Abstract
We present a systematic approach for fusion of multi-sensory nondestructive testing data. Our data set consists of impact-echo, ultrasonic pulse echo and ground penetrating radar data collected on a large-scale concrete specimen with built-in honeycombing defects. From each data set, the most significant signatures of honeycombs were extracted in the form of features. We applied two simple data fusion algorithms to the data: Dempster's rule of combination and the Hadamard product. The performance of the fusion rules versus the single-sensor testing was evaluated. The fusion rules exhibit a slight improvement of false alarm rate over the best single sensor.
Original language | English (US) |
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Pages (from-to) | 54-60 |
Number of pages | 7 |
Journal | NDT and E International |
Volume | 71 |
DOIs | |
State | Published - Apr 2015 |
All Science Journal Classification (ASJC) codes
- General Materials Science
- Condensed Matter Physics
- Mechanical Engineering