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.

Ultrasonic Imaging System Based on Virtual Instrument

2013 ◽  
Vol 663 ◽  
pp. 616-620
Author(s):  
Yu Gong ◽  
Yue Gang Hu ◽  
Guo Rong Song ◽  
Cun Fu He ◽  
Bin Wu
Keyword(s):  
Cross Section ◽  
Virtual Instrument ◽  
Imaging System ◽  
Complex Structures ◽  
Non Destructive Testing ◽  
Destructive Testing ◽  
Bulk Metal ◽  
Instrument Technology ◽  
Control Devices ◽  
Non Destructive

An imaging system of ultrasonic detection is presented for non-destructive testing (NDT) of complex structures by using virtual instrument technology. The control devices for C-scan as well as for imaging system are designed and manufactured. In the coarse scan mode with the scan step of 1 mm, the system can quickly give an image display of a cross section of 80 mm (L) ×60 mm (D) by one measurement. In the refined scan model, the system can show a refine image of the coin. All experiments on coin, bulk metal, and other forms of specimen verify the efficiency of the proposed method. The experimental results are accurate and reliable.

scholarly journals A Cost-Effective System for Aerial 3D Thermography of Buildings

2020 ◽  
Vol 6 (8) ◽  
pp. 76
Author(s):  
Claudia Daffara ◽  
Riccardo Muradore ◽  
Nicola Piccinelli ◽  
Nicola Gaburro ◽  
Tullio de Rubeis ◽  
...  
Keyword(s):  
3D Imaging ◽  
Three Dimensional ◽  
Cost Effective ◽  
Complex Structures ◽  
Non Destructive Testing ◽  
Ir Thermography ◽  
Destructive Testing ◽  
Effective System ◽  
Reconstruction Software ◽  
Non Destructive

Three-dimensional (3D) imaging and infrared (IR) thermography are powerful tools in many areas in engineering and sciences. Their joint use is of great interest in the buildings sector, allowing inspection and non-destructive testing of elements as well as an evaluation of the energy efficiency. When dealing with large and complex structures, as buildings (particularly historical) generally are, 3D thermography inspection is enhanced by Unmanned Aerial Vehicles (UAV—also known as drones). The aim of this paper is to propose a simple and cost-effective system for aerial 3D thermography of buildings. Special attention is thus payed to instrument and reconstruction software choice. After a very brief introduction to IR thermography for buildings and 3D thermography, the system is described. Some experimental results are given to validate the proposal.

A Non-Destructive Testing Based on Electromagnetic Measurements and Neural Networks for the Inspection of Concrete Structures

2011 ◽  
Vol 301-303 ◽  
pp. 597-602 ◽  
Author(s):  
Naasson P. de Alcantara ◽  
Danilo C. Costa ◽  
Diego S. Guedes ◽  
Ricardo V. Sartori ◽  
Paulo S. S. Bastos
Keyword(s):  
Neural Networks ◽  
Concrete Structures ◽  
Concrete Surface ◽  
Non Destructive Testing ◽  
Destructive Testing ◽  
Electromagnetic Devices ◽  
Electromagnetic Measurements ◽  
Steel Bars ◽  
Non Destructive ◽  
The Magnetic Field

This paper presents a new non-destructive testing (NDT) for reinforced concrete structures, in order to identify the components of their reinforcement. A time varying electromagnetic field is generated close to the structure by electromagnetic devices specially designed for this purpose. The presence of ferromagnetic materials (the steel bars of the reinforcement) immersed in the concrete disturbs the magnetic field at the surface of the structure. These field alterations are detected by sensors coils placed on the concrete surface. Variations in position and cross section (the size) of steel bars immersed in concrete originate slightly different values for the induced voltages at the coils.. The values ​​for the induced voltages were obtained in laboratory tests, and multi-layer perceptron artificial neural networks with Levemberg-Marquardt training algorithm were used to identify the location and size of the bar. Preliminary results can be considered very good.

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