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Sensors 2017, 17(10), 2208;

Pulsed Eddy Current Sensing for Critical Pipe Condition Assessment

Centre for Autonomous Systems (CB 11.09.300), Faculty of Engineering and Information Technology, University of Technology Sydney, 15 Broadway, Ultimo, NSW 2007, Australia
Author to whom correspondence should be addressed.
Received: 1 August 2017 / Revised: 5 September 2017 / Accepted: 20 September 2017 / Published: 26 September 2017
(This article belongs to the Special Issue Magnetic Sensors and Their Applications)
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Pulsed Eddy Current (PEC) sensing is used for Non-Destructive Evaluation (NDE) of the structural integrity of metallic structures in the aircraft, railway, oil and gas sectors. Urban water utilities also have extensive large ferromagnetic structures in the form of critical pressure pipe systems made of grey cast iron, ductile cast iron and mild steel. The associated material properties render NDE of these pipes by means of electromagnetic sensing a necessity. In recent years PEC sensing has established itself as a state-of-the-art NDE technique in the critical water pipe sector. This paper presents advancements to PEC inspection in view of the specific information demanded from water utilities along with the challenges encountered in this sector. Operating principles of the sensor architecture suitable for application on critical pipes are presented with the associated sensor design and calibration strategy. A Gaussian process-based approach is applied to model a functional relationship between a PEC signal feature and critical pipe wall thickness. A case study demonstrates the sensor’s behaviour on a grey cast iron pipe and discusses the implications of the observed results and challenges relating to this application. View Full-Text
Keywords: critical pipes; eddy currents; Gaussian process; NDE; NDT; PEC; sensors critical pipes; eddy currents; Gaussian process; NDE; NDT; PEC; sensors

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Ulapane, N.; Alempijevic, A.; Vidal Calleja, T.; Valls Miro, J. Pulsed Eddy Current Sensing for Critical Pipe Condition Assessment. Sensors 2017, 17, 2208.

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