Dataset · IEEE DataPort · March 27, 2026
"High-Speed Directional Eddy-Current Smart Sensor"
Abstract
"a { text-decoration: none; color: #464feb; } tr th, tr td { border: 1px solid #e6e6e6; } tr th { background-color: #f5f5f5; }This dataset supports an uncertainty\u2011quantified evaluation of a high\u2011speed eddy\u2011current (ECT) sensing system designed for in\u2011line nondestructive inspection. As industrial NDE transitions from controlled laboratory settings to production\u2011rate operation, it becomes essential to establish traceable and standards\u2011compliant uncertainty estimates under realistic measurement conditions. Following the methodology prescribed in VDA 5.1, the uncertainty of two defect\u2011severity indicators\u2014voltage\u2011based and phase\u2011based signal\u2011to\u2011noise ratios (SNR)\u2014was systematically assessed. A structured series\u2011parts study was performed, comprising ten discrete scan velocities and ten repeated measurements at each speed. The resulting dataset enables decomposition of variance contributions using an ANOVA\u2011based framework, providing a transparent basis for quantifying measurement process uncertainty in high\u2011speed ECT applications."
More by Meirbek Mussatayev
- "Quantitative Detectability and Adjacent-Defect Resolution in Directional Eddy-Current Inspection of Rail Defects"IEEE DataPort · 2026
- High-speed directional eddy-current smart sensor with VDA 5.1–compliant uncertainty analysisScientific Reports · 2026
- Integrated NDT Approaches for Characterizing Stud-Type Rail Defects: A Comparative Case Studye-Journal of Nondestructive Testing · 2026
- Certification Systems and Training Facilities for Enabling UAV Deployment in Kazakhstan and the EAEUJournal of Intelligent & Robotic Systems · 2026
