Abstract

Thickness quantification of conductive ferromagnetic materials has become a common necessity in present-day structural health monitoring and infrastructure maintenance. Recent research has found Pulsed Eddy Current (PEC) sensing, especially the detector-coil-based PEC sensor architecture, to effectively serve as a nondestructive sensing technique for this purpose. As a result, several methods of varying complexity have been proposed in recent years to extract PEC signal features, against which conductive ferromagnetic material thickness behaves as a function, in return enabling thickness quantification owing to functional behaviours. It can be seen that almost all features specifically proposed in the literature for the purpose of conductive ferromagnetic material-thickness quantification are in some way related to the diffusion time constant of eddy currents. This paper examines the relevant feature-extraction methods through a controlled experiment in which the methods are applied to a single set of experimentally captured PEC signals, and provides a review by discussing the quality of the extractable features, and their functional behaviours for thickness quantification, along with computational time taken for feature extraction. Along with this paper, the set of PEC signals and some MATLAB codes for feature extraction are provided as supplementary materials for interested readers.

Highlights

  • Conductive ferromagnetic wall-like structures are commonly encountered as civil infrastructures, especially in the form of walls of large pipes [1]

  • While several techniques have been investigated for defect and crack detection of conductive materials [4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20], when it comes to thickness quantification of conductive ferromagnetic materials, the Pulsed Eddy Current (PEC) technique, especially the detector coil-based PEC sensor architecture, has been commonly used [21,22,23,24]

  • The RMSE values suggest that τ values estimated from the Savitzky–Golay/Adaptive Least-Squares Fitting-Line (ALSFL) method were least affected by lift-off, while the τ values estimated from the Exponential Fitting method were most affected

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Summary

Introduction

Conductive ferromagnetic wall-like structures are commonly encountered as civil infrastructures, especially in the form of walls of large pipes [1]. The resultant effect of induced eddy currents and the excitation pulse is captured by the second coil, i.e., the detector coil, in the form of a unique time-varying voltage This detector-coil voltage is identified as the PEC signal that carries information about the test piece. As noted in Reference [23], when a detector coil-based PEC sensor is placed above a uniform, homogeneous, conductive ferromagnetic plate having electrical conductivity σ, magnetic permeability μ, and thickness d, the dominant time constant τ of the captured PEC signal, where τ ∈ R+ , τ = 1/c j for some j ∈ Z+ , holds the proportionality τ ∝ μσd. This paper reviews the feature-extraction methods of those works in the sections to come

Experimental PEC Signals
Review of Feature-Extraction Methods
Fitting a Sum of Exponentials
Fitting a Straight Line to the Later Stage
Least Squares-Based Fixed-Region Line-Fitting Method
Results Comparison
Conclusions
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