Citation

BibTex format

@article{Cegla:2013:10.1121/1.4831176,
author = {Cegla, FB and Huthwaite, PE and Lowe, MJ},
doi = {10.1121/1.4831176},
journal = {J Acoust Soc Am},
title = {Inspection vs structural health monitoring: Manual ultrasonic thickness measurements compared to monitoring with permanently installed sensors.},
url = {http://dx.doi.org/10.1121/1.4831176},
volume = {134},
year = {2013}
}

RIS format (EndNote, RefMan)

TY  - JOUR
AB - Corrosion is a major issue in industry and inspection and monitoring for wall thickness loss are important to assess the structural integrity of pipework and process vessels. Manual ultrasonic thickness measurements are widely used; however, they are also notoriously unreliable because of operator errors. Therefore, automated inspection scans and monitoring at fixed locations with permanently installed sensors are becoming more attractive; they help to remove some of the error introduced by operators. However, this raises the question of what the underlying uncertainties of automated ultrasonic wall thickness measurements are. A key contributor to the uncertainty is the surface roughness condition and the authors have been researching this topic for some time. This talk will give an overview of the physics of scattering of ultrasonic waves from rough corroded surfaces. The different scales of roughness will be discussed, and a simulation technique based on the Distributed Point Source Method (DPSM) to model the scattering and its experimental validation will be presented. The need for statistical results makes both the speed and accuracy of the simulation very important. Finally, based on the simulations, results of the estimated ultrasonic measurement errors due to roughness are presented.
AU - Cegla,FB
AU - Huthwaite,PE
AU - Lowe,MJ
DO - 10.1121/1.4831176
PY - 2013///
TI - Inspection vs structural health monitoring: Manual ultrasonic thickness measurements compared to monitoring with permanently installed sensors.
T2 - J Acoust Soc Am
UR - http://dx.doi.org/10.1121/1.4831176
UR - http://www.ncbi.nlm.nih.gov/pubmed/24181508
VL - 134
ER -