Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Simulation method for variation modal decomposition parameter optimization

A technique of variational modal decomposition and parameters, which is applied in computational models, biological models, character and pattern recognition, etc., can solve problems such as decreased search efficiency, easy to fall into local optimum, and poor local search ability

Inactive Publication Date: 2020-02-14
TIANJIN UNIV
View PDF0 Cites 3 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] Based on the intelligent optimization algorithm, the optimal screening of VMD preset parameters can be carried out. The particle swarm optimization algorithm (PSO) has a fast calculation speed and can quickly lock the optimal solution range, but it is easy to fall into a local optimum
Genetic Algorithm (GA) has good global optimization performance, but poor local search ability, resulting in a decline in search efficiency in the later stages of evolution

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Simulation method for variation modal decomposition parameter optimization
  • Simulation method for variation modal decomposition parameter optimization
  • Simulation method for variation modal decomposition parameter optimization

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0030] The purpose of the present invention is to overcome the deficiencies of the existing algorithms, through a large number of simulation signal analysis, found that with the amplitude spectral entropy as the fitness function can accurately reflect the characteristics of the intrinsic mode function (IMF) and the original signal, based on the particle swarm algorithm (PSO) and Genetic Algorithm (GA) are combined to search for the optimal parameters of VMD to improve the adaptability of VMD. The specific analysis process is as figure 1 , the execution steps are as follows:

[0031] (1) Build an analog signal

[0032] Use MATLAB to construct an analog signal as follows:

[0033]

[0034] The analog signal S is as follows image 3 (a), the composite signal contains 30Hz, 50Hz, 150Hz, and 2000Hz frequency bands. By constructing the analog signal, the optimization accuracy of PSOGA-VMD parameters (K, a) is verified.

[0035] (2) Initialize PSO-GA parameters

[0036] After...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention relates to a simulation method for variation modal decomposition parameter optimization. The method comprises the following steps: constructing an analog signal; using a genetic algorithm to improve a particle swarm algorithm to optimize variational mode decomposition, and calling as PSOGA-VMD; using wavelet transform analog signal components to perform time-frequency analysis, and comparing the time-frequency analysis with analog signal set frequency characteristics to detect decomposition precision.

Description

technical field [0001] The present invention relates to the optimization of a non-stationary signal decomposition method. When signal processing is performed based on variational mode decomposition (VMD), the accuracy of parameter selection directly determines the accuracy of signal decomposition. Therefore, this patent proposes adaptively performing VMD based on an intelligent optimization algorithm The default parameters are determined. Background technique [0002] Empirical Mode Decomposition (EMD) [1], as an adaptive signal processing method, has been widely used in mechanical fault feature extraction once proposed. EMD converts non-stationary signals into different modal components to decompose analyze. However, although EMD lacks a mathematical foundation, the algorithm efficiency is low, and there is a problem of modal aliasing. When modal aliasing occurs, the IMF component will lose its own physical meaning, which seriously affects the accuracy of EMD decomposition...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
IPC IPC(8): G06K9/62G06N3/00
CPCG06N3/006G06F18/2134
Inventor 林杰威张俊红周启迪龙飞企周天意
Owner TIANJIN UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com