In industrial non-destructive evaluation (NDE), it is increasingly common for data acquisition to be automated, driving a recent substantial increase in the availability of data. The collected data need to be analysed, typically necessitating the painstaking manual labour of a skilled operator. Moreover, in automated NDE a region of an inspected component is typically interrogated several times, be it within a single data channel due to multiple probe passes, across several channels acquired simultaneously or over the course of repeated inspections. The systematic combination of these diverse readings is recognized to offer an opportunity to improve the reliability of the inspection, but is not achievable in a manual analysis. This paper describes a data-fusion-based software framework providing a partial automation capability, allowing component regions to be declared defect-free to a very high probability while readily identifying defect indications, thereby optimizing the use of the operator's time. The system is designed to applicable to a wide range of automated NDE scenarios, but the processing is exemplified using the industrial ultrasonic immersion inspection of aerospace turbine discs. Results obtained for industrial datasets demonstrate an orders-of-magnitude reduction in false-call rates, for a given probability of detection, achievable using the developed software system.
The issue of trapped powder within a part made using powder bed fusion additive manufacturing (AM) is one of the 'dirty secrets' of AM, yet it has not received significant attention by the research community. Trapped powders limit the application of AM for complex geometries, including heat exchangers and dies with conformal cooling channels. Being able to detect and remove trapped powder from the build is a necessary step to avoid downstream processing and performance challenges. In this work, 'powder challenge geometries' with complex internal features were fabricated via laser powder bed fusion (L-PBF) and electron beam selective melting (EBSM) and were used to assess the effectiveness of several powder removal and inspection methods. Hand-held ultrasonic polishing was explored as a powder removal technique and was shown to effectively clear extremely elongated channels that grit-blasting (the current industry standard) cannot clear. X-ray computed tomography (XCT) and weighing were used to inspect and quantitatively assess the effectiveness of powder removal techniques on the challenge geometries. Using the lesser known 'vacuum boiling' powder removal process and the more common ultrasonic bathing process, trapped L-PBF powder was easily removed from the deep channels. Conversely, trapped EBSM powder was difficult to remove using ultrasonic polishing as the powder was sintered inside the channels. It was shown that the powder recovered by the ultrasonic polishing process had size distributions, surface chemistry, morphology and porosity similar to the virgin powder. It is suggested, on these bases, that the recovered powder could likely be recycled without detrimental effects on the process operation.
A high power laser (TW) was used to accelerate electrons in a laser-driven wakefield accelerator. The high energy electrons were then used to generate an X-ray beam by passing them through a converter target. This bremsstrahlung source was characterised and used to perform penetrative imaging of industrially relevant samples. The photon spectrum had a critical energy in excess of 100 MeV and a source size smaller than the resolution of the diagnostic (150 µm). Simulations indicate a significantly smaller source is achievable. Variations in the X-ray source characteristics were realised through changes to the plasma and converter parameters while simulations confirm the adaptability of the source. Imaging of high areal density objects with 150 µm resolution was performed, demonstrating the unique advantages of this novel source.
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