Fractional Fourier Transform for Ultrasonic Chirplet Signal Decomposition | Zendy

Yufeng Lu | Zendy; Alireza Kasaeifard | Zendy; Erdal Oruklu | Zendy; Jafar Saniie | Zendy

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Fractional Fourier Transform for Ultrasonic Chirplet Signal Decomposition

Author(s) -

Yufeng Lu,

Alireza Kasaeifard,

Erdal Oruklu,

Jafar Saniie

Publication year - 2012

Publication title -

advances in acoustics and vibration

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.237

H-Index - 14

eISSN - 1687-627X

pISSN - 1687-6261

DOI - 10.1155/2012/480473

Subject(s) - fractional fourier transform , signal (programming language) , chirp , fourier transform , kurtosis , algorithm , short time fourier transform , computer science , ultrasonic sensor , signal processing , constant q transform , spectral density estimation , acoustics , speech recognition , artificial intelligence , mathematics , fourier analysis , physics , telecommunications , statistics , optics , mathematical analysis , radar , laser , programming language

A fractional fourier transform (FrFT) based chirplet signal decomposition (FrFT-CSD) algorithm is proposed to analyze ultrasonic signals for NDE applications. Particularly, this method is utilized to isolate dominant chirplet echoes for successive steps in signal decomposition and parameter estimation. FrFT rotates the signal with an optimal transform order. The search of optimal transform order is conducted by determining the highest kurtosis value of the signal in the transformed domain. A simulation study reveals the relationship among the kurtosis, the transform order of FrFT, and the chirp rate parameter in the simulated ultrasonic echoes. Benchmark and ultrasonic experimental data are used to evaluate the FrFT-CSD algorithm. Signal processing results show that FrFT-CSD not only reconstructs signal successfully, but also characterizes echoes and estimates echo parameters accurately. This study has a broad range of applications of importance in signal detection, estimation, and pattern recognition

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