• Journal of the Korea Society of Computer and Information
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• v.16 no.5
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• pp.61-71
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• 2011

To measure the fatigue of metallic objects at high speed vibration while non-contact precision displacement measurement on how to have a lot of research conducted. Noncontact high-speed vibration detection sensor of the eddy current sensors and laser sensors are used, but it is very expensive. Recently, High-speed vibrations detection using an inexpensive inductive sensor to have been studied, but is still a beginner. In this paper, a new design of an inexpensive inductive proximity sensor has been suggested in order to measure high frequency dynamic displacements of metallic specimens in a noncontact manner. Detection of the existing inductive sensors, detection, integral, and amplified through a process to detect the displacement noise due to weak nature of analog circuits and integral factor in the process of displacement detection is slow. The proposed method could be less affected by noise, the analog receive and high-speed signal processing is a new way, because AD converter (Analog to Digital converter) without using the vibration frequency signals directly into digital signals are converted. In order to evaluate the sensing performance, The proposed sensor module using non-contact vibration signals were detected while shaker vibration frequencies from 30Hz to 1,100 Hz at intervals of vibrating metallic specimens. Experimental results, Vibration frequency detection range of the metallic specimins within close proximity to contactless 5mm could be measured from DC to 1,100Hz and vibration amplitude of the resolution was $20{\mu}m$. Therefore, the proposed non-contact inductive sensor module for precision vibration detection sensor is estimated to have sufficient performance.

• Proceedings of the KOSOMBE Conference
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• v.1998 no.11
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• pp.245-246
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• 1998

AMB(Active Magnetic Bearing) systems are popularly used in various areas. In biomedical engineering applications it is a key part of magnetically suspended rotary blood pumps. The special advantage of AMBs is that they enable the rotor to revolve with no physical contact and provide rotary blood pumps with better performances such as low hemolysis level. Fundamentally, AMB systems consist of three parts, proximity sensors for distance detection, microprocessor for control algorithm and power amplifiers for actuating electromagnets. We have developed an inductive type proximity sensor with satisfactory characteristics that can be used in AMB systems. Frequency response was flat at least up to 10 kHz and sensitivity, resolution$(>5{\mu}m)$ and sensing range(<5mm) of the sensor could be adjustable for various purposes. The characteristics of the completed model showed to have satisfactory behaviors compared with the commercially available ones that already appeared to have reliable behaviors in AMB systems.

• Tribology and Lubricants
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• v.32 no.6
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• pp.189-194
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• 2016

Wear debris in lubricating oil can be indicative of potential damage to mechanical parts in rotating and reciprocating machinery. Therefore, on-line or in-line monitoring of lubricating components in machinery is of great importance. This work presents a device based on inductive measurement of lubricating oil to detect magnetic wear particles in a tested volume. The circuit in the device consists of Maxwell Bridge and LVDT to measure inductance differences between pure and contaminated oil. The device detects the passage of ferrous particles by monitoring inductance change in a coil. The sensing principle is initially demonstrated at the microscale using a solenoid. The device is then tested using iron particles ranging from $50{\mu}m$ to $100{\mu}m$, which are often found in severely worn mechanical components. The test results show that the device is capable of detecting and distinguishing ferrous particles in lubricating oil. The design concept demonstrated here can be extended to an in-line monitoring device for real-time monitoring of ferrous debris particles. A simulation using the CST code is performed to better understand the inductive response in the presence of magnetic bodies in the oil. The CST simulation further verifies the effectiveness of inductance measurement for monitoring magnetic particles within a tube.

• The Transactions of the Korean Institute of Power Electronics
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• v.24 no.1
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• pp.62-65
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• 2019

Wireless power transfer systems require an algorithm to determine the presence of the target object for mitigating standby power and safety issues. Although many schemes that sense various external objects have been actively proposed for inductive power transfer systems, not many studies on capacitive power transfer systems have been conducted compared with those on inductive power transfer systems. This study proposes a target object detection algorithm by monitoring the capacitance in transmitter-side electrodes without additional pressure sensors or distance sensors. The proposed algorithm determines the presence of a target object by monitoring the change in capacitance in transmitter-side electrodes using the step pulse of the microcontroller unit. The algorithm is verified by two step processes. First, the performance in capacitance measurement is compared with that of an LCR meter. Then, the verification is conducted in a 5-W capacitive power transfer hardware. Experimental result shows that the interelectrode capacitance increases by 6 times when the target object is fully aligned. Thus, the proposed scheme can successfully detect the presence of the target object.

• Journal of the Korean Society for Nondestructive Testing
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• v.28 no.5
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• pp.395-400
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• 2008

Alternating magnetic field was used for detection of surface flaws on nonmagnetic and magnetic metallic specimens. The nondestructive sensor probe was composed of the planar coil with inductive magnetic thin film yoke as a sensing component and a single straight typed exciting coil. The planar inductive coil sensor with magnetic yoke was fabricated by sputtering, electroplating, dry etching and photolithography process. The alternative currents with the range of 0.1A to 1.0A (0.7 MHz to 1.8 MHz) were applied to the exciting coil. The specimens were prepared with the slit shaped artificial surface flaws (minimum depth and width; 0.5 mm) on metallic plate (Al; nonmagnetic metal and FeC; magnetic metal). The detected signal for the positions and shapes of surface flaws on specimens were obtained with high sensitivity and high signal to ratio. The measured output signals by the non-contacted scanning on surface of FeC specimen with micron-sized crack were converted to the images of the flaws. And these results were compared with the optical images, respectively.

• Journal of the Korean Geographical Society
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• v.43 no.5
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• pp.761-774
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• 2008

Integration of GIS data and human expert knowledge into digital image processing has long been acknowledged as a necessity to improve remote sensing image analysis. We propose inductive machine learning algorithm for GIS data integration and rule-based classification method for land cover classification. Proposed method is tested with a land cover classification of a Landsat ETM+ multispectral image and GIS data layers including elevation, aspect, slope, distance to water bodies, distance to road network, and population density. Decision trees and production rules for land cover classification are generated by C5.0 inductive machine learning algorithm with 350 stratified random point samples. Production rules are used for land cover classification integrated with unsupervised ISODATA classification. Result shows that GIS data layers such as elevation, distance to water bodies and population density can be effectively integrated for rule-based image classification. Intuitive production rules generated by inductive machine learning are easy to understand. Proposed method demonstrates how various GIS data layers can be integrated with remotely sensed imagery in a framework of knowledge base construction to improve land cover classification.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2008.04a
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• pp.869-873
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• 2008

Optimization method for the open loop commutation time intervals in HDD spindle start-up control is presented in this paper. A hard disk drive(HDD) uses a sensorless brushless DC motor(BLDC) for the platter rotation. Because there is no direct sensor for the rotor position, open loop commutations after sensing the rotor position at a standstill using inductive sensing method are performed to speed up the rotor up to a certain speed where the zero crossings of the back electromotive force(EMF) are measurable. Therefore successful open loop commutations are necessary for the stable start-up control of the spindle motors. Random neighborhood search(RNS) algorithm is introduced as a optimization technic in this paper. Rotor speed and its standard deviation are used as a cost function and commutation intervals obtained from the spindle motion equation are used as initial parameter values for the RNS. With the help of the proposed method optimized open loop commutation time intervals for the very low start-up current are acquired and tested. The experimental results shows that the proposed method can decrease the start-up failure rate of a HDD spindle motor.

• Design & Manufacturing
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• v.15 no.1
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• pp.14-20
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• 2021

The objective of this study is to introduce the new possibility of sensing technology based on inductive displacement sensors to monitor the status of wheel position in the hot forging process. In order to validate effectiveness of proposed sensing technology, the indirect forging force measurement with displacement sensor was applied into a typical closed hot forging die-set used for the manufacturing of flange bolts. The locations to implement the displacement sensor were selected carefully by simulating forming process and static structural. From the measurement results of the forging force change during one hot forging cycle, it was found that the proposed monitoring system can provide useful information to understand the detailed behaviors of die-set in the closed hot forging process.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.18 no.10
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• pp.1065-1072
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• 2008

A HDD adopts a sensorless brushless DC (BLDC) motor as a spindle motor. Because there is no direct sensor measuring rotor position. open loop commutations with inductive sensing are used to increase the rotor speed up to a certain speed where the zero crossings of the back electromotive force (EMF) voltage are measurable. Therefore, successful open loop commutations are necessary for the stable start-up control of the spindle motors. In this paper, the time scale and the number of the open loop commutations are employed for design parameters to guarantee robustness to torque constant variation and initial rotor position. The design results are verified by experiments on a very low current start-up of the spindle motor with various environment. The experimental results show that the design results can decrease the start-up failure rate considerably.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1485-1488
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• 1997

The capacity of memory chip has increased vert quickly and 64MDRAM becomes main product in semiconductor manufacturing lines consists of many sequential processes, including etching process. although it needs direct sensing of wafer state for the accurae detching, it depends on indirect esnsing and sample test because of the complexity of the plasma etching. This equipment receives the inner light of etch chamber through the viewport and convets it to the voltage inetnsity. In this paper, EDP voltage signal has a new role to detect etching failure. First, we gathered data(EPD sigal, etching time and etchrate) and then analyzed the relationships between the signal variatin and the etch rate using two neural network modeling. These methods enable to predict whether ething state is good or not per wafer. For experiments, it is used High Density Inductive coupled Plasma(HDICP) ethcing equipment. Experiments and results proved to be abled to determine the etching state of wafer on-line and analyze the causes by modeling and EPD signal data.