Journal Article

High-resolution non-destructive evaluation of defects using artificial neural networks and wavelets

Abstract

This paper presents artificialneuralnetworks (ANN) and wavelet analysis as methods that can assist highresolutionof multiple defects in close proximity in components. Without careful attention to analysis, multiple defects can be mis-interpreted as single defects and with the possibility of significantly underestimated sizes. The analysis in this work focussed on A-scan type ultrasonic signal. Amplitudes corresponding to the sizes of two defects as well as the phase shift parameter representing the distance between them were determined. The results obtained demonstrate very good correlation for sizes and distances respectively even in cases involving noisy signal data

Attached files

Authors

Farley, S
Durodola, J
Fellows, N
Hernandez-Gomez, L

Oxford Brookes departments

Faculty of Technology, Design and Environment\Department of Mechanical Engineering and Mathematical Sciences

Dates

Year of publication: 2012
Date of RADAR deposit: 2013-05-31

---

---

Related resources

This RADAR resource is the Accepted Manuscript of High-resolution non-destructive evaluation of defects using artificial neural networks and wavelets