Dr Nick Brierley
EngD student 2009-2014
University: Imperial College
Sponsoring company: RWE npower
EngD research: The Computational Enhancement of Automated Non-Destructive Inspection
In industrial NDE it is increasingly common for data acquisition to be automated, driving a recent substantial increase in the availability of data. The collected data need to be analysed and currently this is largely done manually by a skilled operator – a rather painstaking task given how rarely defects occur. Moreover, in automated NDE a region of an inspected component is typically interrogated several times, be it within a single data channel due to multiple probe passes, across several channels acquired simultaneously or over the course of repeated inspections. The systematic combination of these diverse readings is recognised to offer an opportunity to improve the reliability of the inspection, for example by enabling noise suppression, but is not achievable in a manual analysis. Hence there is scope for the inspection reliability to be improved whilst reducing the time taken for the data analysis by computational means. The output of the project was a software framework providing a partial automation capability, aligning then fusing the available experimental data to declare regions of the component defect-free to a very high probability whilst readily identifying indications, thereby optimising the use of the operator’s time. The framework is designed to applicable to a wide range of automated NDE scenarios, but the focus in development was on two distinct, industrial inspections: the ultrasonic inspection of power station turbine rotor bores and the ultrasonic immersion inspection of aerospace turbine disks. Results obtained for industrial datasets from these two applications convincingly demonstrate the benefits of using the developed software system.
Research Engineer at The Manufacturing Technology Centre (MTC), working in the Metrology & Non-Destructive Testing Group. The organisation has aims well-aligned with the EngD scheme, working to take academic research through into industry in support of British manufacturing. The position builds directly on the EngD course, with the breadth provided by the taught courses allowing me to contribute to a greater range of projects than would be the case otherwise. I am also able to apply some of the more project-specific skills and knowledge acquired during the EngD by seeking out related project work.