Dynamic estimation of heat source distribution during solidification of composite materials under sparse monitoring samples
Carbon fiber reinforced polymer(CFRP)has excellent properties and has become the material of choice for reducing weight and enhancing efficiency in high-end aerospace equipment.Curing is a critical process in achieving the forming and load-bearing of a composite member.The temperature field of the component in the curing process directly determines the curing quality and mechanical properties of the component.Accurately and dynamically reversing the heat source distribution on the surface of the composite member is the key to realizing the accurate control of the temperature field.However,in the actual curing process,auxiliary materials such as breathable felt and vacuum bags are attached to the surface of the composite,making it difficult to directly monitor the surface temperature field.Only several optical fiber temperature measurement points can be introduced to obtain sparse temperature samples,posing challenges to the reconstruction of the high-dimensional scalar field of heat source distribution.Therefore,a dynamic estimation method of heat source distribution in the curing process based on Gaussian mixture distribution model(GMM)was proposed,which introduced the physical a priori equivalence of Gaussian fuzzy and in-plane heat diffusion,established a Gaussian fuzzy-based temperature field evolution model,and then use multiple Gaussian distributions in the GMM to characterize heat source distribution in the curing process,which transformed the difficult problem of high-dimensional field reconstruction into an optimization problem of solving several Gaussian distribution parameters.The feasibility and effectiveness of this method were verified by simulation experiments,demonstrating that it can achieve accurate dynamic estimation of heat source distribution during solidification.
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维普
