Artificial intelligence for help in decision making during non Destructive Testing of Materials

2014 ◽  
Author(s):  
Thouraya Merazi-Meksen ◽  
Malika Boudraa ◽  
Bachir Boudraa
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
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.

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

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

The Soil Base Bearing Capacity Relevance Research in the Highway Overhaul Decision-Making

2013 ◽  
Vol 361-363 ◽  
pp. 1778-1782
Author(s):  
Jie Sun ◽  
Qiang Sun ◽  
Ming Hua Wang
Keyword(s):  
Decision Making ◽  
Bearing Capacity ◽  
Linear Relationship ◽  
Non Destructive Testing ◽  
Soil Base ◽  
Destructive Testing ◽  
Good Linear ◽  
The Road ◽  
Good Linear Relationship ◽  
Non Destructive

Based on theexamples works of the road site excavation pits channels and supplemented by road non-destructive testing methods, this paper mainly adopts the road performance of the structural layers , main site designated point FWD test, soil base DCP test and soil base structure bearing capacity correlation. The results show that the existing common road on FWD detection inverse soil base modulus has a good linear relationship with soil base DCP measured modulus, in addition, measured soil base modulus with moisture content of the soil base also have a good linear relationship, but the three correlation does not comply with the actual situation of the road. Thus, before the decision making of the highway overhaul conservation , old Road usage evaluation, the road of non-destructive testing, the excavation pits survey and structural layers indicators detection are very necessary and effective methods.

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
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