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

• Journal of the Institute of Electronics and Information Engineers
• /
• v.53 no.2
• /
• pp.62-69
• /
• 2016

This paper proposes to select Measure of Performance(MOP) for object attainment in the counterfire operation and deduce the reasonable combination of blue force's hitting resources satisfying MOP's optimal value and regression equation for the object achievement time. Also, in the study-methodological perspective, a series of procedures for drawing the regression equation from the real world is presented. Firstly the model was made by simplifying the weapon-system information of red force and blue force, then the time for object attainment was derived from its simulation. Simulating the model for the counterfire operation was divided into three phases-detection, decision and hitting. The probability method by applying the random numbers were used for detection, fixed constant numbers for decision and hitting. The simulation was repeatedly performed to get the minimum time for the object attainment against the fixed enemy, and it was estimated as the optimal value of simulation. From this result, the optimum combination of blue force's weapon system against the red force and finally, the regression equation were obtained by using the response surface analyzing method in MINITAB. Thereafter this equation was completely verified by using 'the 2-sample t-test.' As a result, the regression equation is suitable.

• Journal of the Korean institute of surface engineering
• /
• v.43 no.3
• /
• pp.159-164
• /
• 2010

Surface roughness of deposited or etched film strongly depends on ion bombardment. Relationships between ion bombardment variables and surface roughness are too complicated to model analytically. To overcome this, an empirical neural network model was constructed and applied to a deposition process of silicon nitride (SiN) films. The films were deposited by using a pulsed plasma enhanced chemical vapor deposition system in $SiH_4$-$NH_4$ plasma. Radio frequency source power and duty ratio were varied in the range of 200-800 W and 40-100%. A total of 20 experiments were conducted. A non-invasive ion energy analyzer was used to collect ion energy distribution. The diagnostic variables examined include high (or) low ion energy and high (or low) ion energy flux. Mean surface roughness was measured by using atomic force microscopy. A neural network model relating the diagnostic variables to the surface roughness was constructed and its prediction performance was optimized by using a genetic algorithm. The optimized model yielded an improved performance of about 58% over statistical regression model. The model revealed very interesting features useful for optimization of surface roughness. This includes a reduction in surface roughness either by an increase in ion energy flux at lower ion energy or by an increase in higher ion energy at lower ion energy flux.

• Journal of Korea Technical Association of The Pulp and Paper Industry
• /
• v.47 no.3
• /
• pp.34-39
• /
• 2015

Fluorescent whitening agents (FWAs) are widely applied in the papermaking process to improve the CIE whiteness and the ISO brightness of papers. Large amounts of FWAs are used in the paper and paperboard industry, but no standard method exists for quantitative FWA analysis. Therefore, a new method is needed to analyze the presence of FWAs in paper and paperboard to control their additions and applications. In particular, FWA analysis must concentrate on those used for surface treatment of paper because their use in surface applications has increased recently. The purposes of this study were to measure the optical properties of papers surface-treated with oxidized starch containing FWAs and to deduce the regression equations for the quantitative analysis of FWAs used for surface treatments. Surface sizing was carried out to treat the surface of a base paper with T-FWA and H-FWA, and the pickup weight of the surface sized paper was measured to determine the real weight of FWAs transferred onto the paper surface. After surface sizing and preconditioning, the paper was evaluated for CIE whiteness, ISO brightness, fluorescence index, and reflectance at 440 nm using an Elrepho spectrophotometer. The CIE whiteness and the ISO brightness increased linearly as FWA content increased. The fluorescence index and the reflectance showed linear relationships with T-FWA and H-FWA. Linear regression equations were determined for the quantitative analysis of FWAs used for surface treatments.

• Journal of the Korean Society of Costume
• /
• v.45
• /
• pp.17-28
• /
• 1999

This study was to analyze factors of the body form and factors of bodice pattern through a surface developement figure for the tight bodice pattern design. Fifty replicas of the trunk surface were made by applying a surgical tape method of female subjects between 18 and 24 years old. The result was as follows: 1. The gaps between direct measurements and measurements of the surface development figure were regarded as allowances for the tight bodice pattern. 2. There are four factors of body form selected by factor analysis. The 1st factor signifies th degree of fatness in the upper body. The 2nd factor signifies the length of the upper body. The 3rd factor signifies the part of the front shoulder. The 4th factor signifies the part of the neck. 3. There are high correlations between center back line of the surface development figure and back length line side line front length line back neck depth back upper chest depth. There are high correlations between back bust line of the surface development figure and back interscye breadth line back upper chest line back armhole line. There are high correlations between front bust line of the surface development figure and front upper chest line front interscye breadth line front armhole line front neck breadth 4. The regression expressions of measurements of the surface development figure of the upper body were analyzed as(Fig. 3).

• 한국지구물리탐사학회:학술대회논문집
• /
• 2003.11a
• /
• pp.129-141
• /
• 2003

The precise prediction of ground displacement plays an important role in planning and constructing tunnels. In this study, an equation for predicting the surface and crown settlement is suggested by examining the theories of ground movement caused by tunnel excavation. From the 3D numerical modeling, the reinforcement effect of UAM (Umbrella Arch Method) is quantitatively analyzed with respect to deformation modulus and overburden. By using a regression technique for the numerical results, an equation for predicting the settlement is suggested.

• Proceedings of the KWS Conference
• /
• 2004.05a
• /
• pp.39-41
• /
• 2004

This study is to optimize the condition of pulse parameters using the response surface method in micro pulse TIG welding of pleated type metallic filter. The input parameters used were pulse current, base current, pulse duty, frequency and welding speed and the hydraulic pressure was used as the output parameter. The central composite design was designed using second order regression model, As the results, the optimal welding condition to manufacture the pleated type metallic filter was obtained.

• Journal of Biosystems Engineering
• /
• v.17 no.4
• /
• pp.382-395
• /
• 1992

The surface color of several varieties of apples were expressed quantitatively in xyz chromaticity coordinates. The spectral reflectance of 'Fuji' apples were measured in 400-820 nm range by using a spectrophotometer. Based on the spectrophotometer data and the result of visual sensory test, linear regression models were developed to select wavelengths effective for sorting apples. The models utilized reflectance at single wavelength, and the difference and ratio of the reflectance at two distinct wavelengths. The model which best fitted the visual sensory test data was one utilizing the ratio of the reflectance at 618 nm and 514nm. The correlation coefficient for this model was 0.967. Several other models were also described.

• Journal of Environmental Science International
• /
• v.7 no.6
• /
• pp.827-831
• /
• 1998

Statistical $SO_2$ forecasting technique by multiple regression analysis was designed and developed to predict $SO_2$ concentration in Wonju City. $SO_2$ concentration data measured from air pollution monitoring system and meteorological factors data such as : wind speed, atmospheric stability, surface temperature, relative humidity and precipitation were used in Wonju City during the 1996~1997. As the results, correlation model for forecasting was well fitted with some parameters including minimum temperature, wind speed and the $SO_2$ concentration of the previous day.

• Journal of The Korean Society of Agricultural Engineers
• /
• v.53 no.6
• /
• pp.51-58
• /
• 2011

The objective of this study is to identify whether or not the ground water level is decreasing. We suggest a method of estimating the change in groundwater level using newly developed groundwater pumping station data. The Goseong area located in Gyeongnam province was selected considering three factors. First, this area demands relatively large amount of irrigation water because most of the land is used as a paddy field and the proportion of the paddy field within total arable land is increasing. Second, groundwater level data in nearby area are available since these are monitored by Water Management Information System (WAMIS). Third, many groundwater pumping stations have been developed in this area in order to overcome droughts thus detail information for pumping stations are available. Regression results indicate groundwater level has been decreased for over 20 years. This decreasing trend is due to the shortage of surface irrigation water which was caused by the decrease in rainfall.