• Proceedings of the KSR Conference
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• 2010.06a
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• pp.330-337
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• 2010

This paper shows an algorithm for identifying track irregularities using wavelet transfer function along the railway. An equivalent SISO wavelet transfer function is defined using continuous wavelet transform by the measured track geometry and acceleration at a bogie of a train. The estimated track geometry is made by inverse continuous wavelet transform from the regressed signals of measured acceleration signal and the pre-defined wavelet transfer function. The estimated rail irregularity geometry is evaluated by the coherence function and comparison of FRF(Frequency Response Function). As a result of evaluated outcome, This algorithm is regarded as appropriate for estimation of rail irregularity.

• Journal of KSNVE
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• v.10 no.5
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• pp.769-774
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• 2000

The purpose of the work is to present successful applications of a modified wavelet shrinkage method for the accurate and fast estimation of a transfer function. Although the experimental process of determining a transfer function introduces not only Gaussian but also non-Gaussian noises, most existing estimation methods are based only on a Gaussian noise model. To overcome this limitation, we propose to employ a modified wavelet shrinkage method in which L1 -based median filtering and L2 -based wavelet shrinkage are applied repeatedly. The underlying theory behind this approach is briefly explained and the superior performance of this modified wavelet shrinkage technique is demonstrated by a numerical example.

• Journal of the Korean Society for Railway
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• v.13 no.3
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• pp.304-308
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• 2010

This paper presents a methodology for identifying track irregularity using a wavelet transfer function. An equivalent wavelet SISO (single-input single-output) transfer function is defined by the measured track geometry and the acceleration data measured at a bogie of a train. All the measured data with various sampling frequencies were rearranged according to the constant 25cm reference recording distance of the track recording vehicle used in the field. Before applying the wavelet transform, measured data were regressed by eliminating those out of the range. The inverse wavelet transfer function is also formulated to estimate track geometry. The closeness of the estimated track geometry to the actual one is evaluated by the coherence function and also by FRF (frequency response function). A track irregularity index is defined by comparing the variance of the estimation error from the intact condition and that from the current condition. A simulation study has been carried out to examine the proposed algorithm.

• Geomechanics and Engineering
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• v.7 no.2
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• pp.149-164
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• 2014

One of the most advanced classes of techniques for ground response analysis is based on the use of Transfer Functions. They represent the ratio of Fourier spectrum of amplitude motion at the free surface to the corresponding spectrum of the bedrock motion and they are applied in frequency domain usually by FFT method. However, Fourier spectrum only shows the dominant frequency in each time step and is unable to represent all frequency contents in every time step and this drawback leads to inaccurate results. In this research, this process is optimized by decomposing the input motion into different frequency sub-bands using Wavelet Multi-level Decomposition. Each component is then processed with transfer Function relating to the corresponding component frequency. Taking inverse FFT from all components, the ground motion can be recovered by summing up the results. The nonlinear behavior is approximated using an iterative procedure with nonlinear soil properties. The results of this procedure show better accuracy with respect to field observations than does the Conventional method. The proposed method can also be applied to other engineering disciplines with similar procedure.

• Journal of Communications and Networks
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• v.4 no.2
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• pp.97-101
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• 2002

Based on their shift and scale orthogonality properties, scaling and wavelet functions may be used as signaling functions having good frequency localization as determined by the fractional-out-of-band power (FOOBP). In this paper, application of Daubechies' wavelet and scaling functions as baseband signaling functions is described, with a focus on finding discretely realizable pulse-shaping transfer function circuits whose outputs approximate scaling and wavelet functions when driven by more conventional digital signaling waveforms. It is also shown that the inter-symbol interference (ISI) introduced by the approximation has negligible effect on the performance in terms of signal-to-noise ratio (SNR). Moreover, the approximations are often more bandwidth efficient than the original wavelet functions. These waveforms thus illustrate an example solution of a tradeoff between residual ISI and bandwidth efficiency as a signal design problem.

• International Journal of Control, Automation, and Systems
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• v.6 no.5
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• pp.639-650
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• 2008

Electricity price forecasting has become an integral part of power system operation and control. In this paper, a wavelet transform (WT) based neural network (NN) model to forecast price profile in a deregulated electricity market has been presented. The historical price data has been decomposed into wavelet domain constitutive sub series using WT and then combined with the other time domain variables to form the set of input variables for the proposed forecasting model. The behavior of the wavelet domain constitutive series has been studied based on statistical analysis. It has been observed that forecasting accuracy can be improved by the use of WT in a forecasting model. Multi-scale analysis from one to seven levels of decomposition has been performed and the empirical evidence suggests that accuracy improvement is highest at third level of decomposition. Forecasting performance of the proposed model has been compared with (i) a heuristic technique, (ii) a simulation model used by Ontario's Independent Electricity System Operator (IESO), (iii) a Multiple Linear Regression (MLR) model, (iv) NN model, (v) Auto Regressive Integrated Moving Average (ARIMA) model, (vi) Dynamic Regression (DR) model, and (vii) Transfer Function (TF) model. Forecasting results show that the performance of the proposed WT based NN model is satisfactory and it can be used by the participants to respond properly as it predicts price before closing of window for submission of initial bids.

• Journal of the Korea Institute of Military Science and Technology
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• v.8 no.3 s.22
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• pp.73-82
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• 2005

This paper describes shock waveform synthesis methods for a shock response spectnlm over a short time interval with which intereference between parts within a test item is increased to perform a sufficient shock test for damage or malfunction which may be caused by the interference between parts, and a digital filter for obtaining a shock response history required for the shock waveform synthesis and a digital inverse filter for restoration by inversely using the digital filter. The time at which the maximax value occurs in the response history is detected in order to establish a delay time which is one of the parameters in the wavelet, on the condition that the natural frequency of SDOF system with a Q (quality factor) of 10 equals to the wavelet frequency of the zero delay wavelet input. A shock response spectrum over a short time interval and an abrupt change in the acceleration for an instant are illustrated as features of the synthesized waveform.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.12
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• pp.1094-1098
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• 2013

AVI (Automatic Vision Inspection) systems automatically detect defect features and measure their sizes via camera vision. Defect detection is not an easy process because of noises from various sources and optical distortion. In this paper the acquired images from a TFT panel are enhanced with the adoption of an HVS (Human Visual System). A human visual system is more sensitive on the defect area than the illumination components because it has greater sensitivity to variations of intensity. In this paper we modified an MTF (Modulation Transfer Function) in the Wavelet domain and utilized the characteristics of an HVS. The proposed algorithm flattens the inner illumination components while preserving the defect information intact.

• Journal of Advanced Navigation Technology
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• v.11 no.4
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• pp.371-377
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• 2007

Ionospheric time delay is one of the main error source for single-frequency DGPS applications, including time transfer and Wide Area Differential GPS (WADGPS). Grid-based algorithm was already developed for WADGPS but that algorithm is not applicable to geomagnetic storm condition in accuracy and management. In geomagnetic storm condition, the spatial distribution of vertical ionospheric delay is noisy and therefore the accuracy of modeling become low in grid-based algorithm. For better accuracy, function based algorithm can be used but the continuity of correction message is not guranteed. In this paper, we propose the ionospheric model using wavelet based algorithm. This algorithm shows better accuracy with the same number of correction message than the existing spherical harmonics algorithm and guarantees the continuity of correction messages when the number of message is expanded for geomagnetic storm condition.

• Smart Structures and Systems
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• v.8 no.3
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• pp.303-320
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• 2011

Comparing to active damage monitoring, impact localization on composite by using time reversal focusing method has several difficulties. First, the transfer function of the actuator-sensor path is difficult to be obtained because of the limitation that no impact experiment is permitted to perform on the real structure and the difficulty to model it because the performance of real aircraft composite is much more complicated comparing to metal structure. Second, the position of impact is unknown and can not be controlled as the excitation signal used in the active monitoring. This makes it not applicable to compare the difference between the excitation and the focused signal. Another difficulty is that impact signal is frequency broadband, giving rise to the difficulty to process virtual synthesis because of the highly dispersion nature of frequency broadband Lamb wave in plate-like structure. Aiming at developing a practical method for on-line localization of impact on aircraft composite structure which can take advantage of time reversal focusing and does not rely on the transfer function, a PZT sensor array based phase synthesis time reversal impact imaging method is proposed. The complex Shannon wavelet transform is presented to extract the frequency narrow-band signals from the impact responded signals of PZT sensors. A phase synthesis process of the frequency narrow-band signals is implemented to search the time reversal focusing position on the structure which represents the impact position. Evaluation experiments on a carbon fiber composite structure show that the proposed method realizes the impact imaging and localization with an error less than 1.5 cm. Discussion of the influence of velocity errors and measurement noise is also given in detail.