Article Article
MWM-Array and MR-MWM-Array Eddy Current Testing for Piping and Vessels

The MWM®-Array and MR-MWM-Array are eddy current sensor arrays with single or dual rectangle drive configurations and linear arrays of inductive or magnetoresistive sensing elements. This presentation describes a range of applications for these sensors including stress/strain imaging/monitoring, corrosion imaging (internal and external) with and without coatings, insulation or fireproofing for piping, vessels and structures, and crack detection and depth measurement for fatigue and stress corrosion cracking. These solutions use multivariate inverse methods with precomputed databases called HyperLattices that enable estimation of multiple unknown properties of interest such as magnetic permeability, lift-off, pipe wall thickness, insulation thickness and weather jacket properties. The unique approach improves robustness to variations in field conditions (e.g. insulation sagging that causes substantial variation in insulation thickness around a pipe, or temperature variations that make inspection during operation challenging, or surface conditions that make crack or pit depth measurement more difficult). Handheld and larger portable instruments are also described that are uniquely capable of providing reliable imaging of multiple unknown properties (as required for reliable corrosion imaging through coatings or difficult surface conditions). These instruments provide simultaneous measurement of all channels in the arrays (no multiplexing) to enable improved image reliability and even rescaling of crack responses for cracks falling between channels. Furthermore, impedance values at up to three frequencies are recorded simultaneously at every sensing element. This is essential for reliable correction for uncontrolled variations, such as changes in lift-off (sensor proximity to the surface) and/or magnetic permeability, to provide accurate pipe wall thickness measurement for example. Basic methods are described along with practical application results.

DOI: 10.32548/RS.2019.010

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