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Damage modeling and detection for a tree network using fractional-order calculus

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Abstract

Large networks are increasingly common in engineered systems, and therefore, monitoring their operating conditions is increasingly important. This paper proposes a model-based frequency-domain damage detection method for an infinitely large self-similar network. The first aim is to exactly model the overall frequency response for any specific damage case of that network, which we show has an explicit multiplicative relation to the undamaged transfer function. Then, leveraging that knowledge from modeling, this paper also proposes an algorithm to identify damaged components within that network as well as quantifies their respective damage amounts given a noisy measurement for that network’s overall frequency response.

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Authors and Affiliations

  1. Aerospace and Mechanical Engineering, University of Notre Dame, 365 Fitzpatrick Hall, Notre Dame, IN, 46556, USA

    Xiangyu Ni & Bill Goodwine

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  1. Xiangyu Ni
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  2. Bill Goodwine
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Correspondence to Xiangyu Ni.

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Xiangyu Ni has worked in MathWorks for 3 months. The authors have no other conflicts of interest in addition to that.

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The support of the US National Science Foundation under Grant No. CMMI 1826079 is gratefully acknowledged.

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Ni, X., Goodwine, B. Damage modeling and detection for a tree network using fractional-order calculus. Nonlinear Dyn 101, 875–891 (2020). https://doi.org/10.1007/s11071-020-05847-5

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