An Ensemble Approach to Computationally Efficient Radiological Anomaly Detection and Isotope Identification

Radiological source search is a challenging task involving detection and identification of weak sources in a constantly changing radiological background. As of now, many radiological source detection algorithms have been proposed; however, their computational complexity and, hence, reliance on power...

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Vydáno v:IEEE transactions on nuclear science Ročník 69; číslo 10; s. 2168 - 2178
Hlavní autoři: Lee, J., Cooper, R. J., Joshi, T. H., Bilton, K. J., Raji, D. M., Bandstra, M. S., Vetter, K.
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York IEEE 01.10.2022
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:
Algorithms
Anomalies
Anomaly detection
Barium
Benchmark testing
Computer applications
Detection algorithms
Detectors
Energy resolution
Estimation
gamma-ray detection
Identification
INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND TECHNOLOGY
low-power electronics
Microcontrollers
non-negative matrix factorization (NMF)
Power consumption
Power demand
radiation source search
Statistical analysis
ISSN:0018-9499, 1558-1578
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Shrnutí:Radiological source search is a challenging task involving detection and identification of weak sources in a constantly changing radiological background. As of now, many radiological source detection algorithms have been proposed; however, their computational complexity and, hence, reliance on power intensive processing units inhibit low-power applications of radiological source search systems. In this work, we introduce the anomaly filter (AF) algorithm; a computationally light, yet effective time-series source detection algorithm based on exponential weighted moving average (EWMA) and Poisson deviance statistics. Then, we demonstrate that the proposed algorithm can be used in ensemble with other more computationally intensive source detection and identification algorithms to achieve both increased detection performance and reduced power consumption. The proposed AF algorithm and the ensemble algorithms were thoroughly benchmarked against several existing source detection and identification algorithms. The results show that the AF algorithm outperforms existing conventional source detection algorithms, and the ensemble approach improves the overall performance of existing source detection and isotope identification algorithms. Furthermore, the AF algorithm and the non-negative matrix factorization approach-based source identification (NMF-ID) algorithm were combined and implemented on a single-board microcontroller, and the power consumption was measured. This ensemble algorithm reduced the power consumption of the NMF-ID algorithm almost by a factor of 100, while improving the detection performance of the overall system.
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USDOE Office of Science (SC), Basic Energy Sciences (BES). Materials Sciences & Engineering Division
Defense Threat Reduction Agency (DTRA)
AC02-05CH11231; 13081-31571
ISSN:0018-9499
1558-1578
DOI:10.1109/TNS.2022.3198906