• Journal of Electrical Engineering and Technology
• /
• v.13 no.2
• /
• pp.781-789
• /
• 2018

This paper proposes a new approach utilizing empirical mode decomposition (EMD) reconstruction to process vibration signals of a transformer under DC bias caused by high voltage direction transmission (HVDC), which is the potential cause of additional vibration and noise from transformer. Firstly, the Calculation Method is presented and a 3D model of transformer is simulated to analyze transformer deformation characteristic and the result indicate the main vibration is produced along axial direction of three core limbs. Vibration test system has been built and test points on the core and shell of transformer have been measured. Then, the signal reconstruction method for transformer vibration based on EMD is proposed. Through the EMD decomposition, the corrupted noise can be selectively reconstructed by the certain frequency IMFs and better vibration signals of transformer have been obtained. After EMD reconstruction, the vibrations are compared between transformer in normal work and with DC bias. When DC bias occurs, odd harmonics, vibration of core and shell, behave as a nonlinear increase and the even harmonics keep unchanged with DC current. Experiment results are provided to collaborate our theoretical analysis and to illustrate the effectiveness of the proposed EMD method.

• Journal of Aerospace System Engineering
• /
• v.7 no.1
• /
• pp.8-18
• /
• 2013

Recently, the advanced condition monitoring methods such as the model-based method and the artificial intelligent method have been applied to maximize the availability as well as to minimize the maintenance cost of the aircraft gas turbines. Among them the non-linear GPA(Gas Path Analysis) method and the GA(Genetic Algorithms) have lots of advantages to diagnose the engines compared to other advanced condition monitoring methods such as the linear GPA, fuzzy logic and neural networks. Therefore this work applies both the non-linear GPA and the GA to diagnose AE3007 turbofan engine for an aircraft, and in case of having sensor noise and bias it is confirmed that the GA is better than the GPA through the comparison of two methods.

• The Journal of Information Systems
• /
• v.24 no.2
• /
• pp.189-208
• /
• 2015

Purpose While individuals have unique abilities for planned behavior, they also often act irrationally. In this study, we draw on myopic loss aversion perspective as a meta-theoretical lens to explain why mobile applications users have inertia from updating their applications, ultimately leading them to use current version of applications. Design/methodology/approach Based on a survey of 219 users, this study conducts its research model using partial least square analysis and also demonstrates that both subconscious triggers (habit and anxiety) of system 1 thinking and conscious triggers (sunk cost and transition cost) of system 2 thinking promotes user's inertia, thus leading to the willness to continue use current versions. Findings By grounding the research model in the combination of both status quo bias and dual information processing theory from the behavioral economics, this study provide an alternative theoretical lens to describe why mobile users hesitate to update their applications. The results of this research show that all triggers have significant impacts on inertia. This study also found that the relationship between inertia and willingness to continue to use current version was positively significant.

• Journal of Korean Society for Atmospheric Environment
• /
• v.33 no.1
• /
• pp.11-18
• /
• 2017

The performance of a modeling system consisting of WRF model v3.3 and CMAQ model v4.7.1 for forecasting $PM_{2.5}$ concentrations were evaluated during the period May 2012 through December 2014. Twenty-four hour averages of $PM_{2.5}$ and its major components obtained through filter sampling at the Bulgwang intensive measurement station were used for comparison. The mean predicted $PM_{2.5}$ concentration over the entire period was 68% of the mean measured value. Predicted concentrations for major components were underestimated except for $NO_3{^-}$. The model performance for $PM_{2.5}$ generally tended to degrade with increasing the concentration level. However, the mean fractional bias (MFB) for high concentration above the $80^{th}$ percentile fell within the criteria, the level of accuracy acceptable for standard model applications. Among three bias correction methods, the ratio adjustment was generally most effective in improving the performance. Albeit for limited test conditions, this analysis demonstrated that the effects of bias correction were larger when using the data with a larger bias of predicted values from measurement values.

• International Journal of Aeronautical and Space Sciences
• /
• v.18 no.2
• /
• pp.344-351
• /
• 2017

This paper presents a method to estimate steady wind and airspeed bias error using an aircraft with GPS and airspeed sensor. The estimation uses the vector relation between the inertial, air, and wind velocities through a novel design of an extended Kalman filter. The observability analysis is also presented to show that the aircraft is required to keep changing its flight direction for the desired observability. The feasibility and performance of the proposed algorithm is demonstrated through simulations and flight experiments.

• Journal of Korean Society for Atmospheric Environment
• /
• v.17 no.5
• /
• pp.395-405
• /
• 2001

To make an assessment of the compatibility between DOAS and conventional point monitoring system (MCSAM-2: MS2), we investigated the concentrations of three criteria pollutants which include S $O_2$, N $O_2$, and $O_3$from a national monitoring station in Seoul during the periods of June 1999~August 2000. The average concentration values for the whole study period derived from hourly concentration data sets of those three species indicated that the mean differences between the two methods can be approximated as 18%. When the bias structure of two systems was evaluated through the computation of percent difference(PD) between the two such as ( $C_{DOAS}$- $C_{conventional}$ $C_{DOAS}$*100, differences between the two systems appeared to be quite systematic among different compounds. While the mode of bias peaked at 0~20% or 20~40% in terms of PD values, the cause of such positive bias mainly arised from generally enhanced concentration values of DOAS system. The structure of bias among different species was further assessed through linear regression analysis. Results of the analysis indicated that the dominant portions of differences observed from two monitoring systems can be accounted for by the systematic differences in their spanning and zeroing systems. S $O_2$(MS2)=0.6385 S $O_2$(DOAS)+2.0985($r^2$=0.7894) N $O_2$(MS2)=0.6548 N $O_2$(DOAS)+7.437($r^2$=0.7687) $O_3$(MS2)=1.0359 $O_3$(DOAS)-7.7885($r^2$=0.7944) The findings of slope values at around 0.64~0.65 from two species suggest that DOAS should respond more sensitively in upper bound concentration range. The offset values apart from zero indicate that more deliberate comparison needs to be made between these monitoring systems. However, based on the existence of strong correlations from at least 8,000 data points for each species of comparison, we were able to conclude that the compatibility of two monitoring systems is highly significant. With the improvement of calibration techniques for the DOAS system. its applicability for routine monitoring of airborne pollutant species is expected to be quite extendable.

• Transactions of The Korea Fluid Power Systems Society
• /
• v.3 no.1
• /
• pp.7-14
• /
• 2006

In this paper, an in-process diagnosis method for performance of position control servo system was studied, which was based upon null bias, slew-rate ratio and delay time measurement. Slew-rate ratio and delay time were analyzed by theoretical analysis, computer simulation and experiment. As a result of these analysis, when spool of servovalve was weared, slew-rate ratio was decreased and delay time was increased.

• 제어로봇시스템학회:학술대회논문집
• /
• 1993.10a
• /
• pp.34-39
• /
• 1993

Presented in this paper is a complete error covariance analysis for strapdown inertial navigation system(SDINS). We have found that in SDINS the cross-coupling terms in gyrocompass alignment errors can significantly influence the SDINS error propagation. Initial heading error has a close correlation with the east component of gyro bias erro, while initial level tilt errors are closely related to accelerometer bias errors. In addition, pseudo-state variables are introduced in covariance analysis for SDINS utilizing the characteristics of gyrocompass alignment errors. This approach simplifies the covariance analysis because it makes the initial error covariance matrix to a diagonal form. Thus a real implementation becomes easier. The approach is conformed by comparing the results for a simplified case with the covariance analysis obtained from the conventional SDINS error model.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.35 no.1C
• /
• pp.123-129
• /
• 2010

In this paper, we analyze the code tracking biases of single and double early-minus-late processing schemes which are widely used code tracking method for global navigation satellite systems. The code tracking bias which results from the distortion in symmetry of correlation values is arisen in the presence of multipath signals. To analyze them, two civil signals which are spreading signals modulated by binary phase shift keying and binary offset carrier are considered.

• The Korean Journal of Applied Statistics
• /
• v.22 no.5
• /
• pp.981-993
• /
• 2009

It would cause a serious problem in the panel data when panel attrition is concentrated on certain socioeconomic groups. Using the GOMS, this study investigates whether there exists non-random attrition bias in the data and seeks for feasible solutions to minimize the bias. The results of logit analyses show that panel attrition in the GOMS results mainly from surveying system but not from the surveyed. Therefore, the result suggests to develop well-organized management skill and systems as well as to construct weighting methods.