Automated robotic inspection systems allow the collection of large data volumes, compared to existing inspection systems. To maximize the throughput associated with the nondestructive evaluation phase, it is crucial that the reconstructed inspection data sets are generated and examined rapidly without a loss of detail. Data analysis often becomes the bottleneck of automated inspections. Therefore, new data visualization tools, suitable to screen the NDT information obtained through robotic systems, are urgently required. This paper presents a new approach, for the generation of three-dimensional ultrasonic C-scans of large and complex parts, suitable for application to high data throughput ultrasonic phased array inspection. This approach produces 3D C-scan presented as colored tessellated surfaces and the approach works efficiently on challenging geometry, with concave and convex regions. Qualitative and quantitative results show that the approach runs up to 500 times faster than other C-scan visualization techniques.
Introducing a new method for efficient visualization of complex shape 3D ultrasonic phased-array C-scans
Mineo Carmelo;
2017
Abstract
Automated robotic inspection systems allow the collection of large data volumes, compared to existing inspection systems. To maximize the throughput associated with the nondestructive evaluation phase, it is crucial that the reconstructed inspection data sets are generated and examined rapidly without a loss of detail. Data analysis often becomes the bottleneck of automated inspections. Therefore, new data visualization tools, suitable to screen the NDT information obtained through robotic systems, are urgently required. This paper presents a new approach, for the generation of three-dimensional ultrasonic C-scans of large and complex parts, suitable for application to high data throughput ultrasonic phased array inspection. This approach produces 3D C-scan presented as colored tessellated surfaces and the approach works efficiently on challenging geometry, with concave and convex regions. Qualitative and quantitative results show that the approach runs up to 500 times faster than other C-scan visualization techniques.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.