scholarly journals Failure strength prediction of glass/epoxy composite laminates from acoustic emission parameters using artificial neural network

2017 ◽  
Vol 115 ◽  
pp. 32-41 ◽  
Author(s):  
C. Suresh Kumar ◽  
V. Arumugam ◽  
R. Sengottuvelusamy ◽  
S. Srinivasan ◽  
H.N. Dhakal
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Acoustic Emission ◽  
Composite Laminates ◽  
Epoxy Composite ◽  
Strength Prediction ◽  
Failure Strength ◽  
Artificial Neural

Research of the cold resistance of metals by indentation with registration of an acoustic emission signal

2020 ◽  
pp. 61-64
Author(s):  
Yu.G. Kabaldin ◽  
A.A. Khlybov ◽  
M.S. Anosov ◽  
D.A. Shatagin
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Acoustic Emission ◽  
Acoustic Emission Signal ◽  
Low Temperatures ◽  
Cold Resistance ◽  
Emission Signal ◽  
Impact Bending ◽  
Artificial Neural

The study of metals in impact bending and indentation is considered. A bench is developed for assessing the character of failure on the example of 45 steel at low temperatures using the classification of acoustic emission signal pulses and a trained artificial neural network. The results of fractographic studies of samples on impact bending correlate well with the results of pulse recognition in the acoustic emission signal. Keywords acoustic emission, classification, artificial neural network, low temperature, character of failure, hardness. [email protected]

scholarly journals Effect of Freeze–Thaw Cycling on the Failure of Fibre-Cement Boards, Assessed Using Acoustic Emission Method and Artificial Neural Network

Materials ◽  
2019 ◽  
Vol 12 (13) ◽  
pp. 2181 ◽  
Author(s):  
Tomasz Gorzelańczyk ◽  
Krzysztof Schabowicz
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Acoustic Emission ◽  
Acoustic Emission Method ◽  
Emission Method ◽  
Three Point Bending ◽  
Freeze Thaw ◽  
Fibre Cement ◽  
Artificial Neural ◽  
Building Practice

This paper presents the results of investigations into the effect of freeze–thaw cycling on the failure of fibre-cement boards and on the changes taking place in their structure. Fibre-cement board specimens were subjected to one and ten freeze–thaw cycles and then investigated under three-point bending by means of the acoustic emission method. An artificial neural network was employed to analyse the results yielded by the acoustic emission method. The investigations conclusively proved that freeze–thaw cycling had an effect on the failure of fibre-cement boards, as indicated mainly by the fall in the number of acoustic emission (AE) events recognized as accompanying the breaking of fibres during the three-point bending of the specimens. SEM examinations were carried out to gain better insight into the changes taking place in the structure of the tested boards. Interesting results with significance for building practice were obtained.

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