is able to detect and classify the PQ problems such as the transient, the voltage sag, the voltage swell, the voltage interruption and the total harmonics distortion. The 15.36[kHz] sampling frequency is used to measure the voltages in a power system. The measured signals are used for DWT, FFT, RMS calculation. For AI diagnosis of the PQ problems, a simple multi-layered Artificial Neural Network(ANN) with the back-propagation algorithm is adopted, programmed in C++ and tested in PSIM simulation studies. Finally, the algorithm, which is installed in MP PQ+256 with TI DSP320C6713, is proved to diagnose the PQ problems efficiently.

• Computational Structural Engineering
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• v.9 no.2
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• pp.163-171
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• 1996

A hybrid knowledge model which amalgamates an object-oriented modeling approach and logic programming implementation is presented for structural health monitoring and diagnosis of instrumented structures. Domain knowledge in structural monitoring and diagnosis is formalized and represented in a logic-based object-oriented modeling environment. The model and environment have been implemented and illustrated in the context of a laboratory case study of damage detection in a successively damaged steel structure.

• KIPS Transactions on Software and Data Engineering
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• v.7 no.12
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• pp.497-504
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• 2018

This paper studies about the Oriental Medical Expert System, based on Open Source Drools for rule engine processing, which contains scalability, availability, and modifiability. The system is developed with the Spring MVC framework and Ajax for stable services of the Web-based Medical Expert System. The diagnosis and treatment process of this Medical Expert system provides a service that provides the general users to accesses the web with a series of questionnaires. In order to compensate for the asynchronous communication between clients and services, and also for the complicated JDBC weaknesses, we applied the data handling in JSON to reduce the servers' loads, and also the Mybatis framework to improve the performance of the RDBMS, respectively. In addition, as the number of users increases to cope with the maximum available services of the web-based system, the load balancing structure using Nginx has been developed to solve the server traffic problems and the service availability has been increased. The experimental results show the stable services by approving the scalability test.

• Proceedings of the Korea Information Processing Society Conference
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• 2012.04a
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• pp.1208-1210
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• 2012

BIT(Built-In Test)란 S/W 또는 H/W 의 기능 및 상태를 진단하고 오류에 대응하기 위한 방법론으로 기능에 대한 신뢰성 및 빠른 오류 복구를 보장하기 때문에 다양한 분야에서 BIT 처리를 통해 시스템의 안정성을 높이고 있다. 현업에서의 BIT 는 도메인 특성에 따라 처리해야 하는 작업의 변화가 크기 때문에 구조화 되지 않은 형태로 각각 개발되고 있다. 따라서 BIT 개발 시 반복적인 작업이 수반되며 처리 과정의 수정 또는 처리 범위의 확장을 위해서는 많은 시간 및 인력이 요구된다. 이에 본 논문에서는 BIT 처리를 구조화하기 위하여 처리과정에 필요한 정보들을 일반화된 형태로 기록할 수 있도록 하는 BIT 처리 병세 방안과 BIT 처리 명세를 기반으로 한 자동 코드 생성 체계를 제안한다. 이를 통해 개발 과정의 편의성과 생산성을 향상하고 BIT 처리의 유연성과 확장성을 높일 수 있다.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.4
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• pp.179-188
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• 2022

There have been many successful researches on a bearing fault diagnosis based on Deep Learning, but there is still a critical issue of the data distribution difference between training data and test data from their different working conditions causing performance degradation in applying those methods to the machines in the field. As a solution, a data adaptation method has been proposed and showed a good result, but each and every approach is strictly limited to a specific applying scenario or presupposition, which makes it still difficult to be used as a real-world application. Therefore, in this study, we have proposed a method that, using a data transformation with MFCCs and a simple CNN architecture, can perform a robust diagnosis on a target domain data without an additional learning or tuning on the model generated from a source domain data and conducted an experiment and analysis on the proposed method with the CWRU bearing dataset, which is one of the representative datasests for bearing fault diagnosis. The experimental results showed that our method achieved an equal performance to those of transfer learning based methods and a better performance by at least 15% compared to that of an input transformation based baseline method.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.11a
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• pp.434-436
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• 2021

의료산업은 진단 및 치료 위주의 기술개발이 진행되어왔다. 최근 의료 빅데이터를 기반으로 진단, 치료 및 재활뿐만 아니라 예방과 예후관리까지 지원하는 의료서비스에 대한 패러다임이 변화되고 있다. 특히, 여러 의료 중심의 플랫폼 기술 가운데 객관적인 진단지표를 가지고 있는 의료영상을 기반으로 인공지능 학습에 적용하여 진단 및 예측을 중심으로 한 플랫폼 개발이 진행되고 있다. 하지만, 인공지능 연구에는 많은 학습 데이터가 요구될 뿐만 아니라 학습에 적용하기 위해서는 데이터 특성에 따른 전처리 기술과 분류 작업에 많은 시간 소요되어 이와 같은 문제점을 해결할 수 있는 방법들이 요구되고 있다. 따라서, 본 논문은 인공지능 학습까지 적용하기 위한 의료영상 데이터에 대한 확장 모델을 개발하여 공통적인 조건에 따라 의료영상 데이터가 표준화되어 변환하며, 자동화 시스템 구조에 따라 데이터가 분류·저장되어 인공지능 학습까지 지원할 수 있는 플랫폼을 제안하고자 한다. 그리고 근감소증 학습데이터 관리 및 적용 결과를 통해 플랫폼의 수행성을 검증하였다. 향후 제안한 플랫폼을 통해 의료데이터에 대한 전처리, 분류, 관리까지 지원함으로써 CDM 확장 표준 의료데이터 플랫폼으로 활용 가능성을 보였다.