Time frequency decomposition method for signals including intersections in instantaneous frequencies

Abstract

The invention provides a time frequency decomposition method for signals including intersections in instantaneous frequencies. The method comprises the following steps of: modulating an original signal by using a linear frequency modulation operator to remove the intersection of the instantaneous frequency momentarily; performing empirical mode decomposition on the signal to obtain an intrinsic mode function; modulating the intrinsic mode function by using the conjugate of the linear frequency modulation operator; performing Hilbert transform to obtain a clear time-frequency distribution diagram. The invention mainly provides a method for improving the signal time frequency decomposition capacity by means of linear frequency modulation wavelet transform specific to signals including intersections in the instantaneous frequencies.

Description

technical field [0001] The invention relates to the technical field of signal processing, in particular to a decomposition method of a signal whose instantaneous frequency contains a cross point. Background technique [0002] Time-frequency analysis provides the joint distribution information of signal time domain and frequency domain, which can clearly describe the relationship of signal frequency with time. Hilbert-Huang transform (Hilbert-Huang transform) is an adaptive time-frequency analysis method, which can deal with non-stationary and nonlinear signals. At present, scholars at home and abroad have carried out extensive research on Hilbert-Huang transform, and this technology has gradually been applied to geophysics, structural dynamics, fluid mechanics, fault diagnosis and other fields. [0003] The Hilbert-Huang transform mainly includes two parts: first, the signal is decomposed into a finite number of intrinsic mode functions by using empirical mode decomposition...

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Problems solved by technology

[0005] In response to this problem, some international research can improve the signal decomposition ability of the Hilbert-Huang transform when the processing frequency is similar by masking signal (masking signal), signal-assisted empirical mode decomposition, etc., but none of them can process the signal The case where the instantaneous frequency curve contains a cross point

At present, there is no effective method for the Hilbert-Huang transform to deal with the instantaneous frequency of the signal containing the cross point

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