IMPLEMENTATION OF AUTOMATED EDDY CURRENT TESTING TOOLS IN TECHNICAL DIAGNOSTICS SYSTEMS

Abstract

This study presents a comprehensive analysis of methods for configuring and optimizing automated eddy current testing tools in technical diagnostics systems. The advantages of eddy current testing were analyzed, and its classification was determined based on methodological, functional, technical, operational, and industry-specific characteristics. The evaluation of the effectiveness of automated eddy current testing tools in technical diagnostics should consider regulatory requirements, regulatory control, and economic feasibility, ensuring compliance with international standards and cost optimization. It was noted that the use of multi-channel sensor arrays significantly improves the efficiency of technical diagnostics with modern matrix-type eddy current testing tools, reducing monitoring time and enhancing defect detection effectiveness. It was determined that the primary task of improving the productivity of eddy current testing is the effective processing of electrical signals from sensor arrays, which allows for accurate amplitude and phase characterization of the signal. Digital extraction of these characteristics using discrete Hilbert transforms and adapted mathematical techniques helps to reduce errors and improve diagnostic accuracy, which is essential for defectoscopy tasks. Furthermore, the study proposed mathematical modeling of diagnostic processes based on sensors from the eddy current testing complex, which enables effective detection of defects on surfaces and in subsurface layers of materials, as well as adaptation of the model for solving other engineering problems such as crack detection and mechanical damage in objects with complex geometries. Signals received from the sensors during scanning reflect changes in voltage levels that occur when passing over defects, and are converted into digital values that allow for determining the depth of the defects. A three-dimensional map of the object is formed during the scanning process, and specialized algorithms for sensor connection management and placement schemes are used to enhance diagnostic accuracy and scanning speed.