• Nuclear Engineering and Technology
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• v.42 no.2
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• pp.219-230
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• 2010

In nuclear power plants (NPPs), periodic sensor calibrations are required to assure that sensors are operating correctly. By checking the sensor's operating status at every fuel outage, faulty sensors may remain undetected for periods of up to 24 months. Moreover, typically, only a few faulty sensors are found to be calibrated. For the safe operation of NPP and the reduction of unnecessary calibration, on-line instrument calibration monitoring is needed. In this study, principal component-based auto-associative support vector regression (PCSVR) using response surface methodology (RSM) is proposed for the sensor signal validation of NPPs. This paper describes the design of a PCSVR-based sensor validation system for a power generation system. RSM is employed to determine the optimal values of SVR hyperparameters and is compared to the genetic algorithm (GA). The proposed PCSVR model is confirmed with the actual plant data of Kori Nuclear Power Plant Unit 3 and is compared with the Auto-Associative support vector regression (AASVR) and the auto-associative neural network (AANN) model. The auto-sensitivity of AASVR is improved by around six times by using a PCA, resulting in good detection of sensor drift. Compared to AANN, accuracy and cross-sensitivity are better while the auto-sensitivity is almost the same. Meanwhile, the proposed RSM for the optimization of the PCSVR algorithm performs even better in terms of accuracy, auto-sensitivity, and averaged maximum error, except in averaged RMS error, and this method is much more time efficient compared to the conventional GA method.

• Bulletin of the Korean Chemical Society
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• v.25 no.6
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• pp.801-805
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• 2004

In this work, the fundamental study of on-line monitoring of $SiO_2$ particles in the size range of 40 nm to 725 nm was carried out using turbidimetry. The size of particle was measured using a field emission scanning electron microscope (FE-SEM). The factors affecting on the turbidity were discussed, for example, wavelength, size, and concentration. In order to observe the dependence of turbidity on the wavelength, a turbidimetric system equipped with charged coupled detector (CCD) was built. The shape of the transmitted peak was changed and the peak maximum was shifted to the red when the concentration of particle was increased. This result indicates that the turbidity is related to the wavelength, which corresponds to the characteristic of the Mie extinction coefficient, Q, that is a function of not only particle diameter and refractive index but also wavelength. It is clear that a linear calibration curve for each particle in different size can be obtained at an optimized wavelength.

• Nuclear Engineering and Technology
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• v.39 no.2
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• pp.133-142
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• 2007

The Electric Power Research Institute (EPRI) demonstrated a method for monitoring the performance of instrument channels in Topical Report (TR) 104965, 'On-Line Monitoring of Instrument Channel Performance.' This paper presents the results of several models originally developed by EPRI to monitor three nuclear plant sensor sets: Pressurizer Level, Reactor Protection System (RPS) Loop A, and Reactor Coolant System (RCS) Loop A Steam Generator (SG) Level. The sensor sets investigated include one redundant sensor model and two non-redundant sensor models. Each model employs an Auto-Associative Kernel Regression (AAKR) model architecture to predict correct sensor behavior. Performance of each of the developed models is evaluated using four metrics: accuracy, auto-sensitivity, cross-sensitivity, and newly developed Error Uncertainty Limit Monitoring (EULM) detectability. The uncertainty estimate for each model is also calculated through two methods: analytic formulas and Monte Carlo estimation. The uncertainty estimates are verified by calculating confidence interval coverages to assure that 95% of the measured data fall within the confidence intervals. The model performance evaluation identified the Pressurizer Level model as acceptable for on-line monitoring (OLM) implementation. The other two models, RPS Loop A and RCS Loop A SG Level, highlight two common problems that occur in model development and evaluation, namely faulty data and poor signal selection

• Journal of Korean Society of Rural Planning
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• v.21 no.4
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• pp.177-186
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• 2015

The main objective of this study was to assess the applicability of IoT (Internet of Things)-based flood management under climate change by developing intelligent water level monitoring platform based on IoT. In this study, Arduino Uno was selected as the development board, which is an open-source electronic platform. Arduino Uno was designed to connect the ultrasonic sensor, temperature sensor, and data logger shield for implementing IoT. Arduino IDE (Integrated Development Environment) was selected as the Arduino software and used to develop the intelligent algorithm to measure and calibrate the real-time water level automatically. The intelligent water level monitoring platform consists of water level measurement, temperature calibration, data calibration, stage-discharge relationship, and data logger algorithms. Water level measurement and temperature calibration algorithm corrected the bias inherent in the ultrasonic sensor. Data calibration algorithm analyzed and corrected the outliers during the measurement process. The verification of the intelligent water level measurement algorithm was performed by comparing water levels using the tape and ultrasonic sensor, which was generated by measuring water levels at regular intervals up to the maximum level. The statistics of the slope of the regression line and $R^2$ were 1.00 and 0.99, respectively which were considered acceptable. The error was 0.0575 cm. The verification of data calibration algorithm was performed by analyzing water levels containing all error codes in a time series graph. The intelligent platform developed in this study may contribute to the public IoT service, which is applicable to intelligent flood management under climate change.

• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 1997.10a
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• pp.59-65
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• 1997

The calibration of O.M.D is carried out experimentally and is analysed theoretically. O.M.D experimentally measures the change in optical density of artificially contaminated oil which contains Fe powder of 5, 10, 20, 30, 40, 50, 70, 100, 200 ppm. The change in optical density, D$_1$ means the logarithmic transmittance of I$_0$ over $I_1 D_2$ denotes the logarithmic transmittance I$_2$ over I$_1$ on electromagnetic force which arranges the ferrous particles along the line of magnetic force. The theoretical D$_1$ which increases linearly as increasing Fe concentrations, is analysed by light attenuation theory. The difference between theoretical D$_1$ and experimental D$_1$ is due to the attenuation of micro bubbles and the agglomeration of fine particles in the sample oil. The calibrated O.M.D is applied to the sample oil from the high-powered diesel engine. Also the results are compared with those out of the off-line techniques such as JOAP and ICP.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.13 no.2
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• pp.28-34
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• 2014

A non-contact type measurement system is specially devised to measure the width of a piston ring groove in the grinding process. This system comprises a line camera with an imaging lens, collimated white light source, and a one axis translation stage. When the measurement system movesalong the diagonal direction of the cylinder, the line camera captures an image. By analyzing such images, the width of the piston ring groove can be determined. The experimental results prove that the proposed system is useful, especially as a monitoring system in grinding piston ring grooves on cylinders with accuracy of several micrometers in an area of dozens of millimeters.

• Mycobiology
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• v.31 no.4
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• pp.226-228
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• 2003

The multiple correlation coefficient between the values determined by dry weight and those determined by fluorometer was observed with r=0.96 and the standard error of calibration was 0.034. Using the best calibration data, in order to reconfirm the reliability of the fluorometer results in comparison with those obtained by dry weight on the cell concentration, fedbatch cultures were carried out. The results obtained by fluorometer measurements were in good agreement with those obtained by dry weight. The on-line monitoring of cell concentration by the fermentor system linked to a computer equipped with fluorometer was successfully carried out.

• Smart Structures and Systems
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• v.5 no.6
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• pp.663-679
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• 2009

The use of Micro-Electro-Mechanical Systems (MEMS) accelerometers in geotechnical instrumentation is relatively new but on the rise. This paper describes a new MEMS-based system for in situ deformation and vibration monitoring. The system has been developed in an effort to combine recent advances in the miniaturization of sensors and electronics with an established wireless infrastructure for on-line geotechnical monitoring. The concept is based on triaxial MEMS accelerometer measurements of static acceleration (angles relative to gravity) and dynamic accelerations. The dynamic acceleration sensitivity range provides signals proportional to vibration during earthquakes or construction activities. This MEMS-based in-place inclinometer system utilizes the measurements to obtain three-dimensional (3D) ground acceleration and permanent deformation profiles up to a depth of one hundred meters. Each sensor array or group of arrays can be connected to a wireless earth station to enable real-time monitoring as well as remote sensor configuration. This paper provides a technical assessment of MEMS-based in-place inclinometer systems for geotechnical instrumentation applications by reviewing the sensor characteristics and providing small- and full-scale laboratory calibration tests. A description and validation of recorded field data from an instrumented unstable slope in California is also presented.

• Bulletin of the Korean Chemical Society
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• v.32 no.6
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• pp.2039-2044
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• 2011

A semi-continuous and automated method for quantifying atmospheric ammonia at the parts per billion level has been developed. The instrument consists of a high efficiency diffusion scrubber, an electrolytic on-line anion exchange device, and a conductivity detector. Water soluble gases in sampled air diffuse through the porous membrane and are absorbed in an absorbing solution. Interferences are eliminated by using an anion exchange devises. The electrical conductivity of the solution is measured without chromatographic separation. The collection efficiency was over 99%. Over the 0-200 ppbv concentration range, the calibration was linear with $r^2$ = 0.99. The lower limit of detection was 0.09 ppbv. A parallel analysis of Seoul air over several days using this method and a diffusion scrubber coupled to an ion chromatography system showed acceptable agreement, $r^2$ = 0.940 (n = 686). This method can be applied for ambient air monitoring of ammonia.

• Progress in Medical Physics
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• v.28 no.3
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• pp.129-133
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• 2017

The machine log files recorded by a scanning control unit in proton beam therapy system have been studied to be used as a quality assurance method of scanning beam deliveries. The accuracy of the data in the log files have been evaluated with a standard calibration beam scan pattern. The proton beam scan pattern has been delivered on a gafchromic film located at the isocenter plane of the proton beam treatment nozzle and found to agree within ${\pm}1.0mm$. The machine data accumulated for the scanning beam proton therapy of five different cases have been analyzed using a statistical method to estimate any systematic error in the data. The high-precision scanning beam log files in line scanning proton therapy system have been validated to be used for off-line scanning beam monitoring and thus as a patient-specific quality assurance method. The use of the machine log files for patient-specific quality assurance would simplify the quality assurance procedure with accurate scanning beam data.