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Spectral analysis for non-linear systems, Part II: Interpretation of non-linear frequency response functions

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TLDR
In this paper, the interpretation and properties of the non-linear frequency response functions are discussed and illustrated by example, and new methods of parametric spectral analysis for a wide class of nonlinear systems were introduced.
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This article is published in Mechanical Systems and Signal Processing.The article was published on 1989-10-01. It has received 99 citations till now. The article focuses on the topics: Frequency response & Parametric statistics.

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Citations
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Past, present and future of nonlinear system identification in structural dynamics

TL;DR: In this article, a review of the past and recent developments in system identification of nonlinear dynamical structures is presented, highlighting their assets and limitations and identifying future directions in this research area.
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An identification algorithm for polynomial NARX models based on simulation error minimization

TL;DR: Two modifications are suggested: namely, a new index, based on the simulation error, is employed as the regressor selection criterion and a pruning mechanism is introduced in the model selection algorithm, which is shown to be effective in the identification of compact and robust models.
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Proper orthogonal decomposition for model updating of non-linear mechanical systems

TL;DR: In this paper, the use of the proper orthogonal modes of displacements for the identification of parameters of non-linear dynamical structures with an optimisation procedure based on the difference between the experimental and simulated POM.
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A procedure for the identification of linear and non-linear multi-degree-of-freedom systems

TL;DR: In this paper, a generalized non-iterative approach in which spectral techniques are used is presented for the identification of multi-degree-of-freedom systems from input/output records, which is suitable for the analysis not only of systems with significant cross-damping but also of highly coupled nonlinear systems.
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Interpretation of non-linear frequency response functions

TL;DR: In this article, analytical and graphical methods of interpreting generalised frequency response functions for non-linear systems are derived and it is shown that nonlinear phenomena can be classified into intra-kernel and inter-kernel interference and that worstcase responses can be computed.
References
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Journal ArticleDOI

Spectral analysis for non-linear systems, Part I: Parametric non-linear spectral analysis

TL;DR: A new theory of spectral analysis for non-linear systems is introduced which consists of estimating the parameters in a NARMAX model description of the system and then computing the generalised frequency response functions directly from the estimated model.
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Spectral analysis for non-linear systems, part III: Case study examples

TL;DR: The algorithms derived in Part I are applied to estimate the generalised frequency response functions of two unknown real systems and the results are interpreted using the techniques developed in Part II of the study.

Estimating Higher Order Spectra

TL;DR: In this article, new parametric algorithms for estimating the frequency response for linear systems and generalised frequency response functions for nonlinear systems are described and a generalized frequency response function is proposed.