It is increasingly common for NDE data acquisition to be automated, driving a substantial increase in the availability of data. The collected data needs to be analysed, typically necessitating the painstaking manual labour of a skilled operator. The Imperial team have identified methods for significantly improving reliability in a number of automated NDE applications. For example, in automated NDE a region of an inspected component is typically interrogated several times which provides an opportunity to improve the reliability of the inspection not achievable in a standard manual analysis. A data fusion based software framework has been developed to provide a partially automated capability for systematic combination of diverse readings, allowing components to be declared defect-free to a very high probability while readily identifying any defect indications.

The framework is designed to be applicable to a wide range of automated NDE scenarios, but one important application is the industrial ultrasonic immersion inspection of aerospace turbine discs (see picture). Data fusion gives a three orders of magnitude reduction in false alarm rate compared with current technique with no reduction in probability of detection.