Shape sensing for thin-shell spaceborne antennas with adaptive isogeometric analysis and inverse finite element method

Yu, Dewen; Wang, Shun; Li, Weidong; Yang, Yaowen; Hong, Jun

doi:10.1016/j.tws.2023.111154

Cited by 7 publications

(1 citation statement)

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“…To enhance the precision and cost effectiveness of shape-sensing analysis, especially when dealing with a limited number of sensors, a viable strategy involves pre-extrapolating the structure’s strain field. The inverse problem is then addressed by means of the iFEM, utilizing the pre-extrapolated data as an input [ 39 ]. This approach enables the use of a finer mesh with a large number of measurement samples, ensuring higher accuracy in the reconstruction of the displacement field.…”

Section: Theoretical Backgroundmentioning

confidence: 99%

Shape Sensing in Plate Structures through Inverse Finite Element Method Enhanced by Multi-Objective Genetic Optimization of Sensor Placement and Strain Pre-Extrapolation

Del Priore,

Lampani

2024

Sensors

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The real-time reconstruction of the displacement field of a structure from a network of in situ strain sensors is commonly referred to as “shape sensing”. The inverse finite element method (iFEM) stands out as a highly effective and promising approach to perform this task. In the current investigation, this technique is employed to monitor different plate structures experiencing flexural and torsional deformation fields. In order to reduce the number of installed sensors and obtain more accurate results, the iFEM is applied in synergy with smoothing element analysis (SEA), which allows the pre-extrapolation of the strain field over the entire structure from a limited number of measurement points. For the SEA extrapolation to be effective for a multitude of load cases, it is necessary to position the strain sensors appropriately. In this study, an innovative sensor placement strategy that relies on a multi-objective genetic algorithm (NSGA-II) is proposed. This approach aims to minimize the root mean square error of the pre-extrapolated strain field across a set of mode shapes for the examined plate structures. The optimized strain reconstruction is subsequently utilized as input for the iFEM technique. Comparisons are drawn between the displacement field reconstructions obtained using the proposed methodology and the conventional iFEM. In order to validate such methodology, two different numerical case studies, one involving a rectangular cantilevered plate and the other encompassing a square plate clamped at the edges, are investigated. For the considered case studies, the results obtained by the proposed approach reveal a significant improvement in the monitoring capabilities over the basic iFEM algorithm with the same number of sensors.

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Section: Theoretical Backgroundmentioning

confidence: 99%