• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2005년도 춘계학술대회 논문집
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• pp.300-306
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• 2005

This paper presents the methodology for measuring eccentricity of the machined cylindrical part using CCS(cylindrical capacitance spindle sensor) signal in the CNC turning process. We use capacitance type sensor to take full advantage of averaging effect by using large capacitance area to encompass the whole side of a sensor. The intentionally proposed initial eccentricity is applied to the experimental testpieces, and their resultant relationships between CCS orbits and eccentricities are investigated. As a result, the possibility as a automatic detection apparatus for the CNC lathe is considered based on the linearities of CCS signal and magnitude of eccentricity of machined cylindrical surfaces.

• Journal of Electrical Engineering and Technology
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• 제11권3호
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• pp.653-661
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• 2016

This paper proposes a capacitance estimation method of the dc-link capacitor for brushless DC motor (BLDCM) drive systems. In order to estimate the dc-link capacitance, the BLDCM is operated in quadrant-II or -IV among four-quadrant operation. Quadrant-II and -IV are called reverse braking and forward braking, respectively. During the braking operation of the BLDCM, the capacitor is charged by the phase current and then the voltage is increased during the braking operation time. The capacitor current and voltage can be obtained by using the phase current sensor of BLDCM and the dc-link voltage sensor. The capacitance and be easily obtained by the voltage equation of the capacitor. The proposed method guarantees the reliable and simple calculation of the dc-link capacitance without additional hardware system except several the sensors already installed for the motor control system. The effectiveness of the proposed method is verified through both the simulation and experimental results.

• 대한의용생체공학회:의공학회지
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• 제39권1호
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• pp.10-15
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• 2018

In this paper, we present a wearable measurement system for monitoring rounded shoulders. The system contains a shoulder correction band and a stretch sensor that can correct and measure shoulder posture, respectively. The capacitance of the stretch sensor changes linearly according to changes in the shoulders. To verify measurement, a motion analysis system was used as the reference to compare the change in the rounded angles of the shoulders and the change in the stretch sensor's capacitance. The results indicated that there is a high correlation between the two changes and the system can be used as a monitoring device for rounded shoulders.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권2호
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• pp.654-670
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• 2020

Workers at construction sites are easily exposed to many dangers and accidents involving falls, tripping, and missteps on stairs. However, researches on construction site monitoring system to prevent work-related injuries are still insufficient. The purpose of this study was to develop a wearable textile pressure insole sensor and examine its effectiveness in managing the real-time safety of construction workers. The sensor was designed based on the principles of parallel capacitance measurement using conductive textile and the monitoring system was developed by C# language. Three separate experiments were carried out for performance evaluation of the proposed sensor: (1) varying the distance between two capacitance plates to examine changes in capacitance charges, (2) repeatedly applying 1 N of pressure for 5,000 times to evaluate consistency, and (3) gradually increasing force by 1 N (from 1 N to 46 N) to test the linearity of the sensor value. Five subjects participated in our pilot test, which examined whether ascending and descending the stairs can be distinguished by our sensor and by weka assessment tool using k-NN algorithm. The 10-fold cross-validation method was used for analysis and the results of accuracy in identifying stair ascending and descending were 87.2% and 90.9%, respectively. By applying our sensor, the type of activity, weight-shifting patterns for balance control, and plantar pressure distribution for postural changes of the construction workers can be detected. The results of this study can be the basis for future sensor-based monitoring device development studies and fall prediction researches for construction workers.

• Biomaterials and Biomechanics in Bioengineering
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• 제2권2호
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• pp.71-84
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• 2015

A low-profile flow sensor has been designed, fabricated, and characterized to demonstrate the feasibility for monitoring hemodynamics in cerebral aneurysm. The prototype device is composed of three micro-membranes ($500-{\mu}m$-thick polyurethane film with $6-{\mu}m$-thick layers of nitinol above and below). A novel super-hydrophilic surface treatment offers excellent hemocompatibility for the thin nitinol electrode. A computational study of the deformable mechanics optimizes the design of the flow sensor and the analysis of computational fluid dynamics estimates the flow and pressure profiles within the simulated aneurysm sac. Experimental studies demonstrate the feasibility of the device to monitor intra-aneurysmal hemodynamics in a blood vessel. The mechanical compression test shows the linear relationship between the applied force and the measured capacitance change. Analytical calculation of the resonant frequency shift due to the compression force agrees well with the experimental results. The results have the potential to address important unmet needs in wireless monitoring of intra-aneurysm hemodynamic quiescence.

• Journal of Power Electronics
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• 제19권1호
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• pp.307-315
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• 2019

Condition monitoring has been recognized as an effective and low-cost method to enhance the reliability and improve the maintainability of power electronic converters. In power electronic converters, high-frequency oscillation occurs during the switching transients of power transistors, which is known as ringing. The ringing frequency mainly depends on the values of the parasitic capacitance and stray inductance in the oscillation loop. Although circuit stray inductance is an important factor that leads to the ringing, it does not change with transistor aging. A shift in either the inside inductance or junction capacitance is an important failure precursor for power transistors. Therefore, ringing frequency can be used to monitor the health of power transistors. However, the switching actions of power transistors usually result in a dynamic behavior that can generate oscillation signals mixed with background noise, which makes it hard to directly extract the ringing frequency. A frequency extraction method based on empirical mode decomposition (EMD) and Fast Fourier transformation (FFT) is proposed in this paper. The proposed method is simple and has a high precision. Simulation results are given to verify the ringing analysis and experimental results are given to verify the effectiveness of the proposed method.

• Journal of Power Electronics
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• 제16권5호
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• pp.1752-1762
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• 2016

To achieve higher reliability in the modular multilevel converters (MMC) for HVDC transmission systems, the internal condition of the DC capacitors of the submodules (SM) needs to be monitored regularly. For an online estimation of the SM capacitance, a controlled AC current with double the fundamental frequency is injected into the circulating current loop of the MMC, which results in current and voltage ripples in the SM capacitors. The capacitor currents are calculated from the arm currents and their switching states. By processing these AC voltage and current components with digital filters, their capacitances are estimated by a recursive least square (RLS) algorithm. The validity of the proposed scheme has been verified by simulation results for a 300-MW, 300-kV HVDC system. In addition, its feasibility has been verified by experimental results obtained with a reduced-scale prototype. It has been shown that the estimation errors for both the simulation and experimental tests are 1.32% at maximum.

• Advances in aircraft and spacecraft science
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• 제5권4호
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• pp.499-513
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• 2018

One of the major problems in glass fiber reinforced epoxy (GFRE) composite pipes is the durability under water absorption. This condition is generally recognized to cause degradations in strength and mechanical properties. Therefore, there is a need for an intelligent system for detecting the absorption rate and computing the mass of water absorption (M%) as a function of absorption time (t). The present work represents a new non-destructive evaluation (NDE) technique for detecting the water absorption rate by evaluating the dielectric properties of glass fiber and epoxy resin composite pipes subjected to internal hydrostatic pressure at room temperature. The variation in the dielectric signatures is employed to design an electrical capacitance sensor (ECS) with high sensitivity to detect such defects. ECS consists of twelve electrodes mounted on the outer surface of the pipe. Radius-electrode ratio is defined as the ratio of inner and outer radius of pipe. A finite element (FE) simulation model is developed to measure the capacitance values and node potential distribution of ECS electrodes on the basis of water absorption rate in the pipe material as a function of absorption time. The arrangements for positioning12-electrode sensor parameters such as capacitance, capacitance change and change rate of capacitance are analyzed by ANSYS and MATLAB to plot the mass of water absorption curve against absorption time (t). An analytical model based on a Fickian diffusion model is conducted to predict the saturation level of water absorption ($M_S$) from the obtained mass of water absorption curve. The FE results are in excellent agreement with the analytical results and experimental results available in the literature, thus, validating the accuracy and reliability of the proposed expert system.

• Structural Monitoring and Maintenance
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• 제3권4호
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• pp.377-393
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• 2016

The present work develops an expert system for detecting and predicting the crude oil types and properties at normal temperature ${\theta}=25^{\circ}C$, by evaluating the dielectric properties of the fluid transfused inside glass fiber reinforced epoxy (GFRE) composite pipelines, by using electrical capacitance sensor (ECS) technique, then used the data measurements from ECS to predict the types of the other crude oil transfused inside the pipeline, by designing an efficient artificial neural network (ANN) architecture. The variation in the dielectric signatures are employed to design an electrical capacitance sensor (ECS) with high sensitivity to detect such problem. ECS consists of 12 electrodes mounted on the outer surface of the pipe. A finite element (FE) simulation model is developed to measure the capacitance values and node potential distribution of ECS electrodes by ANSYS and MATLAB, which are combined to simulate sensor characteristic. Radial Basis neural network (RBNN), structure is applied, trained and tested to predict the finite element (FE) results of crude oil types transfused inside (GFRE) pipe under room temperature using MATLAB neural network toolbox. The FE results are in excellent agreement with an RBNN results, thus validating the accuracy and reliability of the proposed technique.

• Tribology and Lubricants
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• 제30권3호
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• pp.156-167
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• 2014

This paper presents the test results of small dipstick-gage-type engine-oil-deterioration-detection sensor. The measured sensor signal characteristics for the capacitance and temperature are analyzed. The engine oil deterioration condition correlates with the electrical property of the dielectric constant that comprised with physical properties such as TAN (Total Acid Number), TBN (Total Base Number) and viscosity. Several problems encontered during the test of the sensor system are improved. The results of vehicle tests show that the capacitance signal is stable after the engine stops. Therefore, the sensor should start measuring the parameters for monitoring the engine oil condition after the engine stops. The engine is considered to be in a stopped state if the difference between the maximum and minimum values of the oil capacitance measured every 1 min is below 0.02 pF. The key test results in this paper will help in the development of an engine oil change warning algorithm.