Study on 3D reconstruction techniques of rocket body model based on strain monitor

Chen, Aihua; Cao, Liangzhi; Yan, Guowei; Xu, Ze

doi:10.1051/matecconf/202133602003

Cited by 3 publications

(2 citation statements)

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“…The object Error IFEM [27] subsea pipelines 5% Ko [22] rocket body 3.1% Modal suspension [12] Standard cantilever beam 2.5%…”

Section: Methodsmentioning

confidence: 99%

“…Marco Esposito et al [20,21] conducted experiments on composite wing box structures subjected to complex bending and twisting deformation and proved that the KO displacement theory can reconstruct the displacement field with only a small number of sensors. Chen et al [22] implemented a three-dimensional reconstruction algorithm for the cylindrical structure rocket model based on Ko's theory. The fourth category is neural network methods.…”

Section: Introductionmentioning

confidence: 99%

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A strain reconstruction method for uncertain boundary conditions

Huo

Zhang

et al. 2023

Preprint

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Affected by complex boundary conditions and redundant structural assembly, it is difficult to collect stress and strain information on key structures of complex mechanical equipment, resulting in difficult life monitoring and large calculation errors. The purpose of this study is to provide reliable strain data for accurate life prediction and solve the problem of obtaining critical structural strain under uncertain loads and other complex boundary conditions. In this paper, a neural network training dataset is established based on finite element analysis data and experimental data, and the neural network architecture and parameter optimization are carried out for each data set. Finally, the strain reconstruction model based on a neural network is established, which solves the two problems of accurate equivalence from structure to strain and equivalence from strain to load. Feature experimental samples were designed to verify the universality of the research method. The model is experimentally verified with an average error of less than 5%. It realizes the global strain reconstruction from the local measurement point to the overall structure, which can be used for real-time and full-cycle life monitoring of the structure;

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“…The object Error IFEM [27] subsea pipelines 5% Ko [22] rocket body 3.1% Modal suspension [12] Standard cantilever beam 2.5%…”

Section: Methodsmentioning

confidence: 99%