4.8 Article

Eddy Current Probe With Three-Phase Excitation and Integrated Array Tunnel Magnetoresistance Sensors

Journal

IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
Volume 68, Issue 6, Pages 5325-5336

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TIE.2020.2989704

Keywords

Array probe; eddy current testing (ECT); magnetoresistive sensor (MR); nondestructive testing (NDT); safety maintenance; structure health inspection; three phase

Funding

  1. Shanghai Pujiang Program [18PJ1408400]

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The study introduces an eddy current testing probe with coils carrying three-phase currents and integrated array tunnel magnetoresistance sensors for quick defect detection in metal structures. The probe uses high sensitivity sensors and fine spatial resolution to accurately identify and localize defects of various orientations.
Detecting defects in metal structures quickly and robustly is critical to maintaining safe operation in industry. This work discloses an eddy current (EC) testing probe with coils carrying three-phase currents as excitation and integrated array tunnel magnetoresistance (TMR) sensors measuring the magnetic field as receiver. The three-phase currents in the planar layout coils induce EC that migrates electrically in the material under test. This excitation method does not require multiplexing of the coils and is sensitive to defects of any orientations. The TMR array contains 64 sensors, which are microfabricated and packaged in a line. Within single probe pass, the sensors generate magnetic field image with high sensitivity (1.99 nT/v Hz@30 kHz) and fine spatial resolution (0.5 mm pitch). By analyzing the output image, defects are identified and localized. The operating principle of the probe was investigated based on a finite-element method model. A prototype probe was developed and tested, with which machined defects in aluminum samples were inspected. Experimental results show that the probe has comparable sensitivity for horizontal and vertical defects, and it can recognize a small defect with length x width x depth = 1 x 0.2 x 1 mm(3). The defects are located within 1 mm with an artificial neural network.

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