Multiple sensors on pulsed eddy-current detection for 3-D subsurface crack assessment

TLDR

The study proposes using multiple sensors in pulsed eddy‑current detection to image three‑dimensional subsurface flaws. The technique employs these sensors to capture 3‑D flaw data through pulsed eddy‑current excitation. By normalizing Hall‑device and lift‑off effects and applying PCA‑based feature extraction for sensor fusion, the method accurately reconstructs surface flaws and experimentally delivers more defect information than conventional peak‑value and time metrics.

Abstract

This paper proposes the use of multiple sensors in pulsed eddy-current detection for three-dimensional (3-D) subsurface flaw imaging. A normalization technique has been proposed to eliminate the characteristic variation among the Hall devices used in the probe and lift off effects. A principal component analysis-based feature extraction that provides orthogonal information for multiple sensor fusion has been introduced and investigated. Using the features of multiple projection coefficients, 3-D surface flaws can be measured and reconstructed. The experimental tests have illustrated that the proposed method has delivered more defect information than the conventional peak value and time for pulsed eddy-current sensors.