Abstract
Abstract The article presents a review of modern non-destructive testing (NDT) methods used for monitoring the technical condition of belt conveyor drive systems. The main diagnostic approaches are considered, including vibration diagnostics, thermal imaging inspection, analysis of electrical parameters of drive motors, acoustic emission methods, and intelligent monitoring systems based on machine learning and computer vision. A comparative analysis of the capabilities of various NDT methods has been carried out in terms of their informativeness, sensitivity to early-stage defects, and applicability in industrial conditions. It is shown that vibration and electrical diagnostics provide the highest efficiency in continuous monitoring of drive units. In contrast, thermal imaging and visual inspection are advisable to use as part of integrated equipment condition assessment systems. Particular attention is paid to modern approaches based on Motor Current Signature Analysis (MCSA) and signal processing methods using neural network algorithms. It is noted that integrating several diagnostic methods increases the reliability of defect detection and enables the transition to predictive maintenance. Based on the review, developing multi-level monitoring systems that integrate electrical, vibration, thermal, and intelligent diagnostic methods is advisable to enhance the reliability and operational efficiency of belt conveyors.