Ultrasonic thickness structural health monitoring photoelastic visualization and measurement accuracy for internal pipe corrosion

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2015-05-01
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Eason, Thomas
Bond, Leonard
Lozev, Mark
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Bond, Leonard
Professor Emeritus
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Aerospace EngineeringCenter for Nondestructive Evaluation
Abstract

Oil refinery production of fuels is becoming more challenging as a result of the changing world supply of crude oil towards properties of higher density, higher sulfur concentration, and higher acidity. One such production challenge is an increased risk of naphthenic acid corrosion that can result in various surface degradation profiles of uniform corrosion, non-uniform corrosion, and localized pitting in piping systems at temperatures between 150°C and 400°C. The irregular internal surface topology and high external surface temperature leads to a challenging in-service monitoring application for accurate pipe wall thickness measurements. Improved measurement technology is needed to continuously profile the local minimum thickness points of a non-uniformly corroding surface. The measurement accuracy and precision must be sufficient to provide a better understanding of the integrity risk associated with refining crude oils of higher acid concentration. This paper discusses potential technologies for measuring localized internal corrosion in high temperature steel piping and describes the approach under investigation to apply flexible ultrasonic thin-film piezoelectric transducer arrays fabricated by the sol-gel manufacturing process. Next, the elastic wave beam profile of a sol-gel transducer is characterized via photoelastic visualization. Finally, the variables that impact measurement accuracy and precision are discussed and a maximum likelihood statistical method is presented and demonstrated to quantify the measurement accuracy and precision of various time-of-flight thickness calculation methods in an ideal environment. The statistical method results in confidence values analogous to the a90 and a90/95terminology used in Probability-of-Detection (POD) assessments.

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This paper is from Proc. SPIE 9439, Smart Materials and Nondestructive Evaluation for Energy Systems 2015, 94390M (March 27, 2015); doi:10.1117/12.2084223. Posted with permission.

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Thu Jan 01 00:00:00 UTC 2015