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ASSAI: Unmanned aerial systems for advanced contact inspection of civil structures

Unmanned aerial systems (UAS) have the potential to support operations in a potentially safe and reliable way because they can access areas that are otherwise too difficult to reach without extensive manpower and support.  However although rapid gains have been made in this field of technology, in order for UAS to truly become the primary method of facilitating inspection and monitoring, there remains the need to carry out advanced contact, non-destructive testing (NDT).  Currently, the sensor equipment being produced for use with UAS is limited to a range of imaging tools, such as video and thermal imaging, as well as surveying and mapping technology.  As a result, human inspection, coupled with ultrasonic sensing systems, is still required in parallel with the UAS, especially for critical infrastructure.

The objective of the ASSAI project was to develop a functioning, ultrasonic inspection, unmanned aerial system (UAS) with a fully integrated ultrasonic transducer (UT) probe capable of performing under bridge thickness measurements of steel support beams.

 Brunel Innovation Centre (BIC) developed a novel, artificial intelligence assisted, ultrasonic signal processing method combining the advantages of both conventional signal processing and the deep learning assisted method, enhancing the accuracy and reliability of the inspection.  Based on the acquired data, an algorithm, decides which method can offer higher reliability and accuracy in the output data, and processes the signal accordingly.  For the algorithm, Brunel University London actually developed three: 

  • Corrosion detection – the combination of signal processing and machine learning enabled automation of the detection as well as going beyond the accepted sensor standard sensitivity
  • Quality of data assessment (standard, substandard) using machine learning – this is critical for drone inspection as it informs whether a measurement should be repeated or not, automatically and in real time, without downloading and assessing the data
  • Surface finish detection

Benefits delivered by ASSAI incude significant productivity increases for the project partners’ customers as well as provided exciting growth for the SME partners in the consortium. During the first five years (2021-2025), the project is predicted to generate cumulative total revenue of £28.3m and a cumulative profit of £6.2m from the sale of 345 ASSAI systems, with an estimated financial return of 1027% (IRR).  Internal-Rate-of-Return is more representative of the longer-term investment than ROI, which does takes into account depreciation/inflation

Partners: Air Control Entech Ltd, JR Dynamics Ltd, James Fisher Testing Services Ltd and BIC (Brunel University London and TWI)

ASSAI secured funding from Innovate UK.

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