• 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.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2005.05a
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• pp.383-386
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• 2005

Low frequency heavy-weight impact noise is the most irritating noise in Korean high-rise reinforced concrete apartment buildings. This low frequency noise is generated by foot traffic due to the fact that Koreans do not wear shoes at home. The transmission of the noise is facilitated by a load bearing wall structural system without beams and columns which is used in these buildings. In order to control low frequency heavy-weight impact noise, floating floors using isolation materials such as glass-wool mat and poly-urethane mat are used. However, it was difficult to control low frequency heavy-weight impact sound using isolation material. In this study, reinforcement of concrete slab using beams and plate was conducted. Using the FEM analysis, the effect of concrete slab reinforcement using FRP(fiber-glass reinforced plastic) on the bang machine impact vibration acceleration level and sound were conducted at the standard floor impact sound test building. The $3{\sim}4dB$ floor impact vibration acceleration level and impact sound pressure level were reduced and the natural frequency of slabs were changed.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2005.11a
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• pp.551-554
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• 2005

The method of the reduction of the automotive induction noise can be classified by the method of passive control and the method of active control. However, the passive control method has a demerit to reduce the effect of noise reduction at low frequency (below 500Hz) range and to be limited by a space of the engine room. Whereas, the active control method can overcome the demerit of passive control method. The algorithm of active control is mostly used the LMS (Least-Mean-Square) algorithm because the LMS algorithm can easily obtain the complex transfer function in real-time. Especially, When the Filtered-X LMS (FXLMS) algorithm is applied to an ANC system. However, the convergence performance of LMS algorithm goes bad when the FXLMS algorithm is applied to an active control of the induction noise under rapidly accelerated driving conditions. Thus Normalized FXLMS algorithm was developed to improve the control performance under the rapid acceleration. The advantage of Normalized FXLMS algorithm is that the step size is no longer constant. Instead, it varies with time. But there is one additional practical difficulty that can arise when a nonstationary input is used. If the input is zero for consecutive samples, then the step size becomes unbounded. So, in order to solve this problem. the Correlation FXLMS algorithm was developed. The Correlation FXLMS algorithm is realized by using an estimate of the cross correlation between the adaptation error and the filtered input signal to control the step size. In this paper, the performance of the Correlation FXLMS Is presented in comparison with that of the other FXLMS algorithms based on computer simulations.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.49 no.3
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• pp.82-89
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• 2012

This paper presents the intelligent tracking algorithm for maneuvering target using the positional error compensation of the maneuvering target. The difference between measured point and predict point is separated into acceleration and noise. Fuzzy c-mean clustering and predicted impact point are used to get the optimal acceleration value. The membership function is determined for acceleration and noise which are divided by fuzzy c-means clustering and the characteristics of the maneuvering target is figured out. Divided acceleration and noise are used in the tracking algorithm to compensate computational error. The filtering process in a series of the algorithm which estimates the target value recognize the nonlinear maneuvering target as linear one because the filter recognize only remained noise by extracting acceleration from the positional error. After filtering process, we get the estimates target by compensating extracted acceleration. The proposed system improves the adaptiveness and the robustness by adjusting the parameters in the membership function of fuzzy system. To maximize the effectiveness of the proposed system, we construct the multiple model structure. Procedures of the proposed algorithm can be implemented as an on-line system. Finally, some examples are provided to show the effectiveness of the proposed algorithm.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2001.11a
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• pp.433-438
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• 2001

This study is performed to evaluate hand-arm vibration syndrome(HA VS) of the workers in swaging process. Vibration measurement and assessment of human exposure are based on the international standard(ISO 5349). Triaxial acceleration of each operation and exposure time are measured to predict the periods before finger blanching, As results, it is found that acceleration is concerned with the diameter of pipes in swaging process, and also found that combined work is more harmful than a single operation.

• Smart Structures and Systems
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• v.3 no.3
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• pp.245-261
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• 2007

Nonlinear time-domain system identification (SI) algorithm is proposed to assess damage in a shear building by synchronously estimating time-varying stiffness and damping parameters using measured acceleration data. Mass properties have been assumed as the a priori known information. Viscous damping was utilized for the current research. To chase possible nonlinear dynamic behavior under severe vibration, an incremental governing equation of vibrational motion has been utilized. Stiffness and damping parameters are estimated at each time step by minimizing the response error between measured and computed acceleration increments at the measured degrees-of-freedom. To solve a nonlinear constrained optimization problem for optimal structural parameters, sensitivities of acceleration increment were formulated with respect to stiffness and damping parameters, respectively. Incremental state vectors of vibrational motion were computed numerically by Newmark-${\beta}$ method. No model is pre-defined in the proposed algorithm for recovering the nonlinear response. A time-window scheme together with Monte Carlo iterations was utilized to estimate parameters with noise polluted sparse measured acceleration. A moving average scheme was applied to estimate the time-varying trend of structural parameters in all the examples. To examine the proposed SI algorithm, simulation studies were carried out intensively with sample shear buildings under earthquake excitations. In addition, the algorithm was applied to assess damage with laboratory test data obtained from free vibration on a three-story shear building model.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.23 no.3
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• pp.258-266
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• 2013

This paper presents the correlation between psychological and physiological acoustics for the automotive acceleration sound. The research purpose of this paper is to evaluate the sound quality of acceleration sound of a passenger car based EEG signal. The previous method for the objective evaluation of sound quality is to use sound metrics based on psychological acoustics. This method uses not only psychological acoustics but also physiological acoustics. For this work, the sounds of 7 premium passenger cars are recorded and evaluated subjectively by 33 people. The correlation between the subjective rating and sound metrics is calculated based on physiological acoustics. Finally the correlation between the subjective rating and the EEG signal measured on the brain is also calculated. Throughout these results the new evaluation system for the sound quality on the automotive acceleration sound of a passenger car has been developed based on bio-signal.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.24 no.6
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• pp.483-492
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• 2014

Uncomfortable feelings of occupants by indoor floor impact noise in a residential building are not accurately represented by the floor impact noise from a standard impact source. It is due to the characteristics of standard impact sources, which are different from the impact forces produced by occupants. It varies significantly by impact source, and it is not easy to be replicated for testing. As a result, the indoor floor impact noise under different acoustic conditions cannot be directly compared. Using frequency response function(FRF), which represents the input-output relationships of a dynamic system, it is possible to examine the characteristics of the system. Especially, FRF can predict the response of a linear dynamic system subjected to various excitation. To determine the relationship between impact force and the corresponding response of dynamic system in residential building, the acceleration response of a concrete slab and the floor impact noise in the living room, produced by bang-machine and rubber-ball excitation, were measured. The test results are compared to the estimates based on FRF and impact force spectrum.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2004.11a
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• pp.103-108
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• 2004

In this study, examined heavy-weight floor impact sound to structure that have slab thickness of 4 form at a standard laboratory through noise and vibration measured. The results show that the nature Natural frequency increased according to change of thickness of each slab by finite element analysis, and acceleration value decreased. Results of measurements of noise and vibration at a standard laboratory, the slab 210, 240mm structures was construed result such as finite element analysis but the slab 150, 180mm structures is construed that influence in vibration acceleration level because edge condition has condition that contact to ground. Therefore, in modelling process for analysis, is thought that need that condition analyzes examining element influencing about structure that contact to ground.

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 2003.03a
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• pp.238-246
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• 2003

By using simulated ground motions, which is sum of earthquake signals and noise, we measured the distortion of response spectra due to noise. We found that the distortion is more closely related to the signal-to-noise (S/N) ratio of root-mean-square (RMS) measurement than that of conventional peak measurement. Given a S/M ratio, the distortion of absolute acceleration response spectra is independent on the earthquake magnitude, while that of relative displacement response spectra has a strong dependence on the earthquake magnitude. This means that, when we calculate response spectra from time histories, we can efficiently predict the distortion of acceleration response spectra simply by measuring the RMS SJN ratios, or the distortion of displacement response spectra by combining the RMS S/N ratios and the earthquake magnitudes.