• 제어로봇시스템학회:학술대회논문집
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• 1992.10b
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• pp.176-180
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• 1992

At the KACC'91 conference, we proposed a method of automatic detection of shape of the faulty holes of a shadow mask which is used in a cathode-ray tube of a color television. In this method, the image data are taken from two areas of the mask with CCD camera. Comparing the shape of holes in these two areas by use of a signal processing technique, we can find any fault in the shape of holes. This paper describes the effect of smoothing filters of effectively finding the faulty holes from the difference image data. A computer simulation and actual experiment with a shadow mask have shown that this method of fault detection is very effective for practical use.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.17 no.5
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• pp.444-451
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• 2005

The fault detection and diagnosis technology may be applied in order to decrease the energy consumption and the maintenance cost of an air-conditioning system. In this study, partial faults for fans, coils, dampers, and sensors of a constant volume air handling unit were considered. A fuzzy algorithm was developed to detect and diagnose these faults. Diagnostic results by the fuzzy algorithm were compared with those by the model reference algorithm. The fuzzy algorithm showed better results in diagnostic accuracies.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2006.11a
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• pp.46-53
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• 2006

This paper presents the fault diagnosis of induction motor based on support vector machine (SVMs). SVMs are well known as intelligent classifier with strong generalization ability. Application SVMs using kernel function is widely used for multi-class classification procedure. In this paper, the algorithm of SVMs will be combined with feature extraction and reduction using component analysis such as independent component analysis, principal component analysis and their kernel (KICA and KPCA). According to the result, component analysis is very useful to extract the useful features and to reduce the dimensionality of features so that the classification procedure in SVM can perform well. Moreover, this method is used to induction motor for faults detection based on vibration and current signals. The results show that this method can well classify and separate each condition of faults in induction motor based on experimental work.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.28 no.11
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• pp.1685-1691
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• 2004

This paper describes the fault detection and failsafe logic to be used in an Electronic Stability Program(ESP). The aim of this paper is to prevent of erroneous controls in the ESP. Developed this paper introduces the fault detection logic and evaluation of residual signals. The failsafe logic consists of four redundant sub-models, which can be used for detecting the faults in various sensors (yaw rate, lateral acceleration, steering wheel angle). We present two mathematical residual generation methods : one is a method using the average value and the other is a method using the minimum value of the each residual. We verified a failsafe logic developed using vehicle test results also we compare vehicle model based simulation results with test vehicle results.

• Proceedings of the KSME Conference
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• 2004.04a
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• pp.822-827
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• 2004

In this paper, an intelligent fault diagnosis system is proposed for induction motors through the combination of feature extraction, genetic algorithm (GA) and neural network (ANN) techniques. Features are extracted from motor vibration signals, while reducing data transfers and making on-line application available. GA is used to select most significant features from whole feature database and optimize the ANN structure parameter. Optimized ANN diagnoses the condition of induction motors online after trained by the selected features. The combination of advanced techniques reduces the learning time and increases the diagnosis accuracy. The efficiency of the proposed system is demonstrated through motor faults of electrical and mechanical origin on the induction motors. The results of the test indicate that the proposed system is promising for real time application.

• Journal of the Korean Society for Precision Engineering
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• v.33 no.12
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• pp.985-992
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• 2016

Bearings have various uses in industrial equipment. The lifetime of bearings is often lesser than anticipated at the time of purchase, due to environmental wear, processing, and machining errors. Bearing conditions are important, since defects and damage can lead to significant issues in production processes. In this study, we developed a method to diagnose faults in the bearing conditions. The faults were determined using kurtosis, average, and standard deviation. An intrinsic mode function for the data from the selected axis was extracted using empirical mode decomposition. The intrinsic mode function was obtained based on the frequency, and the learning data of ANN (Artificial Neural Network) was concluded, following which the normal and fault conditions of the bearing were classified.

• Journal of the Korean Society for Heat Treatment
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• v.32 no.2
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• pp.61-67
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• 2019

This study was carried out to investigate the effect of thermo-mechanical treatment on the tensile properties of Fe-20Mn-12Cr-3Ni-3Si alloy with deformation induced martensite transformation. ${\alpha}^{\prime}$ and ${\varepsilon}$-martensite, dislocation, stacking fault were formed, and grain size was refined by thermo-mechanical treatment. With the increasing cycle number of thermo-mechanical treatment, volume fraction of ${\varepsilon}$ and ${\alpha}^{\prime}$-martensite, dislocation, stacking fault were increased, and grain size decreased. In 5-cycle number thermo-mechanical treated specimens, more than 10% of the volume fraction of ${\varepsilon}$-martensite and less than 3% of the volume fraction of ${\alpha}^{\prime}$-martensite were attained. Tensile strength was increased and elongation was decreased with the increasing cycle number of thermo-mechanical treatment. Tensile properties of thermo-mechanical treated alloy with deformation induced martensite transformation was affected to formation of martensite by thermo-mechanical treatment, but was large affected to increasing of dislocation and grain refining.

• International Journal of Control, Automation, and Systems
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• v.5 no.4
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• pp.410-418
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• 2007

For the purpose of fault detection of the primary control surface, real-time estimation of the longitudinal stability and control derivatives of the DURUMI-II using the flight data is considered in this paper. The DURUM-II, a research UAV developed by KARI, is designed to have split control surfaces for the redundancy and to guarantee safety during the fault mode flight test. For fault mode analysis, the right elevator was deliberately fixed to the specified deflection condition. This study also mentions how to implement the multi-step control input efficiently, and how to switch between the normal mode and the fault mode during the flight test. As a realtime parameter estimation technique, Fourier transform regression method was used and the estimated data was compared with the results of the analytical method and the other available method. The aerodynamic derivatives estimated from the normal mode flight data and the fault mode data are compared and the possibility to detect the elevator fault by monitoring the control derivative estimated in real time by the computer onboard was discussed.

• Journal of Positioning, Navigation, and Timing
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• v.13 no.2
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• pp.189-197
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• 2024

Galileo is a European Global Navigation Satellite System (GNSS) that has offered the Galileo Open Service since 2016. Consequently, the standardization of GNSS augmentation systems, such as Satellite Based Augmentation System (SBAS), Ground Based Augmentation System (GBAS), and Aircraft Based Augmentation System (ABAS) for Galileo signals, is ongoing. In 2023, the European Union Space Programme Agency (EUSPA) released prior probabilities of a satellite fault and a constellation fault for Galileo, which are 3×10^-5 and 2×10^-4 per hour, respectively. In particular, the prior probability of a Galileo constellation fault is significantly higher than that for the GPS constellation fault, which is defined as 1×10^-8 per hour. This raised concerns about its potential impact on GBAS integrity monitoring. According to the Global Positioning System (GPS) Standard Positioning Service Performance Standard (SPS PS), a constellation fault is classified as a wide fault. A wide fault refers to a fault that affects more than two satellites due to a common cause. Such a fault can be caused by a failure in the Earth Orientation Parameter (EOP). The EOP is used when transforming the inertial axis, on which the orbit determination is based, to Earth Centered Earth Fixed (ECEF) axis, accounting for the irregularities in the rotation of the Earth. Therefore, a faulty EOP can introduce errors when computing a satellite position with respect to the ECEF axis. In GNSS, the ephemeris parameters are estimated based on the positions of satellites and are transmitted to navigation satellites. Subsequently, these ephemeris parameters are broadcasted via the navigation message to users. Therefore, a faulty EOP results in erroneous broadcast ephemeris data. In this paper, we assess the conventional ephemeris fault detection monitor currently employed in GBAS for wide faults, as current GBAS considers only single failure cases. In addition to the existing requirements defined in the standards on the Probability of Missed Detection (PMD), we derive a new PMD requirement tailored for a wide fault. The compliance of the current ephemeris monitor to the derived requirement is evaluated through a simulation. Our findings confirm that the conventional monitor meets the requirement even for wide fault scenarios.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.27 no.8
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• pp.51-59
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• 2013

High temperature fuel cell system, such as molten carbonate fuel cells(MCFC) and solid oxide fuel cells(SOFC), are capable of operating at MW rated power output. The power output change of high temperature fuel cell imposes the thermal and mechanical stresses on the fuel cell stack. To minimize the thermal-mechanical stresses on the stack, increases in the power output of high temperature fuel cell typically must be made at a slow rate. So, the short time interruption of high temperature fuel cell causes considerable generated energy losses. Because of the characteristic of high temperature fuel cell, we analyzed the impact of electrical fault in the fuel cell plant on other fuel cell generators in the same plant site. A various grounding configuration and voltage sag are analyzed. Finally, we presented the solution to minimize the effect of fault on other fuel cell generators.