Detection And Mitigation Of X-ray Scanner Interference And Gamma-ray Background Suppression In Radiation Portal Monitors

Year
2020
Author(s)
Michael Kuhn - IB3 Global Solutions, Oak Ridge, TN
Nathan Rowe - Oak Ridge National Laboratory (ORNL)
Alex Enders - Oak Ridge National Laboratory
Chris Pope - IB3 Global Solutions
Jason Messimore - Oak Ridge National Laboratory
Jeremy Patterson - Oak Ridge National Laboratory
Abstract

Radiation portal monitors (RPMs) are common border security tools for detecting nuclear and radiologic materials and are commonly deployed across the world including at seaports, airports, and land border crossings. Interference in the gamma background signal is common in these applications from X-ray interference and suppressed gamma-ray background conditions. We have developed a peak detection algorithm to detect interference from X-ray scanners and suppressed gamma-ray background conditions. Our gamma background peak detection algorithm employs a window-threshold method that is optimized for typical peaks caused by X-ray interference and background suppression. This algorithm is robust in tracking the true gamma background level for real-time threshold calculations. Our main signal processing algorithm for automated analysis processes each gamma detector background signal in an RPM and logs characteristics (e.g., width, height) of the positive and negative peaks to assess the frequency and intensity of X-ray interference and gamma background suppression for an RPM. Data from this peak detection algorithm is fed into two classifiers that we trained to detect significant versus insignificant X-ray interference and suppression of the gamma background. The classifiers are trained on ground truth data and then tested on a larger dataset. The results of our analysis show that our peak detection algorithm provides robust detection of both significant X-ray interference and improper suppression of the gamma background by achieving successful classification of greater than 96%. This approach can be extended in future work to detection of equipment failure and other environmental effects that can be observed in RPM gamma background data.