Large deformation flexible body dynamic stress measurement information conversion method based on neural networks

A neural network, a technology for measuring information, used in parachute measurement technology and computer machine learning

Active Publication Date: 2015-09-16
NANJING UNIV OF AERONAUTICS & ASTRONAUTICS
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] At present, there is no information conversion method that applies neural networks to the dynamic force measurement of large deformation flexible bodies in the existing technologies at home and abroad.

Method used

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  • Large deformation flexible body dynamic stress measurement information conversion method based on neural networks
  • Large deformation flexible body dynamic stress measurement information conversion method based on neural networks
  • Large deformation flexible body dynamic stress measurement information conversion method based on neural networks

Examples

Experimental program
Comparison scheme
Effect test

Embodiment

[0107] Use the dynamic measurement of flexible body material calendar brocade silk plaid 544 fabrics as an embodiment, its specific implementation is as follows:

[0108] Step 1: Use the strain sensor to carry out voltage-force calibration on the calendered silk plaid 544 fabric;

[0109] Step 2: Filter the measurement data obtained by the strain sensor for measuring calendered silk plaid 544 fabric, where the sampling frequency of the sensor is 100 times the sampling frequency of the high-precision universal material testing machine, so k is taken as 100, which can make There is a one-to-one correspondence between voltage and force measurement data. Get the corresponding voltage-force curve see image 3 ;

[0110] Step 3: Calculate the corresponding voltage-force function according to the measurement data obtained in steps 1 and 2 as follows:

[0111] f(x)=11.3665x 5 -66.0142x 4 +146.3219x 3 -113.4386x 2 +198.6501x+0.8352

[0112] Step 4: Obtain and filter the voltage...

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Abstract

The invention discloses a large deformation flexible body dynamic stress measurement information conversion method based on neural networks, and belongs to the field of parachute measurement technologies and computer machine learning. The method is applied to the stress measurement in the movement process of a large deformation flexible body and especially applied to the stress measurement information conversion in the inflation process of parachutes, hovercrafts and the like. The method mainly includes the following steps of firstly, conducting voltage-stress calibration; secondly, filtering calibration data; thirdly, establishing a voltage-stress function; fourthly, obtaining voltage data under the actual environment and conducting filtering; fifthly, establishing the large deformation flexible body dynamic measurement data conversion neural network; sixthly, using the data training neural network under the actual environment; seventhly, obtaining and outputting stress information obtained through conversion. The voltage-stress information conversion is conducted through the neural networks, the calculation complexity is low, the conversion accuracy is high, and the method can be effectively applied to the dynamic stress measurement information conversion of the large deformation flexible body.

Description

technical field [0001] The invention belongs to the field of parachute measurement technology and computer machine learning, in particular to a neural network-based dynamic force measurement method for large deformation flexible bodies. Background technique [0002] At present, the mathematical simulation of the working process of large-deformation flexible bodies is generally based on the CFD-MSD (Mass Spring Damper Model, Mass Spring Damper Model) coupling model. Using the basic knowledge of computational fluid dynamics and structural dynamics, numerical solutions are carried out to simulate the structure and flow field changes in the working process of large deformation flexible bodies. Although this model can better reflect the aeroelastic force on the flexible body. However, the existing mathematical simulation methods ignore many factors, such as the fabric air permeability, the uncertainty of elastic coefficient and damping coefficient, etc. In particular, the coupl...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/50G06N3/08
Inventor 庄毅张偲郝纲顾晶晶牛涛杨金龙赵金辉徐彦
Owner NANJING UNIV OF AERONAUTICS & ASTRONAUTICS
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