• Smart Structures and Systems
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• v.14 no.1
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• pp.55-70
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• 2014

The paper presents a multi-objective optimization strategy for a multi-type sensor placement for Structural Health Monitoring (SHM) of long span bridges. The problem is formulated for simultaneous placement of strain sensors and accelerometers (heterogeneous network) based on application demands for SHM system. Modal Identification (MI) and Accurate Mode Shape Expansion (AMSE) were chosen as the application demands for SHM. The optimization problem is solved through the use of integer Genetic Algorithm (GA) to maximize a common metric to ensure adequate MI and AMSE. The performance of the joint optimization problem solved by GA is compared with other established methods for homogenous sensor placement. The results indicate that the use of a multi-type sensor system can improve the quality of SHM. It has also been demonstrated that use of GA improves the overall quality of the sensor placement compared to other methods for optimization of sensor placement.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.11
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• pp.1939-1946
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• 2008

The Oceanic ecosystem destruction caused by Water-Bloom, Jellyfish development, and Oil contamination in nation's waters becomes serious problem. For these reasons, the oceanic conditions are observed in air and on the water using helicopters and vessels. But, employing helicopters and vessels are limitted on a budget, and weather conditions. To overcome these problems, an unattended automated monitoring system not only gather all sorts of the oceanic condition in spite of bad weather, but save labor and oil costs. For each sensor connected in network and radiodetermination, location of sensors are verified in the tidal water to improve gathering informations.

• Journal of Korea Water Resources Association
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• v.54 no.spc1
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• pp.1053-1060
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• 2021

Current water quality monitoring systems in Korea carried based on in-situ grab sample analysis. It is difficult to improve the current water quality monitoring system, i.e. shorter sampling period or increasing sampling points, because the current systems are both cost- and labor-intensive. One possible way to improve the current water quality monitoring system is to adopt a modeling approach. In this study, a modeling technique was introduced to support the current water quality monitoring system, and an artificial neural network model, the computational tool which mimics the biological processes of human brain, was applied to predict water quality of the river. The approach tried to predict concentrations of Total coliform at the outlet of the river and this showed, somewhat, poor estimations since concentrations of Total coliform were rapidly fluctuated. The approach, however, could forecast whether concentrations of Total coliform would exceed the water quality standard or not. As results, modeling approaches is expected to assist the current water quality monitoring system if the approach is applied to judge whether water quality factors could exceed the water quality standards or not and this would help proper water resource managements.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.123-125
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• 2015

Wireless ad hoc network which is comprised of wireless nodes that have the limited communication range is utilized to monitoring disaster area, tracing object, and tactical system. But in the case of wireless node on the ground, a network performance decrease because wireless channel is affected from obstacle or the node deployment is restricted. In this paper, we consider wireless network based on UAV(Unmanned Aerial Vehicle) which has little spatial constraint and quickly deploy a position. We implement test-bed included ground nodes and UAV, and measure throughput and PDR(Packet Delivery Ratio) according to the usage of UAV. We show that network performance is improved by relaying data on UAV.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.410-413
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• 2004

In this paper, a simulator system for Fuel Cell Hybrid Electric Vehicles(FCHEV) is implemented using DSP boards with CAN bus. The subsystems of a FCHEV i.e., the fuel cell system, the battery system, the vehicle dynamics with the transmission mechanism are coded into 3 DSP boards. The power distribution control algorithm and battery SOC control are also coded into a DSP board. The real-time monitoring program is also developed to examine the control performance of power control and SOC control algorithms.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2005.05a
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• pp.945-948
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• 2005

Mobile computing devices are becoming increasingly prevalent in a huge range of physical area, offering a considerable market opportunity. The focus of this paper is on the development of a platform of fault diagnosis system integrating with personal digital assistant (PDA). An improvement of induction machine rotor fault diagnosis based on AI algorithms approach is presented. This network system consists of two parts; condition monitoring and fault diagnosis by using Artificial Intelligence algorithm. LabVIEW allows easy interaction between acquisition instrumentation and operators. Also it can easily integrate AI algorithm. This paper presents a development environment fur intelligent application for PDA. The introduced configuration is a LabVIEW application in PDA module toolkit which is LabVIEW software.

• Journal of Electrical Engineering and Technology
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• v.11 no.2
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• pp.416-424
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• 2016

In this study, automatic detection of stator winding inter-turn short circuit fault (SWISCFs) in surface-mounted permanent magnet synchronous motors (SPMSMs) and automatic classification of fault severity via a pattern recognition system (PRS) are presented. In the case of a stator short circuit fault, performance losses become an important issue for SPMSMs. To detect stator winding short circuit faults automatically and to estimate the severity of the fault, an artificial neural network (ANN)-based PRS was used. It was found that the amplitude of the third harmonic of the current was the most distinctive characteristic for detecting the short circuit fault ratio of the SPMSM. To validate the proposed method, both simulation results and experimental results are presented.

• ETRI Journal
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• v.39 no.2
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• pp.202-212
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• 2017

With the advent of the Internet-of-Things paradigm, the amount of data production has grown exponentially and the user demand for responsive consumption of data has increased significantly. Herein, we present DART, a fast and lightweight stream processing framework for the IoT environment. Because the DART framework targets a geospatially distributed environment of heterogeneous devices, the framework provides (1) an end-user tool for device registration and application authoring, (2) automatic worker node monitoring and task allocations, and (3) runtime management of user applications with fault tolerance. To maximize performance, the DART framework adopts an actor model in which applications are segmented into microtasks and assigned to an actor following a single responsibility. To prove the feasibility of the proposed framework, we implemented the DART system. We also conducted experiments to show that the system can significantly reduce computing burdens and alleviate network load by utilizing the idle resources of intermediate edge devices.

• Journal of the Korean Solar Energy Society
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• v.22 no.4
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• pp.68-76
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• 2002

This paper discusses thermal and ventilation performance which might be caused by the adoption of one of specific building facade techniques, Double Skin System(DSS). One building with a prototypical DSS was selected and systematically investigated through field monitoring and computer simulation techniques. A network model of ventilation was successfully made using COMIS to evaluate ventilation performance of the system which can hardly be done by field measurements. Various operating conditions of air conditioning on/off and window opening were implemented in this type of building. Through the appropriate operation of the DSS in summer, simulation-based and experimental results implicate that it can lead to cooling energy savings.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.52.4-52
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• 2001

In this paper we propose a framework of an open architectured manufacturing system base on CORBA middleware. The manufacturing system consists of four configurable software modules 9mchine control module, database module, monitoring module, and operation module). Each module is distributed through the network and integrated with CORBA middleware technology. CORBA Characteristics including independence from programming languages, computing platforms and networking protocols makes us to easily develop new applications and to effectively integrate new module into existing distributed systems. The CORBA program used in this study is The ACE ORB (TAO) developed by the laboratory in Washington University.