Improving the reliability of automated non-destructive inspection

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 relia...

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Bibliographic Details
Main Authors: Brierley, N, Tippetts, T, Cawley, P
Format: Conference Proceeding
Language:English
Subjects:
Automation
CALCULATION METHODS
CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS
Coordinates
Data integration
DATASETS
DETECTION
INSPECTION
Multiple objective analysis
Multisensor fusion
NOISE
Nondestructive testing
PROBABILITY
RELIABILITY
Turbine disks
TURBINES
ULTRASONIC TESTING
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Summary: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 multiobjective 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.
ISSN:0094-243X
1551-7616
DOI:10.1063/1.4865057