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Online segmentation of acoustic emission data streams for detection of damages in composites structures in unconstrained environments
[chapter]
2014
Safety, Reliability, Risk and Life-Cycle Performance of Structures and Infrastructures
An approach for unsupervised damage detection in ring-shaped Organic Matrix Composites (OMC) under loading based on acoustic emissions (AE) is proposed. It relies on a specific clustering algorithm called Gustafson-Kessel (GK) that manages fuzzy memberships to clusters and complex cluster's shape. A methodology is proposed to 1) make the algorithm robust to initialisation in order to obtain reproducible results and reliable statistical models representing OMC damages, 2) detect and assess AE
doi:10.1201/b16387-78
fatcat:hcyxpfqxvngp3cybmasjth4dai