• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.11a
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• pp.891-894
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• 2007

This study presents fault diagnosis of low speed bearing using support vector machine (SVM). The data used in the experiment was acquired using acoustic emission (AE) sensor and accelerometer. The aim of this study is to compare the performance of fault diagnosis based on AE signal and vibration signal with same load and speed. A low speed test rig was developed to simulate various defects with shaft speeds as low as 10 rpm under several loading conditions. In this study, component analysis was also performed to extract the feature and reduce the dimensionality of original data feature. Moreover, the classification for fault diagnosis was also conducted using original data feature without feature extraction. The result shows that extracted feature from AE sensor gave better performance in faults classification.

• Proceedings of the IEEK Conference
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• 1998.06a
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• pp.811-814
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• 1998

REcent research about current testing($\textrm{I}_{DDQ}$ testing) has been emphasizing that $\textrm{I}_{DDQ}$ testing in addition to the logical voltage testing is necessary to increase the fault coverage. The $\textrm{I}_{DDQ}$. testing can detect physical faults other than the classical stuck-at type fault, which affect reliability. One of the most critical issues in the $\textrm{I}_{DDQ}$ testing is to insert a built-in current sensor (BICS) that can detect abnormal static currents from the power supply or to the ground. This paper presents a new BICS for internal current testing for large CMOS logic circuits. The proposed BICS uses a single phase clock to minimize the hardware overhead. It detects faulty current flowing and converts it into a corresponding logic voltage level to make converts it into a corresponding logic voltage level to make it possible to use the conventional voltage testing techniqeus. By using current mirroring technique, the proposed BICS can work at very high speed. Because the proposed BICS almost does not affects normal operation of CUT(circuit under test), it can be used to a very large circuit without circuit partitioning. By altenating the operational modes, a circuit can be $\textrm{I}_{DDQ}$-tested as a kind of self-testing fashion by using the proposed BICS.

• Transactions of The Korea Fluid Power Systems Society
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• v.4 no.4
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• pp.1-7
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• 2007

Flow rate is one of the important variables for precise motion control and detection of the faults and fluid loss in many hydraulic components and systems. But in many cases, it is not easy to measure it directly. The orifice area of a servo valve by which the fluid flows is one of key factors to monitor the flow rate. In this paper, we have constructed an estimation algorithm for the effective orifice area by using the model of a servo valve cylinder control system and Kalman filter algorithm. Without geometry information about the servo valve, it is shown that the effective orifice area can be estimated by using only displacement and pressure data corrupted with noise. And the effect of the biased sensor data and system parameter errors on the estimation results are discussed. The paper reveals that sensor calibration is important in accurate estimation and plausible parameter data such as oil bulk modulus and actuator volume are acceptable for the estimation without any error. The estimation algorithm can be used as an useful tool for detecting leakage, monitoring malfunction and/or degradation of the system performance.

• Journal of international Conference on Electrical Machines and Systems
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• v.1 no.3
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• pp.384-390
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• 2012

This paper proposes a fault diagnosis method of the line-to-line voltage sensors in 3-phase AC/DC pulse width modulation (PWM) converters. The line-to-line voltage sensors are an essential device to obtain the information of the grid voltages for controlling the 3-phase AC/DC PWM converters. If the line-to-line voltage sensors are mismeasured by various faults, the voltage sensors can obtain wrong information of the grid voltage. It has an adverse effect on the control of the converter. Therefore, the converter causes the unbalance input AC current and the DC-link voltage ripple in the 3-phase AC/DC PWM converter. Hence, fast fault detection and fault tolerant control are needed. In this paper, the fault diagnosis method is proposed and verified through simulations and experiments.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.8 no.1
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• pp.83-93
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• 1997

This paper deals with measurements and evaluation of the time-changing electric and magnetic fields at a high-voltage laboratory. The electromagnetic disturbances originate mainly from ground faults and on/off operations of electric power equipments. The electronic circuits and control devices are very sensitive to electromagnetic interferences. It is necessory to evaluate the levels of interferences for a given electromagnetic environment. The electric field was observed by the electric field sensor having the bandwidth of the range from 40 Hz to 200 MHz, and the time-changing magnetic field was measured by the loop sensor of which the output is directly proportional to the incident signal. Also, the frequency components of the time-changing electric and magnetic fields induced by an oscillatory transient current and a chopped impulse voltage were analyzed by terms of the fast Fourier transformation, and those give the information about the levels of the electromagnetic interferences and the design of the electromagnetic shielding enclosures.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.57 no.2
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• pp.202-208
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• 2008

Condition monitoring technologies allow achieving this goal by minimizing downtime through the integrated planning and scheduling of repairs indicated by condition monitoring techniques. Thermal runaways induced by conduction problems deteriorate insulating material and cause disruptive dielectric discharges resulting in arcing faults. Therefore, having the ability to directly measure the temperature of the contacts while in service will provide more information to determine the true condition of the equipment. It allows connective measures to be taken to prevent upcoming failure. Continuous temperature monitoring and event recording provides information on the energized equipment's response to normal and emergency conditions. On-line temperature monitoring helps to coordinate equipment specifications and ratings, determine the real limits of the monitored equipment and optimize facility operations. Using wireless technique eliminates any need for special cables and wires with lower installation costs if compared to other types of online condition monitoring equipment. In addition, wireless temperature monitoring works well under difficult conditions in strategically important locations. Wireless technology for on -line condition monitoring of energized equipment is applicable both as stand alone system and with an interface for power quality monitoring system. The paper presents the results of wireless temperature monitoring: of electrical equipment at a power plant.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.55 no.3
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• pp.91-97
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• 2006

A major difficulty with the practical application of the multiple observer based IFDI schemes is the computational burden of the residual generation. In this paper, a new residual generator that employs function observers is proposed to reduce the computational burden, and the design methods of the IFDIS, equipped with the residual generator, are presented. The function observers employed in the residual generator can be considered as a dual of the unknown input (function) observer And it can be designed to estimate the measurement errors that are due to sensor faults. The error estimates are further processed to generate the residuals by which reliable fault detection/isolation result car be obtained. The proposed scheme is more useful, in real-time application, than any other multiple state observer based IFDISs. It can be effectively applied to fault tolerant control because the failure effects can be compensated by the use of the estimates of measurement errors. The proposed IFDI scheme is applied to an inverted pendulum control system for the IFDI of failed sensor and fault compensation.

• Transactions of the Korean Society of Automotive Engineers
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• v.24 no.1
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• pp.16-23
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• 2016

The EWB(electronic wedge brake) is one in which the braking force is developed in a wedge and caliper system and applied to a disk and wedge mechanism. The advantage of the wedge structure is that it produces self-reinforcing effect and hence, utilizes minimal motor power, resulting in reduced gear and current. The extent of use of clamping force sensors and protection from failure of the EWB system directly depends on the level of vehicle mass production. This study investigated the mathematical equations, simulation modeling, and failsafe control algorithm for the clamping force sensor of the EWB and validated the simulations. As this EWB system modeling can be applied to motor inductance, resistance, screw inertia, stiffness, and wedge mass and angle, this study could improve the accuracy of simulation of the EWB. The simulation results demonstrated the braking force, motor speed, and current of the EWB system when the driver desired to the step and pulse the brake force inputs. Moreover, this paper demonstrated that the proposed failsafe control algorithm accurately detects faults in the clamping force sensor, if any.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.1
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• pp.163-169
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• 2020

Recently, research on automation and unmanned operation of machines in the industrial field has been conducted with the advent of AI, Big data, and the IoT, which are the core technologies of the Fourth Industrial Revolution. The machines for these automation processes are controlled based on the data collected from the sensors attached to them, and further, the processes are managed. Conventionally, the abnormalities of sensors are periodically checked and managed. However, due to various environmental factors and situations in the industrial field, there are cases where the inspection due to the failure is not missed or failures are not detected to prevent damage due to sensor failure. In addition, even if a failure occurs, it is not immediately detected, which worsens the process loss. Therefore, in order to prevent damage caused by such a sudden sensor failure, it is necessary to identify the failure of the sensor in an embedded system in real-time and to diagnose the failure and determine the type for a quick response. In this paper, a deep neural network-based fault diagnosis system is designed and implemented using Raspberry Pi to classify typical sensor fault types such as erratic fault, hard-over fault, spike fault, and stuck fault. In order to diagnose sensor failure, the network is constructed using Google's proposed Inverted residual block structure of MobilieNetV2. The proposed scheme reduces memory usage and improves the performance of the conventional CNN technique to classify sensor faults.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1440-1443
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• 1997

The optimal residual generator based on parity relation approach for the fault detection and isolation of a arge diesel engine actuator position servo system is presented. The closed-loop residual generator is designed to have robustness against modeling errors and noise. Main purpose of the fault detection and isolation system in the process is to detect and isolate two important faults, i.e., actuatro fault and fault of speed sensor, that, if not detected and compensated, degrade the overall control system performance. Simulation results are give to show the practical applicability of the fault detecrtion and isloation scherme.