Gross distortion flexible body dynamic stress compensation method based on mixing nerve network model

A hybrid neural network and dynamic stress technology, applied in biological neural network models, neural learning methods, etc., can solve problems such as dynamic stress compensation of large-deformation flexible bodies, shorten the modeling cycle, reduce the scale, and solve the problem of convergence slow effect

Active Publication Date: 2015-09-09
NANJING UNIV OF AERONAUTICS & ASTRONAUTICS
View PDF2 Cites 5 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the hybrid neural network model in the prior art mainly compensates nonlinear stress and strain in the application scenarios of small deforma...

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
  • Gross distortion flexible body dynamic stress compensation method based on mixing nerve network model
  • Gross distortion flexible body dynamic stress compensation method based on mixing nerve network model
  • Gross distortion flexible body dynamic stress compensation method based on mixing nerve network model

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0016] combine figure 1 , a method for dynamic stress compensation of a large deformation flexible body based on a hybrid neural network model of the present invention, comprising the following steps:

[0017] Step 1. Collect the static test data of the large-deformation flexible body. The collected content includes: collecting the output voltage of the stress sensor, the ambient temperature, the longitudinal strain of the large-deformation flexible body, and the longitudinal stress of the large-deformation flexible body; For X=(x 1 ,x 2 ,ε,σ) T , where x 1 is the output voltage of the stress sensor, x 2 is the ambient temperature, ε is the longitudinal strain of the large deformation flexible body, and its calculation formula is ε=ΔL / L, where ΔL is the longitudinal elongation of the large deformation flexible body, L is the length of the large deformation flexible body, and σ is the large deformation flexible body The longitudinal stress of the body, the calculation form...

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 discloses a gross distortion flexible body dynamic stress compensation method based on a mixing nerve network model, and belongs to the parachute measure technology and computer machine learning field; the method is applied to gross distortion flexible body dynamic stress compensation, and especially applied to dynamic stress compensation in a parachute or air cushion ship equipment work process; the mixing nerve network model comprises a knowledge base model and a reverse direction propagation nerve network model; the knowledge base model represents main features of a gross distortion flexible body mechanics model; the reverse direction propagation nerve network model represents difference characteristic between the gross distortion flexible body mechanics model and the knowledge base model. The method uses a high precision universal testing machine to obtain sample data, uses the mixing nerve network model to construct a dynamic stress compensation model, and is high in compensation precision, low in computing complexity, can be effectively applied to gross distortion flexible body dynamic stress compensation, thus providing a novel idea for dynamic stress compensation problem under a complex work environment.

Description

technical field [0001] The invention belongs to the fields of parachute measurement technology and computer machine learning, and in particular relates to a dynamic stress compensation method for a large-deformation flexible body based on a hybrid neural network model (Hybrid Neural Network Model, HNNM). Background technique [0002] At present, the CFD (Computational Fluid Dynamics)-MSD (Mass Spring Damper) coupling model established on the basis of parachute measurement technology, aerodynamics and structural mechanics uses the basic knowledge of computational fluid dynamics and structural dynamics to perform numerical solutions and simulate The structure and flow field changes of large deformation flexible body during working process. This model can better reflect the nature of the aeroelastic force on the flexible body with large deformation. However, the uncertainty of the air flow rate, elastic coefficient and damping coefficient of the large deformation flexible body...

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): G06N3/08
Inventor 罗韬庄毅顾晶晶孙健范璧健夏晓东崔鸿飞杨金龙郝纲
Owner NANJING UNIV OF AERONAUTICS & ASTRONAUTICS
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