Composite thin-walled circular tube hinges have broad application prospects in large space deployable structures, such as, satellite antennas and solar wings, and their structural parametric design greatly affects their working performance in space. Here, in order to improve their mechanical performance, firstly, the analytical and finite element models for a composite tape measure spring were established to analyze its bending characteristics. Then the finite element model for a composite thin-walled circular tube hinge was established to study its folding and torsional characteristics and analyze effect laws of structural parameters on the hinge performance. The results showed that increasing the ratio of slotting length to width and reducing the ratio of hinge thickness to diameter can obviously improve the hinge’s bending and torsional performance. The hinge’s structural parameters were taken as design variables to build a multi-objective optimization mathematical model. The optimal Latin hyper-cubic test design method was used to construct the RPF neutral network agent model among structural parameters and hinge’s peak bending moment, maximum stress and torsional stiffness, and it was optimized using the NSGA-Ⅱ genetic algorithm. The optimization results showed that the hinge’s peak bending moment is increased by 44.8%, its torsional rigidity is increased by 110%, and its mass is decreased by 20.4%, so the hinge’s mechanical performance is improved and meanwhile its mass is reduced to enhance the hinge mechanism’s self-driving ability and self-locking one; the study results provide a theoretical basis for practical engineering application of composite thin-walled circular tube hinges in space deployable structures.
Key words
composite thin-walled hinges /
RBF neural network /
NSGA-Ⅱ genetic algorithm /
Multi-objective optimization /
Spatial deployable structure
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