• KSCE Journal of Civil and Environmental Engineering Research
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• v.34 no.3
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• pp.729-737
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• 2014

A study has been carried out that effectively controls the vibration of asymmetric cable-stayed bridges caused by earthquakes with MR dampers. In order to enhance the practical serviceability of MR dampers, an asymmetric cable-stayed bridge structure has been designed and produced, and a MR damper has been produced so as to have this bridge structure controlled appropriately. An experiment that controls vertical and horizontal vibrations has been carried out by exciting the asymmetric cable-stayed bridge in the horizontal direction with the El-centro seismic wave. The control performance of the MR damper has been evaluated under the five control conditions in the experiments of vibration control in each direction. As a result of the experiment, MR dampers were proved to control vibrations more effectively when either Lyapunov control algorithm or Clipped-optimal control algorithm was used to control vibrations of the asymmetric cable-stayed bridge caused by earthquakes. In addition, different controlling effects were found in vibration controls in vertical and horizontal directions due to the asymmetry of the structure and the horizontal excitation. With such controlling effects, semi-active MR dampers are evaluated to effectively control vibrations caused by earthquakes in flexible and asymmetric structures such as asymmetric cable-stayed bridges.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.46 no.5
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• pp.8-14
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• 2009

In the research field of speech recognition, pinpointing the endpoints of speech utterance even with the presence of background noise is of great importance. These noise present during recording introduce disturbances which complicates matters since what we just want is to get the stationary parameters corresponding to each speech section. One major cause of error in automatic recognition of isolated words is the inaccurate detection of the beginning and end boundaries of the test and reference templates, thus the necessity to find an effective method in removing the unnecessary regions of a speech signal. The conventional methods for speech endpoint detection are based on two linear time-domain measurements: the short-time energy, and short-time zero-crossing rate. They perform well for clean speech but their precision is not guaranteed if there is noise present, since the high energy and zero-crossing rate of the noise is mistaken as a part of the speech uttered. This paper proposes a novel approach in finding an apparent threshold between noise and speech based on Lyapunov Exponents (LEs). This proposed method adopts the nonlinear features to analyze the chaos characteristics of the speech signal instead of depending on the unreliable factor-energy. The excellent performance of this approach compared with the conventional methods lies in the fact that it detects the endpoints as a nonlinearity of speech signal, which we believe is an important characteristic and has been neglected by the conventional methods. The proposed method extracts the features based only on the time-domain waveform of the speech signal illustrating its low complexity. Simulations done showed the effective performance of the Proposed method in a noisy environment with an average recognition rate of up 92.85% for unspecified person.