SoC-Based Pattern Recognition Systems for Non Destructive Testing

2015 ◽  
pp. 209-221
Author(s):  
Omar Schiaratura ◽  
Pietro Ansaloni ◽  
Giovanni Lughi ◽  
Mattia Neri ◽  
Matteo Roffilli ◽  
...  
Keyword(s):  
Pattern Recognition ◽  
Non Destructive Testing ◽  
Destructive Testing ◽  
Pattern Recognition Systems ◽  
Recognition Systems ◽  
Non Destructive

Advanced Signal Processing Techniques in Non-Destructive Testing

2011 ◽  
pp. 127-146
Author(s):  
A. Al-Ataby ◽  
W. Al-Nuaimy
Keyword(s):  
Pattern Recognition ◽  
Signal Processing ◽  
Non Destructive Testing ◽  
Destructive Testing ◽  
Recent Advances ◽  
Processing Techniques ◽  
Non Destructive ◽  
Signal Processing Techniques

This chapter describes some recent advances in signal processing as applied to NDT problems. This is an area that has made progress for over twenty years and its importance is gaining attention gradually, especially since the new advanced techniques in signal processing and pattern recognition.

scholarly journals Diverse time-frequency distributions integrated to an art2 network for non-destructive testing

2008 ◽  
Vol 6 (01) ◽  
Author(s):  
H. Bení­tez-Pérez ◽  
L. Medina-Gómez
Keyword(s):  
Neural Network ◽  
Pattern Recognition ◽  
Ultrasonic Pulse ◽  
Non Destructive Testing ◽  
Destructive Testing ◽  
Resonance Theory ◽  
Frequency Distributions ◽  
Time Frequency ◽  
The Neural Network ◽  
Non Destructive

The Ultrasonic Pulse-Echo technique has been successfully used in a non-destructive testing of materials. To perform Ultrasonic Non-destructive Evaluation (NDE), an ultrasonic pulsed wave is transmitted into the materials using a transmitting/receiving transducer or arrays of transducers,that produces an image of ultrasonic reflectivity. The information inherent in ultrasonic signals or image are the echoes coming from flaws, grains, and boundaries of the tested material. The main goal of this evaluation is to determine the existence of defect, its size and its position; for that matter, an innovative methodology is proposed based on pattern recognition and wavelet analysis for flaws detection and localization. The pattern recognition technique used in this work is the neural network named ART2 (Adaptive Resonance Theory) trained by the information given by the time-scale information of the signals via the wavelet transform. A thorough analysis between the neural network training and the type wavelets used for the training has been developed, showing that the Symlet 6 wavelet is the optimum for our problem.

Non destructive testing of works of art by terahertz analysis

2013 ◽  
Vol 64 (2) ◽  
pp. 21001 ◽  
Author(s):  
Jean-Luc Bodnar ◽  
Jean-Jacques Metayer ◽  
Kamel Mouhoubi ◽  
Vincent Detalle
Keyword(s):  
Non Destructive Testing ◽  
Destructive Testing ◽  
Works Of Art ◽  
Non Destructive

Modeling of a sensitive element on a planar mushroom-shaped metamaterial for non-destructive testing and searching for inhomogeneities in technological media

2020 ◽  
pp. 54-59
Author(s):  
A. A. Yelizarov ◽  
A. A. Skuridin ◽  
E. A. Zakirova
Keyword(s):  
Sensitive Element ◽  
Non Destructive Testing ◽  
Destructive Testing ◽  
Resonant Frequency Shift ◽  
Maltese Cross ◽  
Informative Parameters ◽  
Non Destructive ◽  
Cross Type ◽  
Electrodynamic Structure ◽  
Electrophysical Parameters

A computer model and the results of a numerical experiment for a sensitive element on a planar mushroom-shaped metamaterial with cells of the “Maltese cross” type are presented. The proposed electrodynamic structure is shown to be applicable for nondestructive testing of geometric and electrophysical parameters of technological media, as well as searching for inhomogeneities in them. Resonant frequency shift and change of the attenuation coefficient value of the structure serve as informative parameters.

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