A Review of Artificial Intelligence Applications in Thermographic Non-Destructive Testing

2021 ◽  
Author(s):  
Kailun Deng ◽  
Lichao Yang ◽  
Haochen Liu ◽  
Wenhan Li ◽  
John Ahmet Erkoyuncu ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Non Destructive Testing ◽  
Destructive Testing ◽  
Non Destructive

scholarly journals A NEW APPROACH TO ASSESSING THE OPERATIONAL SAFETY OF COMPOSITE MATERIALS AND PARTS OF COMPLEX STRUCTURES BASED ON ARTIFICIAL INTELLIGENCE METHODS AS A PART OF NEURAL NETWORKS AND DEEP RESULTS OF MULTI-CRITERIA COMPLEX NON-DESTRUCTIVE TESTING

2020 ◽  
pp. 18-27
Author(s):  
D. A. Akimov ◽  
A. D. Kleymenov ◽  
S. O. Kozelskaya ◽  
O. N. Budadin
Keyword(s):  
Artificial Intelligence ◽  
Neural Networks ◽  
Complex Structures ◽  
Non Destructive Testing ◽  
Destructive Testing ◽  
New Approach ◽  
Heterogeneous Information ◽  
Operational Safety ◽  
Non Destructive

The article proposes a new approach to assessing the operational safety of materials and parts of complex structures based on artificial intelligence methods based on artificial neural networks and multi-criteria complex non-destructive testing, and special mathematical and algorithmic support for systems for evaluating operational safety and predicting residual life under external influences. A method of morphological analysis of the procedures for using measurement tools for heterogeneous information with different a priori information, both about the type of characteristics and the distribution of errors in the input and output signals, has been developed. The classification of problems of measuring parameters for the integration of heterogeneous information is proposed. A macromodel of error is obtained that can be used for research purposes to minimize errors in the developed equipment or for the purpose of correcting errors during operation. A classification of methods for measuring heterogeneous information from the standpoint of probability distribution theory is proposed. Experimental testing of developed algorithms tailored aggregation of information non-destructive testing and adaptation to poorly formalized parameters, which confirmed the effectiveness of the developed methods and algorithms for assessment of structures and resource forecasting their operational reliability was carried out.

Artificial intelligence for non-destructive testing of CFRP prepreg materials

2019 ◽  
Vol 13 (5) ◽  
pp. 617-626 ◽  
Author(s):  
Carsten Schmidt ◽  
Tristan Hocke ◽  
Berend Denkena
Keyword(s):  
Artificial Intelligence ◽  
Non Destructive Testing ◽  
Destructive Testing ◽  
Non Destructive

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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