Abstract
This paper presents research into the adaptation of monitoring techniques from maintainability and reliability (M&R) engineering for remote unattended monitoring of gas centrifuge enrichment plants (GCEPs) for international safeguards. Two categories of techniques are discussed: the sequential probability ratio test (SPRT) for diagnostic monitoring, and sequential Monte Carlo (SMC or, more commonly, “particle filtering”) for prognostic monitoring. Development and testing of the application of condition-based monitoring (CBM) techniques was performed on the Oak Ridge Mock Feed and Withdrawal (F&W) facility as a proof of principle.
CBM techniques have been extensively developed for M&R assessment of physical processes, such as manufacturing and power plants. These techniques are normally used to locate and diagnose the effects of mechanical degradation of equipment to aid in planning of maintenance and repair cycles. In a safeguards environment, however, the goal is not to identify mechanical deterioration, but to detect and diagnose (and potentially predict) attempts to circumvent normal, declared facility operations, such as through protracted diversion of enriched material. The CBM techniques are first explained from the traditional perspective of maintenance and reliability engineering. The adaptation of CBM techniques to inspector monitoring is then discussed, focusing on the unique challenges of decision-based effects rather than equipment degradation effects. These techniques are then applied to the Oak Ridge Mock F&W facility – a water-based physical simulation of a material feed and withdrawal process used at enrichment plants that is used to develop and test online monitoring techniques for fully information-driven safeguards of GCEPs. Advantages and limitations of the CBM approach to online monitoring are discussed, as well as the potential challenges of adapting CBM concepts to safeguards applications.
