• Transactions of the Korean Society of Automotive Engineers
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• v.23 no.1
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• pp.112-121
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• 2015

In this paper, powertrain of output split type plug-in hybrid electric vehicle is analyzed for the operation range of speed, torque, and power. First, it is assumed that the efficiency of motor is 100%. And, the speed and torque equations are derived based on the lever analogy. With the above equations, the simulations are performed for the powertrain of output split type plug-in hybrid electric vehicle. From the simulation results, it is found that the output torques of EV1 and series modes are larger than the EV2 and power split modes' ones. It means the EV1 and series modes can be used for the rapid acceleration. But the EV1 and series modes can be used only the velocity of under the 120 km/h. It is because the motor reaches its maximum speed when the velocity is over the 120 km/h for the EV1 and series modes. When the engine is turned on, the engine power is transmitted through the two motors. But, the power split mode shows the power split of engine at the output shaft, and it has the point of zero motor power. Thus, the transmission efficiency of the power split mode can be higher than the series mode's one, it the motor efficiency is considered.

• Journal of the Society of Naval Architects of Korea
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• v.45 no.5
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• pp.469-476
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• 2008

In this paper, it is shown that an input-output (I/O) feedback linearized controller can be designed rationally by utilizing the time-scale properties of heave and pitch for an underwater vehicle. It is assumed that the dynamics of the vehicle is restricted to the vertical plane. An output-feedback control is designed, which stabilizes steady cruising paths. It is shown that the vehicle dynamics with acceleration as output becomes minimum phase. The dynamics can be transformed into a reduced system through a kind of partial linearization and singular perturbation technique. The reduced system is not only minimum phase but also exactly I/O linearizable via feedback. The I/O dynamic characteristics of the heave and pitch modes can be made linear and decoupled. Furthermore it becomes independent of cruising condition such as vehicle velocity. This study may help for designing autopilot systems for underwater vehicles.

• Smart Structures and Systems
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• v.32 no.5
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• pp.281-295
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• 2023

The purpose of this study is to demonstrate and verify the application of phase-control absolute-acceleration-feedback active tuned mass dampers (PCA-ATMD) to multiple-degree-of-freedom (MDOF) building structures. In addition, servo speed control technique has been developed as a replacement for force control in order to mitigate the negative effects caused by friction and inertia. The essence of the proposed PCA-ATMD is to achieve a 90° phase lag for a structure by implementing the desired control force so that the PCA-ATMD can receive the maximum power flow with which to effectively mitigate the structural vibration. An MDOF building structure with a PCA-ATMD and a real-time filter forming a complete system is modeled using a state-space representation and is presented in detail. The feedback measurement for the phase control algorithm of the MDOF structure is compact, with only the absolute acceleration of one structural floor and ATMD's velocity relative to the structure required. A discrete-time direct output-feedback optimization method is introduced to the PCA-ATMD to ensure that the control system is optimized and stable. Numerical simulation and shaking table experiments are conducted on a three-story steel shear building structure to verify the performance of the PCA-ATMD. The results indicate that the absolute acceleration of the structure is well suppressed whether considering peak or root-mean-square responses. The experiment also demonstrates that the control of the PCA-ATMD can be decentralized, so that it is convenient to apply and maintain to real high-rise building structures.

• Smart Structures and Systems
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• v.14 no.2
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• pp.191-207
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• 2014

In this research, an internal model based method is proposed to estimate the structural displacements and velocities under ambient excitation using only acceleration measurements. The structural response is assumed to be within the linear range. The excitation is assumed to be with zero mean and relatively broad bandwidth such that at least one of the fundamental modes of the structure is excited and dominates in the response. Using the structural modal parameters and partial knowledge of the bandwidth of the excitation, the internal models of the structure and the excitation can be respectively established, which can be used to form an autonomous state-space representation of the system. It is shown that structural displacements, velocities, and accelerations are the states of such a system, and it is fully observable when the measured output contains structural accelerations only. Reliable estimates of structural displacements and velocities are obtained using the standard Kalman filtering technique. The effectiveness and robustness of the proposed method has been demonstrated and evaluated via numerical simulations on an eight-story lumped mass model and experimental data of a three-story frame excited by the ground accelerations of actual earthquake records.

• Smart Structures and Systems
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• v.10 no.4_5
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• pp.375-391
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• 2012

This paper reports the structural health monitoring benchmark study results for the Canton Tower using Bayesian methods. In this study, output-only modal identification and finite element model updating are considered using a given set of structural acceleration measurements and the corresponding ambient conditions of 24 hours. In the first stage, the Bayesian spectral density approach is used for output-only modal identification with the acceleration time histories as the excitation to the tower is unknown. The modal parameters and the associated uncertainty can be estimated through Bayesian inference. Uncertainty quantification is important for determination of statistically significant change of the modal parameters and for weighting assignment in the subsequent stage of model updating. In the second stage, a Bayesian model updating approach is utilized to update the finite element model of the tower. The uncertain stiffness parameters can be obtained by minimizing an objective function that is a weighted sum of the square of the differences (residuals) between the identified modal parameters and the corresponding values of the model. The weightings distinguish the contribution of different residuals with different uncertain levels. They are obtained using the Bayesian spectral density approach in the first stage. Again, uncertainty of the stiffness parameters can be quantified with Bayesian inference. Finally, this Bayesian framework is applied to the 24-hour field measurements to investigate the variation of the modal and stiffness parameters under changing ambient conditions. Results show that the Bayesian framework successfully achieves the goal of the first task of this benchmark study.

• Journal of Sensor Science and Technology
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• v.13 no.2
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• pp.101-109
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• 2004

This paper presents a novel z-axis accelerometer with perfectly aligned vertical combs fabricated using the extended sacrificial bulk micromachining (extended SBM) process. The z-axis accelerometer is fabricated using only one (111) SOI wafer and two photo masks without wafer bonding or CMP processes as used by other research efforts that involve vertical combs. In our process, there is no misalignment in lateral gap between the upper and lower comb electrodes, because all critical dimensions including lateral gaps are defined using only one mask. The fabricated accelerometer has the structure thickness of $30{\mu}m$, the vertical offset of $12{\mu}m$, and lateral gap between electrodes of $4{\mu}m$. Torsional springs and asymmetric proof mass produce a vertical displacement when an external z-axis acceleration is applied, and capacitance change due to the vertical displacement of the comb is detected by charge-to-voltage converter. The signal-to-noise ratio of the modulated and demodulated output signal is 80 dB and 76.5 dB, respectively. The noise equivalent input acceleration resolution of the modulated and demodulated output signal is calculated to be $500{\mu}g$ and $748{\mu}g$. The scale factor and linearity of the accelerometer are measured to be 1.1 mV/g and 1.18% FSO, respectively.

• Smart Structures and Systems
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• v.15 no.2
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• pp.447-468
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• 2015

Modal identification of civil engineering structures based on ambient vibration measurement has been widely investigated in the past decades, and a variety of output-only operational modal identification methods have been proposed. However, vibration modes, even fundamental low-order modes, are not always identifiable for large-scale structures under ambient vibration excitation. The identifiability of vibration modes, deficiency in modal identification, and criteria to evaluate robustness of the identified modes when applying output-only modal identification techniques to ambient vibration responses were scarcely studied. In this study, the mode identifiability of the cable-stayed Ting Kau Bridge using ambient vibration measurements and the influence of the excitation intensity on the deficiency and robustness in modal identification are investigated with long-term monitoring data of acceleration responses acquired from the bridge under different excitation conditions. It is observed that a few low-order modes, including the second global mode, are not identifiable by common output-only modal identification algorithms under normal ambient excitations due to traffic and monsoon. The deficient modes can be activated and identified only when the excitation intensity attains a certain level (e.g., during strong typhoons). The reason why a few low-order modes fail to be reliably identified under weak ambient vibration excitations and the relation between the mode identifiability and the excitation intensity are addressed through comparing the frequency-domain responses under normal ambient vibration excitations and under typhoon excitations and analyzing the wind speeds corresponding to different response data samples used in modal identification. The threshold value of wind speed (generalized excitation intensity) that makes the deficient modes identifiable is determined.

• 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 Society for Aeronautical & Space Sciences
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• v.45 no.2
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• pp.106-113
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• 2017

Attitude determination algorithms for aircraft and land vehicles use earth gravitational vector and geomagnetic vector; hence, magnetometers and accelerometers are employed. In dynamic situation, the output from accelerometers includes not only gravitational vector but also motional acceleration, thus it is hard to determine accurate attitude. The acceleration compensation method treated in this paper solves the problem to compensate the specific force vector for motional acceleration calculated by a GPS receiver. This paper analyzed the error from the corrected vector regarded as a constant by conventional acceleration compensation method, and improve the error by rederivation from measurements. The analyzed error factors and improvements by the proposed algorithm are verified by computer simulations.

• Proceedings of the KSR Conference
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• 2011.05a
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• pp.427-434
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• 2011

This paper is focused on application of recursive least squares method to estimate rail irregularities from the acceleration measurement on an axle-box or a bogie for the rail condition monitoring with in-service high-speed trains. Generally, the rail condition was monitored by a special railway inspection vehicle but the monitoring method needs an expensive measurement system. A monitoring method using accelerometers on an axle-box or a bogie was already proposed in the previous study, and the displacement was successfully estimated from the acceleration data by using Kalman and frequency selective band-pass filters. However, it was found that the displacement included not only the rail irregularities but also phase delay of the applied filters, and effect of suspension of the bogie and conicity of the wheel. To identify the rail irregularities from the estimated displacement, a compensation filter method is proposed. The compensation filters are derived by using recursive least squares method with the estimated displacement as input and the measured rail irregularity as output. The estimated rail irregularities are compared with the true rail irregularity data from the rail inspection system. From the comparison, the proposed method is a useful tool for the measurement of lateral and vertical rail irregularity.