• Transactions of the Korean Society of Automotive Engineers
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• v.11 no.3
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• pp.65-70
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• 2003

In this paper, an adapted TWC model and its application to the monitoring algorithm are proposed. As TWCs have the different characteristics, the model has to be corrected to diagnose more accurately. In the TWC model oxygen storage and release rate model are adapted to the installed TWC to whose characteristics related. The model learns from the downstream $O_2$ sensor output during the vehicle's operation. From the results, the model is adapted to the Installed TWC's characteristics. using this model, the monitoring algorithm can diagnose the no more accurately. Finally the algorithm is validated with simulations using the data logged from a retail car.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.190-195
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• 2009

With the growth of information and communication technologies adoption in construction projects, it could be anticipated that more property owners and construction firms will attempt to use electronic gears and gadgets for site monitoring or surveillance purposes. As the construction workers may be the major group of project team members being monitored, from managerial perspectives and for ethical reasons, it is essential to investigate their degree of acceptance on site monitoring systems. Indeed studies on office workplace monitoring suggest that a monitoring system could shape or control the behaviors of employees. With adequate refinements, their research models could be applicable in the construction industry. This paper presents a model for analyzing the antecedences that affect workers' acceptance level on electronic monitoring, and investigating if there is any behavioral change.

• 한국방재학회:학술대회논문집
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• 2007.02a
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• pp.49-52
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• 2007

Terrestrial Laser Scanning(TLS) was developed at the mid-to-late 1990s. This technique enables to perform reconnaissance surveying of regions or structures hard to access. Besides, TLS has been extended its application gradually such as preservation of historical remains, underground surveys, slopes, glaciers monitoring and so on. However, though the technique has a lot of advantages, an application for structural health and safety monitoring is a beginning stage and it need much research. Therefore in this study, as a groundwork, the estimation model on stress of structures using TLS and Finite Element Method(FEM) applied by the Digital Elevation Model(DEM) technique of geoinformatics is proposed. For the verification of this model, experiments were performed with a continuous steel beam subjected to point loads and outputs were compared with those of electrical strain sensors.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.178-179
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• 2011

The exchange of information with legacy systems is a main issue in the era of SMARTGRID. Because WAMAC(Wide Area Monitoring and Control) system has monitoring function, as well as control function, it is very necessary for WAMAC to exchange data and information with SCADA(Supervisory Control and Data Acquisition) / EMS(Energy Management System). IEC 61970 CIM(Common Information Model) is an abstract model that represents all the major objects in an electric utility enterprise typically involved in utility operations. In this paper, a proposal that adopting CIM to WAMAC model be submitted so that the integration of various legacy system and application for itself be able to be flexible.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.17 no.1
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• pp.98-105
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• 2008

In this paper, the system for monitoring process of aluminum laser welding was developed using the light signal emitted from the plasma which comes from interaction between material and laser. Photodiode for monitoring system was selected based on the spectrum analysis of light from plasma and keyhole. Behavior of plasma and keyhole was analyzed through the sensor signals. Value of sensor signal represented the light intensity and fluctuation of signal indicated the stability of plasma and keyhole. For the relation between welding condition and sensor signals, the input power and weld geometry greatly effected on the average of each sensor signals. Using the feature values of signals, estimation model for tensile strength of weld was formulated with neural network algorithm. Performance of this model was verified through coefficient of determination and average error rate.

• Smart Structures and Systems
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• v.20 no.2
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• pp.181-195
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• 2017

In this study, the severity of damage in tendon anchorage caused by the loss of tendon forces is quantitatively identified by using the PZT interface-based impedance monitoring technique. Firstly, a 2-DOF impedance model is newly designed to represent coupled dynamic responses of PZT interface-host structure. Secondly, the 2-DOF impedance model is adopted for the tendon anchorage system. A prototype of PZT interface is designed for the impedance monitoring. Then impedance signatures are experimentally measured from a laboratory-scale tendon anchorage structure with various tendon forces. Finally, damage severities of the tendon anchorage induced by the variation of tendon forces are quantitatively identified from the phase-by-phase model updating process, from which the change in impedance signatures is correlated to the change in structural properties.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.10
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• pp.827-832
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• 2002

We propose a prediction method of the pollutant and a synchronous classification of the current state of SOx emission in the power plant. We use the auto-regressive with exogeneous (ARX) model as a predictor of SOx emission and use a radial basis function network (RBFN) as a pattem classifier. The ARX modeling scheme is implemented using recursive least squares (RLS) method to update the model parameters adaptively. The capability of SOx emission monitoring is utilized with the application of the RBFN classifier. Experimental results show that the ARX model can predict the SOx emission concentration well and ARX modeling parameters can be a good feature for the state monitoring. in addition, its validity has been verified through the power spectrum analysis. Consequently, the RBFN classifier in combination with ARX model is shown to be quite adequate for monitoring the state of SOx emission.

• Journal of the Korean Institute of Plant Engineering
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• v.23 no.4
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• pp.21-27
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• 2018

This paper proposed the real-time monitoring methodology of a traffic signal controller. The proposed methodology is based on the simulation technology, and it is necessary to construct a simulation model imitating the behavior of a traffic signal controller. By executing the simulation model, we can obtain the 'nominal system trajectory' of the traffic signal controller. On the other hand, an IoT(Internet of Things)-based monitoring device is implemented in a traffic signal controller. Through the monitoring device, it is possible to obtain the 'actual system trajectory'. By comparing the nominal system trajectory and the actual system trajectory, we can estimate the degree of deterioration of a traffic signal controller.

• Proceedings of the Korea Society of Environmental Biology Conference
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• 2004.12a
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• pp.68-69
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• 2004

• Journal of the Korea Convergence Society
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• v.11 no.6
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• pp.7-14
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• 2020

A Battery Monitoring System capable of State-of-Charge(SOC) estimation using the Extended Kalman Filter(EKF) is described in this paper. In order to accurately estimate the SOC of the battery, the battery cells were modeled as the Thevenin equivalent circuit model. The Thevenin model's parameters were measured in experiments. For the Battery Monitoring System, we designed a battery monitoring device that can calculate the SOC estimation using the EKF and a monitoring server that controls multiple battery monitoring devices. We also develop a web-based dashboard for controlling and monitoring batteries. Especially the computation of the monitoring server could be reduced by calculating the battery SOC estimation at each Battery Monitoring Device.