• Smart Structures and Systems
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• v.2 no.2
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• pp.171-188
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• 2006

This paper deals with damage detection using active Lamb waves. The wavelet transform and empirical mode decomposition methods are discussed for measuring the Lamb wave's arrival time of the group velocity. An experimental system to diagnose the damage in the composite plate is developed. A method to optimize this system is also given for practical applications of active Lamb waves, which involve optimal arrangement of the piezoelectric elements to produce single mode Lamb waves. In the paper, the single mode Lamb wave means that there exists no overlapping among different Lamb wave modes and the original Lamb wave signal with the boundary reflection signals. Based on this optimized PZT arrangement method, five damage localizations on different plates are completed and the results using wavelet transform and empirical mode decomposition methods are compared.

• Korean Journal of Optics and Photonics
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• v.3 no.1
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• pp.20-26
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• 1992

The fourier transform method of retrieving the phase of the test wavefront from a Twyman-Green interferometer was reviewed by numerical simulations and experiments. Of the two methods reviewed, Takeda's approach proved more reliable in reconstructing the deformation of the test surface. The application of this approach to a plane mirror showed the existence of the surface curvature, whose maximum deviation was about $\lambda$/6. The accuracy in the measurement was evaluated to be around $\lambda$/40.

• Bulletin of the Korean Mathematical Society
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• v.58 no.1
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• pp.235-251
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• 2021

We consider the Schrödinger type operator ��k = (-∆)k+Vk on ℝn(n ≥ 2k + 1), where k = 1, 2 and the nonnegative potential V belongs to the reverse Hölder class RHs with n/2 < s < n. In this paper, we establish the (Lp, Lq)-boundedness of the higher order Riesz transform T��,�� = V2��∇2��-��2 (0 ≤ �� ≤ 1/2 < �� ≤ 1, �� - �� ≥ 1/2) and its adjoint operator T∗��,�� respectively. We show that T��,�� is bounded from Hardy type space $H^1_{\mathcal{L}_2}({\mathbb{R}}_n)$ into Lp2 (ℝn) and T∗��,�� is bounded from ��p1 (ℝn) into BMO type space $BMO_{\mathcal{L}_1}$ (ℝn) when �� - �� > 1/2, where $p_1={\frac{n}{4({\beta}-{\alpha})-2}}$, $p_2={\frac{n}{n-4({\beta}-{\alpha})+2}}$. Moreover, we prove that T��,�� is bounded from $BMO_{\mathcal{L}_1}({\mathbb{R}}_n)$ to itself when �� - �� = 1/2.

• Steel and Composite Structures
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• v.38 no.5
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• pp.523-531
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• 2021

The generalized thermoelastic analysis problem of a two-dimension porous medium with and without energy dissipation are obtained in the context of Green-Naghdi's (GNIII) model. The exact solutions are presented to obtain the studying fields due to the pulse heat flux that decay exponentially in the surface of porous media. By using Laplace and Fourier transform with the eigenvalues scheme, the physical quantities are analytically presented. The surface is shocked by thermal (pulse heat flux problems) and applying the traction free on its outer surfaces (mechanical boundary) through transport (diffusion) process of temperature to observe the analytical complete expression of the main physical fields. The change in volume fraction field, the variations of the displacement components, temperature and the components of stress are graphically presented. Suitable discussion and conclusions are presented.

• Smart Structures and Systems
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• v.30 no.3
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• pp.263-271
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• 2022

In this paper we present an overview of damage diagnosis algorithms that have been developed over the past two decades using vibration signals obtained from structures. Then, the paper focuses primarily on algorithms that can be used following an extreme event such as a large earthquake to identify structural damage for responding in a timely manner. The algorithms presented in the paper use measurements obtained from accelerometers and gyroscope to identify the occurrence of damage and classify the damage. Example algorithms are presented include those based on autoregressive moving average (ARMA), wavelet energies from wavelet transform and rotation models. The algorithms are illustrated through application of data from test structures such as the ASCE Benchmark structure and laboratory tests of scaled bridge columns and steel frames. The paper concludes by identifying needs for research and development in order for such algorithms to become viable in practice.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.28.5-28
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• 2001

This paper investigates a classification method of the electrocardiogram (ECG) into different disease categories. The features for the classification of the ECG are the coefficients of the discrete wavelet transform (DWT) of ECG signals. The coefficients are calculated with Haar wavelet, and after DWT we can get 64 coefficients. Each coefficient has morphological information and they may be good features when conventional time-domain features are not available. Since all of them are not meaningful, it is needed to reduce the size of meaningful coefficients set. The distributions of each coefficient can be the rules to classify ECG signal. The optimally reduced feature set is obtained by fuzzy c-means algorithm and rough set theory. First, the each coefficient is clustered by fuzzy c-means algorithm and the clustered ...

• Structural Monitoring and Maintenance
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• v.9 no.4
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• pp.373-388
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• 2022

A USW based diagnostic procedure is presented for estimating the depth of surface-breaking cracks. The diagnosis is demonstrated on seven lab-scale SFRC beam specimens, which are subjected to the CMOD controlled three-point bending test to create real bending cracks. Then, the recorded multiple ultrasonic signals are examined with the signal processing techniques, including wavelet transform and two-dimensional Fourier transform, to investigate the relationships between the crack depth and two diagnostic indices, namely the attenuation coefficient and dispersion index (DI). Finally, the reliabilities of these indices for depth estimation are verified with the visually measured crack depths as well as the crack features obtained with a digital image processing algorithm. It is found that the DI outperforms the attenuation coefficient in depth estimation, where this index displays good agreement with the visual inspection for 86% of the inspected specimens.

• Annual Conference of KIPS
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• 2009.11a
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• pp.243-244
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• 2009

So far, many researches have been conducted in the area of audio based context recognition. Nevertheless, most of them are based on existing feature extraction techniques derived from linear signal processing such as Fourier transform, wavelet transform, linear prediction... Meanwhile, environmental audio signal may potentially contains non-linear dynamic properties. Therefore, it is a big potential to utilize non-linear dynamic signal processing techniques in audio based context recognition.

• The Transactions of the Korean Institute of Power Electronics
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• v.28 no.1
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• pp.15-21
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• 2023

With the development of technology, a new class of smaller and more sensitive electrical systems have emerged, requiring higher quality power system. Improving the quality of the power system requires removing harmonics as much as possible to ensure better efficiency. We should first collect information on what harmonic frequencies are included in the current power system to remove the harmonics. In this paper, a new frequency analysis algorithm is introduced for a three-phase and a 1-phase power system. MTE PRS 600.3 is used to generate any harmonics to ensure that the algorithm performs well. Typing any harmonics on the Windows GUI program shows the analyzed result from the board developed for the algorithm.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.1
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• pp.96-107
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• 1996

A voice personality transformation algorithm using orthogonal vector space conversion is proposed in this paper. Voice personality transformation is the process of changing one person's acoustic features (source) to those of another person (target). In this paper, personality transformation is achieved by changing the LPC cepstrum coefficients, excitation spectrum and pitch contour. An orthogonal vector space conversion technique is proposed to transform the LPC cepstrum coefficients. The LPC cepstrum transformation is implemented by principle component decomposition by applying the Karhunen-Loeve transformation and minimum mean-square error coordinate transformation(MSECT). Additionally, we propose a pitch contour modification method to transform the prosodic characteristics of any speaker. To do this, reference pitch patterns for source and target speaker are firstly built up, and speaker's one. The experimental results show the effectiveness of the proposed algorithm in both subjective and objective evaluations.