Joint noise reduction method based on variational mode decomposition and permutation entropy

A variational modal decomposition and variational modal technology, applied in the field of signal processing, can solve the problems of end effect and modal aliasing, large decomposition error, sampling frequency influence, etc., and achieve strong adaptability and real-time performance, The effect of simple algorithm, good technical value and application prospect

Pending Publication Date: 2020-01-07
SHANDONG UNIV OF SCI & TECH
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Problems solved by technology

EMD, EEMD or LMD belong to the recursive "screening" mode, there are endpoint effects and mode

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  • Joint noise reduction method based on variational mode decomposition and permutation entropy
  • Joint noise reduction method based on variational mode decomposition and permutation entropy
  • Joint noise reduction method based on variational mode decomposition and permutation entropy

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Embodiment Construction

[0055] The present invention proposes a joint noise reduction method based on variational mode decomposition and permutation entropy. In order to make the advantages and technical solutions of the present invention clearer and clearer, the present invention will be described in detail below in conjunction with specific embodiments.

[0056] Such as figure 1 As shown, a joint noise reduction method based on variational mode decomposition and permutation entropy, specifically includes the following steps:

[0057] Step 1: read the noisy signal x(t), where t=1, 2, ..., N, N is the number of sampling points of the signal;

[0058] Step 2: Use the detrended fluctuation analysis (DFA) method to calculate the value of the scale index a of x(t), and determine the value of the parameter J and the range of the decomposition number K of the variational mode decomposition (VMD) according to the value of a. The specific steps as follows:

[0059] Step 2.1: Calculate the cumulative time s...

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Abstract

The invention discloses a joint noise reduction method based on variational mode decomposition and permutation entropy, and belongs to the technical field of signal processing. The joint noise reduction method comprises the following steps: firstly, reading a noisy signal x (t); calculating the scale index a value of x (t), and determining the decomposition number K of variational mode decomposition (VMD) according to the a value; secondly, performing K-layer VMD decomposition on the noisy signal x (t) to obtain a series of variational mode components uk; then, calculating the permutation entropy of each variational mode component uk, and further determining the value of K; and finally, removing the noise uk component, and reconstructing the remaining uk component to obtain a noise-reducedand filtered signal. The method has the advantages of adaptively determining the decomposition number, effectively removing noise components and being high in robustness and real-time performance, effective noise reduction and filtering processing can be carried out on signals, and the method has good technical value and application prospects for non-stationary signal noise reduction methods.

Description

technical field [0001] The invention belongs to the technical field of signal processing, and in particular relates to a joint noise reduction method based on variational mode decomposition and permutation entropy. Background technique [0002] The monitoring signal obtained by many sensor devices has the characteristics of strong noise and non-stationarity. Noise reduction processing on the monitoring signal is a necessary pre-procedure step for data analysis of the signal. It is necessary to separate the real and effective signal from the noise. come out. [0003] The commonly used signal decomposition methods include Empirical Mode Decomposition (EMD), Ensemble Empirical Mode Decomposition (EEMD), Local Mean Decomposition (LMD) and wavelet transform. EMD, EEMD or LMD belong to the recursive "screening" mode, which has endpoint effect and mode aliasing phenomenon, and is affected by the sampling frequency, and the decomposition error is relatively large. Wavelet transfor...

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Application Information

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IPC IPC(8): G06K9/00G01D18/00
CPCG01D18/00G06F2218/04
Inventor 张杏莉卢新明赵震华曹连跃
Owner SHANDONG UNIV OF SCI & TECH
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