Comparison of Fourier and wavelet analyses for defect detection in lock-in and pulse phase thermography

Olbrycht, R.; Więcek, B.; Gralewicz, Grzegorz; Świątczak, T.; Owczarek, Grzegorz

doi:10.3166/qirt.4.219-232

Cited by 19 publications

(10 citation statements)

References 4 publications

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“…The prediction of switch faults in the brushless excitation system of synchronous generators by second and fifth harmonic components as diagnostic indices using DFT was proposed in [12]. DFT provides accurate information of frequency components, but the time information of the transients in the signal is totally lost [13]. STFT provides a compromise between time and frequency resolution when the signals are decomposed, but the size of window is not adaptive.…”

Section: Switching Statesmentioning

confidence: 99%

Wavelet Modulus Maxima for Single Switch Open Fault in Multi-level Inverter

Keswani¹,

Suryawanshi

Renge³

2014

Electric Power Components and Systems

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Section: Switching Statesmentioning

confidence: 99%

Wavelet Modulus Maxima for Single Switch Open Fault in Multi-level Inverter

Keswani¹,

Suryawanshi

Renge³

2014

Electric Power Components and Systems

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“…FFT decreases the computational cost by reducing N, the number of points needed for computation from 2 2N to 2 log NN . If the frequency is constant in time, FFT works effectively [33]. However, in nonlinear ultrasonic testing, the objective is to find the complex nonstationary higher-order harmonic signals, which potentially poses a challenge for FFT.…”

Section: Fast Fourier Transformmentioning

confidence: 99%

Wavelet based harmonics decomposition of ultrasonic signal in assessment of plastic strain in aluminum

et al. 2017

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In nonlinear ultrasonics, the correlation between microstructural change and ultrasonic properties is investigated by the acoustic nonlinearity parameter, calculated by experimentally measuring the first and second harmonic amplitudes of ultrasound signals. The most prevalent signal processing method is to transform the time-domain signal into the frequency domain and acquire the amplitudes of each frequency from the frequency spectrum. However, the major drawback of this approach is that temporal information is not preserved and the transformation errors increase dramatically in analyzing nonlinear signals with discontinuities. In this study, two wavelet-based algorithms are introduced to analyze the waveform in nonlinear ultrasonic testing. The algorithms are applied to correlate the acoustic nonlinearity parameter and the plastic deformation of aluminum 1100 specimens, for the purpose of validation. The results showed that the acoustic nonlinearity parameter calculated through the proposed algorithms is not influenced by the signal processing variables, and the signal processing error is reduced when the waveletbased decomposition is applied.

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“…By analyzing the surface thermal wave signals to obtain the phase or amplitude difference, internal defects can be detected and identified. At present, the fast Fourier transform (FFT) is the commonly used signal processing method for MT, and the wavelet transform (WT) can also be used successfully [4]. The results in literature [4] by Robert Olbrych showed that the processing result obtained by the complex Morlet WT was similar to that of the FFT, and could characterize the transient process of the infrared modulated signal.…”

Section: Introductionmentioning

confidence: 99%

Infrared modulated thermography based on the adaptive complex Morlet wavelet analysis

Guo¹,

Zhao²

2018

Proceedings of the 2018 International Conference on Quantitative InfraRed Thermography

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An adaptive infrared modulated image sequence processing method based on the complex Morlet wavelet analysis is proposed for the modulated thermography of composite materials, focusing on the complicated parameter selections. A wavelet scale selection algorithm is proposed according to the modulation frequency of thermal excitation and the sampling frequency of infrared imaging. The phase images obtained using this method and FFT are compared. The results show that the method can select the scale parameter of wavelet analysis automatically, and has a good tolerance to the change of modulation frequency.

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Comparison of Fourier and wavelet analyses for defect detection in lock-in and pulse phase thermography

Cited by 19 publications

References 4 publications

Wavelet Modulus Maxima for Single Switch Open Fault in Multi-level Inverter

Wavelet Modulus Maxima for Single Switch Open Fault in Multi-level Inverter

Wavelet based harmonics decomposition of ultrasonic signal in assessment of plastic strain in aluminum

Infrared modulated thermography based on the adaptive complex Morlet wavelet analysis

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