• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.13 no.3
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• pp.288-300
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• 2002

In this paper, a novel method of equalization of RF transceivers is suggested for MIMO(Multiple Input Multiple Output) antenna actively studied for high speed data transmission in the recent IMT-2000 system. The core of suggestion is in equalizing the transfer characteristics of multiple transceivers using feedback and memory during the predefined calibration time. This makes it possible to weight the signals in the intermediate frequency, which is easier in the application of recently developed DoA(Direction of Arrival) algorithms. In addition, the time varying optimum cell formation according to traffic is feasible by antenna beam-forming based on the DoA information. The suggested method of equalizing multiple transceivers are successfully verified using envelope simulation. two outputs. This paper is concerned with the diagnosis of multiple crosstalk-faults in OSM. As the network size becomes larger in these days, the convent.
nal diagnosis methods based on tests and simulation be.
me inefficient, or even more impractical. We propose a simple and easily implementable alg？ithm for detection and isolation of the multiple crosstalk-faults in OSM. Specifically, we develop an algorithm for isolation of the source fault in switc.
ng elements whenever the multiple crosstalk-faults are.
etected in OSM. The proposed algorithm is illustrated by an example of 16$\times$16 OSM.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.43 no.5
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• pp.449-455
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• 2015

Built-In-Test(hereafter: BIT) is necessary functionality for aircraft flight safety and it requires a high failure detection capacity of more than 95 % in the case of avionics equipment. The BIT coverage analysis is needed to make sure that BIT meets its fault diagnosis capability. FMECA is used a lot of for the BIT coverage analysis. However, in this paper, the BIT coverage analysis based on electronic components is introduced to minimize the analytical error. Further, by applying the failure mode of the electronic components and excluding electronic components that do not affect flight safety, the BIT coverage analysis can be more accurate. Finally, BIT demo was performed and it was confirmed that the performance of the actual BIT matches the analysis of BIT performance.

• The Journal of Bigdata
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• v.7 no.1
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• pp.125-137
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• 2022

The transportation industry is one of the important industries due to the geographical requirements surrounded by the sea on three sides of Korea and the problem of resource poverty, which relies on imports for most of its resource consumption. Among them, the proportion of the shipping industry is large enough to account for most of the transportation industry, and maintenance in the shipping industry is also important in improving the operational efficiency and reducing costs of ships. However, currently, inspections are conducted every certain period of time for maintenance of ships, resulting in time and cost, and the cause is not properly identified. Therefore, in this study, the proposed methodology, LSTM-AutoEncoder, is used to detect abnormalities that may cause ship failure by considering the time of actual ship operation data. In addition, clustering is performed through clustering, and the potential causes of ship main engine failure are identified by grouping outlier by factor. This enables faster monitoring of various information on the ship and identifies the degree of abnormality. In addition, the current ship's fault monitoring system will be equipped with a concrete alarm point setting and a fault diagnosis system, and it will be able to help find the maintenance time.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.10
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• pp.1949-1954
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• 2016

Smart grid technology can be called grid techniques to improve the efficiency of the electric power by exchanging bidirectional information of electric power with real-time between electric power suppliers and consumers. Recently, the solar power generation system is being applied actively. However the solar power system has several problems leading to reduce overall electricity generation, because the difficult of the diagnosis and the solar power system failure such as PV(PhotoVoltaics) and inverter. In order to build an efficient smart grid, a stable electric power energy requirements capture and management and early fault detection is essentially required in solar power generation system. In this paper, it is designed to monitor the operating status of the solar power monitoring system from a remote location through a RS-485 or TCP/IP communication module to monitoring the output of solar power energy and abnormal phenomenon, to developing the measurement module and to transfer measured data.

• The Journal of the Korea institute of electronic communication sciences
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• v.11 no.7
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• pp.671-676
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• 2016

This study is about design for the Rotational Instrument of the Industry factory which is used management safety and maintenance. We developed the multichannel vibration monitering system of the self-diagnosis for middle level CMS(Condition Monitoring System) market, and that system are new features to the expandability and flexibility. Normally one channel is used for treating one signal, but developed instrument can treat four channel with one signal processing card. One rack have redundant power supply and displace and it can check vibration measurement value in field without computer. Bearing fault detection is fundamental of vibration surveillance, but sometimes can not check with vibration velocity and acceleration. So it need the filtering and the amplitude modulation on the acceleration enveloping technology when irregular vibration is happened. We developed the vibration analysis instrument which is applied such technology. And the development prototype shows activated within the vibration error limit.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.5
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• pp.412-417
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• 2013

Analytical modeling of photovoltaic power systems has been receiving significant attentions in recent years in that it is easy to apply for prediction of its dynamics and fault detection and diagnosis in advanced engineering technologies. This paper presents a novel probabilistic modeling approach for such power systems with a big data sequence. Firstly, we express input/output function of photovoltaic power systems in which solar irradiation and ambient temperature are regarded as input variable and electric power is output variable respectively. Based on this functional relationship, conditional probability for these three random variables(such as irradiation, temperature, and electric power) is mathematically defined and its estimation is accomplished from ratio of numbers of all sample data to numbers of cases related to two input variables, which is efficient in particular for a big data sequence of photovoltaic powers systems. Lastly, we predict the output values from a probabilistic model of photovoltaic power systems by using the expectation theory. Two case studies are carried out for testing reliability of the proposed modeling methodology in this paper.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.29 no.8
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• pp.98-103
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• 2015

Power plant is that very high reliability when industrial and economic impact on the overall electric power system is required, it is essential to improve the reliability, especially the fault prediction diagnosis. Since an accident caused by the partial discharge in the power plant is above state has a faster response characteristic than the other indications in the case of any, the partial discharge generated in the power plant immediately detect the deterioration of insulation due to the accident of the power plant and the non-drawn It should prevent or reduce. Partial Discharge Measuring Systems for UHV SF6 Gas Insulated Switchgear and power transformer on site installed has some probability of abnormal recognition in case of non-flexible deal with on site noise. Many methode to eliminate these kinds of noises, UHF Detection System is chosen as purchase description in Korea, but this system having a bandwidth between 500MHz 1.5GHz wide band. Initial install periods(about 20 years ago), this band had no strong signal source, but in these days this wide band have strong signals, such as LTE. So, module described in this paper is designed as simultaneously use with wide and narrow band for solve this noise problem, and introduce this system.

• The Journal of Society for e-Business Studies
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• v.23 no.2
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• pp.111-121
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• 2018

Many problems in rotating machinery such as aircraft engines, wind turbines and motors are caused by bearing defects. The abnormalities of the bearing can be detected by analyzing signal data such as vibration or noise, proper pre-processing through a few signal processing techniques is required to analyze their frequencies. In this paper, we introduce the condition monitoring method for diagnosing the failure of the rotating machines by analyzing the vibration signal of the bearing. From the collected signal data, the normal states are trained, and then normal or abnormal state data are classified based on the trained normal state. For preprocessing, a Hamming window is applied to eliminate leakage generated in this process, and the cepstrum analysis is performed to obtain the original signal of the signal data, called the formant. From the vibration data of the IMS bearing dataset, we have extracted 6 statistic indicators using the cepstral coefficients and showed that the application of the Mahalanobis distance classifier can monitor the bearing status and detect the failure in advance.