• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.10
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• pp.1776-1786
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• 2010

Intelligent distribution automation system have total monitoring and control capability. The system covers substation, distribution network, distributed generations and customers at HV system. Various intelligent distribution facilities installed at distribution systems have voltage sensor, current sensor, aging monitoring sensor. Intelligent Feeder Remote Terminal Unit (IFRTU) tied to intelligent distribution facilities process information from facilities and it checks information of fault, power quality and aging of distribution facilities. The information is transmitted to master station through communication line. The master station have remote monitoring system covers substation, distribution network, distributed generations and customers. It also have various application programs that maintain optimal network operation by using information from on-site devices.

• Journal of the Korean Institute of Gas
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• v.18 no.3
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• pp.53-59
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• 2014

In this study, we suggest a system to build the monitoring model for compressed natural gas (CNG) stations, operated in only non-stationary modes, and perform the real-time monitoring and the abnormality diagnosis using principal component analysis (PCA) that is suitable for processing large amounts of multi-dimensional data among multivariate statistical analysis methods. We build the model by the calculation of the new characteristic variables, called as the major components, finding the factors representing the trend of process operation, or a combination of variables among 7 pressure sensor data and 5 temperature sensor data collected from a CNG station at every second. The real-time monitoring is performed reflecting the data of process operation measured in real-time against the built model. As a result of conducting the test of monitoring in order to improve the accuracy of the system and verification, all data in the normal operation were distinguished as normal. The cause of abnormality could be refined, when abnormality was detected successfully, by tracking the variables out of the score plot.

• Journal of the Korea Safety Management & Science
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• v.16 no.3
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• pp.239-248
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• 2014

Most systems used in industrial sites, actually have non-linearity and uncertainty. Therefore there are a lot of difficulties in evaluating conditions of these systems. Generally, the quantitative analysis and expression are found hard because the general public cannot easily make an accurate interpretation on the systems. Thus development of a system that utilizes an expertise from skilled analysts is required. In this research, a real-time sensor signal conditioning system and Fuzzy-expert system have been separately set up into an inference algorithm. So that it ensures a fast, accurate, objective and quantitative operational condition value provided to the manager. Therefore, FE_AFCDM is suggested in this literature, as an effective system for diagnosing the problems related to the air compressor. It can quantify the uncertain and absurd condition to operate the air compressor facilities safely and financially.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.35 no.8
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• pp.965-970
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• 2011

We develop a diagnostic system to monitor failures in an engine-assembly line. Existing techniques such as sensory analysis, time domain analysis, frequency analysis, and statistical analysis have limitations in the diagnosis of engine-assembly failure when there are abnormal vibration waveforms (crashing and damping signals) during the assembly. We use a wavelet technique to deal with crashing and damping signals. We also implement a new technique for developing diagnostic rules from sensor data, and we demonstrate its validity.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.28 no.4
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• pp.109-115
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• 2005

In the study, Methods for operating measures in equipment security to find out dangerousness timely in the system and to need for the prevention and measures. The method for analyzing and reconstructing the causes of accident of equipment in site, and try to save the information of site in real-time and to analyze the state of equipment to look for the factors of accidents. By this analysis, one plan for efficiency of production, Equipment Fault Diagnosis Management and security is integrating and building module of using the Fuzzy Inference based on fuzzy theory. The case study is applied to the industrial electric motors that are necessarily used to all manufacturing equipment. Using the sensor for temperature is attached to gain the site information in real time and to design the hardware module for signal processing. In software, realize the system supervising and automatically saving to management data base by the algorithm based in fuzzy theory from the existing manual input system

• Korean Chemical Engineering Research
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• v.46 no.2
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• pp.233-247
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• 2008

Process monitoring technology is able to detect the faults and the process changes which occur in a process unpredictably, which makes it possible to find the reasons of the faults and get rid of them, resulting in a stable process operation, high-quality product. Statistical process monitoring method based on data set has a main merit to be a tool which can easily supervise a process with the statistics and can be used in the analysis of process data if a high quality of data is given. Because a real process has the inherent characteristics of nonlinearity, non-Gaussianity, multiple operation modes, sensor faults and process changes, however, the conventional multivariate statistical process monitoring method results in inefficient results, the degradation of the supervision performances, or often unreliable monitoring results. Because the conventional methods are not easy to properly supervise the process due to their disadvantages, several advanced monitoring methods are developed recently. This review introduces the theories and application results of several remarkable monitoring methods, which are a nonlinear monitoring with kernel principle component analysis (KPCA), an adaptive model for process change, a mixture model for multiple operation modes and a sensor fault detection and reconstruction, in order to tackle the weak points of the conventional methods.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.45 no.1
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• pp.41-49
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• 2008

Many machineries and equipments are being changing to various and complicated by development of recent technology and arrival of convergence age in distant future. These various and complicate equipments need more precise outcomes and low-power consumption sensors to get close and exact results. In this paper, we proposed fault tolerance and feedback theorem for sensor network and MEMS circuit which has a benefit of energy efficiency through wireless sensor network. The system is provided with independent sensor communication if possible as unused action, using idle condition of system and is proposed the least number of circuits. These technologies compared system efficiency after examining product of each Moving Distance by developed sensor which gives effects to execution of system witch is reduced things like control of management side and requirement for hardware, time, and interaction problems. This system is designed for practical application; however, it can be applied to a normal life and production environment such as "Ubiquitous City", "Factory Automata ion Process", and "Real-time Operating System", etc.

• Proceedings of the KIPE Conference
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• 2008.10a
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• pp.88-90
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• 2008

본 논문에서는 유도전동기에서 발생되는 고장들 중에서 고정자 권선 단락 고장 특성 해석과 고장 판별에 대한 방법을 제시한다. 고정자 권선 단락을 판별하기 위해서 단락상태의 고정자를 모델링하여 3상 전류 불평형과 공극자속밀도에 대한 유한요소해석을 수행하였다. 유한요소해석으로 얻어진 결과의 타당성을 입증하기 위해 실험을 통하여 전류와 공극자속에 대한 유기기전력 측정값을 비교하였다. 공극자속의 유기기전력을 측정하기 위해 고정자 슬롯에 자속센서를 취부하였다. 고정자 권선 단락 시 3상 전류는 불평형을 이루고 공극자속밀도가 감소되어 유도전동기의 고정자 고장을 판별하는 기초자료가 된다.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.744-745
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• 2007

변압기를 진단하는 분석 요소 중 흔히 사용하는 방법으로 유중가스분석을 이용하는 방식을 많이 사용하고 있다. 유중가스 분석은 변압기 내 Oil이 열과 Arc등에 의해 화학적으로 변화된 것을 측정하여 열화 정도를 추정하는 방식이지만 신속한 검출 및 위치추정이 불가능하다는 단점이 있다. 신속한 검출이 되지 않으면 신속한 보고가 이루어 질 수 없으므로 변압기 교체시점을 맞추지 못하여 사고로 인한 막대한 피해보상이 발생한다. 이런 단점을 보완하기 위해 변압기내 부분방전 및 Arc에 의해 발생하는 부분방전신호를 초음파 대역에서 검출하여 열화 및 위치를 추정할 수 있는 초음파 분석이 필요하게 되었고 실험을 통해 변압기에 대한 분석, 진단을 시행하였다.

• Journal of the Korean Society of Systems Engineering
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• v.18 no.2
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• pp.40-49
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• 2022

Remote-controlled and autonomous driving based on artificial intelligence are key elements required for unmanned combat vehicles. The required capability of such an unmanned combat vehicle should be expressed in reasonable required operational capability(ROC). To this end, in this paper, the requirements of an unmanned combat vehicle operated under a manned-unmanned teaming were analyzed. The functional requirements are remote operation and control, communication, sensor-based situational awareness, field environment recognition, autonomous return, vehicle tracking, collision prevention, fault diagnosis, and simultaneous localization and mapping. Remote-controlled and autonomous driving of unmanned combat vehicles could be achieved through the combination of these functional requirements. It is expected that the requirement analysis results presented in this study will be utilized to satisfy the military operational concept and provide reasonable technical indicators in the system development stage.