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Registration Number

0224U031423, 0123U105198 , R & D reports

Title

Research on the Prospects of Applying Automated Control with a Learning Neuroregulator in Multifrequency Eddy Current Non-Destructive Testing

Head

Bazhenov Viktor , Кандидат технічних наук

Registration Date

24-04-2024

Organization

National Technscal University of Ukraine "Kiev Polytechnic Institute".

Description

Non-destructive testing (NDT) is a crucial stage in the manufacturing and operation of products made from various materials. Due to its informativeness, simplicity, and affordability, the Eddy Current Testing (ECT) method is widely used in many industries. However, traditional ECT methods have several drawbacks. The use of phase trajectories, defect signals, and other parameters requires considerable experience and qualification of the operator. Data processing and defect detection are usually performed manually, which limits the inspection speed. The inspection results depend on the operator's data interpretation, which can lead to errors. This report is devoted to the substantiation of the development and research of an automated control system with a learning neuroregulator for multi-frequency eddy current non-destructive testing. Such a system will allow to increase the accuracy and reliability of defect detection, increase inspection productivity by automating data processing, reduce the subjectivity of the inspection results assessment. The analysis of literature sources on ECT, neural networks, and automated control showed that the development of a mathematical model of an automated control system with a learning neuroregulator is an actual task, since computer simulation of such systems has not been performed. Accordingly, experimental studies of the proposed system on laboratory samples will help to analyze the possibilities of increasing the accuracy and reliability of defect detection by such systems. In addition, it will allow to increase the inspection productivity and reduce the subjectivity of the inspection results assessment. This topic is relevant and has practical value, since there have been very few works on automated control with a learning neuroregulator for multi-frequency eddy current non-destructive testing.

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Kalenychenko Yurii O.
Lysenko Yuliia Yu.
Momot Andrii S.
Muraviov Oleksandr V.
Ratsebarskyi Serhii S.