Minimization of Cable-Net Reflector Shape Error by Target-Approaching and Procedural-Learning Method
Publication: Journal of Aerospace Engineering
Volume 35, Issue 3
Abstract
Cable length adjustment is a critical step to minimize the shape error of cable-net reflectors. The adjustment requires tedious repetitive work, but the surface accuracy is often unsatisfactory because of inevitable operating error and modeling inaccuracy. To solve this problem, this work proposes a target-approaching and procedural-learning method. At the initial stage of the adjustment process, the target-approaching method is proposed to ensure the shape error is improved and that adjustment data are generated. Then an online prediction model is built by sensitivity analysis and least-squares support vector machine. On this basis, a multidimensional forward-backward algorithm is applied to calculate the optimal adjustment amounts in order to achieve fast convergence of adjustment accuracy. Finally, the proposed method is verified by both numerical simulation and prototype experimentation. The results show that the proposed method can well reflect the adjustment characteristics of cable-net reflectors, effectively improve shape accuracy, and greatly shorten adjustment time.
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Data Availability Statement
Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.
Acknowledgments
This project is supported by the National Natural Science Foundation of China (Grant Nos. 51775403 and 51905401).
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Published In
Journal of Aerospace Engineering
Volume 35 • Issue 3 • May 2022
Copyright
© 2022 American Society of Civil Engineers.
History
Received: Oct 18, 2021
Accepted: Dec 28, 2021
Published online: Feb 10, 2022
Published in print: May 1, 2022
Discussion open until: Jul 10, 2022
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