Open AccessCharacterisation of Damage in Composite Structures using Acoustic Emission
Author(s) -
Mark Jonathan Eaton,
Michaël May,
Carol Ann Featherston,
Karen Margaret Holford,
S. R. Hallet,
Rhys Pullin
Publication year - 2011
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/305/1/012086
Subject(s) - acoustic emission , composite number , delamination (geology) , materials science , composite material , ultimate tensile strength , cracking , lamb waves , structural health monitoring , matrix (chemical analysis) , stress (linguistics) , structural engineering , wave propagation , geology , optics , seismology , physics , engineering , linguistics , philosophy , subduction , tectonics
Detection and characterisation of damage in composite structures during in-service loading is highly desirable. Acoustic emission (AE) monitoring of composite components offers a highly sensitive method for detecting matrix cracking and delamination damage mechanisms in composites. AE relies on the detection of stress waves that are released during damage propagation and using an array of sensors, damage location may be determined. A methodology for damage characterisation based on measuring the amplitude ratio (MAR) of the two primary lamb wave modes; symmetric (in-plane) and asymmetric (out-of-plane) that propagate in plate like structures has been developed. This paper presents the findings of a series of tensile tests in composite coupons with large central ply blocks. The specimens were monitored using AE sensors throughout loading and once significant AE signals were observed the loading process was stopped. The specimens were removed and subjected to x-ray inspec tion to assess for any damage. The onset of damage was successfully detected using AE and was identified as being matrix cracking using the MAR methodology. The results were validated with x-ray inspection and a strong correlation was observed between the number of significant AE signals recorded and the number of identified matrix cracks