• Journal of the Korean Society of Industry Convergence
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• v.23 no.6_1
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• pp.889-896
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• 2020

We describe a new approach to the analyze the control performance of robotic manipulator based on the monitoring system. The structure of monitoring simulator is consist of seven modes such as control state mode, coordinate mode, input/output mode, program mode, parameters mode, and track mode. The applied control algorithme consists of an time varying feed-forward and feedback controller. The proposed scheme is simple in structure, fast in computation, and suitable for real-time implimemtation. Moreover, this scheme does not require any accurate dynamic modeling and values of parameters. Performance of the proposed monitoring system is illustrated by simulation and experiment for robot manipulator with six degrees of freedom.

• Structural Monitoring and Maintenance
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• v.1 no.2
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• pp.231-247
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• 2014

This paper focuses on the dynamic behaviour of Mirandola City Hall (a XV century Renaissance Palace) that was severely damaged during May 2012 Emilia earthquake in Northern Italy. Experimental investigations have been carried out on this monumental building. Firstly, detailed investigations have been carried out to identify the identification of the geometry of the main constructional parts as well as the mechanical features of the constituting materials of the palace. Then, Ambient Vibration Tests (AVT) have been applied, for the detection of the main dynamic features. Three output-only identification methods have been compared: (i) the Frequency Domain Decomposition, (ii) the Random Decrement (RD) and the (iii) Eigensystem Realization Algorithm (ERA). The modal parameters of the Palace were difficult to be identified due to the severe structural damage; however the two bending modes in the perpendicular directions were identified. The comparison of the three experimental techniques showed a good agreement confirming the reliability of the three identification methods.

• Journal of the Korean Institute of Telematics and Electronics
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• v.26 no.9
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• pp.1444-1452
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• 1989

This paper describes the implementation of a real time fetal ECG monitoring system in which an adaptive multi-channel noise canceller is realized using the Texas Instruments TMS32020 progrmmmable ditital signal processor. An ECG signal from the electrode placed on the mother's abdomen and three ECGs from those on the chest are applied as the desired signal and the referened inputs, respectively, of the multi-channel filter. The coefficients of the filter are updated using the LMS algorithm such that the output of the multi-channel filter copies the maternal ECG embedded in the abdominal ECG. The enhanced fetal ECG is obtained by subtracting the filter output from the abdominal ECG, and the difference signal is recorded. Both off-line and on-line experimental results are presented to verify the effectiveness of the parameters for the digital signal processing algorithms and the prototype system.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.23 no.7
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• pp.75-80
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• 2009

In this study, a Web server was constructed using LabVIEW's DataSocket, which makes possible acquisition, analysis, and saving in real time. The output value of the optical current sensor at the web server PC was measured and the output value was displayed using the Web browser of the client PC. DataSocket by LabVIEW makes the construction of a Web server easier than other languages and is compatible with other application programs. An optical current sensor was composed using a 1310 [nm] laser diode, and 9/125 [${\mu}m$] standard single mode optical fiber and was created to be a close type sensor. Data measurement using Web servers has the advantage of monitoring electric power systems at a great distance and can fuse IT technology and electric power systems. Also, this measurement uses inexpensive mounting and programming when compared to existing measurement equipment allowing the construction of a measurement system in any situation or surrounding.

• Journal of Biosystems Engineering
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• v.25 no.3
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• pp.233-240
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• 2000

A commercially available Doppler radar was modified and evaluated for on-board monitoring of ground speed. The radar output was corrected for pitch angle of aircraft based on the output of an electrolytic tilt sensor. The effects of aircraft speed, height and mounting angle on error in the ground speed were evaluated. The speed error decreased with an increase of the mounting angle since the radar contact angle with respect to the ground approached to the mounting angle. The error increased with an increase of the nominal aircraft speed. The altitude insignificantly affected the speed error. The Doppler radar provided acceptable percent errors within 5% in most measurements. The error can be reduced within ${\pm}$1.5% by increasing the mounting angle ($43^{\circ}$). The error of -3.8% at the mounting angle of $29^{\circ}$could be reduced by adjusting the mounting angle with respect to the radar contact angle.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.978-983
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• 2003

In this paper, we propose a fault detection method for extended Kalman filter in decentralized filter structure. To detect a fault, a consistency between filter output and a monitoring signal is tested. State propagators are used to obtain the monitoring signal. However, the output of state propagator increases in magnitude and finally diverges as time runs. To solve such problem, two-propagator method was proposed for linear system. Two propagators are reset by Kalman filter output, alternatively, to avoid divergence. But a test statistics change abruptly at the reset instant in that method. Hence a N-step propagator method is proposed to fix up the problem. In the N-step propagator, only time propagations are performed from k-N+1 step to k step without measurement updates. A test statistics are defined by errors and its covariance between extended Kalman filter and N-step propagator. These fault detection methods are applied to integrated strapdown inertial navigation system (SDINS). By computer simulation, it is shown that the proposed methods detect a fault effectively.

• Computers and Concrete
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• v.30 no.3
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• pp.225-236
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• 2022

In this article, Multi-Gene Genetic Programming (MGGP) is proposed for the estimation of the compressive strength of concrete. MGGP is known to be a powerful algorithm able to find a relationship between certain input space features and a desired output vector. With respect to most conventional machine learning algorithms, which are often used as "black boxes" that do not provide a mathematical formulation of the output-input relationship, MGGP is able to identify a closed-form formula for the input-output relationship. In the study presented in this article, MGPP was used to predict the compressive strength of plain concrete, concrete with fly ash, and concrete with furnace slag. A formula was extracted for each mixture and the performance and the accuracy of the predictions were compared to the results of Artificial Neural Network (ANN) and Extreme Learning Machine (ELM) algorithms, which are conventional and well-established machine learning techniques. The results of the study showed that MGGP can achieve a desirable performance, as the coefficients of determination for plain concrete, concrete with ash, and concrete with slag from the testing phase were equal to 0.928, 0.906, 0.890, respectively. In addition, it was found that MGGP outperforms ELM in all cases and its' accuracy is slightly less than ANN's accuracy. However, MGGP models are practical and easy-to-use since they extract closed-form formulas that may be implemented and used for the prediction of compressive strength.

• KIEAE Journal
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• v.15 no.1
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• pp.89-95
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• 2015

The centralized power supply system and rainwater treatment system, which are major infrastructure in modern cities, are showing their limitations in accommodating environment load due to climate changes that has aggravated recently. As a result, complex issues such as shortage of reserve power and urban flooding have emerged. As a single solution, decentralized systems such as a model integrating photovoltaic system and rooftop greening system are suggested. When these two systems are integrated and applied together, the synergy effect is expected as the rooftop greening has an effect of preventing urban flooding by controlling peak outflow and also reduces ambient temperature and thus the surface temperature of solar cells is lowered and power generation efficiency is improved. This study aims to compare and analyze the monitoring results of four algorithms that define correlations between micro-climate variables around rooftop greening and the surface temperature of solar cells and generate their significance. By doing so, this study seeks to present an effective algorithm that can estimate the surface temperature of solar cell that has direct impact on the efficiency of photovoltaic power generation by observing climate variables.

• Composites Research
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• v.27 no.4
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• pp.141-145
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• 2014

This paper presents a structural health monitoring method using piezoelectric paint sensor designed for an impact sensor. The piezoelectric paint sensor can be flexibly deposited onto most structural surfaces in a thin form of the paint, and measure impact signals without any external device such as a power amplifier. In this study, a composite plate having four zones coated with piezoelectric paint was used for impact monitoring test. The sensitivity of the piezoelectric paint sensor was obtained by measuring the output voltages against the impact force. In addition to the sensitivity measurement, the impact position has been also estimated by comparing the output signals of the paint sensors when the impact occurs on the specimen.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.9 no.6
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• pp.135-139
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• 2009

In order to cope with safety issues regarding fisher vessels, a device is required with the real-time monitoring for the safety and risk factors for a capability of informing and alerting function. In embedded modules, there is a trouble that we should design device drivers and application programs for usage of the multi-function sensors in order to detect risk factors. In this paper, we designed hardware circuit and implemented control program of the sensor part using PIC18F, in order to control and process the input and output data of multi-function sensors without device drivers and application programs. We confirmed the operation of multi-function sensor module to generate output data according to sensor operation.