• Proceedings of the KIPE Conference
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• 1998.10a
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• pp.410-413
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• 1998

In this paper, we present the method that improve alarm security system using the electronic circuits added the emergency lamp by our proposed Algorithms. In conventional method the emergency lamp of warning & alarm system didn't work perfectly its performance because of battery with short life. For improving this problem we, using Peripheral Interface Controller IC, designed the circuit added the emergency lamp for an warning & alarm system and for prevention against stopping the electric current, and compared our proposed method with conventional method. By designing the circuit to stop up over charge we can extend life of battery, use for a stoppage of electric current in emergency and according to the lightness around. Therefore we are very convenient and profitable in our life. In the future we will study the method to lower the cost of architecture for practical utilization.

• Earthquakes and Structures
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• v.18 no.2
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• pp.163-170
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• 2020

Floor acceleration plays a major role in the seismic design of nonstructural components and equipment supported by structures. Large floor acceleration may cause structural damage to or even collapse of buildings. For precision instruments in high-tech factories, even small floor accelerations can cause considerable damage in this study. Six P-wave parameters, namely the peak measurement of acceleration, peak measurement of velocity, peak measurement of displacement, effective predominant period, integral of squared velocity, and cumulative absolute velocity, were estimated from the first 3 s of a vertical ground acceleration time history. Subsequently, a new predictive algorithm was developed, which utilizes the aforementioned parameters with the floor height and fundamental period of the structure as the new inputs of a support vector regression model. Representative earthquakes, which were recorded by the Structure Strong Earthquake Monitoring System of the Central Weather Bureau in Taiwan from 1992 to 2016, were used to construct the support vector regression model for predicting the peak floor acceleration (PFA) of each floor. The results indicated that the accuracy of the predicted PFA, which was defined as a PFA within a one-level difference from the measured PFA on Taiwan's seismic intensity scale, was 96.96%. The proposed system can be integrated into the existing earthquake early warning system to provide complete protection to life and the economy.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.66 no.2
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• pp.82-87
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• 2017

This paper presents performance improvement of CO gas sensor signal conditioner for early fire warning system. The warning system is based on the CO sensor and its advanced signal conditioning modules network that employ electochemical gas sensor. The electochemical has advantage of having a linear output and operating with a low consumption and fast response. This electrochemical gas sensor contains a gas membrane and three electrodes(working, counter, reference electrode) in contact with an electrolyte. To use a three-electrode sensor, a voltage has to be applied between the working and the reference electrode according to the specification of the sensor. In this paper, we designed these requirements that should be considered in temperature compensation algorithm and electrode measurement of CO sensor modules by using advanced signal conditioning method included 3-electrode. Simulation and experimental results show that signal conditioner of CO sensor module using 3-electrode have a advantage linearity, sensitivity and stability, fast response etc..

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.7
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• pp.537-543
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• 2000

mathematical models for a hydraulic brake actuator and a brake control law for vehicle collision warning/collision avoidance (CW/CA) systems will be presented in this paper. The control law have been designed for optimzied safety and comfort. A solenoid-valve-controlled hydraulic brake actuator system for the CW/CA systems has been investigated, A nonlinear computer model and a linear model of the hydraulic brake actuator system have been developed. Both models were found to represent the actual system with good accuracy. Uncertainties in the brake actuator model have been considered in the design of the control law for the roubustness of the controller. The effects of brake control on CW/CA vehicle response has been investigated via simulations. The simulations were performed using the hydraulic brake system model and a complete nonlinear vehicle model. The results indicate that the proposed brake control law can provide the CW/CA vehicles with an opimized compromise between safety and comfort.

• Smart Structures and Systems
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• v.33 no.5
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• pp.365-374
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• 2024

This paper adopts a new approach in which nonlinear vibrations can be controlled using fuzzy controllers by optimal grey evolutionary algorithm. If the fuzzy controller cannot stabilize the systems, then the high frequency is injected into the system to assist the controller, and the system is asymptotically stabilized by adjusting the parameters. This paper uses the GM (grey model) and the neural network prediction model. The structure of the neural network is improved from a single factor, and multiple data inputs are extended to various factors and numerous data inputs. The improved model expands the applicable range of uncontrolled elements and improves the accuracy of controlled prediction, using the model that has been trained and stabilized by multiple learning. The simulation results show that the improved gray neural network model has higher prediction accuracy and reliability than the traditional GM model, improving controlled management and pre-control ability. In the combined prediction, the time series parameters and the predicted values obtained from the GM (1,1) (Grey Model of first order and one variable) are simultaneously used as the input terms of the neural network, considering the influence of the non-equal spacing of the data, which makes the results of the combined gray neural network model more rationalized. By adjusting the model structure and system parameters to simulate and analyze the controlled elements, the corresponding risk change trend graphs and prediction numerical calculation results are obtained, which also realize the effective prediction of controlled elements. According to the controlled warning principle and objective, the fuzzy evaluation method establishes the corresponding early warning response method. The goals of this paper are towards access to adequate, safe and affordable housing and basic services, promotion of inclusive and sustainable urbanization and participation, implementation of sustainable and disaster-resilient buildings, sustainable human settlement planning and manage.

• Journal of Korean Tunnelling and Underground Space Association
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• v.26 no.5
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• pp.551-561
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• 2024

Underground utility tunnels are spaces densely packed with various infrastructure facilities, such as power, telecommunications, and water supply and drainage systems, making internal environment management crucial. An investigation into accident cases and on-site demands in these tunnels revealed that while fires and floods are the most common types of incidents, the demand for real-time condensation prevention and response is frequent according to on-site managers. Condensation occurs due to the difference in humidity and temperature between the inside and outside of the tunnel. Frequent or prolonged condensation can lead to metal pipe corrosion, electrical failures, and reduced equipment lifespan. Therefore, this study developed a control algorithm and monitoring system to prevent condensation in underground utility tunnels. The proposed control algorithm estimates the likelihood of condensation in real-time based on the measured temperature and humidity and suggests appropriate responses for each stage to the managers. Finally, a practical condensation prevention monitoring system was built based on the developed algorithm, verifying the feasibility and applicability of this technology in the field.

• Journal of Korean Society for Quality Management
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• v.45 no.1
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• pp.25-38
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• 2017

Purpose: Hot strip rolling mill consists of a lot of mechanical and electrical units. In condition monitoring and diagnosis phase, various units could be failed with unknown reasons. In this study, we propose an effective method to detect early the units with abnormal status to minimize system downtime. Methods: The early warning problem with various units is defined. K-means and PAM algorithm with Euclidean and Manhattan distances were performed to detect the abnormal status. In addition, an performance of the proposed algorithm is investigated by field data analysis. Results: PAM with Manhattan distance(PAM_ManD) showed better results than K-means algorithm with Euclidean distance(K-means_ED). In addition, we could know from multivariate field data analysis that the system reliability of hot strip rolling mill can be increased by detecting early abnormal status. Conclusion: In this paper, clustering-based monitoring and fault detection algorithm using Manhattan distance is proposed. Experiments are performed to study the benefit of the PAM with Manhattan distance against the K-means with Euclidean distance.

• Proceedings of the Korea Contents Association Conference
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• 2009.05a
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• pp.521-525
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• 2009

In this paper, we introduce fire detection system and software learning algorithm that recognize fire patterns. Flame patterns means that periodical and consistent pattern about general conception of fire, and to process it with the definition. Learning algorithm for flame pattern recognition that we propose is the method which is faster and more exactly than existing algorithm. Also, we trying to elicit the method through experiment result and by applying it, we show the validity of an early fire warning system.

• Journal of Auto-vehicle Safety Association
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• v.5 no.2
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• pp.17-23
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• 2013

This paper describes an algorithm for Advanced Emergency Braking(AEB) with tire-road friction coefficient estimation. The AEB is a system to avoid a collision or mitigate a collision impact by decelerating the car automatically when forward collision is imminent. Typical AEB system is operated by Time-to-collision(TTC), which considers only relative velocity and clearance from control vehicle to preceding vehicle. AEB operation by TTC has a limit that tire-road friction coefficient is not considered. In this paper, Tire-road friction coefficient is also considered to achieve more safe operation of AEB. Interacting Multiple Model method(IMM) is used for Tire-road friction coefficient estimation. The AEB algorithm consists of friction coefficient estimator and upper level controller and lower level controller. The numerical simulation has been conducted to demonstrate the control performance of the proposed AEB algorithm. The simulation study has been conducted with a closed-loop driver-controller-vehicle system using using MATLAB-Simulink software and CarSim Vehicle model.

• Journal of Auto-vehicle Safety Association
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• v.5 no.1
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• pp.56-61
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• 2013

This paper presents a development of the Advanced Emergency Braking (AEB) Algorithm for passenger vehicles. The AEB is the system to slow the vehicle and mitigate the severity of an impact when a rear end collision probability is increased. To mitigate a rear end collision, the AEB comprises of a millimeter wave radar sensor, CCD camera and vehicle parameters of which are processed to judge the likelihood of a collision occurring. The main controller of the AEB algorithm is composed of the two control stage: upper and lower level controller. By using the collected obstacle information, the upper level controller of the main controller decides the control mode based not only on parametric division, but also on physical collision capability. The lower level controller determines warning level and braking level to maintain the longitudinal safety. To decide the braking level, Last Ponit To Brake and Steer (LPTB/LPTS) are compared with current driving statues. To demonstrate the control performance of the proposed AEBS algorithm's, closed-loop simulation of the AEBS was conducted by using the Matlab simlink and CarSim software.