4.7 Article

Clustering of AE signals collected during torsional tests of 3D braiding composite shafts using PCA and FCM

Journal

COMPOSITES PART B-ENGINEERING
Volume 161, Issue -, Pages 547-554

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.compositesb.2018.12.145

Keywords

Acoustic emission; 3D braiding composites shaft; Torsional test; Principal component analysis; Fuzzy clustering method

Funding

  1. National Natural Science Foundation of China [11872025, 11520101001, 11672279, 51502276]
  2. Jiangsu Province Science Foundation for Youths [BK20170518, BK20180878]
  3. Natural Science Foundation of Colleges and Universities in Jiangsu Province [18KJB560004]
  4. Foundation for Advanced Talent of Jiangsu University [16JDG027]

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In this work, the acoustic emission (AE) signals collected during the torsional tests of the 3D braiding composite shafts were clustered using the principal component analysis (PCA) and the fuzzy clustering method (FCM). The 3D 4-directional braided composite shafts with various braiding angles were prepared using Vacuum Assisted Resin Transfer Moulding (VARTM). The torsional tests were performed on the static torsion machine and the AE was used to monitor the damage progression. The AE signals were analyzed by PCA and FCM. The accumulated damage was manifested by matrix cracking, fiber bundle-matrix debonding, and fiber breakage by the proposed method. The failure modes and the mechanisms of the 3D 4-directional braided composite shafts were characterized. The results will play important engineering roles in the design and the application of the 3D 4-directional braided composite shaft.

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