An enhanced method of resizing support links for a planar closed-loop overconstrained deployable structure considering kinematic reliability and surface accuracy

Zhao, Qiangqiang; Guo, Junkang; Yu, Dewen; Hong, Jun; Chen, Feifei

doi:10.1016/j.ast.2020.105988

Cited by 13 publications

(3 citation statements)

References 30 publications

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“…And Eq. ( 6) can be expressed in an equivalent form: (7) where Δli represents the deviation of li; Δr and Δθ denote the position and orientation deviations of panels, respectively.…”

Section: Assembly Deviation Modeling Of the Structure Without The Auxiliary Linkmentioning

confidence: 99%

“…However, for the convenience of modeling, they treated the ESS as a planar configuration and removed one of the support links, which results in an obvious discrepancy with the practical spatial structure and therefore limits the application of their method. Zhao et al [7] developed an enhanced approach of combining the Taguchi method and grey relational analysis to determine the combination of link adjustments. Nevertheless, this work has the same limitation with [6].…”

Section: Introductionmentioning

confidence: 99%

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Link Adjustment for Assembly Deviation Control of Extendible Support Structures via Sparse Optimization

Guo

et al. 2021

IEEE Access

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The assembly accuracy of the extendible support structure is of importance for the imaging capability of synthetic aperture radar antennas. In general, due to manufacturing imperfections and installation variations, its assembly accuracy will be inevitably degraded. Therefore, controlling the assembly deviation is highly concerned in practice. To meet the accuracy requirement and make "the control" more efficient, this study proposes a novel method to quantitatively conduct dimensional adjustment of links for extendible support structures of synthetic aperture radar antennas. Since the extendible support structure is generally over-constrained in the deployed configuration, the relationship between the assembly deviation and the variation sources is first derived by means of equivalent transformation. Based on the mathematical expression of assembly deviation, an inequality constrained sparse optimization model for quantitatively resizing links is formulated. Then, an efficient algorithm integrating the alternating direction method of multipliers and binary search is developed to solve the above optimization model, thereby acquiring the optimal combination of link adjustment. Finally, numerical case studies are carried out to demonstrate the effectiveness of the proposed method in Matlab, which show that it can not only achieve satisfactory performance in prediction but also significantly improve the assembly efficiency.

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“…And Eq. ( 6) can be expressed in an equivalent form: (7) where Δli represents the deviation of li; Δr and Δθ denote the position and orientation deviations of panels, respectively.…”

Section: Assembly Deviation Modeling Of the Structure Without The Auxiliary Linkmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Link Adjustment for Assembly Deviation Control of Extendible Support Structures via Sparse Optimization

Guo

et al. 2021

IEEE Access

Self Cite

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“…Zhuang proposed an efficient wear prediction method in the framework of multi-body dynamics and combined it with Monte Carlo hair to analyze the kinematic reliability of a two-axis actuator mechanism with non-uniform joint clearance over time [13]. Zhao et al developed a discrete optimization model with two objectives based on support vector machine training and error model computation and proposed an enhancement method for quantitatively adjusting the size of the support links of a planar closed-loop over-constrained expandable structure [14]. Weng et al proposed an efficient post-processing simulation method for the stochastic structural reliability analysis: the conditional extreme value distribution (CEVD) method [15].…”

Section: Introductionmentioning

confidence: 99%

Reliability Analysis and Optimization Method of a Mechanical System Based on the Response Surface Method and Sensitivity Analysis Method

Zhao,

Yue,

Zhao

et al. 2023

Actuators

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Mechanical system reliability analysis constitutes a primary research focus in the field of engineering. This study aims to address the issue of complex mechanical systems with intricate mechanisms and nonlinear reliability equations that are challenging to solve. To this end, we present a reliability analysis and optimization methodology that merges the response surface and sensitivity analysis methods. A comprehensive formation of reliability assessment and optimization of complex mechanical systems is achieved by creating a response surface model to fit the complex state function and solving the reliability parameters, followed by an error sensitivity analysis to determine the mechanical system’s reliability adjustment strategy. Finally, these methods are applied to a cylindrical material transport device to preliminarily realize the reliability assessment and average reliability optimization goals. The study’s findings may offer a theoretical framework and research opportunities to evaluate and enhance the reliability of intricate mechanical systems.

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Form-finding design optimization method of cable mesh reflectors based on a weighting surface accuracy with electromagnetic performance

Zhang

Zheng

Zhang

2023

Struct Multidisc Optim

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An enhanced method of resizing support links for a planar closed-loop overconstrained deployable structure considering kinematic reliability and surface accuracy

Cited by 13 publications

References 30 publications

Link Adjustment for Assembly Deviation Control of Extendible Support Structures via Sparse Optimization

Link Adjustment for Assembly Deviation Control of Extendible Support Structures via Sparse Optimization

Reliability Analysis and Optimization Method of a Mechanical System Based on the Response Surface Method and Sensitivity Analysis Method

Form-finding design optimization method of cable mesh reflectors based on a weighting surface accuracy with electromagnetic performance

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