Paper
9 March 2014 Nonlinear damage detection in composite structures using bispectral analysis
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Abstract
Literature offers a quantitative number of diagnostic methods that can continuously provide detailed information of the material defects and damages in aerospace and civil engineering applications. Indeed, low velocity impact damages can considerably degrade the integrity of structural components and, if not detected, they can result in catastrophic failure conditions. This paper presents a nonlinear Structural Health Monitoring (SHM) method, based on ultrasonic guided waves (GW), for the detection of the nonlinear signature in a damaged composite structure. The proposed technique, based on a bispectral analysis of ultrasonic input waveforms, allows for the evaluation of the nonlinear response due to the presence of cracks and delaminations. Indeed, such a methodology was used to characterize the nonlinear behaviour of the structure, by exploiting the frequency mixing of the original waveform acquired from a sparse array of sensors. The robustness of bispectral analysis was experimentally demonstrated on a damaged carbon fibre reinforce plastic (CFRP) composite panel, and the nonlinear source was retrieved with a high level of accuracy. Unlike other linear and nonlinear ultrasonic methods for damage detection, this methodology does not require any baseline with the undamaged structure for the evaluation of the nonlinear source, nor a priori knowledge of the mechanical properties of the specimen. Moreover, bispectral analysis can be considered as a nonlinear elastic wave spectroscopy (NEWS) technique for materials showing either classical or non-classical nonlinear behaviour.
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Francesco Ciampa, Simon Pickering, Gennaro Scarselli, and Michele Meo "Nonlinear damage detection in composite structures using bispectral analysis", Proc. SPIE 9064, Health Monitoring of Structural and Biological Systems 2014, 906402 (9 March 2014); https://doi.org/10.1117/12.2046631
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CITATIONS
Cited by 11 scholarly publications.
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KEYWORDS
Composites

Ultrasonics

Sensors

Structural health monitoring

Damage detection

Signal processing

Statistical analysis

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