Model-based reliability and diagnostics: A common framework for reliability and diagnostics

Abstract

Generally, technical systems are not guaranteed to work correctly. They are more or less reliable. One main problem for technical systems is the computation of the reliability of a system as studied in reliability theory. A second main problem for technical systems is the problem of diagnostic, i.e., explanations why something does not work. In fact, these problems are, in some sense, dual to each other.In this article, we will use the concept of probabilistic argumentation systems (PASs) for modeling the system description as well as observation and specifications of behavior in one common framework. We show that PASs provide a framework that allows us to formulate and solve reliability and diagnostic problems, and all concepts for these two problems can be defined clearly therein. Using PASs, reliability and diagnostics can be considered as dual problems. PASs offer one common strategy for computing answers to the questions in these different situations.

Probabilistic argumentation

“…4 Translated into our terminology, it means that if both witnesses report the truth of a hypothesis h, then the value for Bel(h) is given by the expression in (2). In Section 3, we will show how to obtain the same result from a probabilistic argumentation system.…”

“…Some existing applications areas are information retrieval [86][87][88], the authentication of public keys [37,50,63], model-based diagnostics and reliability analysis [4,60], Bayesian networks [110,111], statistics [65], and information fusion in the presence of unreliable sources [38]. The theory may also serve as a starting point for a more general decision theory, in which the amount and relevance of the available information is taken into account [45,77,106].…”

“…Another possible author is the Scottish mathematician John Craig (1663-1731). 4 In its substance, this statement was considered important enough to be included in Francis Edgeworth's (1845-1926) article on probability in the 11th edition of the Encyclopaedia Britannica [22].…”

Behavior Bounding: An Efficient Method for High-Level Behavior Comparison

“…Prior work in model-based diagnosis (e.g., Anrig & Kohlas, 2002;Lucas, 1998) has examined how to detect errors given a model of correct behavior. In general, however, the models in these systems are relatively complicated and intended to identify problems with mechanical or solid state devices as opposed to software agents.…”

Increasing Effectiveness of Model-Based Fault Diagnosis: A Dynamic Bayesian Network Design for Decision Making

“…Thus, reliability analyses classically computed by means of stochastic process model as Markov Chains (MC) define the a priori behavior of the probabilities distribution over the functioning and mal-functioning states of the system. Also this additional information is seldom used to improve decision making in model-based fault diagnosis (Anrig and Kohlas, 2002). The aim of the paper is to propose a new approach in order to increase the performance of the decision making in fault diagnosis by taking into account a priori knowledge of the system state through the dynamic Bayesian network.…”