A Genetic Algorithm-Based Structural Optimization Method for Low-Frequency Electromagnetic Sensors

An electromagnetic sensor, genetic algorithm technology, applied in the field of non-destructive testing, to achieve the effect of overall optimization

Active Publication Date: 2019-07-26
BEIJING UNIV OF TECH
View PDF4 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, in the above studies, only the influence of a single factor was considered to optimize the design of low-frequency electromagnetic sensors, and the optimization design of low-frequency electromagnetic sensors was not comprehensively considered at the same time.

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
  • A Genetic Algorithm-Based Structural Optimization Method for Low-Frequency Electromagnetic Sensors
  • A Genetic Algorithm-Based Structural Optimization Method for Low-Frequency Electromagnetic Sensors
  • A Genetic Algorithm-Based Structural Optimization Method for Low-Frequency Electromagnetic Sensors

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0030] Below in conjunction with concrete experiment the present invention will be further described:

[0031] In this experiment, the optimal design of the magnetic core size model of the low-frequency electromagnetic sensor is carried out. The COMSOL simulation model is as follows: Figure 5 shown.

[0032] Step 1: Simplify the low-frequency electromagnetic sensor model for COMSOL simulation.

[0033] Save the COMSOL simulation model of the low-frequency electromagnetic sensor as an M file in JAVA language. According to the general sequence of modeling, this file will store all the operation steps such as parameter assignment, modification and annotation in the modeling process. Therefore, before saving the model, it is necessary to clean up the model, delete the redundant steps in the modification process, and obtain the M file model.m of the simplified model.

[0034] Step 2: Parameterize the COMSOL low-frequency electromagnetic sensor optimization model.

[0035] In t...

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 structure optimization method for a low frequency electromagnetic sensor based on a genetic algorithm. The method is suitable for the structure design of a COMSOL analog low frequency electromagnetic sensor model and the shape reconstruction for defect detecting and belongs to the field of nondestructive detection. The method comprises the following steps: on the basis of simplifying the COMSOL analog low frequency electromagnetic sensor model, parameterizing an optimization model of the COMSOL analog low frequency electromagnetic sensor and defining the reading paths for different variables; setting a genetic optimized fitness function and main parameters including an algorithm running parameter and a control parameter; compiling a dynamic link function, calling for the COMSOL model by MATLAB and constructing a channel for mutually transferring data; calling a COMSOL genetic algorithm for optimizing the parameters of the low frequency electromagnetic sensor model, and while acquiring the fitness function meeting the convergence criterion, acquiring an optimized result, namely, the optimized structure parameter of the low frequency electromagnetic sensor. According to the method provided by the invention, the limitation of the COMSOL single assignment operation is broken through and the intelligent optimization of the COMSOL model parameters is realized.

Description

technical field [0001] The invention relates to a structure optimization method of a low-frequency electromagnetic sensor simulated by COMSOL finite element, in particular to a simulation model parameter optimization method based on MATLAB genetic algorithm. The method is applicable to the structural design of the simulation model of the low-frequency electromagnetic sensor and the shape reconstruction of the defect detection of the low-frequency electromagnetic sensor, and belongs to the technical field of non-destructive testing. Background technique [0002] Low-frequency electromagnetic sensor is the primary key link in the realization of damage detection of low-frequency electromagnetic detection technology. When low-frequency electromagnetic sensors are used to detect ferromagnetic materials, the sensitivity and spatial resolution of the detection signals are mainly affected by the excitation signal, the structure of the magnetic circuit and the type of the magnetic se...

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
Patent Type & Authority Patents(China)
IPC IPC(8): G06F17/50G06N3/12
CPCG06F30/23G06N3/126
Inventor 焦敬品常予张强李光海吴斌何存富
Owner BEIJING UNIV OF TECH
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

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

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap