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

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...

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 deformation, large displacement and large rotation, and there is no related description of dynamic stress compensation applied to large deformation flexible bodies.

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