Data fusion for defect characterisation using a dual probe system

We present recent work on a dual probe system containing electromagnetic acoustic transducers (EMATs) generating and detecting surface ultrasonic waves, and a pulsed eddy current (PEC) probe. This system is able to detect and size surface and near-surface defects in electrically conducting samples by looking at changes in the detected signal for each probe. By combining the information from each probe using a weighted logic function for data fusion, it is possible to both classify and size defects, with increased reliability. By combining the data in this way one obtains information about the defects which is not available when using either probe in isolation. Typical results on steel and aluminium samples are presented, along with information about the data fusion function. The dual probe and data fusion routine has been demonstrated to work at manual-scanning speeds, with higher speeds possible following some simple improvements to the system.