• Smart Structures and Systems
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• v.15 no.2
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• pp.489-503
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• 2015

Response estimation at unmeasured locations using the limited number of measurements is an attractive topic in the field of structural health monitoring (SHM). Because of increasing complexity and size of civil engineering structures, measuring all structural responses from the entire body is intractable for the SHM purpose; the response estimation can be an effective and practical alternative. This paper investigates a response estimation technique based on the Kalman state estimator to combine multi-sensor data under non-zero mean input excitations. The Kalman state estimator, constructed based on the finite element (FE) model of a structure, can efficiently fuse different types of data of acceleration, strain, and tilt responses, minimizing the intrinsic measurement noise. This study focuses on the effects of (a) FE model error and (b) combinations of multi-sensor data on the estimation accuracy in the case of non-zero mean input excitations. The FE model error is purposefully introduced for more realistic performance evaluation of the response estimation using the Kalman state estimator. In addition, four types of measurement combinations are explored in the response estimation: strain only, acceleration only, acceleration and strain, and acceleration and tilt. The performance of the response estimation approach is verified by numerical and experimental tests on a simply-supported beam, showing that it can successfully estimate strain responses at unmeasured locations with the highest performance in the combination of acceleration and tilt.

• 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.

• Wind and Structures
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• v.9 no.5
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• pp.397-412
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• 2006

This paper presents the wind excited acceleration responses of a 50 m guyed mast under the action of Typhoon Dujuan. The response of the structure is reconstructed from using a full finite element model and an equivalent beam-column model. The wind load is modelled based on the measured wind speed and recommendations for high-rise structures. The nonlinear time response analysis is conducted using the Newton Raphson iteration procedure. Comparative studies on the measured and computed frequencies and acceleration responses show that the torsional vibration of the structure is significant particularly in the higher vibration modes after the first few bending modes. The equivalent model, in general, gives less accurate amplitude predictions than the full model because of the omission of torsional stiffness of the mast in the vibration analysis, but the root-mean-square value is close to the measured value in general with an error of less than 10%.

• The Transactions of the Korean Institute of Power Electronics
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• v.18 no.6
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• pp.523-529
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• 2013

A sensorless speed control of a permanent magnet synchronous motor(PMSM) which utilizes MRAS based scheme to estimate rotor speed and position is presented. Considering an error between real and estimated rotor position values, a state equation of PMSM in the synchronous d-q reference frame is represented. A state equation of model system which uses estimated speed and nominal parameter values is expressed. To minimize the errors between the derivatives of d-q axis currents of real and model system, MRAS based adaptation mechanisms for the estimation of rotor speed and position are derived. On the other hand, for the acceleration stage of motor just before the sensorless operation, an acceleration scheme using only d-axis current control is proposed. To show the validity of the proposed scheme, experimental works are carried out and evaluated. During acceleration stage, the acceleration scheme using only d-axis current command shows good acceleration performance and controlled current level. For the sensorless operation, at low speed (5% of rated speed), a good performance is observed.

• Journal of The Korean Astronomical Society
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• v.36 no.3
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• pp.111-121
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• 2003

In order to explore the cosmic ray acceleration at the cosmological shocks, we have performed numerical simulations of one-dimensional, plane-parallel, cosmic ray (CR) modified shocks with the newly developed CRASH (Cosmic Ray Amr SHock) numerical code. Based on the hypothesis that strong Alfven waves are self-generated by streaming CRs, the Bohm diffusion model for CRs is adopted. The code includes a plasma-physics-based 'injection' model that transfers a small proportion of the thermal proton flux through the shock into low energy CRs for acceleration there. We found that, for strong accretion shocks with Mach numbers greater than 10, CRs can absorb most of shock kinetic energy and the accretion shock speed is reduced up to $20\%$, compared to pure gas dynamic shocks. Although the amount of kinetic energy passed through accretion shocks is small, since they propagate into the low density intergalactic medium, they might possibly provide acceleration sites for ultra-high energy cosmic rays of $E\ll10^{18}eV$. For internal/merger shocks with Mach numbers less than 3, however, the energy transfer to CRs is only about $10-20\%$ and so nonlinear feedback due to the CR pressure is insignificant. Considering that intracluster medium (ICM) can be shocked repeatedly, however, the CRs generated by these weak shocks could be sufficient to explain the observed non-thermal signatures from clusters of galaxies.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2007.04a
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• pp.43-48
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• 2007

In this study, an ANN-based damage detection algorithm using acceleration signals is developed for alarming locations of damage in beam-type structures. A new ANN-algorithm using output-only acceleration responses is designed for 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 for 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.

• Structural Monitoring and Maintenance
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• v.7 no.2
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• pp.149-166
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• 2020

This paper presents the results of an experimental investigation on a vibration-based damage identification framework for a steel girder type and a truss bridge based on acceleration responses to operational loading. The method relies on sensor clustering-based time-series analysis of the operational acceleration response of the bridge to the passage of a moving vehicle. The results are presented in terms of Damage Features from each sensor, which are obtained by comparing the actual acceleration response from the sensors to the predicted response from the time-series model. The damage in the bridge is detected by observing the change in damage features of the bridge as structural changes occur in the bridge. The relative severity of the damage can also be quantitatively assessed by observing the magnitude of the changes in the damage features. The experimental results show the potential usefulness of the proposed method for future applications on condition assessment of real-life bridge infrastructures.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.1039-1040
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• 2007

This paper is derived a solutions for an analytical model of an induction motor and the formula of regenerative power, based on spiral vector. The torque is controlled linearity through variations of the slip angular velocity, based on the field acceleration method (FAM). And also PWM inverter fed induction motor drives is schemed to be easily a regenerative power. The experimental tests verify the performance of the FAM, proving that good behavior of the drive is achieved in the transient and steady state operating condition. and are discussed to shave the power that regenerative power is measured at the operating acceleration or deceleration of servo system.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2002.05a
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• pp.166-169
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• 2002

The accuracy in maneuvering target tracking using multiple models is caused by the suitability of each target motion model to be used. The interacting multiple model (IMM) algorithm and the adaptive IMM algorithm require the predefined sub-models and the predetermined acceleration intervals, respectively, in consideration of the properties of maneuvers to construct multiple models. In this paper, to solve these problems intelligently, a genetic algorithm (GA) based-IMM method using fuzzy logic is proposed. In the proposed method, a sub-model is represented as a set of fuzzy rules to model the time-varying variances of the process noises of a new piecewise constant white acceleration model, and the GA is applied to identify this fuzzy model. The proposed method is compared with the AIMM algorithm in simulations.

• Structural Engineering and Mechanics
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• v.52 no.2
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• pp.275-290
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• 2014

In this paper, Simple Adaptive Control (SAC) method is used to mitigate the detrimental effects of earthquakes on MR-damper equipped structures. Acceleration Feedback (AF) is utilized since measuring the acceleration response of structures is known to be reliable and inexpensive. The SAC is simple, fast and as an adaptive control scheme, is immune against the effects of plant and environmental uncertainties. In the present study, in order to translate the desired control force into an applicable MR damper command voltage, a neural network inverse model is trained, validated and used through the simulations. The effectiveness of the proposed AF-based SAC control system is compared with optimal H2/LQG controllers through numerical investigation of a three-story model building. The results indicate that the SAC controller is substantially effective and reliable in both undamaged and damaged structural states, specifically in reducing acceleration responses of seismically excited buildings.