• 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.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.11
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• pp.2446-2452
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• 2012

In order to meet the recently enhanced emission standards at home and abroad, it is necessary to develop the CRDI ECU control algorithm that users can adjust fuel injection timing and amount in response to their needs. Therefore, this study developed the simulator for knocking analysis that enables knocking discrimination and engine balance correction applicable to the ECU exclusive to the industrial CRDI engine. The purpose of this study is to provide the driver-oriented diagnostic service that enable drivers to diagnose vehicles directly by developing diagnostic devices for vehicles with ths use of the results of the developed simulator for knocing analysis according to the OBD-II standards. For this purpose, this study aims to improve the fuel efficiency of vehicles by proposing the S/W design method of the OBD-II diagnosis device that can provide real-time communcations with the use of wired system and bluetooth module as a wireless system to send and recevice automobile fault diagnosis signal and sensor output signal, and to suggest an improvement for engine efficiency by minimizing the generation of harmful exhaust gas.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.7
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• pp.299-306
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• 2022

In recent, sensors embedded in robots, equipment, and circuits have become common, and research for diagnosing device failures by learning measured sensor data is being actively conducted. This failure diagnosis study is divided into a classification model for predicting failure situations or types and a regression model for numerically predicting failure conditions. In the case of a classification model, it simply checks the presence or absence of a failure or defect (Class), whereas a regression model has a higher learning difficulty because it has to predict one value among countless numbers. So, the reason that regression modeling is more difficult is that there are many irregular situations in which it is difficult to determine one output from a similar input when predicting by matching input and output. Therefore, in this paper, we focus on input and output data with periodicity, analyze the input/output relationship, and secure regularity between input and output data by performing sliding window-based input data patterning. In order to apply the proposed method, in this study, current and temperature data with periodicity were collected from MMC(Modular Multilevel Converter) circuit system and learning was carried out using ANN. As a result of the experiment, it was confirmed that when a window of 2% or more of one cycle was applied, performance of 97% or more of fit could be secured.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.10
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• pp.5899-5905
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• 2014

Faults in electric power system can be a critical problem for vehicles. The system durability is determined mainly by the durability of their components and operating conditions. Monitoring the conditions of the electric power system may be necessary because it is very difficult to predict precisely when it will fail. Therefore, the aim of this study was to develop a diagnosis system for an electric power system of a vehicle. The alternator voltage, excitation voltage, lamp voltage, battery voltage, and engine rpm from a crank angle sensor are monitored continuously and the system fault can be then detected in real time. NI USB- 9201 DAQ and LabVIEW SW have been used to measure the voltages and analyze the data. Compared to conventional measurements for only each component, an integrated and portable measurement method was developed. In addition to the monitoring the electric power system in real time, the saved data from the measurement also provides valuable information to improve the durability of the components.