Acceleration and Velocity Sensing from Measured Strain

Pak, Chan-gi; Truax, Roger

doi:10.2514/6.2016-1229

Cited by 5 publications

(4 citation statements)

References 6 publications

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“…The strain data of each measurement point under the corresponding load in the finite element model is extracted, and the finite element extraction data is the strain value of all nodes under the same area where the actual strain gauge is located, and the regional average is shown in Fig 10(a). According to the strain reconstruction model and experimental data, the reconstruction strain value of each sample was calculated, and the regional node reconstruction strain was shown in The relative error calculation method in the table is shown in Eq (18).…”

Section: Finite Elements Datamentioning

confidence: 99%

“…Later, the theory was applied to the Ikhana wing, and it was found that the Ko displacement theory formulated for the weak nonlinear cantilever beam was very accurate in the prediction of the deformation shape of the double-conical Ikhana wing. Pak et al 18] developed a method to further extend the applicability of Ko displacement theory. A.…”

Section: Introductionmentioning

confidence: 99%

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A strain reconstruction method for uncertain boundary conditions

Huo

Zhang

et al. 2023

Preprint

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Affected by complex boundary conditions and redundant structural assembly, it is difficult to collect stress and strain information on key structures of complex mechanical equipment, resulting in difficult life monitoring and large calculation errors. The purpose of this study is to provide reliable strain data for accurate life prediction and solve the problem of obtaining critical structural strain under uncertain loads and other complex boundary conditions. In this paper, a neural network training dataset is established based on finite element analysis data and experimental data, and the neural network architecture and parameter optimization are carried out for each data set. Finally, the strain reconstruction model based on a neural network is established, which solves the two problems of accurate equivalence from structure to strain and equivalence from strain to load. Feature experimental samples were designed to verify the universality of the research method. The model is experimentally verified with an average error of less than 5%. It realizes the global strain reconstruction from the local measurement point to the overall structure, which can be used for real-time and full-cycle life monitoring of the structure;

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Section: Finite Elements Datamentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A strain reconstruction method for uncertain boundary conditions

Huo

Zhang

et al. 2023

Preprint

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show abstract

“…A simple harmonic motion assumption for the computation of wing acceleration works with undamped free vibration problems [8], but this assumption cannot handle the heavy damping issues associated with aeroelastic oscillation problems. Also, the orthonormalized coordinate vector fηg k used for the computation of velocities in [8] is not fully decoupled because of coupling between structural dynamics and unsteady aerodynamics.…”

Section: B Computation Of Velocity and Acceleration From Computed Win...mentioning

confidence: 99%

“…The availability of wing deflections, velocities, and accelerations at all element grid points across the structural finite element (FE) model [7,8] will allow engineers to undertake more accurate real-time analyses of both internal elastic and inertial forces, as well as external aerodynamic forces, at any point on the structure. These force values over the entire surface of a structure may also find application in structural health monitoring, active flexible motion control, and active drag reduction.…”

mentioning

confidence: 99%

Unsteady Aerodynamic Force Sensing from Strain Data

Pak

2017

Journal of Aircraft

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Linear and Geometrically Nonlinear Structural Shape Sensing from Strain Data

Pak

2023

AIAA Journal

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An aircraft’s shape must be measured during flight to implement active shape controls such as active trim shape, divergence, and sonic boom controls. A basis function method for linear as well as geometrically nonlinear structural shape sensing is proposed in this study. Basis functions can be mode shapes, linear static deformation shapes, and/or geometrically nonlinear static deformation shapes. The proposed basis function method is validated using a high-aspect-ratio wing, a swept test plate, and the National Aeronautics and Space Administration X-59 aircraft. A large structural deformation of a high-aspect-ratio wing is successfully captured using the proposed basis function method with less than 0.3% prediction error at the wing-tip section. The basis function method gives excellent deformation prediction, even with stress concentration. Performance of the basis functions is compared using the X-59 stabilator sample case. In most of the sample load cases, static deformations give a better correlation with the target deformation than do mode shapes. Wing shape sensing with sparse strain data are also demonstrated in this study using the X-59 aircraft. Predicted structural deformations match reasonably with the target deformations, even without strain gauges on some structural components. The predicted deformations have a good match with the target deformations.

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Acceleration and Velocity Sensing from Measured Strain

Cited by 5 publications

References 6 publications

A strain reconstruction method for uncertain boundary conditions

A strain reconstruction method for uncertain boundary conditions

Unsteady Aerodynamic Force Sensing from Strain Data

Linear and Geometrically Nonlinear Structural Shape Sensing from Strain Data

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