Open Access

ARTICLE

Shape Sensing of Thin Shell Structure Based on Inverse Finite Element Method

Zhanjun Wu¹, Tengteng Li¹, Jiachen Zhang², Yifan Wu³, Jianle Li¹, Lei Yang¹, Hao Xu^1,*

1 State Key Laboratory of Structural Analysis for Industrial Equipment, Dalian University of Technology, Dalian, 116024, China
2 Division of Science and Technology, Beijing Normal University—Hong Kong Baptist University United International College, Zhuhai, 519000, China
3 Country School of Marxism, Northeastern University, Shenyang, 110167, China

* Corresponding Author: Hao Xu. Email:

Structural Durability & Health Monitoring 2022, 16(1), 1-14. https://doi.org/10.32604/sdhm.2022.019554

Received 29 September 2021; Accepted 22 December 2021; Issue published 11 February 2022

Abstract

Shape sensing as a crucial component of structural health monitoring plays a vital role in real-time actuation and control of smart structures, and monitoring of structural integrity. As a model-based method, the inverse finite element method (iFEM) has been proved to be a valuable shape sensing tool that is suitable for complex structures. In this paper, we propose a novel approach for the shape sensing of thin shell structures with iFEM. Considering the structural form and stress characteristics of thin-walled structure, the error function consists of membrane and bending section strains only which is consistent with the Kirchhoff–Love shell theory. For numerical implementation, a new four-node quadrilateral inverse-shell element, iDKQ4, is developed by utilizing the kinematics of the classical shell theory. This new element includes hierarchical drilling rotation degrees-of-freedom (DOF) which enhance applicability to complex structures. Firstly, the reconstruction performance is examined numerically using a cantilever plate model. Following the validation cases, the applicability of the iDKQ4 element to more complex structures is demonstrated by the analysis of a thin wallpanel. Finally, the deformation of a typical aerospace thin-wall structure (the composite tank) is reconstructed with sparse strain data with the help of iDKQ4 element.

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Keywords

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