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Method for monitoring elasticity modulus of composite material based on deep learning

An elastic modulus, composite material technology, applied in the field of engineering acoustics, can solve the problems of difficult to characterize the elastic properties of composite materials, material performance degradation, etc., to achieve the effect of convenient use, low cost and high precision

Pending Publication Date: 2022-02-15
SOUTHEAST UNIV
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Problems solved by technology

Most techniques require prior knowledge of the elastic properties of materials, and it is always difficult to characterize the elastic properties of composite materials due to the lamination and anisotropy of elastic properties of composite materials. The complex relationship between the dispersion curve and the elastic modulus of the composite material is difficult to express with a specific mathematical relationship, and the uncertainty of the composite material in the manufacturing process, the existence of material impurities, and the decline in material performance over time during use , so that composite materials can only be monitored by online non-intrusive detection techniques for changes in elastic properties

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  • Method for monitoring elasticity modulus of composite material based on deep learning
  • Method for monitoring elasticity modulus of composite material based on deep learning
  • Method for monitoring elasticity modulus of composite material based on deep learning

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[0043] In order to deepen the understanding of the present invention, the present invention will be further described below in conjunction with the accompanying drawings. This embodiment is only used to explain the present invention, and does not constitute a limitation to the protection scope of the present invention.

[0044] Such as figure 1 As shown, a specific embodiment of a method for monitoring the modulus of elasticity of a composite material based on deep learning, comprising the following steps:

[0045] Step 10: According to the elastic properties of the composite material, including density, thickness, orientation of reinforcing fibers, number of superimposed layers and elastic constants, use the semi-analytical finite element method to construct a data set suitable for deep neural network training;

[0046] Step 20: Install actuators and sensors in the composite material structure to be tested to transmit and receive guided wave signals;

[0047] Step 30: Using ...

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Abstract

The invention discloses a method for monitoring elasticity modulus of composite materials based on deep learning. According to the method, a deep neural network is utilized to establish a complex relationship between a frequency dispersion curve of a guided wave propagating in composite materials and elasticity modulus of the composite materials, so that accurate testing on elastic constants of the composite materials is realized; and meanwhile, a spectral element method improved semi-analytical finite element method is used for generating a related data set for training a neural network, the method can be applied to industrial facilities, aerospace equipment and the like, and rapid ultrasonic nondestructive testing of elastic properties of the composite materials is achieved.

Description

technical field [0001] The invention relates to the technical field of engineering acoustics, in particular to a method for monitoring the elastic modulus of composite materials based on deep learning. Background technique [0002] Composite materials are becoming more and more common in engineering and aerospace applications due to the advantages of light weight and excellent structural properties, but composite materials may be subjected to shocks during application, resulting in a decrease in their mechanical properties. Therefore, non-destructive testing (NDT) and structural health monitoring (SHM) of composite materials have become widely concerned and discussed issues. Most techniques require prior knowledge of the elastic properties of materials, and it is always difficult to characterize the elastic properties of composite materials due to the lamination and anisotropy of elastic properties of composite materials. The complex relationship between the dispersion curv...

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Application Information

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IPC IPC(8): G06F30/27G06F30/23G06N3/04G06N3/08G16C60/00G06F113/26
CPCG06F30/27G06F30/23G06N3/08G16C60/00G06F2113/26G06N3/045
Inventor 张辉王胜倪中华罗志涛
Owner SOUTHEAST UNIV
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