Evaluation of Shiryaev-Roberts procedure for on-line environmental radiation monitoring (original) (raw)

Abstract

An on-line radiation monitoring system that simultaneously concentrates and detects radioactivity is needed to detect an accidental leakage from a nuclear waste disposal facility or clandestine nuclear activity. Previous studies have shown that classical control chart methods can be applied to on-line radiation monitoring data to quickly detect these events as they occur; however, Bayesian control chart methods were not included in these studies. This work will evaluate the performance of a Bayesian control chart method, the Shiryaev-Roberts (SR) procedure, compared to classical control chart methods, Shewhart 3-σ and cumulative sum (CUSUM), for use in on-line radiation monitoring of 99 Tc in water using extractive scintillating resin. Measurements were collected by pumping solutions containing 0.1-5 Bq/L of 99 Tc, as 99 TcO − 4 , through a flow cell packed with extractive scintillating resin coupled to a Beta-RAM Model 5 HPLC detector. While 99 TcO − 4 accumulated on the resin, simultaneous measurements were acquired in 10-s intervals and then re-binned to 100-s intervals. The Bayesian statistical method, Shiryaev-Roberts procedure, and classical control chart methods, Shewhart 3-σ and cumulative sum (CUSUM), were applied to the data using statistical algorithms developed in MATLAB®. Two SR control charts were constructed using Poisson distributions and Gaussian distributions to estimate the likelihood ratio, and are referred to as Poisson SR and Gaussian SR to indicate the distribution used to calculate the statistic. The Poisson and Gaussian SR methods I would like to express my sincere gratitude to my advisor, Dr. Tim DeVol, for supporting me through my Master's degree the last two years. I am forever grateful for the freedom he gave me to work on my research, but am also grateful for his willingness to help when needed, particularly when equipment did not work. His expertise and guidance were also greatly appreciated when filling out applications for scholarships, fellowships, and doctoral programs. I do not believe that I would have been as successful without his advice and recommendation. I would also like to thank my other committee members, Dr.

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References (64)

  1. 'Position',[100 100 400 575]);
  2. % Plot Shewhart 3-sigma fig1=subplot(4,1,1); % subplot 1 data=data./100; plot(fig1,x,data,'black') high=refline(0,a/100+3 * s/100);
  3. set(high,'LineStyle',':','Color','black');
  4. title('Shewhart 3-sigma') xlabel('Volume [mL]');
  5. ylabel('Count Rate [cps]');
  6. % Plot CUSUM statistic fig2=subplot(4,1,2); % subplot 2 plot(fig2,x,c,'black') h=refline(0,4.77);
  7. set(h,'LineStyle',':','Color','black');
  8. title('CUSUM') xlabel('Volume [mL]');
  9. ylabel('CUSUM Statistic');
  10. % Plot Poisson SR statistic fig3=subplot(4,1,3); % subplot 3 semilogy(fig3,x,Wp,'black')
  11. Wstop=refline(0,700);
  12. set(Wstop,'LineStyle',':','Color','black');
  13. title('Poisson Shiryaev-Roberts') xlabel('Volume [mL]');
  14. ylabel('SR Statistic');
  15. % Plot Gaussian SR statistic fig4=subplot(4,1,4); % subplot 3 semilogy(fig4,x,Wn,'black')
  16. Wstop=refline(0,700);
  17. set(Wstop,'LineStyle',':','Color','black');
  18. title('Gaussian Shiryaev-Roberts') xlabel('Volume [mL]');
  19. ylabel('SR Statistic');
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