Automated ultrasonic inspection of aerospace composites with enhanced defect detection probabilities aided by gantry deployed, CAD controlled robotics (AutoDISC)

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Future generation aircraft will consist mostly of carbon composite materials. The modes of failure in composite intensive aircraft are not fully known as they are still near the beginning of their design life, although it is clear that they are susceptible to internal impact damage, not visible at the surface. Yet current NDI of composites in production and service is still largely manual with low area coverage and NDI images are difficult to interpret for any technique because of macroscopic structural anisotropy. To address these problems the project proposes two key NDI innovations: (1) Up to 100% volume NDI coverage using gantry deployed, CAD controlled robotics so that inspection records at any point can be accurately compared at successive maintenance downtime intervals to allow health diagnostics and progostics. (2) A step increase in current detection probability for composite defects implemented through an inference engine performing similarity analysis on spatial and temporal changes in images with coherent noise removal performed by Bayesian separation. The innovations, validated using ultrasonic NDI, are applicable to any type of NDI sensor.