Performance of modern robotic manipulators has enabled research and development of fast automated non-destructive testing (NDT) systems for complex geometries. This paper presents recent outcomes of work aimed at removing the bottleneck due to data acquisition rates, to fully exploit the scanning speed of modern 6-DoF manipulators. State of the art ultrasonic instrumentation has been integrated into a large robot cell to enable fast data acquisition, high scan resolutions and accurate positional encoding. A fibre optic connection between the ultrasonic instrument and the server computer enables data transfer rates up to 1.6GB/s. Multiple data collection methods are compared. Performance of the integrated system allows traditional ultrasonic phased array scanning as well as full matrix capture (FMC). In FMC configuration, linear scan speeds up to 156mm/s with 64 pulses per frame are achieved - this speed is only constrained by the acoustic wave propagation in the component. An 8x increase of the speed (up to 1.25m/s) can be achieved using multiple transmission elements, reaching the physical limits for acceptable acoustic alignment of transmission and reception paths. Scan results, relative to a 1.2m x 3m carbon fibre sample, are presented
The growth of the automated welding sector and emerging technological requirements of Industry 4.0 have driven demand and research into intelligent sensor-enabled robotic systems. The higher production rates of automated welding have increased the need for fast, robotically deployed Non-Destructive Evaluation (NDE), replacing current time-consuming manually deployed inspection. This paper presents the development and deployment of a novel multi-robot system for automated welding and in-process NDE. Full external positional control is achieved in real time allowing for on-the-fly motion correction, based on multi-sensory input. The inspection capabilities of the system are demonstrated at three different stages of the manufacturing process: after all welding passes are complete; between individual welding passes; and during live-arc welding deposition. The specific advantages and challenges of each approach are outlined, and the defect detection capability is demonstrated through inspection of artificially induced defects. The developed system offers an early defect detection opportunity compared to current inspection methods, drastically reducing the delay between defect formation and discovery. This approach would enable in-process weld repair, leading to higher production efficiency, reduced rework rates and lower production costs.
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