Title
Adaptive neuro-fuzzy estimation of conductive silicone rubber mechanical properties
Abstract
Conductive silicone rubber has great advantages for tactile sensing applications. The electrical behavior of the elastomeric material is rate-dependent and exhibit hysteresis upon cyclic loading. Several constitutive models were developed for mechanical simulation of this material upon loading and unloading. One of the successful approaches to model the time-dependent behavior of elastomers is Bergstrom-Boyce model. An adaptive neuro-fuzzy inference system (ANFIS) model will be established in this study to predict the stress-strain changing of conductive silicone rubber during compression tests. Various compression tests were performed on the produced specimens. An ANFIS is used to approximate correlation between measured features of the material and to predict its unknown future behavior for stress changing. ANFIS has unlimited approximation power to match any nonlinear functions well and to predict a chaotic time series.
Year
DOI
Venue
2012
10.1016/j.eswa.2012.02.111
Expert Syst. Appl.
Keywords
Field
DocType
cyclic loading,time-dependent behavior,mechanical property,constitutive model,bergstrom-boyce model,conductive silicone rubber,unknown future behavior,various compression test,compression test,electrical behavior,adaptive neuro-fuzzy estimation,elastomeric material,strain stress
Compression (physics),Data mining,Neuro-fuzzy,Composite material,Computer science,Hysteresis,Silicone rubber,Stress–strain curve,Adaptive neuro fuzzy inference system,Elastomer,Constitutive equation
Journal
Volume
Issue
ISSN
39
10
0957-4174
Citations 
PageRank 
References 
15
1.21
4
Authors
5
Name
Order
Citations
PageRank
Dalibor Petkovic122320.91
Mirna Issa2533.65
Nenad D. Pavlović3653.77
Nenad T. Pavlović4312.08
Lena Zentner5534.33