Neural network prediction of aluminum-silicon carbide tensile strength from acoustic emission rise angle data

Neural network prediction of aluminum-silicon carbide tensile strength from acoustic emission rise angle data

In this work, the ultimate strength of aluminum/silicon carbide (Al/SiC) composites was predicted by using acoustic emission (AE) parameters through artificial neural network (ANN) analysis. With this aim, a series of fourteen Al/SiC tensile samples were loaded up to the failure to investigate the a...

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Bibliographic Details
Main Authors: Christopher Loo Mahil C., Sasikumar T., Santulli C., Fragassa C.
Format: Article
Language:English
Published: University of Belgrade - Faculty of Mechanical Engineering, Belgrade 2018-01-01
Series:FME Transactions
Subjects:
failure prediction
acoustic emission
felicity ratio
riseangle
feed forward neural network
Online Access:https://scindeks-clanci.ceon.rs/data/pdf/1451-2092/2018/1451-20921802253C.pdf

Internet

https://scindeks-clanci.ceon.rs/data/pdf/1451-2092/2018/1451-20921802253C.pdf

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