SBIR/STTR Award attributes
TRI Austin will develop an automated approach to translate full ultrasonic inspection datasets for detection and identification of disbonds and other defects within composite aerospace structures.In-service inspection data from Global Hawk structures will be used in an automated process for converting ultrasonic information into defect descriptions suitable for defect growth predictions and modeling.TRIs automated ultrasonic data analysis algorithms are already being used to feed information on manufacturing defects into modeling software to predict structural performance.These algorithms will continue to be optimized to detect disbonds and other defects in the reduced datasets found in MAUS generated ultrasonic C-scans.The output of TRIs algorithms will be mapped to 3D CAD models along with other digital data - creating a digital twin - to allow depth visualization of indications, identification and sizing anomalies in 3D, comparing data across multiple datasets to identify the growth of disbonds and other defects, and to map and track repairs/replacements to models.Taking into account flight hours, number of flights, and flight profiles will help predict appropriately timed maintenance cycles of the aircraft and the resulting digital twin will provide a better holistic view of the structure to improve its overall sustainment.
