Imperial College London

ProfessorPeterCawley

Faculty of EngineeringDepartment of Mechanical Engineering

Professor of Mechanical Engineering
 
 
 
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Contact

 

+44 (0)20 7594 7069p.cawley CV

 
 
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Assistant

 

Ms Nina Hancock +44 (0)20 7594 7068

 
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Location

 

568City and Guilds BuildingSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@inproceedings{Brierley:2013,
author = {Brierley, N and Tippetts, T and Cawley, P},
pages = {279--289},
title = {Improving the reliability of automated non-destructive inspection},
year = {2013}
}

RIS format (EndNote, RefMan)

TY  - CPAPER
AB - In automated NDE a region of an inspected component is often interrogated several times, be it within a single data channel, across multiple channels or over the course of repeated inspections. The systematic combination of these diverse readings is recognized to provide a means to improve the reliability of the inspection, for example by enabling noise suppression. Specifically, such data fusion makes it possible to declare regions of the component defect-free to a very high probability whilst readily identifying indications. Registration, aligning input datasets to a common coordinate system, is a critical pre-computation before meaningful data fusion takes place. A novel scheme based on a multi-objective optimization is described. The developed data fusion framework, that is able to identify and rate possible indications in the dataset probabilistically, based on local data statistics, is outlined. The process is demonstrated on large data sets from the industrial ultrasonic testing of aerospace turbine disks, with major improvements in the probability of detection and probability of false call being obtained. © (2013) by the British Institute of Non-Destructive Testing. All rights reserved.
AU - Brierley,N
AU - Tippetts,T
AU - Cawley,P
EP - 289
PY - 2013///
SP - 279
TI - Improving the reliability of automated non-destructive inspection
ER -