• Smart Structures and Systems
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• 제14권2호
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• pp.129-144
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• 2014

In this paper, a fuzzy inference system and an analytical hierarchy process-based online evaluation technique is developed to monitor the condition of the 32-km Donghai Bridge in Shanghai. The system has 478 sensors distributed along eight segments selected from the whole bridge. An online evaluation subsystem is realized, which uses raw data and extracted features or indices to give a set of hierarchically organized condition evaluations. The thresholds of each index were set to an initial value obtained from a structure damage and performance evolution analysis of the bridge. After one year of baseline monitoring, the initial threshold system was updated from the collected data. The results show that the techniques described are valid and reliable. The online method fulfills long-term infrastructure health monitoring requirements for the Donghai Bridge.

• Structural Monitoring and Maintenance
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• 제9권2호
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• pp.129-155
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• 2022

In this study, parametric analyses on a hoop-type PZT (lead-zirconate-titanate) interface are performed to estimate the effects of the PZT interface's materials and geometries on sensitivities of impedance responses under strand breakage. The paper provides a guideline for installing the PZT interface suitable in tendon anchorages for damage-sensitive impedance signatures. Firstly, the concept of the PZT interface-based impedance monitoring technique in prestressed tendon anchorage is briefly described. A FE (finite element) analysis is conducted on a multi-strands anchorage equipped with a hoop-type PZT interface for analyzing materials and geometric effects. Various material properties, geometric sizes of the interface, and PZT sensor are simulated under two states of prestressing force for acquiring impedance responses. Changes in impedance signals are statistically quantified to analyze the effect of these factors on damage-sensitive impedance monitoring in the tendon anchorage. Finally, experimental analyses are performed to demonstrate the effects of materials and geometrical properties of the PZT interface on damage-sensitive impedance monitoring.

• Smart Structures and Systems
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• 제6권5_6호
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• pp.481-504
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• 2010

Wireless smart sensor networks (WSSNs) have been proposed by a number of researchers to evaluate the current condition of civil infrastructure, offering improved understanding of dynamic response through dense instrumentation. As focus moves from laboratory testing to full-scale implementation, the need for multi-hop communication to address issues associated with the large size of civil infrastructure and their limited radio power has become apparent. Multi-hop communication protocols allow sensors to cooperate to reliably deliver data between nodes outside of direct communication range. However, application specific requirements, such as high sampling rates, vast amounts of data to be collected, precise internodal synchronization, and reliable communication, are quite challenging to achieve with generic multi-hop communication protocols. This paper proposes two complementary reliable multi-hop communication solutions for monitoring of civil infrastructure. In the first approach, termed herein General Purpose Multi-hop (GPMH), the wide variety of communication patterns involved in structural health monitoring, particularly in decentralized implementations, are acknowledged to develop a flexible and adaptable any-to-any communication protocol. In the second approach, termed herein Single-Sink Multi-hop (SSMH), an efficient many-to-one protocol utilizing all available RF channels is designed to minimize the time required to collect the large amounts of data generated by dense arrays of sensor nodes. Both protocols adopt the Ad-hoc On-demand Distance Vector (AODV) routing protocol, which provides any-to-any routing and multi-cast capability, and supports a broad range of communication patterns. The proposed implementations refine the routing metric by considering the stability of links, exclude functionality unnecessary in mostly-static WSSNs, and integrate a reliable communication layer with the AODV protocol. These customizations have resulted in robust realizations of multi-hop reliable communication that meet the demands of structural health monitoring.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2021년도 추계학술발표대회
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• pp.6-8
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• 2021

슈퍼컴퓨터 5호기 누리온은 8,437대의 계산노드와 33.88PB 규모의 병렬스토리지가 100Gbps의 Omni-Path(OPA) 인터커넥트로 연결되어 있는 초대형 클러스터 시스템이다. 누리온의 계산자원은 PBS 작업스케줄러를 통해 관리되고 있고 병렬 스토리지는 DDN사의 Exascaler Monitoring System(ESMON)을 통해 influxDB에 read/write IO 통계 데이터를 수집하고 있다. 본 논문에서는 PBS의 과금 데이터와 ESMON influxDB의 IO 통계 데이터를 활용하여 사용자의 작업별 IO 통계 정보를 생성하는 방안에 대하여 소개한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권8호
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• pp.2801-2815
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• 2022

With the advent and realization of Software Defined Network (SDN) architecture, many organizations are now shifting towards this paradigm. SDN brings more control, higher scalability, and serene elasticity. The SDN spontaneously changes the network configuration according to the dynamic network requirements inside the constrained environments. Therefore, a monitoring system that can monitor the physical and virtual entities is needed to operate this type of network technology with high efficiency and proficiency. In this manuscript, we propose a real-time monitoring system for data collection and visualization that includes the Prometheus, node exporter, and Grafana. A node exporter is configured on the physical devices to collect the physical and virtual entities resources utilization logs. A real-time Prometheus database is configured to collect and store the data from all the exporters. Furthermore, the Grafana is affixed with Prometheus to visualize the current network status and device provisioning. A monitoring system is deployed on the physical infrastructure of the KOREN topology. Data collected by the monitoring system is further pre-processed and restructured into a dataset. A monitoring system is further enhanced by including machine learning techniques applied on the formatted datasets to identify the elephant flows. Additionally, a Random Forest is trained on our generated labeled datasets, and the classification models' performance are verified using accuracy metrics.

• Smart Structures and Systems
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• 제29권1호
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• pp.181-193
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• 2022

Data-driven structural health monitoring (SHM) of civil infrastructure can be used to continuously assess the state of a structure, allowing preemptive safety measures to be carried out. Long-term monitoring of large-scale civil infrastructure often involves data-collection using a network of numerous sensors of various types. Malfunctioning sensors in the network are common, which can disrupt the condition assessment and even lead to false-negative indications of damage. The overwhelming size of the data collected renders manual approaches to ensure data quality intractable. The task of detecting and classifying an anomaly in the raw data is non-trivial. We propose an approach to automate this task, improving upon the previously developed technique of image-based pre-processing on one-dimensional (1D) data by enriching the features of the neural network input data with multiple channels. In particular, feature engineering is employed to convert the measured time histories into a 3-channel image comprised of (i) the time history, (ii) the spectrogram, and (iii) the probability density function representation of the signal. To demonstrate this approach, a CNN model is designed and trained on a dataset consisting of acceleration records of sensors installed on a long-span bridge, with the goal of fault detection and classification. The effect of imbalance in anomaly patterns observed is studied to better account for unseen test cases. The proposed framework achieves high overall accuracy and recall even when tested on an unseen dataset that is much larger than the samples used for training, offering a viable solution for implementation on full-scale structures where limited labeled-training data is available.

• 한국산업융합학회 논문집
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• 제26권6_3호
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• pp.1251-1258
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• 2023

Traditional markets are infrastructure with facilities and characteristics of very high population density. Recently, arcades have been installed through traditional market modernization policies, and aging infrastructure has been repaired. However, gas and electrical facilities of traditional markets cannot be easily replaced because of its high density. And because regular inspections are not conducted, management of facilities is on very poor condition. In addition, when a fire occurs in a traditional market, the fire easily spreads to nearby stores and is likely to spread to a large fire because of a lot of highly flammable substances. Smoke detectors and heat detectors are installed in most traditional markets to monitor fires, but malfunctions are frequent due to the nature of smoke detectors and heat detectors, and network facilities are not properly maintained. Therefore, in this study, gas detection sensors and flame detectors are additionally installed in Gwangmyeong Traditional Market, and a digital twin-based traditional market fire monitoring system is implemented in conjunction with existing sensors in the market's 3D model. With this digital twin based fire monitoring system, we can reduce the malfunctions of fire detect sensors, and can easily guide the evacuation route.

• Smart Structures and Systems
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• 제16권4호
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• pp.607-621
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• 2015

Wireless sensor technology has been opened up numerous opportunities to advanced health and maintenance monitoring of civil infrastructure. Compare to the traditional tactics, it offers a better way of providing relevant information regarding the condition of building structure health at a lower price. Numerous domestic buildings, especially longer-span buildings have a low frequency response and challenging to measure using deployed numbers of sensors. The way the sensor nodes are connected plays an important role in providing the signals with required strengths. Out of many topologies, the dense and sparse topologies wireless sensor network were extensively used in sensor network applications for collecting health information. However, it is still unclear which topology is better for obtaining health information in terms of greatest components, node's size and degree. Theoretical and computational issues arising in the selection of the optimum topology sensor network for estimating coverage area with sensor placement in building structural monitoring are addressed. This work is an attempt to fill this gap in high-rise building structural health monitoring application. The result shows that, the sparse topology sensor network provides better performance compared with the dense topology network and would be a good choice for monitoring high-rise building structural health damage.

• 한국농공학회논문집
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• 제61권4호
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• pp.43-54
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• 2019

The present study aims to monitor three of the community empowerment projects implemented as part of the community central revitalization projects in Yeongwol. We used an established indicator (i.e., quantitative evaluation) as well as an interview (i.e., qualitative evaluation) throughout the monitoring process. The PM (project manager) committee members, consisting of six interdisciplinary experts, carried out the monitoring from $24^{th}$ of October until the $26^{th}$ of November 2018. We categorized the results of the monitoring into the aspects of needs, software, and hardware, and analyzed them as follows: First, although the locals were willing to take part in programs, they were in overall not well informed about the ongoing programs and the program that suits their needs the most. The service organization should therefore actively publicize the program and provide sufficient information about it .Second, instead of a one-off program, the locals should be empowered to take over the program eventually and develop it as a local business model. Last, the locals from the center as well as the outskirts of Yeongwol should organize a learning net, collaboratively develop a further program, and assess its effectiveness by employing a thorough monitoring system.

• 정보보호학회논문지
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• 제26권3호
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• pp.809-820
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• 2016

스마트그리드는 사물인터넷의 핵심 응용서비스이고, 그 중 가장 핵심적인 구성요소인 AMI((Advanced Metering Infrastructure)는 전기사업자와 소비자의 접점에 위치하고 있으며, 스마트 미터는 소비자의 전기사용을 기록하고 사업자에게 전달하는 역할을 한다. 본 논문에서는 스마트그리드에서 소비자와 직접 맞닿아 있는 스마트 미터를 중심으로 AMI에 대한 NESCOR에서 제시하고 있는 사이버공격 및 피해 시나리오를 기반으로 피해비용을 산정한다. 본 연구의 결과는 정책입안자나 전기사업자가 스마트그리드 관련 투자의사결정을 하는데 참고가 될 수 있을 것이다.