4.7 Article

Application of automated and robotically deployed in situ X-ray fluorescence analysis for nuclear waste management

Journal

JOURNAL OF FIELD ROBOTICS
Volume 39, Issue 8, Pages 1205-1217

Publisher

WILEY
DOI: 10.1002/rob.22104

Keywords

characterization; elemental mapping; manipulator; nuclear; robotic assay; robotic vision; X-ray fluorescence

Categories

Funding

  1. National Centre for Nuclear Robotics (NCNR)
  2. Robotics and AI in Nuclear (RAIN)
  3. Engineering and Physical Sciences Research Council
  4. National Nuclear User Facility Hot Robotics (NNUF-HR)

Ask authors/readers for more resources

Laboratory and synchrotron X-ray fluorescence analysis is a rapid and quantitative elemental analysis technique that has been widely used. Recent developments in miniaturized equipment enable portable and on-site elemental characterization. Combining this technique with a robotic manipulator allows for autonomous assessments of material composition in nuclear and decommissioning scenarios.
Laboratory and synchrotron X-ray fluorescence (XRF) analysis has both served as mainstay rapid and quantitative elemental analysis techniques for decades, attaining parts per million sensitivities for the majority of elements. Formerly, XRF was the reserve of large X-ray generating systems and national facilities. More recently, developments in miniaturized X-ray generators and detectors have allowed for this nondestructive technique to be utilized for portable and in situ elemental characterization of materials, away from the confines of the laboratory. When combined with a robotic manipulator, these usually handheld systems present a powerful method for autonomous assessments of material composition for a wide range of nuclear characterization and decommissioning scenarios. In this study, we present a proof-of-concept XRF system integrated with a robotic manipulator to autonomously identify a suite of nuclear relevant materials. Such remotely deployable noncontact tools are crucial for use within hazardous environments where it may not be possible, for physical and safety reasons, for a human operator to manually undertake characterization tasks. It is envisaged that this robotically deployed XRF system will comprise part of the wider autonomous characterization toolkit; capable of extensive large-area mapping alongside targeted compositional point analysis. The system was demonstrated to rapidly and repeatably derive accurate and precise compositional information of different test materials, autonomously on both flat and complex, object-rich surfaces.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.7
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available