Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/24877
Title: Diagnostic feature extraction and filtering criterion for fatigue crack growth using high frequency parametrical analysis
Authors: Angulo, Á
Mares, C
Gan, TH
Keywords: parametrical analysis;signal feature extraction;high-frequency signals;filtering criterion;fatigue crack growth;mooring chains
Issue Date: 24-Jul-2021
Publisher: MDPI
Citation: Angulo, A., Mares, C., Gan, T.H. (2021) 'Diagnostic feature extraction and filtering criterion for fatigue crack growth using high frequency parametrical analysis', Sensors, 21(15), pp. 1 - 20. doi:10.3390/s21155030.
Abstract: Mooring systems are an integral and sophisticated component of offshore assets and are subject to harsh conditions and cyclic loading. The early detection and characterisation of fatigue crack growth remain a crucial challenge. The scope of the present work was to establish filtering and alarm criteria for different crack growth stages by evaluating the recorded signals and their features. The analysis and definition of parametrical limits, and the correlation of their characteristics with the crack, helped to identify approaches to discriminate between noise, initiation, and growth-related signals. Based on these, a filtering criterion was established, to support the identifi-cation of the different growth stages and noise with the aim to provide early warnings of potential damage.
URI: http://bura.brunel.ac.uk/handle/2438/24877
DOI: http://dx.doi.org/10.3390/s21155030
ISSN: 1424-8220
Appears in Collections:Dept of Mechanical and Aerospace Engineering Research Papers

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