• Title/Summary/Keyword: Morlet Wavelet

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Retrieving Phase from Single Interferogram with Spatial Carrier Frequency by Using Morlet Wavelet

  • Hongxin Zhang;Mengyuan Cui
    • Current Optics and Photonics
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    • v.7 no.5
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    • pp.529-536
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    • 2023
  • The Morlet wavelet transform method is proposed to analyze a single interferogram with spatial carrier frequency that is captured by an optical interferometer. The method can retain low frequency components that contain the phase information of a measured optical surface, and remove high frequency disturbances by wavelet decomposition and reconstruction. The key to retrieving the phases from the low-frequency wavelet components is to extract wavelet ridges by calculating the maximum value of the wavelet transform amplitude. Afterwards, the wrapped phases can be accurately solved by multiple iterative calculations on wavelet ridges. Finally, we can reconstruct the wave-front of the measured optical element by applying two-dimensional discrete cosine transform to those wrapped phases. Morlet wavelet transform does not need to remove the spatial carrier frequency components manually in the processing of interferogram analysis, but the step is necessary in the Fourier transform algorithm. So, the Morlet wavelet simplifies the process of the analysis of interference fringe patterns compared to Fourier transform. Consequently, wavelet transform is more suitable for automated programming analysis of interference fringes and avoiding the introduction of additional errors compared with Fourier transform.

Selection of mother wavelet for bivariate wavelet analysis (이변량 웨이블릿 분석을 위한 모 웨이블릿 선정)

  • Lee, Jinwook;Lee, Hyunwook;Yoo, Chulsang
    • Journal of Korea Water Resources Association
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    • v.52 no.11
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    • pp.905-916
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    • 2019
  • This study explores the effect of mother wavelet in the bivariate wavelet analysis. A total of four mother wavelets (Bump, Mexican hat, Morlet, and Paul) which are frequently used in the related studies is selected. These mother wavelets are applied to several bivariate time series like white noise and sine curves with different periods, whose results are then compared and evaluated. Additionally, two real time series such as the arctic oscillation index (AOI) and the southern oscillation index (SOI) are analyzed to check if the results in the analysis of generated time series are consistent with those in the analysis of real time series. The results are summarized as follows. First, the Bump and Morlet mother wavelets are found to provide well-matched results with the theoretical predictions. On the other hand, the Mexican hat and Paul mother wavelets show rather short-periodic and long-periodic fluctuations, respectively. Second, the Mexican hat and Paul mother wavelets show rather high scale intervention, but rather small in the application of the Bump and Morlet mother wavelets. The so-called co-movement can be well detected in the application of Morlet and Paul mother wavelets. Especially, the Morlet mother wavelet clearly shows this characteristic. Based on these findings, it can be concluded that the Morlet mother wavelet can be a soft option in the bivariate wavelet analysis. Finally, the bivariate wavelet analysis of AOI and SOI data shows that their periodic components of about 2-4 years co-move regularly every about 20 years.

Determination of Dynamic Parameters of Continuous Beam Using Morlet Wavelet (Morlet웨이블렛을 이용한 연속보의 동적 파라메터 추정)

  • 박종열;박형기;김규학
    • Proceedings of the Earthquake Engineering Society of Korea Conference
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    • 2002.03a
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    • pp.143-150
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    • 2002
  • This paper presents the application of continuous wavelet transform for determination of dynamic parameters of continuous beam subjected to moving load. Morlet wavelet is used as mother wavelet in wavelet transform. Dynamic parameters are estimated from the magnitudes and arguments of the wavelet coefficients obtained by wavelet transforming the response time histories of joints on the beam. This study shows that the estimated parameters such as natural frequencies, dmping ratios and mode shapes are to be well-compared with those of the finite element analysis.

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Selecting a mother wavelet for univariate wavelet analysis of time series data (시계열 자료의 단변량 웨이블릿 분석을 위한 모 웨이블릿의 선정)

  • Lee, Hyunwook;Lee, Jinwook;Yoo, Chulsang
    • Journal of Korea Water Resources Association
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    • v.52 no.8
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    • pp.575-587
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    • 2019
  • This study evaluated the effect of a mother wavelet in the wavelet analysis of various times series made by combining white noise and/or sine function. The result derived is also applied to short-memory arctic oscillation index (AOI) and long-memory southern oscillation index (SOI). This study, different from previous studies evaluating one or two mother wavelets, considers a total of four generally-used mother wavelets, Bump, Morlet, Paul, and Mexican Hat. Summarizing the results is as follows. First, the Bump mother wavelet is found to have some limitations to represent the unstationary behavior of the periodic components. Its application results are more or less the same as the spectrum analysis. On the other hand, the Morlet and Paul mother wavelets are found to represent the non-stationary behavior of the periodic components. Finally, the Mexican Hat mother wavelet is found to be too complicated to interpret. Additionally, it is also found that the application result of Paul mother wavelet can be inconsistent for some specific time series. As a result, the Morlet mother wavelet seems to be the most stable one for general applications, which is also assured by the recent trend that the Morlet mother wavelet is most frequently used in the wavelet analysis research.

A Study on the Application of Wavelet Transform to Faults Current Discrimination (Wavelet 변환을 이용한 고장전류의 판별에 관한 연구)

  • 조현우;정종원;윤기영;김태우;이준탁
    • Proceedings of the Korean Society of Marine Engineers Conference
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    • 2002.05a
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    • pp.213-217
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    • 2002
  • Recently the subject of "wavelet analysis" has be drawn by both mathematical and engineering application fields such as Signal Processing, Compression/Decomposition, Wavelet-Neural Network, Statistics and etc. Even though its similar to courier analysis, wavelet is a versatile tool with much mathematical content and great potential for applications. Especially, wavelet transform uses localizable various mother wavelet functions in time-frequency domain. Therefore, wavelet transform has good time-analysis ability for high frequency component, and has good frequency-analysis ability for low frequency component. Using the discriminative ability is more easy method than other conventional techniques. In this paper, Morlet wavelet transform was applied to discriminate the kind of line fault by acquired data from real power transformation network. The experimental result presented that Morlet wavelet transform is easier, and more useful method than the FFW (Fast courier Transform).ransform).

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Damage Detection of Frame Structure Using Wavelet Transform (골조의 손상부위 추정에 웨이블렛 변환의 이용)

  • 박종열;이의택;박진호;박형기
    • Proceedings of the Earthquake Engineering Society of Korea Conference
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    • 2002.09a
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    • pp.173-180
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    • 2002
  • This paper presents a signal processing procedure to detect damage locations of frame structures by using continuous wavelet transform. Morlet wavelet is used as a mother wavelet in wavelet transform. Wavelet transform has the characteristics that allows the use of long time intervals at more precise low-frequency information, and shorter regions at high-frequency information. By this wavelet transform characteristics, Morlet wavelet may be used to identify the locations of damages in the structures. The numerical case studies show that this method can be applied to detect the damage location under a controlled sweeping load.

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Ride Comfort Analysis of a Vehicle Based on Continuous Wavelet Transform

  • Lee, Sang-Kwon;Son, Choong-Yul
    • Journal of Mechanical Science and Technology
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    • v.15 no.5
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    • pp.535-543
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    • 2001
  • This paper presents the ride comfort analysis of a vehicle based on wavelet transform. Traditionally, the objective evaluation of impact harshness is based on the vibration dose value (VDV) and frequency weighting method. These methods do not consider the damping effect of the suspension system of a vehicle. In this paper, the damping is estimated using wavelet transform based on Morlet mother wavelet and its effect is considered for the subjective evaluation of impact harshness of a car.

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Rectangular prism pressure coherence by modified Morlet continuous wavelet transform

  • Le, Thai-Hoa;Caracoglia, Luca
    • Wind and Structures
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    • v.20 no.5
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    • pp.661-682
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    • 2015
  • This study investigates the use of time-frequency coherence analysis for detecting and evaluating coherent "structures" of surface pressures and wind turbulence components, simultaneously on the time-frequency plane. The continuous wavelet transform-based coherence is employed in this time-frequency examination since it enables multi-resolution analysis of non-stationary signals. The wavelet coherence quantity is used to identify highly coherent "events" and the "coherent structure" of both wind turbulence components and surface pressures on rectangular prisms, which are measured experimentally. The study also examines, by proposing a "modified" complex Morlet wavelet function, the influence of the time-frequency resolution and wavelet parameters (i.e., central frequency and bandwidth) on the wavelet coherence of the surface pressures. It is found that the time-frequency resolution may significantly affect the accuracy of the time-frequency coherence; the selection of the central frequency in the modified complex Morlet wavelet is the key parameter for the time-frequency resolution analysis. Furthermore, the concepts of time-averaged wavelet coherence and wavelet coherence ridge are used to better investigate the time-frequency coherence, the coherently dominant events and the time-varying coherence distribution. Experimental data derived from physical measurements of turbulent flow and surface pressures on rectangular prisms with slenderness ratios B/D=1:1 and B/D=5:1, are analyzed.

Rotation-invariant pattern recognition using an optical wavelet circular harmonic matched filter (광웨이브렛 원형고조 정합필터를 이용한 회전불변 패턴인식)

  • 이하운;김철수;김정우;김수중
    • Journal of the Korean Institute of Telematics and Electronics S
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    • v.34S no.1
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    • pp.132-144
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    • 1997
  • The rotation-invariant pattern recognition filter using circular harmonic function of the wavelet transforme dsreference image by morlet, mexican-hat, and haar wavelt function is proposed. The rotated reference images, the images sililar to the reference image, and the images which are added by random noise are used for the inpt images, and in case of the input images with random noise, they are applied to the recognition after removing the random noise by the transformed moving average method with proper thresholding value and window size. The proposed optical wavelet circular harmonic matched filter (WCHMF) is a type of the matche dfilter, so that it can be applied to the 4f vander lugt optical correlation system. SNR and discrimination capability of the proposed filter are compared with those of the conventional HF, the POCHF, and the BPOCHF. The proper wavelet function for the reference image used in this paper is achieved by applying morlet, mexican-hat, and harr wavelet function ot the proposed filter, and the proposed filter has good SNR and discrimination capability with rotation-invariance in case of the morlet wavelet function.

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Faults Current Discrimination of Power System Using Wavelet Transform (웨이블렛 변환을 이용한 전력시스템 고장전류의 판별)

  • Lee, Joon-Tark;Jeong, Jong-Won
    • Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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    • v.21 no.3
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    • pp.75-81
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    • 2007
  • Recently the subject of "wavelet analysis" has be drawn by both mathematical and engineering application fields such as Signal Processing, Compression/Decomposition, Wavelet-Neural Network, Statistics and etc. Even though its similar to Fourier analysis, wavelet is a versatile tool with much mathematical content and great potential for applications. Especially, wavelet transform uses localizable various mother wavelet functions in time-frequency domain. Therefore, wavelet transform has good time-analysis ability for high frequency component, and has good frequency-analysis ability for low frequency component. Using the discriminative ability is more easy method than other conventional techniques. In this paper, Morlet wavelet transform was applied to discriminate the kind of line fault by acquired data from real power transformation network. The experimental result presented that Morlet wavelet transform is easier, and more useful method than the Fast Fourier Transform(FFT).