• The Transactions of the Korean Institute of Electrical Engineers P
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• v.61 no.4
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• pp.174-179
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• 2012

The social and economic level of damages might be highly increased in the case of wide-area black-outages, because of heavy dependence of electricity. Therefore, the development of a wide-area protection relay intelligence techniques is required to prevent massive power outages and minimize the impact strength at failure. The frequency monitoring and prediction for wide-area protection relaying intelligence has been considered as an important technology. In this paper, a network-based frequency monitoring system developed for wide-area protection relay intelligence is presented. In addition, conventional techniques for frequency estimation are compared, and a method for advanced frequency estimation and measurement to improve the precision is proposed. Finally, an integrated monitoring system called K-FNET(Korea-Frequency Monitoring Network) is implemented based on the GPS and various energy monitoring cases are studied.

• Journal of Positioning, Navigation, and Timing
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• v.8 no.1
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• pp.1-12
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• 2019

In this paper, we implement a navigation software of a Global Navigation Satellite System (GNSS) receiver based on a commercial purpose GNSS software receiver platform and verify its performance by performing experimental tests for various GNSS signals available in Korea region. The SX3, employed in this paper, is composed of an application program and a Radio Frequency (RF) frontend, and can capture and process multi-constellation and multi-frequency GNSS signals. All the signal processing procedure of SX3 is accessible by the receiver software designer. In particular for an easy research and development, the Application Programing Interface (API) of the SX3 has a flexible architecture to upgrade or change the existing software program, equipped with a real-time monitoring function to monitor all the API executions. Users can easily apply and experiment with the developed algorithms using a form of Dynamic Link Library (DLL) files. Thus, by utilizing this flexible architecture, the cost and effort to develop a GNSS receiver can be greatly reduced.

• Journal of Positioning, Navigation, and Timing
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• v.8 no.2
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• pp.69-77
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• 2019

This study introduces MATLAB Graphical User Interface (GUI)-based software to monitor ionospheric disturbances. This software detects ionospheric disturbances using Global Positioning System (GPS) and Global Navigation Satellite System (GLONASS) measurements, and estimates a location of the disturbance source through the detected disturbance. In addition, this software includes a sky plot making function and frequency analysis function through wavelet transform. To evaluate the performance of the developed software, data of 2011 Tohoku earthquake in Japan were analyzed by using the software. The analysis results verified that the ionospheric disturbances were detected through GPS and GLONASS measurements, and the location of the disturbance source was estimated through the detected disturbance.

• Journal of KIISE:Software and Applications
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• v.37 no.7
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• pp.568-572
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• 2010

Self-healing is one of the techniques that assure dependability of mission-critical system. Self-healing consists of fault detection and fault recovery and fault detection is important first step that enables fault recovery but it causes overhead. We can detect fault based on model, the detection tasks that notify system's behavior and compare normal behavior model and system's behavior are heavy jobs. In this paper, we propose architecture-based multi-level self-adaptive monitoring method that complements model-based fault detection. The priority of fault detection per component is different in the software architecture. Because the seriousness and the frequency of fault per component are different. If the monitor is adapted to intensive to the component that has high priority of monitoring and loose to the component that has low priority of monitoring, the overhead can be decreased and the efficiency can be maintained. Because the environmental changes of software and the architectural changes bring the changes at the priority of fault detection, the monitor learns the changes of fault frequency and that is adapted to intensive to the component that has high priority of fault detection.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.29 no.6
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• pp.306-315
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• 2017

This study introduces a software for real-time assessment of combustion stability for utility gas turbines. The software was written with LabView, and implemented the time-domain kurtosis as a parameter to proactively access the instantaneous combustion stability during operation of the industrial gas turbine. The simple time-domain assessment algorithm incorporated in the software is advantageous over conventional frequency-domain signal processing of dynamic pressure signal since it reduces the computational cost, thereby making the algorithm more appropriate for real-time monitoring of combustion stability. Benchmark data obtained from a model gas turbine combustor were used for the reproducibility test of the software. The assessment obtained from the software agreed well with previously published results, indicating that incorporation of the software could enhance the performance of systems monitoring the combustion stability for gas turbines during power generation.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.2 no.3
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• pp.17-22
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• 2009

The objective of this study was to develop a signal process software for a Electromyograph(EMG). And this paper was developed to general signal process software for a Electromyograph using biomechanics. It was used the clinic, rehabilitation, ergonomics and sports. It was composed to the module type for the monitoring frequency analysis, the zero crossing and comparison analysis etc. It's UI(User Interface) made up the continuous monitoring, the reports and the user-friendly-approach. This developed Electromyography will be applied to biomedical engineering system.

• International Journal of Computer Science & Network Security
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• v.22 no.7
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• pp.191-198
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• 2022

With the ever-increasing frequency of public sector and smalls-cale industries going live on the internet in developing countries, their security of which, while crucial, is often overlooked in most cases. This is especially true in Government services, whilst essential, are poorly monitored if at all. This is due to lack of funds and personnel. Most available software which can help these organizations monitor their services are either expensive or very outdated. Thus, there is a need for any developing country to develop a networking monitoring system. However, developing a network monitoring system is still a challenge and expensive and out sourcing network monitoring system to third party is a security threat. Therefore, in this article we propose a method to anonymize network logs and outsource networking monitoring system to third-party without breach in integrity of their network logs.

• Journal of Biomedical Engineering Research
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• v.20 no.1
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• pp.81-90
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• 1999

This paper describes an EEG(electroencephalogram) software for two-channel cerebral function monitoring system to detect the cerebral ischemia. In the software, two-channel bipolar analog EEG signals are digitized and from the signals various EEG parameters are extracted and displayed on a monitor in real-time. Digitized EEG signal is transformed by FFT(Fast Fourier transform) and represented as CSA(compressed spectral array) and DSA(density spectral array). Additional 5 parameters, such as alpha ratio, percent delta, spectral edge frequency, total power, and difference in total power, are estimated using the FFT spectra. All of these are effectively merged in a monitor and displayed in real-time. Through animal experiments and clinical trials on men, the software is modified and enhanced. Since the software provides raw EEG, CSA, DSA, simultaneously with additional 5 parameters in a monitor, it is possible to observe patients multilaterally. For easy comparison of patient's status, reference patterns of CSA, DSA can be captured and displayed on top of the monitor. And user can mark events of surgical operation and patient's conditions on the software, this allow him jump to the points of events directly, when reviewing the recorded EEG file afterwards. Other functions, such as forward/backward jump, gain control, file management are equipped and these are operated by simple mouse click. Clinical tests in a university hospital show that the software responds accurately according to the conditions of patients and medical doctors can use the software easily.

• Proceedings of the Korea Information Processing Society Conference
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• 2018.05a
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• pp.562-565
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• 2018

A wide range of IoT applications use information collected from networks of sensors for monitoring and controlling purposes. However, the frequent appearance of fault data makes it difficult to extract correct information, thereby sending incorrect commands to actuators that can threaten human privacy and safety. For this reason, it is necessary to have a mechanism to detect fault data collected from sensors. In this paper, we present a trend-adaptive multi-scale principal component analysis (Trend-adaptive MS-PCA) model for data fault detection. The proposed model inherits advantages of Discrete Wavelet Transform (DWT) in capturing time-frequency information and advantages of PCA in extracting correlation among sensors' data. Experimental results on a real dataset show the high effectiveness of the proposed model in data fault detection.

• Journal of the Korean Society of Safety
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• v.25 no.2
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• pp.29-34
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• 2010

This paper is aimed to develop monitoring software for detecting the characteristics of current and voltage signals for series arc on electric wire. In order to attain this purpose, the characteristics of series arc were analyzed by the current and voltage signals on electric wire which were installed, and also analyzed by the changes of RMS, instantaneous of waveform value in time domain and THD in frequency domain. Monitoring program which analyze the signal was developed by Labview which can analyze in time domain and frequency domain, and save data. Experimental setup for detecting verification of monitoring program was composed loads of a lamp, an electric heater and an electric fan loads which were usually using. Measurement points for detecting verification of monitoring program were selected at both the panel board and the arc generator at the same time. As results of the experiments by monitoring program, the arc current waveform showed the same characteristic in all measurement points of all load. But the arc voltage waveform was different in each measurement point. When arc occurred, the THD of current value increased above 20%. The results of this study will be effectively used in developing the preventive system of electric fire by series arc.