Improving the reliability of automated non-destructive inspection
- Imperial College London, South Kensington Campus, SW7 2AZ (United Kingdom)
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.
- OSTI ID:
- 22263782
- Journal Information:
- AIP Conference Proceedings, Vol. 1581, Issue 1; Conference: 40. annual review of progress in quantitative nondestructive evaluation, Baltimore, MD (United States), 21-26 Jul 2013, 10. international conference on Barkhausen noise and micromagnetic testing, Baltimore, MD (United States), 21-26 Jul 2013; Other Information: (c) 2014 AIP Publishing LLC; Country of input: International Atomic Energy Agency (IAEA); ISSN 0094-243X
- Country of Publication:
- United States
- Language:
- English
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