An important issue in the existing inverse finite element method (iFEM) is that reconstruction accuracy cannot satisfy the analytical demand for the flexible structure. To address this issue, this paper presents a multi-nodes iFEM that reconstructs the displacement of structure based on surface measurement strains in real time. Meanwhile, in light of the response characteristics of iFEM, an innovative interpolation method is adapted to regenerate the full field deformation again. The proposed method substantially expands the size of inverse elements, which reduces the numbers of sensors and improves the reconstruction accuracy. The effectiveness of the method to predict displacement is verified by a flexible antenna panel subjected typical boundary conditions.
The inverse finite element method (iFEM) is one of the most effective deformation reconstruction techniques for shape sensing, which is widely applied in structural health monitoring. The distribution of strain sensors affects the reconstruction accuracy of the structure in iFEM. This paper proposes a method to optimize the layout of sensors rationally. Firstly, this paper constructs a dual-objective model based on the accuracy and robustness indexes. Then, an improved adaptive multi-objective particle swarm optimization (IAMOPSO) algorithm is developed for this model, which introduces initialization strategy, the adaptive inertia weight strategy, the guided particle selection strategy and the external candidate solution (ECS) set maintenance strategy to multi-objective particle swarm optimization (MOPSO). Afterwards, the performance of IAMOPSO is verified by comparing with MOPSO applied on the existing inverse beam model. Finally, the IAMOPSO is employed to the deformation reconstruction of complex plate-beam model. The numerical and experimental results demonstrate that the IAMOPSO is an excellent tool for sensor layout in iFEM.
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