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Application of Wavelet Analysis into Singularity Detection of Signals

Zhao Lian

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Abstract

Singualr signal often carries a lot of important information.Unlike Fourier analysis,the wavelet transform has good local property in time and frequency domains,and it be fit to process the nonstationary signal.The concept of wavelet analysis,the good timefrequency localization features of wavelet transform,and theory of detection of signal singularity are introduced in this paper.the wavelet transform technique is adapted to processing the brim signal and the sudden signal so this technique has a good perspective in fault detection and diagnosis.

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What this paper is about

Singualr signal often carries a lot of important information.Unlike Fourier analysis,the wavelet transform has good local property in time and frequency domains,and it be fit to process the nonstationary signal.The concept of wavelet analysis,the good timefrequency localization features of wavelet transform,and theory of detection of signal singularity are introduced in this paper.the wavelet transform technique is adapted to processing the brim signal and the sudden signal so this technique has a good perspective in fault detection and diagnosis.

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Available abstract

Singualr signal often carries a lot of important information.Unlike Fourier analysis,the wavelet transform has good local property in time and frequency domains,and it be fit to process the nonstationary signal.The concept of wavelet analysis,the good timefrequency localization features of wavelet transform,and theory of detection of signal singularity are introduced in this paper.the wavelet transform technique is adapted to processing the brim signal and the sudden signal so this technique has a good perspective in fault detection and diagnosis.

Key concepts: Wavelet, Harmonic wavelet transform, Wavelet transform, Second-generation wavelet transform, Discrete wavelet transform, Wavelet packet decomposition, Stationary wavelet transform, Computer science

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