Dynamic theorem proving algorithm for consistency-based diagnosis

Authors:
Li-Ming Zhang;Hai-Lin Zeng; Fang-Yang;Dan-Tong Ouyang
Affiliations:
School of Computer Science and Technology, Jilin University, Changchun 130012, China and Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University ...;School of Computer Science and Technology, Jilin University, Changchun 130012, China and Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University ...;School of Computer Science and Technology, Jilin University, Changchun 130012, China and Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University ...;School of Computer Science and Technology, Jilin University, Changchun 130012, China and Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University ...
Venue:
Expert Systems with Applications: An International Journal
Year:
2011

Citing 13
Cited 0

A theory of diagnosis from first principles

Artificial Intelligence
Diagnosis of large active systems

Artificial Intelligence
Process algebras for systems diagnosis

Artificial Intelligence
Theorem Proving Based on the Extension Rule

Journal of Automated Reasoning
Hierarchical model-based diagnosis based on structural abstraction

Artificial Intelligence
Fault diagnosis of machines based on D-S evidence theory. Part 1: D-S evidence theory and its improvement

Pattern Recognition Letters
An improved model-based method to test circuit faults

Theoretical Computer Science
Integrating model-based diagnosis techniques into current work processes --- three case studies from the INDIA project

AI Communications
Application of nonlinear feature extraction and support vector machines for fault diagnosis of induction motors

Expert Systems with Applications: An International Journal
An architecture for fault detection and isolation based on fuzzy methods

Expert Systems with Applications: An International Journal
Temporal decision trees: model-based diagnosis of dynamic systems on-board

Journal of Artificial Intelligence Research
Model-based diagnosis in the real world: lessons learned and challenges remaining

IJCAI'99 Proceedings of the 16th international joint conference on Artificial intelligence - Volume 2
Physical impossibility instead of fault models

AAAI'90 Proceedings of the eighth National conference on Artificial intelligence - Volume 1

Quantified Score

Hi-index	12.05

Visualization

Abstract

In this paper, a dynamic theorem proving (DTP) algorithm is proposed for dynamically judging whether a component set is consistency-based diagnosis in model-based diagnosis. Firstly, the model of the system to be diagnosed and all the observations are described with conjunctive normal forms (CNF), and the problem of diagnosis is translated into the satisfiability of the related clauses in the CNF files. Next, all the minimal consistency-based diagnostic sets are derived by calling DTP dynamically combining with the CSSE-tree. As the theorem about the number of components in minimal diagnosis is proposed, the majority of the non-minimal diagnosis can never be produced. Moreover, this approach can compute all the consistency-based diagnostic sets directly, without computing all the conflict sets and therefore the hitting sets of the collection of the corresponding conflict sets like the classical methods. Finally, the approach's soundness, completeness and complexity are analyzed and proved, and results show that the program is easy to be implemented, and the diagnosis efficiency is highly improved.