Evaluation of Pulse Eddy Current for Autonomous Airborne Inspections

Abstract

Unmanned aerial vehicles (UAVs), integrated with pulsed eddy current (PEC) technologies, present a potential solution for nondestructive testing (NDT) in environments where manual inspection is impractical or hazardous. PEC inspections conducted via UAVs facilitate remote structural health monitoring and offer invaluable thickness measurements for integrity assessment. Unlike traditional contact ultrasound inspections, PEC provides thickness measurements without necessitating surface contact. However, challenges, such as aerodynamic influences, probe angular sensitivity, and alignment errors during autonomous inspections can introduce inaccuracies in thickness measurements. Despite its promising applications, the impact of these challenges on the accuracy and reliability of PEC measurements, particularly in autonomous UAV operations, remains underexplored. Consequently, understanding the influence of PEC sensor alignment on UAV inspections becomes vital for ensuring precise NDT outcomes. This letter evaluates the performance of a conventional commercial PEC sensor for its suitability in autonomous airborne inspections. The PEC sensor is affixed to a robot manipulator and precisely controlled to simulate airborne inspections across various alignment angles. Through systematic analysis, the impact of sensor alignment on inspection accuracy is comprehensively assessed, demonstrating critical factors influencing the reliability of UAV-based PEC NDT. The experimental results indicate that the measurement error in PEC can increase to 0.408 mm when the probe was measuring the thickness of a 20 mm sample and experienced misalignment of 4<inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$^\circ$</tex-math></inline-formula> along both the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">x</i>-axis and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">y</i>-axis. The results enhance knowledge of PEC impacts within UAV setups, improving inspection efficiency, and aiding in UAV design to address these issues-advancements critical for the UAV-based PEC NDT.