• International Journal of Advanced Culture Technology
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• v.5 no.2
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• pp.63-73
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• 2017

In this paper, we propose algorithm for determining the static and dynamic posture using the acceleration sensor of smartphone. The measured acceleration values are then analyzed according to a preprocessing to the respective axis (X, Y, Z) and posture (standing, sitting, lying) presents static posture determination criterion. The proposed static posture determination condition is used for static posture determination and dynamic posture determination. The dynamic posture is determined by using regression linear equations. In addition, transition state can be grasped by SVM change in dynamic posture determination. Experimental results are presented using data and app. Experiments were performed using data collected from 10 adults.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10b
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• pp.306-311
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• 1992

We propose software algorithms which provide the characteristics of acceleration/deceleration essential to high dynamic performance at the transient state where industrial robots or CNC machine tools start and stop. The path error, which is one of the most significant factors in performance evaluation of industrial robots and CNC machine tools, is analyzed for linear, exponential, and parabolic acceleration/deceleration algorithms in case of circular interpolation. The analysis shows that the path error depends on the acceleration/deceleration routine and the servo control system. In experiments, the entire control algorithm including the proposed acceleration/deceleration algorithms is executed on the motion control system with a floating point digital signal processor(DSP) TMS320C30 as a CPU. The experimental results demonstrate that the proposed algorithms are very effective in controlling axes of motion of industrial robots or CNC machine tools with the desired characteristics.

• Journal of Power Electronics
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• v.12 no.2
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• pp.294-304
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• 2012

This paper proposes a fuzzy speed tracking controller and a fuzzy rotor angular acceleration observer for a surface-mounted permanent magnet synchronous motor (SPMSM) based on the Takagi-Sugeno (T-S) fuzzy model. The proposed observer-based controller is robust to load torque variations since it utilizes rotor angular acceleration information instead of the load torque value. Linear matrix inequality (LMI) sufficient conditions are given to compute the gain matrices of the speed tracking controller and the observer. In addition, it is mathematically verified that the proposed observer-based control system is asymptotically stable. Simulation and experimental results are presented to confirm that the proposed control algorithm assures a better transient behavior and less sensitivity under model parameter variations than the conventional PI control method.

• Journal of Industrial Technology
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• v.20 no.B
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• pp.189-194
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• 2000

In this paper, we present a BLDC Motor control for needle positioning and velocity control in the industrial sewing machine. In the industrial sewing machine, the fast acceleration control is needed, especially for a person who has a skill in operation of sewing machine for more products. And it is also needed to have a less noise and vibration. But the system which is made in a low price has no feedback system for a current control. Therefore we propose the method of velocity pattern that has an acceleration of velocity and Anti-windup algorithm. By the experiment, we confirmed that these manner have a good performance for low noise, low vibration and fast acceleration in the industrial sewing machine.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.20 no.3
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• pp.229-237
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• 2007

In this study, an artificial neural network (ANN)-based damage detection algorithm using acceleration signals is developed for real-time alarming locations of damage in beam-type structures. A new ANN-algorithm using output-only acceleration responses is designed tot damage detection in real time. The cross-covariance of two acceleration-signals measured at two different locations is selected as the feature representing the structural condition. Neural networks are trained lot potential loading Patterns and damage scenarios of the target structure for which its actual loadings are unknown. The feasibility and practicality of the proposed method are evaluated from laboratory-model tests on free-free beams for which accelerations were measured before and after several damage cases.

• Journal of the Korean Geosynthetics Society
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• v.19 no.1
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• pp.45-53
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• 2020

There is an increasing tendency to try to make predictive analysis using measurement data based on machine learning techniques in the railway industries. In this paper, it was predicted that Track quality index (TQI) using vehicle acceleration data based on the machine learning method. The XGB (XGBoost) was the most accurate with 85% in the all data sets. Unlike the SVM model with a single algorithm, the RF and XGB model with a ensemble system were considered to be good at the prediction performance. In the case of the Surface TQI, it is shown that the acceleration of the z axis is highly related to the vertical direction and is in good agreement with the previous studies. Therefore, it is appropriate to apply the model with the ensemble algorithm to predict the track quality index using the vehicle vibration acceleration data because the accuracy may vary depending on the applied model in the machine learning methods.

• Journal of the Korea institute for structural maintenance and inspection
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• v.24 no.5
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• pp.150-157
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• 2020

In this study, an algorithm was developed to validate the seismic acceleration measurement data of the seismic acceleration measurement system using measurement data from public buildings currently in operation. Through the results of the study, an algorithm was developed to detect errors and abnormalities in the measurement data itself and the process of generating real-time data (MMA/sec) and event measurement data (MiniSEED), which are the main data generated by the system, and the basic data for determining the direction of inspection through measurement data analysis. It is expected that this will be used as a guideline to determine whether or not the seismic acceleration measurement system, which was managed as receiving/not receiving, is inspected and abnormal types of conditions.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.327-332
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• 2006

In airborne gravimetry, there are two data streams. One is the specific force measured by an air/sea gravimeter or accelerometers, the other is kinematic acceleration measured by DGPS. And the difference of them provides the gravity disturbance information. To satisfy the requirement of most applications, an accuracy of 1mGal $(1mCal=10^{-5}m/s^{2})$ with a spatial resolution of 1km is the aim of current airborne gravimetry. There are two different methods to derive the kinematic acceleration. The generally used method is to differentiate the position twice, and the position can be calculated by commercial DGPS software. The main defect of this method is that integer ambiguities need to be fixed to get the precise position solution, but it's not a trivial thing for long base line. And to fix integer ambiguities, the noisier iono-free measurement is used. When differentiation is applied, noise is amplified and will influence the accuracy of acceleration. The other method is to get carrier phase acceleration by differentiate the carrier phase first, and then using the acceleration of GPS satellite to derive the vehicle acceleration. The main advantages include that fixing integer ambiguities is not needed anymore, position can be relaxed to about 10 meters, and smoother acceleration can be got since iono-free measurement is not needed. In some literatures, it's considered that the dynamic performance of the second method is inferior to that of the first. Through analysis, it is found that the performance degradation in dynamic environment results from the simplification of the GPS carrier phase observable model. And an iterative algorithm is presented to compensate the model error. Using a dynamic GPS data from an aeromagnetic survey, the importance of this compensation is showed at last.

• Journal of Electrical Engineering and Technology
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• v.9 no.1
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• pp.15-26
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• 2014

This paper proposes a Modified Particle Swarm Optimization with Time Varying Acceleration Coefficients (MPSO-TVAC) for solving economic load dispatch (ELD) problem. Due to prohibited operating zones (POZ) and ramp rate limits of the practical generators, the ELD problems become nonlinear and nonconvex optimization problem. Furthermore, the ELD problem may be more complicated if transmission losses are considered. Particle swarm optimization (PSO) is one of the famous heuristic methods for solving nonconvex problems. However, this method may suffer to trap at local minima especially for multimodal problem. To improve the solution quality and robustness of PSO algorithm, a new best neighbour particle called 'rbest' is proposed. The rbest provides extra information for each particle that is randomly selected from other best particles in order to diversify the movement of particle and avoid premature convergence. The effectiveness of MPSO-TVAC algorithm is tested on different power systems with POZ, ramp-rate limits and transmission loss constraints. To validate the performances of the proposed algorithm, comparative studies have been carried out in terms of convergence characteristic, solution quality, computation time and robustness. Simulation results found that the proposed MPSO-TVAC algorithm has good solution quality and more robust than other methods reported in previous work.

• Journal of Advanced Research in Ocean Engineering
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• v.4 no.1
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• pp.16-24
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• 2018

This paper addresses the heading control of an offshore floating storage and regasification unit (FSRU) using a resolved motion and acceleration control (RMAC) algorithm. A turret moored vessel tends to have the slewing motion. This slewing motion may cause a considerable decrease in working time in loading and unloading operation because the sloshing in the LNG containment tank might happen and/or the collision between FSRU and LNGC may take place. In order to deal with the downtime problem due to this slewing motion, a heading control system for the turret moored FSRU is developed, and a series of model tests with azimuth thrusters on the FSRU is conducted. A Kalman filter is applied to estimate the low-frequency motion of the vessel. The RMAC algorithm is employed as a primary heading control method and modified I-controller is introduced to reduce the steady-state errors of the heading of the FSRU.