• Smart Structures and Systems
• /
• 제10권3호
• /
• pp.271-298
• /
• 2012

Researchers have made significant progress in recent years towards realizing effective structural health monitoring (SHM) utilizing wireless smart sensor networks (WSSNs). These efforts have focused on improving the performance and robustness of such networks to achieve high quality data acquisition and distributed, in-network processing. One of the primary challenges still facing the use of smart sensors for long-term monitoring deployments is their limited power resources. Periodically accessing the sensor nodes to change batteries is not feasible or economical in many deployment cases. While energy harvesting techniques show promise for prolonging unattended network life, low power design and operation are still critically important. This research presents the WiSeMote: a new, fully integrated ultra-low power wireless smart sensor node and a flexible base station, both designed for long-term SHM deployments. The power consumption of the sensor nodes and base station has been minimized through careful hardware selection and the implementation of power-aware network software, without sacrificing flexibility and functionality.

• 한국정보과학회:학술대회논문집
• /
• 한국정보과학회 2005년도 한국컴퓨터종합학술대회 논문집 Vol.32 No.1 (A)
• /
• pp.610-612
• /
• 2005

Ubiquitous Computing 시대가 도래 하면서 집이나 빌딩 같은 실내 환경에서도 Ubiquitous Computing을 도입하려는 여러 연구가 진행되고 있다. 특히 Smart Home은 집 안에 여러 종류의 센서를 설치하여 센서로부터 얻는 정보를 바탕으로 사용자에게 다양한 서비스를 제공한다. 이와 같은 Smart Home을 구현하기 위해서는 사용자나 물체의 위치 정보가 매우 중요하다. 본 논문에서는 Smart Home에서 위치 정보를 지원하기 위해 초음파와 IEEE 802.15.4 기반의 센서 시스템을 제안한다. 이 시스템에서는 초음파를 사용함으로써 생기는 문제와 센서의 효율적인 에너지 관리를 위해 IEEE 802.15.4를 적용하였다. 이 시스템은 초음파 송신부를 가지고 있는 S-node 와 수신부를 가지고 있는 R-node 로 구성되어 있으며 본문에서 각각의 구조와 알고리즘에 대해 기술할 것이다.

• 한국인터넷방송통신학회논문지
• /
• 제10권6호
• /
• pp.225-233
• /
• 2010

최근, 스마트 그리드, 스마트 홈 네트워크, 유비쿼터스 컴퓨팅 등의 분야에서 필요한 정보를 수집 및 가공하여 실시간 양방향으로 교환하고, 제어 및 감시하는 스마트 정보 모니터링 기술에 대한 연구를 계속 해 왔다. 본 논문에서는 에너지, U-Farm, 차량정보 및 홈 네트워크에 관한 스마트 정보 모니터링 기술의 응용 제품 및 최근 동향들을 알아본다. 특히, 스마트 그리드의 핵심부분인 스마트 미터와 실시간으로 정보를 교환하는 구글 파워미터, 유비쿼터스 농업을 위한 실시간 모니터링 시스템, 차량상태 정보를 위한 실시간 모니터링 시스템, 저전력, 저가격의 ZigBee 기반 스마트 정보 모니터링 기술 응용 및 관련사례에 대하여 기술한다. 마지막으로 스마트그리드 제주 실증단지 구축현황에 대하여 기술한다.

• Smart Structures and Systems
• /
• 제6권1호
• /
• pp.39-56
• /
• 2010

Structural Control relies, with a great deal, on the ability of the control algorithm to identify the current state of the system, at any given point in time. When such algorithms are designed to perform in a smart manner, several smart technologies/devices are called upon to perform tasks that involve pattern recognition and control. Smart pattern recognition is proposed to replace/enhance traditional state identification techniques, which require the extensive manipulation of intricate mathematical equations. Smart pattern recognition techniques attempt to emulate the behavior of the human brain when performing abstract pattern identification. Since these techniques are largely heuristic in nature, it is reasonable to ensure their reliability under real life situations. In this paper, a neural network pattern recognition scheme is explored. The pattern identification of three structural systems is considered. The first is a single bay three-story frame. Both the second and the third models are variations on benchmark problems, previously published for control strategy evaluation purposes. A Neural Network was developed and trained to identify the deformed shape of structural systems under earthquake excitation. The network was trained, for each individual model system, then tested under the effect of a different set of earthquake records. The proposed smart pattern identification scheme is considered an integral component of a Smart Structural System. The Reliability assessment of such component represents an important stage in the evaluation of an overall reliability measure of Smart Structural Systems. Several studies are currently underway aiming at the identification of a reliability measure for such smart pattern recognition technique.

• 전기학회논문지
• /
• 제63권5호
• /
• pp.713-718
• /
• 2014

DC urban railway power system consists of DC power network and AC power network. The DC power network supplies electric power to railway vehicles and the AC power network supplies electric power to station electric equipment. Recently, because of power consumption reduction and peak load shaving, intelligent measurement of regenerative energy and renewable energy adapted on DC urban railway is required. For this reason, DC smart metering system for DC power network shall be developed. Therefore, in this paper, DC voltage sensor, current sensor, and DC smart meter were developed and evaluated by performance test. DC voltage sensor was developed for measuring standard voltage range of DC urban railway, and DC current sensor was developed as hall effect split core type in order to install in existing system. DC smart meter possesses function of general intelligent electric power meter, such as measuring electricity and wireless communication etc. And, DC voltage sensor showed average 0.17% of measuring error for 2,000V/50mA, and current sensor showed average 0.21% of measuring error for ${\pm}2,000V/{\pm}4V$ in performance test. Also DC smart meter showed maximum 0.92% of measuring error for output of voltage sensor and current sensor. In similar environment for real DC power network, measuring error rate was under 0.5%. In conclusion, accuracy of DC smart metering system was confirmed by performance test, and more detailed performance will be verified by further real operation DC urban railway line test.

• 인터넷정보학회논문지
• /
• 제23권3호
• /
• pp.57-65
• /
• 2022

선박 또는 항공기 화물을 이용한 국제적인 마약 및 폭발물 반입 시도가 증가하는 추세이다. 최근 우리나라에서도 마약 및 폭발물의 검출 사례가 증가하고 있어 주 경로인 항만, 공항의 컨테이너 검색을 통해 위험물질(마약 및 폭발물)을 탐지하는 것이 중요하다. 본 논문에서는 이온 이동도 분광법(Ion Mobility Spectrometry: IMS)의 샘플링 된 출력신호를 이용하여 컨테이너 내부의 위험물질을 검출하는 기법을 제안한다. 제안하는 기법은 초기화 단계에서 알고 있는 물질을 사용하여 목표 위험물질의 이온 검출을 위한 문턱값, 윈도우 길이, 잡음 수준 등의 파라미터를 사전에 추정한다. 추정된 파라미터는 컨테이너 내부의 목표 위험물질의 이온 검출에 사용된다. 제안된 기법은 컨테이너 환경에 의해 IMS 신호 최대값과 이온 이동도가 변동하는 경우에 적용될 수 있다.

• Smart Structures and Systems
• /
• 제30권6호
• /
• pp.583-599
• /
• 2022

In this paper, a multi-objective wireless sensor network configuration optimization method is proposed. The proposed method aims to determine the optimal information and lifespan wireless sensor network for structural health monitoring of large-scale infrastructures. In particular, cluster-based wireless sensor networks with multi-type of sensors are considered. To optimize the lifetime of the wireless sensor network, a cluster-based network optimization algorithm that optimizes the arrangement of cluster heads and base station is developed. On the other hand, based on the Bayesian inference, the uncertainty of the estimated parameters can be quantified. The coefficient of variance of the estimated parameters can be obtained, which is utilized as a holistic measure to evaluate the estimation accuracy of sensor configurations with multi-type of sensors. The proposed method provides the optimal wireless sensor network configuration that satisfies the required estimation accuracy with the longest lifetime. The proposed method is illustrated by designing the optimal wireless sensor network configuration of a cable-stayed bridge and a space truss.

• Smart Structures and Systems
• /
• 제32권3호
• /
• pp.179-193
• /
• 2023

This study explores an alternative to the existing centralized process for data anomaly detection in modern Internet of Things (IoT)-based structural health monitoring (SHM) systems. An edge intelligence framework is proposed for the early detection and classification of various data anomalies facilitating quality enhancement of acquired data before transmitting to a central system. State-of-the-art deep neural network pruning techniques are investigated and compared aiming to significantly reduce the network size so that it can run efficiently on resource-constrained edge devices such as wireless smart sensors. Further, depthwise separable convolution (DSC) is invoked, the integration of which with advanced structural pruning methods exhibited superior compression capability. Last but not least, quantization-aware training (QAT) is adopted for faster processing and lower memory and power consumption. The proposed edge intelligence framework will eventually lead to reduced network overload and latency. This will enable intelligent self-adaptation strategies to be employed to timely deal with a faulty sensor, minimizing the wasteful use of power, memory, and other resources in wireless smart sensors, increasing efficiency, and reducing maintenance costs for modern smart SHM systems. This study presents a theoretical foundation for the proposed framework, the validation of which through actual field trials is a scope for future work.

• 한국공간구조학회논문집
• /
• 제21권1호
• /
• pp.79-86
• /
• 2021

Control performance of a smart tuned mass damper (TMD) mainly depends on control algorithms. A lot of control strategies have been proposed for semi-active control devices. Recently, machine learning begins to be applied to development of vibration control algorithm. In this study, a reinforcement learning among machine learning techniques was employed to develop a semi-active control algorithm for a smart TMD. The smart TMD was composed of magnetorheological damper in this study. For this purpose, an 11-story building structure with a smart TMD was selected to construct a reinforcement learning environment. A time history analysis of the example structure subject to earthquake excitation was conducted in the reinforcement learning procedure. Deep Q-network (DQN) among various reinforcement learning algorithms was used to make a learning agent. The command voltage sent to the MR damper is determined by the action produced by the DQN. Parametric studies on hyper-parameters of DQN were performed by numerical simulations. After appropriate training iteration of the DQN model with proper hyper-parameters, the DQN model for control of seismic responses of the example structure with smart TMD was developed. The developed DQN model can effectively control smart TMD to reduce seismic responses of the example structure.

• 한국통신학회논문지
• /
• 제42권1호
• /
• pp.218-226
• /
• 2017

본 논문은 스마트 폰을 활용하여 광 전송망 구간을 실시간으로 감시하는 시스템이다. 기존의 광 통신망 구간은 스마트 폰과 접속함체의 여장판에 스위치 설치를 활용하여 현장의 상황을 실시간으로 인지 하는 시스템이 없었다. 본 연구는 스마트 폰의 Application과 접속함체 스위치를 이용하여 실시간으로 유지보수를 할 수 있도록 했다. 스마트 폰 Web은 접속함체 장애 위치를 찾는데 유용하며, 접속함체 내부에 있는 여장판 벨크로 타이를 분리하면 스위치가 작동하여 심선의 밴딩을 주어서push message를 발생하게 한다. 접속함체 작업과 장애가 발생하면 스마트폰을 이용하여 OTDR측정을 하여 위치 추적을 할 수 있도록 하는 연구이다. 스마트 폰을 이용하여 실시간 광케이블 구간을 관리함으로써 장애 시간 단축과 전송망 품질을 효율적으로 유지보수 할 수 있다.