• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.762-766
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• 1998

Mechanical valve is one of the most widely used implantable artificial organs, Since its failure (mechanical failures and thrombosis to name two representative example) means the death of patient, its reliability is very important and early noninvasive detection is essential requirement . This paper will explain the method to detect the thrombosis formation by spectral analysis and neural network. In order quantitatively to distinguish peak of a normal valve from that of a thrombotic valve, a 3 layer backpropagation neural network, which contains 7,000 input nodes, 20 hidden layer and 1output , was employed. The trained neural network can distinguish normal and thrombotic valve with a probability that is higher than 90% . In conclusion, the acoustical spectrum analysis coupled with a neural network algorithm lent itself to the noninvasive monitoring of implanted mechanical valves. This method will be applied to be applied to the performance evaluation of other implantable rtificial organs.

• The KSFM Journal of Fluid Machinery
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• v.19 no.4
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• pp.39-42
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• 2016

A PFA lined ball valve, which is machined with fluorinated resin PFA to its inner part for improving corrosion resistance, non-stickness, heat-resistance, has been widely used to the chemical/pharmaceutical industries, the semiconductor/LCD manufacturing processes, etc. with the high purity chemicals as working fluid. EPA stated that 60% of all fugitive emissions come from the valve stem packing in a typical petroleum or chemical processing plant. They monitor regulated components for leaks and maintain seal performance at acceptable levels. Korean industrial standards only deals with the bubble test for in-line leakage of valves, which has the detectable leak rate of $10^{-4}$ [$mbar{\cdot}L{\cdot}s^{-1}$], therefore, it is not sufficient to check fugitive emissions. In this study, we conducted Helium leak detection from a PFA lined ball valve and evaluated fugitive emissions according to ISO 15848-1, which has the detectable leak rate of $10^{-9}$ [$mbar{\cdot}L{\cdot}s^{-1}$], for manufacturing the high-reliable PFA lined ball valves against fugitive emissions.

• Journal of Korean Society of Water and Wastewater
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• v.35 no.1
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• pp.15-25
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• 2021

In this study, a method of leakage detection was proposed to locate leak position for a reservoir pipeline valve system using wavelet coherence analysis for an injected pressure wave. An unsteady flow analyzer handled nonlinear valve maneuver and corresponding experimental result were compared. Time series of pressure head were analyzed through wavelet coherence analysis both for no leak and leak conditions. The leak information can be obtained through either time domain reflectometry or the difference in wavelet coherence level, which provide predictions in terms of leak location. The reconstructed pressure signal facilitates the identification of leak presence comparing with existing wavelet coherence analysis.

• Nuclear Engineering and Technology
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• v.48 no.5
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• pp.1280-1290
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• 2016

This paper presents an advanced estimation method for obtaining the probability density functions of a damage parameter for valve leakage detection in a reciprocating pump. The estimation method is based on a comparison of model data which are simulated by using a mathematical model, and experimental data which are measured on the inside and outside of the reciprocating pump in operation. The mathematical model, which is simplified and extended on the basis of previous models, describes not only the normal state of the pump, but also its abnormal state caused by valve leakage. The pressure in the cylinder is expressed as a function of the crankshaft angle, and an additional volume flow rate due to the valve leakage is quantified by a damage parameter in the mathematical model. The change in the cylinder pressure profiles due to the suction valve leakage is noticeable in the compression and expansion modes of the pump. The damage parameter value over 300 cycles is calculated in two ways, considering advance or delay in the opening and closing angles of the discharge valves. The probability density functions of the damage parameter are compared for diagnosis and prognosis on the basis of the probabilistic features of valve leakage.

• Journal of the Society of Disaster Information
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• v.16 no.1
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• pp.144-154
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• 2020

Purpose: This paper is a fundamental study on the applicability of the smart bolt developed for monitoring system to detect the leakage of water supply valve. Method: A leak detection experiments were conducted using the smart bolt having embedded strain sensors and accelerometer. The smart bolt used in study meets the allowable criteria of torque and tensile stress for water supply system, and it can be applied to a joint of the water supply valve by behaving well within the allowable limits. Result: As a result of the simulated leak tests, a leak signal at the valve leak point was detected in a band of 60Hz, and the main pipe leaking point was observed to produce a leak signal having much higher frequency than that of the valve leak point. This seems to result in a total coupled vibration under unconfined conditions of the pipes. Conclusion: The smart bolts appeared applicable to detecting a leaking signal from the water supply valve.

• Journal of Magnetics
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• v.13 no.1
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• pp.30-33
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• 2008

A highly sensitive, giant magnetoresistance-spin valve (GMR-SV) biosensing device with high linearity and very low hysteresis was fabricated by photolithography. The detection of magnetic nanoparticles and Fe-hemoglobin inside red blood cells using the GMR-SV biosensing device was investigated. When a sensing current of 1 mA was applied to the current electrode in the patterned active devices with an area of $2{\times}6{\mu}m^2$, the output signals were about 13.35 mV. The signal from even one drop of human blood and nanoparticles in distilled water was sufficient for their detection and analysis.

• Transactions of The Korea Fluid Power Systems Society
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• v.8 no.3
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• pp.1-7
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• 2011

As the technologies of electronic device have advanced these days, most of mechanical systems are designed with electronic control unit to take advantage of control parameter adaption to operating conditions and firmware flexibilities as well. On-board diagnosis, which detects the system malfunction and identifies potential source of error with its own diagnostic criteria, and fail-safe that can switch the mode of operation in view of recognized error characteristics enables easy maintenance and troubleshooting as well as system protection. This paper dealt with the development of diagnosis and fail-safe function for proportional flow control valve. All type of errors related to valve control system components are investigated and assigned to a specific hexadecimal codes. Cumulative error detection algorithm is applied in order for the sensitivity and reliability to be appropriate. Embedded simulator which runs simultaneously with system program provides the virtual error simulation environment for expeditious development of error detection algorithm. The diagnosis function was verified both with solenoid valve and embedded simulator test and it will enhance the valve control system monitoring function.

• Proceedings of the Korean Magnestics Society Conference
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• 2003.06a
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• pp.48-49
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• 2003

• Proceedings of the Korean Magnestics Society Conference
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• 2010.06a
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• pp.189-190
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• 2010

Our results demonstrate the possibility of implementing a chip-cytometer for biological applications using high-sensitive spin-valve devices integrated with a microfluidic channel. Further studies will be extended to the real-time detection of animal cells coated with magnetic beads for the biological applications.

• Journal of the Korean Society for Nondestructive Testing
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• v.28 no.6
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• pp.524-530
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• 2008

The spin valve tunneling magnetoresistance (SV-TMR) sensor performance is analyzed using Stoner-Wohlfarth model for the detection of eddy current signals in nondestructive testing applications. The SV-TMR response in terms of the applied AC magnetic field dominantly generates the second harmonic amplitude in hard axis direction. The second harmonic eddy current signal detection using SV-TMR sensor shows higher performance than that of the coil sensor at lower frequencies. The SV-TMR sensor with high sensitivity gives a good solution to improve the low frequency performance in comparison with the inductive coil sensors. Therefore, the low frequency eddy current techniques based on SV-TMR sensors are specially useful in the detection of hidden defects, and it can be applied to detect the deeply embedded flaws or discontinuities in the conductive materials.