Using Continuous-Time Bayesian Networks for Standards-Based Diagnostics and Prognostics

In this paper we present a proposal for a new prognostic model to be included in a future revision of the IEEE Std 1232-2010 Standard for Artificial Intelligence Exchange and Service Tie to All Test Environments (AI-ESTATE). Specifically, we introduce the continuous time Bayesian network (CTBN) as an alternative to the previously proposed dynamic Bayesian network to provide an additional model for prognostic reasoning. We specify a semantic model capable of representing a CTBN within the standard and discuss the advantages of using such a model for prognosis. As with previous work, we demonstrate the feasibility and necessity of incorporating prognostic capabilities into the standard.