2010Unpublished venueRequires access

Performance evaluation of fractional Fourier transform(FrFT) for time-frequency analysis of ultrasonic signals in NDE applications

Yufeng Lu, Alireza Kasaeifard, Erdal Oruklu, Jafar Saniie

Open publisher page 12 citations

Abstract

Recently, there has been a growing attention on fractional Fourier transform (FrFT) for time-frequency analysis. In this investigation, an FrFT-based signal decomposition algorithm is utilized to decompose ultrasonic signals into a linear combination of signal components. As a transformation tool, FrFT is employed to estimate an optimal transform order, which leads to the maximum amplitude response, or the highest kurtosis value in the fractional transform domain. Furthermore, a signal component is obtained by applying a window in the fractional domain and inverse FrFT. In an iterative manner, ultrasonic signals are decomposed into the signal components until a predefined stop criterion is satisfied. Analytical and simulation results show that FrFT is an alternative method to perform high-resolution analysis of nonstationary ultrasonic signals.

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What this paper is about

Recently, there has been a growing attention on fractional Fourier transform (FrFT) for time-frequency analysis. In this investigation, an FrFT-based signal decomposition algorithm is utilized to decompose ultrasonic signals into a linear combination of signal components. As a transformation tool, FrFT is employed to estimate an optimal transform order, which leads to the maximum amplitude response, or the highest kurtosis value in the fractional transform domain. Furthermore, a signal component is obtained by applying a window in the fractional domain and inverse FrFT. In an iterative manner, ultrasonic signals are decomposed into the signal components until a predefined stop criterion is satisfied. Analytical and simulation results show that FrFT is an alternative method to perform high-resolution analysis of nonstationary ultrasonic signals.

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Available abstract

Recently, there has been a growing attention on fractional Fourier transform (FrFT) for time-frequency analysis. In this investigation, an FrFT-based signal decomposition algorithm is utilized to decompose ultrasonic signals into a linear combination of signal components. As a transformation tool, FrFT is employed to estimate an optimal transform order, which leads to the maximum amplitude response, or the highest kurtosis value in the fractional transform domain. Furthermore, a signal component is obtained by applying a window in the fractional domain and inverse FrFT. In an iterative manner, ultrasonic signals are decomposed into the signal components until a predefined stop criterion is satisfied. Analytical and simulation results show that FrFT is an alternative method to perform high-resolution analysis of nonstationary ultrasonic signals.

Key concepts: Fractional Fourier transform, Fourier transform, Algorithm, SIGNAL (programming language), Ultrasonic sensor, Frequency domain, Short-time Fourier transform, Time–frequency analysis

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