Volume 5, Issue 3
Investigation on Damage Mechanisms of PE Self-reinforced Composites by Acoustic Emission Technology

Xu Wang & Song-Mei Bi

Journal of Fiber Bioengineering & Informatics, 5 (2012), pp. 281-287.

Published online: 2012-05

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  • Abstract

The purpose of this study is to investigate the damage mechanisms in UHMWPE/LDPE laminated by Acoustic Emission (AE) technique. Model specimens are fabricated to obtain expected damage mechanisms during tensile testing. Then, relationship among AE descriptors is studied by hierarchical cluster analysis, and AE signals are classified by k-means algorithm. Finally, an Artificial Neural Network (ANN) is created and trained by various optimal algorithms to identify damage mechanisms. The results reveal that typical damage mechanisms in PE self-reinforced composite can be classified in terms of the similarity between AE signals and identified by a well trained ANN.

  • Keywords

Damage Mechanisms PE Self-reinforced Composite Acoustic Emission Clustering Analysis Artificial Neural Network

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COPYRIGHT: © Global Science Press

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@Article{JFBI-5-281, author = {}, title = {Investigation on Damage Mechanisms of PE Self-reinforced Composites by Acoustic Emission Technology}, journal = {Journal of Fiber Bioengineering and Informatics}, year = {2012}, volume = {5}, number = {3}, pages = {281--287}, abstract = {The purpose of this study is to investigate the damage mechanisms in UHMWPE/LDPE laminated by Acoustic Emission (AE) technique. Model specimens are fabricated to obtain expected damage mechanisms during tensile testing. Then, relationship among AE descriptors is studied by hierarchical cluster analysis, and AE signals are classified by k-means algorithm. Finally, an Artificial Neural Network (ANN) is created and trained by various optimal algorithms to identify damage mechanisms. The results reveal that typical damage mechanisms in PE self-reinforced composite can be classified in terms of the similarity between AE signals and identified by a well trained ANN.}, issn = {2617-8699}, doi = {https://doi.org/10.3993/jfbi09201206}, url = {http://global-sci.org/intro/article_detail/jfbi/4882.html} }
TY - JOUR T1 - Investigation on Damage Mechanisms of PE Self-reinforced Composites by Acoustic Emission Technology JO - Journal of Fiber Bioengineering and Informatics VL - 3 SP - 281 EP - 287 PY - 2012 DA - 2012/05 SN - 5 DO - http://doi.org/10.3993/jfbi09201206 UR - https://global-sci.org/intro/article_detail/jfbi/4882.html KW - Damage Mechanisms KW - PE Self-reinforced Composite KW - Acoustic Emission KW - Clustering Analysis KW - Artificial Neural Network AB - The purpose of this study is to investigate the damage mechanisms in UHMWPE/LDPE laminated by Acoustic Emission (AE) technique. Model specimens are fabricated to obtain expected damage mechanisms during tensile testing. Then, relationship among AE descriptors is studied by hierarchical cluster analysis, and AE signals are classified by k-means algorithm. Finally, an Artificial Neural Network (ANN) is created and trained by various optimal algorithms to identify damage mechanisms. The results reveal that typical damage mechanisms in PE self-reinforced composite can be classified in terms of the similarity between AE signals and identified by a well trained ANN.
Xu Wang & Song-Mei Bi. (2019). Investigation on Damage Mechanisms of PE Self-reinforced Composites by Acoustic Emission Technology. Journal of Fiber Bioengineering and Informatics. 5 (3). 281-287. doi:10.3993/jfbi09201206
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