The recent development of the Structural Health Monitoring (SHM) framework has required the simultaneous development of the tools fundamentals for its realization. The shape sensing methods and the loads identification ones have established themselves as crucial tools for the monitoring of aerospace structures. The two families of methods have been developed separately, although the possibility to achieve the knowledge of the displacement field and of the external loads together can enable a further progress in the SHM. In this paper, an integrated approach to simultaneously preform loads identification and shape sensing from discrete strain measurements is proposed. The methods is based on a twosteps process. The first step involves the identification of continuously distributed and concentrated external loads from discrete strain measurements. This step is achieved by discretizing the loads with Finite Elements (FE) and by computing the coefficients of influence between the nodal values of the loads and the discrete strain measurements. The second step reduces the shape sensing inverse problem to a simple direct Finite Element Analysis. The loads identified in the previous step are applied to a refined FE model of the structure and the displacement field is easily obtained through a direct FE analysis. This investigation proves that the two-steps method can accurately identify the loads and the displacement field of a wing box subject to an aerodynamic pressure distribution and a set of concentrated forces, when a sufficient number of strain information is available. When the number of discrete strain measurements decreases or the strains are affected by measurement error, the loads are poorly predicted but the method is still capable of an extremely accurate displacements reconstruction

External loads identification and shape sensing on an aluminum wing box: An integrated approach / Esposito, Marco; Gherlone, Marco; Marzocca, Pier. - In: AEROSPACE SCIENCE AND TECHNOLOGY. - ISSN 1270-9638. - ELETTRONICO. - 114:(2021), p. 106743. [10.1016/j.ast.2021.106743]

External loads identification and shape sensing on an aluminum wing box: An integrated approach

Marco Esposito;Marco Gherlone;
2021

Abstract

The recent development of the Structural Health Monitoring (SHM) framework has required the simultaneous development of the tools fundamentals for its realization. The shape sensing methods and the loads identification ones have established themselves as crucial tools for the monitoring of aerospace structures. The two families of methods have been developed separately, although the possibility to achieve the knowledge of the displacement field and of the external loads together can enable a further progress in the SHM. In this paper, an integrated approach to simultaneously preform loads identification and shape sensing from discrete strain measurements is proposed. The methods is based on a twosteps process. The first step involves the identification of continuously distributed and concentrated external loads from discrete strain measurements. This step is achieved by discretizing the loads with Finite Elements (FE) and by computing the coefficients of influence between the nodal values of the loads and the discrete strain measurements. The second step reduces the shape sensing inverse problem to a simple direct Finite Element Analysis. The loads identified in the previous step are applied to a refined FE model of the structure and the displacement field is easily obtained through a direct FE analysis. This investigation proves that the two-steps method can accurately identify the loads and the displacement field of a wing box subject to an aerodynamic pressure distribution and a set of concentrated forces, when a sufficient number of strain information is available. When the number of discrete strain measurements decreases or the strains are affected by measurement error, the loads are poorly predicted but the method is still capable of an extremely accurate displacements reconstruction
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2897534