• Journal of the Korea institute for structural maintenance and inspection
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• v.24 no.6
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• pp.161-170
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• 2020

In this study, develop the seismic acceleration measurement data conversion and signal processing algorithms for improve the operational efficiency of the seismic acceleration measurement system installed for public facilities. Through the analysis of the seismic acceleration time history data, the evaluation methods and criteria and evaluating the safety of buildings were proposed. The system was applied to the test bed building to verify its operation and usability. It is expected to be used as a decision making support data and determining the direction and priority of disaster response in the event of an earthquake.

• 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 the Korean Society for Aeronautical & Space Sciences
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• v.46 no.9
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• pp.742-751
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• 2018

In this paper, we propose a time varying biased proportional navigation guidance law that controls the impact angle under Field-of-View(FOV) and the acceleration limit of the missile. The proposed law is composed of three stages in consideration of the FOV limitation. Since the bias directly affects the acceleration at each stage, the final bias value of the previous stage becomes the initial bias value of the next stage when the stage is switched. In addition, the impact angles were controlled by judging whether impact angles were reached in consideration of engagement conditions and physical constraints.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.1
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• pp.23-29
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• 2016

This paper presents balancing control of a two-wheel mobile robot (TWMR). TWMR is aimed to maintain balance while moving. Although TWMR can be controlled by linear controllers such as PD controller, time-delayed controller is employed for robustness. Performances of PD controllers and time-delayed controllers are compared. Especially, experimental studies on different acceleration estimation for the time-delayed controller are conducted. Performances by different acceleration estimations of the balancing angle, of the position, and of both angle and position are compared empirically.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.2
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• pp.148-154
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• 2009

In this paper, an embedded Kalman filter for a time-delayed controller is designed on an FPGA to estimate accelerations of the robot arm. When the time-delayed controller is used as a controller, the inertia estimation along with accelerations is needed to form the control law. Although the time-delayed controller is known to be robust to cancel out uncertainties in the nonlinear systems, performances are very much dependent upon estimating the acceleration term ${\ddot{q}}(t-{\lambda})$ along with inertia estimation ${\hat{D}}(t-{\lambda})$. Estimating accelerations using the finite difference method is quite simple, but the accuracy of estimation is poor specially when the robot moves slowly. To estimate accelerations more accurately, various filters such as the least square fit filter and the Kalman filter are introduced and implemented on an FPGA chip. Experimental studies of following the desired trajectory are conducted to show the performance of the controller. Performances of different filters are investigated experimentally and compared.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.1
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• pp.29-36
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• 2017

In this paper, we propose a method for recognizing eating behavior with almost no motion acceleration. First, by using the acceleration of gravity acting on the wrist direction, we calculate the angle between the gravity and the wrist direction. After that, detect wrist reciprocating motion when peak and vally exist in specific angle band. And then, when accumulate the number of wrist reciprocating motion occurrences are up to 10, then regard as the meal time 5 minutes before the detection time. Also, estimate the meal time only if its duration is more than 7 minutes. Using the data of 2128 minutes, which was collected from four graduate student, the result of the meal time estimation shows 95.63% accuracy.

• Korean Journal of Applied Biomechanics
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• v.28 no.2
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• pp.79-85
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• 2018

Objective: This study aimed to create a strategic training method to enhance optimal athletic ability using information from 1H to 10H rhythmic units. Method: Top three world class athletes and three national winners of 110-m hurdle finals from the 2010 Daegu International Athletics Competition and 2017 National Athletics Championship, respectively, were selected. To analyze the kinematic variables, Dartfish 9.0 was used for two-dimensional analysis. Results: Regarding the interval time from the start to the finish line, the national athletes took less time during the pure acceleration phase (start to 1H) than the foreign athletes. The horizontal velocity increase was slower after 1H; the national athletes showed a lack of ability to accelerate at the interval phases. Moreover, the hurdle clearance time between phases was longer in the national athletes than in the foreign athletes and lacked consistency. Conclusion: The national athletes lacked the ability to accelerate at the transition, maximum rhythm, rhythm maintenance, and re-acceleration phases and showed a longer hurdle clearance time. If technical improvements and strategic training methods using rhythmic units are applied for hurdling motions, the national athlete's hurdling abilities, performance, and consistency could improve.

• Nuclear Engineering and Technology
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• v.55 no.7
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• pp.2642-2649
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• 2023

A real-time unmeasured dynamic response prediction process for the nuclear power plant pressure pipeline is proposed and its performance is tested in the test-loop system (KAERI). The aim of the process is to predict unmeasurable or unreachable dynamic responses such as acceleration, velocity, and displacement by using a limited amount of directly measured physical responses. It is achieved by combining a well-constructed finite element model and robust inverse force identification algorithm. The pressure pipeline system is described by using the displacement-pressure vibro-acoustic formulation to consider fully filled liquid effect inside the pipeline structure. A robust multiphysics modal projection technique is employed for the real-time sensor synchronized prediction. The inverse force identification method is also derived and employed by using Bathe's time integration method to identify the full-field responses of the target system from the modal domain computation. To validate the performance of the proposed process, an experimental test is extensively performed on the nuclear power plant pressure pipeline test-loop under operation conditions. The results show that the proposed identification process could well estimate the unmeasured acceleration in both frequency and time domain faster than 32,768 samples per sec.

• Smart Structures and Systems
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• v.16 no.2
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• pp.295-328
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• 2015

In recent years the monitoring of structural behavior through acquisition of vibrational data has become common practice. In addition, recent advances in sensor development have made the collection of diverse dynamic information feasible. Other than the commonly collected acceleration information, Global Position System (GPS) receivers and non-contact, optical techniques have also allowed for the synchronous collection of highly accurate displacement data. The fusion of this heterogeneous information is crucial for the successful monitoring and control of structural systems especially when aiming at real-time estimation. This task is not a straightforward one as measurements are inevitably corrupted with some percentage of noise, often leading to imprecise estimation. Quite commonly, the presence of noise in acceleration signals results in drifting estimates of displacement states, as a result of numerical integration. In this study, a new approach based on a time domain identification method, namely the Unscented Kalman Filter (UKF), is proposed for correcting the "drift effect" in displacement or rotation estimates in an online manner, i.e., on the fly as data is attained. The method relies on the introduction of artificial white noise (WN) observations into the filter equations, which is shown to achieve an online correction of the drift issue, thus yielding highly accurate motion data. The proposed approach is demonstrated for two cases; firstly, the illustrative example of a single degree of freedom linear oscillator is examined, where availability of acceleration measurements is exclusively assumed. Secondly, a field inspired implementation is presented for the torsional identification of a tall tower structure, where acceleration measurements are obtained at a high sampling rate and non-collocated GPS displacement measurements are assumed available at a lower sampling rate. A multi-rate Kalman Filter is incorporated into the analysis in order to successfully fuse data sampled at different rates.

• Journal of the Earthquake Engineering Society of Korea
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• v.3 no.4
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• pp.47-60
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• 1999

The stability and efficiency of structural control systems depend on the accuracy of mathematical model of the system to be controlled. In this study, state equation models of a small scale test structure and an AMD(active mass damper) are obtained separately using OKID(observer/Kalman filter identification) which is a time domain system identification method. The test structure with each floor acceleration as outputs is identified for two inputs - the ground acceleration and the acceleration of the moving mass of AMD relative to the installation floor - individually and the two identified state equation models are integrated into one by model reduction method. The AMD is identified with the motor control signal as an input and the relative acceleration of the moving mass as an output, and it is shown that the identified model has large damping ratio and phase shift. The transfer functions and the time histories reconstructed from the identified models of the test model and the AMD match well with those measured from the experiment.