• The Transactions of the Korean Institute of Power Electronics
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• v.27 no.5
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• pp.402-409
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• 2022

In vector-controlled drive systems, the current measurement offset error causes unwanted torque ripple, resulting in speed and torque control performance degradation. The current measurement offset error is caused by various factors, including thermal drift. This study proposes a simple DC offset error compensation method for a surface permanent magnet motor based on a disturbance observer. The disturbance observer is designed in the stationary reference frame. The proposed method uses only the measured current and machine parameters without additional hardware. The effect of parameter variations is analyzed, and the performance of the current measurement offset error compensation method is validated using simulation and experimental results.

• Transactions of Materials Processing
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• v.24 no.1
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• pp.28-36
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• 2015

After a short review of the iterative optimal blank method, a new method of measuring the shape error for stamped parts with 3D contour lines, which is an essential component of the optimal blank design, is proposed. When the contour line of the target shape does not exist in a plane, but exists in 3D space, especially when the shape of the target contour line is very complicated as in the real automotive parts, then the measurement of the shape error is critical. In the current study, a method of shape error measurement based on the minimum distance is suggested as an evolution of the radius vector method. With the proposed method, the optimal blank shapes of real automotive parts were found and compared to the results of the radius vector method. From the current investigation the new method is found to resolve the issues with the radius vector method.

• Communications for Statistical Applications and Methods
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• v.2 no.1
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• pp.1-12
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• 1995

An estimator of coefficients of polynomial measurement error model with vector predictor and first-order interaction terms is derived using Hermite polynomial. Asymptotic normality of estimator is provided and some simulation study is performed to compare the small sample properties of derived estimator with those of OLS estimator.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.3
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• pp.1685-1690
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• 2014

This paper proposes a novel method to compensate for the measurement errors in detecting phase currents for vector-controlled inverter in real-time. The output torque equations for 3-phase induction motor are derived in terms of offset error and transducing gain error in current measurement circuits, and the equations shows that motor output torque has many ripples due to current measurement errors. Especially, if the proposed method is applied to vector-controlled inverter, the torque ripple by transducing gain error can be reduced in real-time at running state of motor. To verify the proposed method, it was applied to vector-controlled inverter for 3-phase induction motor of 200[W] and computer simulation and experimentation were carried out.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.7
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• pp.1204-1210
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• 2016

The phase currents must be accurately measured to achieve the instantaneous torque control of AC motors. In general, those are measured using the current sensors. However, the measured current signals can include the offset errors and scaling errors by several components such as current sensors, analog amplifiers, noise filter circuits, and analog-to-digital converters. Therefore, the torque-controlled performance can be deteriorated by the current measurement errors. In this paper we have analyzed the influence caused by vector control of 2-phase induction motor when two errors are included in measured phase currents. Based on analyzed results, the compensation method is proposed without additional hardware. The proposed compensation method was applied vector-controlled inverter for 2-phase induction motor of 360[W] class and verified through computer simulations and experiments.

• Journal of the Korean Data and Information Science Society
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• v.26 no.1
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• pp.209-216
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• 2015

Quantile regression models with covariate measurement errors have received a great deal of attention in both the theoretical and the applied statistical literature. A lot of effort has been devoted to develop effective estimation methods for such quantile regression models. In this paper we propose the partially linear support vector orthogonal quantile regression model in the presence of covariate measurement errors. We also provide a generalized approximate cross-validation method for choosing the hyperparameters and the ratios of the error variances which affect the performance of the proposed model. The proposed model is evaluated through simulations.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.9
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• pp.4418-4437
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• 2017

In this paper a three-phase secure compressive sensing (CS) and received signal strength (RSS) based target localization approach is proposed to mitigate the effect of malicious node attack. RSS measurements are first arranged into a group of subsets where the same measurement can be included in multiple subsets. Intermediate target position estimates are then produced using individual subsets of RSS measurements and the CS technique. From the intermediate position estimates, the residual error vector and residual error square vector are formed. The least median of residual error square is utilized to define a verifier parameter. The selected residual error vector is utilized along with a threshold to determine whether a node or measurement is under attack. The final target positions are estimated by using only the attack-free measurements and the CS technique. Further, theoretical analysis is performed for parameter selection and computational complexity evaluation. Extensive simulation studies are carried out to demonstrate the advantage of the proposed CS-based secure localization approach over the existing algorithms.

• Communications for Statistical Applications and Methods
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• v.19 no.4
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• pp.517-526
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• 2012

In this paper a support vector method is proposed for use when the sample observations are contaminated by a normally distributed measurement error. The performance of deconvolution density estimators based on the support vector method is explored and compared with kernel density estimators by means of a simulation study. An interesting result was that for the estimation of kurtotic density, the support vector deconvolution estimator with a Gaussian kernel showed a better performance than the classical deconvolution kernel estimator.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.2
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• pp.10-19
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• 1996

This paper presents a finger-shaped multisensor system which can measure the tyep and position of a target surface by contactl. The multi-sensor system consists of a sphere-shpaed optical tactile sensor located at the finger tip and a force/torque sensor located at the joint of a finger. The optial tactile sensor determines the type and position of the target surface using the shape and position of the CCD image of the touching area generated by a contact between the sensor and the taget surface. The force/torque sensor also determines the position and surface normal vector by applying the distributionof forces and torques t the contact point to the equations of finger shape. The measurements on the position and surface normal vector at a contact point obtined by two individual sensors are fused using a statistical method. The integrated sensor system has 0.8mm error in position measurement and 1.31$^{\circ}$ error in normal vector measurement. The developed sensor system has many applications, such as autonomous compliance control, automatic grasping and recognition, etc.

• Transactions of the Korean Society of Pressure Vessels and Piping
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• v.19 no.2
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• pp.146-154
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• 2023

In nuclear power plants, ultrasonic test for pipe wall thickness measurement is used during periodic inspections to prevent pipe rupture due to pipe wall thinning. However, when measuring pipe wall thickness using ultrasonic test, a significant amount of measurement error occurs due to the on-site conditions of the nuclear power plant. If the maximum pipe wall thinning rate is decided by the measured pipe wall thickness containing a significant error, the pipe wall thinning rate data have significant uncertainty and systematic overestimation. This study proposes preprocessing of pipe wall thinning measurement data using support vector machine regression algorithm. By using support vector machine, pipe wall thinning measurement data can be smoothened and accordingly uncertainty and systematic overestimation of the estimated pipe wall thinning rate data can be reduced.