A Non-Linear Inverse Vibration Problem of Estimating the External Forces for a System With Displacement-Dependent Parameters

Huang, Cheng‐Hung

doi:10.1006/jsvi.2001.3838

Cited by 33 publications

(16 citation statements)

References 11 publications

(14 reference statements)

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“…However, this is normally not a source of concern, unless the state and costate problems for some reason are considered separately and discretized independently, see, for example [10]. The important issue is that the choice of spaces for x h , x h , k h and k h for the costate equation must be identical to the choice of spaces for the state equation.…”

Section: Discretized Newton Updatementioning

confidence: 98%

“…Equation (5). With the temporal discretization in mind, the costate and state equations are kept on weak form (in contrast to [10] where the costate and state equations are treated on strong form using Runge-Kutta methods for integration).…”

Section: Z(t)mentioning

confidence: 99%

“…Time domain methods have potential to handle time-variant linear as well as non-linear systems, although a majority of presented algorithms are concerned with linear systems, as the inverse structural filter [7], the partial modal matrix method [8], and Dynamic Programming [9], to mention a few. Time domain methods suitable for treatment of non-linear systems are presented in Huang [10] and Nordberg [11].…”

Section: Introductionmentioning

confidence: 99%

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A strategy for input estimation with sensitivity analysis

Nordström

Johansson

Larsson

2006

Numerical Meth Engineering

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SUMMARYThe estimation of unknown excitation or input signals from measured response is essentially the solution of an optimization problem; a function representing the input is sought such that the discrepancy between measured and simulated response is minimized. From the view of optimization it is convenient to consider the general situation where the governing differential equations may be time-variant and non-linear. Moreover, the choice of parameterization for the sought input, sampling instances of measurement data and discretization of the state problem are all decoupled, in contrast to standard methods such as Dynamic Programming.In this paper, the optimization problem is solved by seeking a stationary point of the pertinent Lagrangian functional, resulting in a Newton-type iterative algorithm. Moreover, the sensitivity of the solution with respect to measurement noise may also be estimated from a perturbation analysis of the optimality conditions. Two numerical examples show that the approach produces results in agreement with those of standard methods, however, with the additional advantage the numerical properties of the considered problem may be investigated. In particular, such knowledge may be used for choosing a proper amount of regularization.

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Section: Discretized Newton Updatementioning

confidence: 98%

Section: Z(t)mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A strategy for input estimation with sensitivity analysis

Nordström

Johansson

Larsson

2006

Numerical Meth Engineering

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“…An inverse vibrations problem to monitor and inspect the structural integrity of multi-story building is formulated in [28], whereas an experimental approach based on vibration measurements is presented in [29] for crack identification in structural members. A crack detection technique based on a dynamic stiffness inverse vibration formulation is presented in [30,31]; within the same framework, a nonlinear inverse problem approach to estimate the external forces in displacement-dependent parameters models is presented in [32,33].…”

Section: Introductionmentioning

confidence: 99%

Sensing linear viscoelastic constitutive parameters with a Timoshenko beam on a multi-layer foundation: Modeling and simulation

Fattahi

Spinello

2015

Sensing and Bio-Sensing Research

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a b s t r a c tWe present a sensor model comprised of a Timoshenko beam coupled with a linear viscoelastic substrate via a distributed system of compliant elements. The system of governing equations includes the evolution of the kinematic descriptors of the Timoshenko beam and of the interface between the coupling elements and the viscoelastic substrate. This model is used to pose an inverse problem aimed at estimating the constitutive parameters of the substrate from deformation measurements of the beam. The sensing model is demonstrated by comparing its prediction with published experimentally obtained constitutive parameters identifying standard linear viscoelastic material models, showing good agreement between model estimations and experimental results.

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“…The conjugate gradient method is used to determine the unknown loading of a nonlinear single-degree-of-freedom system in [7,8]. An artificial neural network is used in [9] to find loads acting on aircraft wings.…”

Section: Introductionmentioning

confidence: 99%

An Iterative Approach to Road/Profile Identification Utilizing Wavelet Parameterization

Nordberg¹

2004

Vehicle System Dynamics

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A time domain simulation error method is presented in the following article for estimating the excitation of structural systems from local operational responses. The present study focuses on the case in which the location of the excitation is known a priori, as it is for the interaction of the road profile and the tyre patch for an automotive vehicle. The road profile is parameterized into coefficients using truncated sets of base functions which greatly reduce the number of unknowns in the resulting non-linear optimization problem. A complex non-linear model of a ground excited vehicle is utilized to illustrate the applicability and performance of the method.

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A Non-Linear Inverse Vibration Problem of Estimating the External Forces for a System With Displacement-Dependent Parameters

Cited by 33 publications

References 11 publications

A strategy for input estimation with sensitivity analysis

A strategy for input estimation with sensitivity analysis

Sensing linear viscoelastic constitutive parameters with a Timoshenko beam on a multi-layer foundation: Modeling and simulation

An Iterative Approach to Road/Profile Identification Utilizing Wavelet Parameterization

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