Method for predicting stratospheric airship skin material deformation by using neural network

Abstract

The invention relates to a method for predicting stratospheric airship skin material deformation through a neural network, and belongs to the technical field of damage analysis. The implementation method comprises the following steps: aiming at the true deformation of a stratospheric airship skin material in a complex working environment close to non-proportional biaxial tension, carrying out biaxial tension tests under various stress ratio conditions, and collecting training sample data required by a neural network; constructing a Bayesian neural network comprising an input layer, a hidden layer and an output layer so as to establish a deformation behavior simple expression model of the skin material; and adopting the trained neural network to predict the deformation behavior of the skinmaterial in real time. The method for predicting the stratospheric airship skin material deformation by using the neural network provided by the invention is relatively high in prediction precision, relatively good in stability and strong in popularization capability, can meet the requirement of accurately predicting the skin material deformation behavior in real time, and provides a new method for optimizing the material design and guiding the stratospheric airship structure design.

Description

technical field [0001] The invention relates to a method for predicting the deformation of a stratospheric airship skin material by using a neural network, and belongs to the technical field of damage analysis. Background technique [0002] The stratospheric airship mainly uses static buoyancy to overcome the gravity of the earth and flies at a stratospheric altitude of 20-50km. Due to its long-term space station, fixed-point and high-resolution earth observation capabilities, the stratospheric airship has high economic and strategic value, and has become a research hotspot for scientists from various countries in recent years. The complex environmental characteristics of the stratosphere and the unique shape design of the airship put forward higher requirements on the mechanical properties of the skin material of the stratospheric airship. At present, no stratospheric airship that can stay in the air for a long time and is practical for engineering has not been developed ye...

AI Technical Summary

Problems solved by technology

[0006] The purpose of the present invention is to provide a method for predicting the deformation of stratospheric airship skin materials using neural networks. This method solves the problems of heavy calculations and complex models in traditional mathematical models. Carry out self-learning and construct a simple representation model to understand and quickly predict the deformation characteristics of skin materials. The method is simple, which reduces the test cost and improves work efficiency

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