5. Summary
In this article, it is shown that artificial neural networks and ANFIS-type neuro-fuzzy systems are effective tools for identifying thermophysical properties and, consequently, a relevant aid to non-destructive testing. The measurements used are responses to excitations with a pseudo-random time profile (PRBS).
As a first step, a forward-propagating neural network of the multilayer Perceptron type was used. Once its topology had been defined and its adjustable parameters identified, this network was capable of accurately estimating the thermal diffusivity of a homogeneous material from its response to a forward or reverse PRBS. To achieve this, we first trained it with a series of fictitious materials of varying thermal behavior, derived from simulations. Then, an initial validation was carried out, again using simulated materials, to check the relevance of the...
Exclusive to subscribers. 97% yet to be discovered!
You do not have access to this resource.
Click here to request your free trial access!
Already subscribed? Log in!
The Ultimate Scientific and Technical Reference
This article is included in
Software technologies and System architectures
This offer includes:
Knowledge Base
Updated and enriched with articles validated by our scientific committees
Services
A set of exclusive tools to complement the resources
Practical Path
Operational and didactic, to guarantee the acquisition of transversal skills
Doc & Quiz
Interactive articles with quizzes, for constructive reading
Summary
Bibliography
Patents
BODNAR (J.L.), CANDORE (J.C.), CARON (D.), NICOLAS (J.L.) . – Système de contrôle non destructif étendu (SAMMTHIR), French patent filed with INPI on March 26, 2008, number 08/01646.
Exclusive to subscribers. 97% yet to be discovered!
You do not have access to this resource.
Click here to request your free trial access!
Already subscribed? Log in!
The Ultimate Scientific and Technical Reference