scispace - formally typeset
Proceedings ArticleDOI

Prediction of damage location in composite plates using artificial neural network modeling

Reads0
Chats0
TLDR
The main objective of this article is to develop a neural network based methodology for prediction of damage location, particularly for the bond inspection of composite plates.
Abstract
Composite is one of the most widely used industrial materials because of high strength, low weight, and high corrosion resistance properties. Different parts of composite structures are normally joined using adhesives or fasteners that are prone to defects and damages. A reliable method for prediction of the defect location is needed for an efficient structural health monitoring (SHM) process. Heterodyne effect is recently utilized for damage detection in the bonding zone of composite structures where debonding is expected to change the linear characteristics of the system into nonlinear characteristics. This paper briefly introduces this novel defect locating approach in composite plates using the heterodyne effect. For the first time, an Artificial Neural Network methodology is utilized with heterodyne effect method to find the defect location in composite plates. The main objective of this article is to develop a neural network based methodology for prediction of damage location, particularly for the bond inspection of composite plates.

read more

Citations
More filters
Journal ArticleDOI

Advances in Computational Intelligence of Polymer Composite Materials: Machine Learning Assisted Modeling, Analysis and Design

TL;DR: In this article , a broad spectrum potential of ML in applications like prediction, optimization, feature identification, uncertainty quantification, reliability and sensitivity analysis along with the framework of different ML algorithms concerning polymer composites are discussed.
Journal ArticleDOI

Acoustic emission source location using Lamb wave propagation simulation and artificial neural network for I-shaped steel girder

TL;DR: The results indicate that using trained neural networks based on numerical data is a viable option for AE source location in the case of the I-shaped girder, increasing the likelihood of design and optimization of the AE technique in monitoring realistic structures.
Journal ArticleDOI

Comparison of neural networks based on accuracy and robustness in identifying impact location for structural health monitoring applications

TL;DR: In this article , the authors quantitatively compared three widely used neural networks, namely, Artificial Neural Network (ANN), Convolutional Neural Networks (CNN), and Long Short-Term Memory network (LSTM), to estimate impact location from the lead zirconate titanate (PZT) sensor response.
References
More filters
Journal ArticleDOI

A logical calculus of the ideas immanent in nervous activity

TL;DR: In this article, it is shown that many particular choices among possible neurophysiological assumptions are equivalent, in the sense that for every net behaving under one assumption, there exists another net which behaves under another and gives the same results, although perhaps not in the same time.
Book

Introduction To The Theory Of Neural Computation

TL;DR: This book is a detailed, logically-developed treatment that covers the theory and uses of collective computational networks, including associative memory, feed forward networks, and unsupervised learning.
Journal ArticleDOI

A logical calculus of the ideas immanent in nervous activity

TL;DR: It is shown that many particular choices among possible neurophysiological assumptions are equivalent, in the sense that for every net behaving under one assumption, there exists another net which behaves under the other and gives the same results, although perhaps not in the same time.
Journal ArticleDOI

An introduction to computing with neural nets

TL;DR: This paper provides an introduction to the field of artificial neural nets by reviewing six important neural net models that can be used for pattern classification and exploring how some existing classification and clustering algorithms can be performed using simple neuron-like components.

A review of structural health monitoring literature 1996-2001

TL;DR: An updated review covering the years 1996 2001 will summarize the outcome of an updated review of the structural health monitoring literature, finding that although there are many more SHM studies being reported, the investigators, in general, have not yet fully embraced the well-developed tools from statistical pattern recognition.
Related Papers (5)