원문정보
초록
영어
To meet the real-time diagnosis requirements of complex systems, this paper presents a novel fault diagnosis framework based on dynamic fault tree and arithmetic circuit. It pays attention to meeting two challenges: model development and real-time reasoning. Specifically, we use a dynamic fault tree to model dynamic fault modes and calculate some quantitative parameters using algebraic technique and Bayesian network (BN) in order to avoid the state space explosion problem. Furthermore, we compile a BN into an arithmetic circuit to obtain answers to probabilistic queries by evaluating and differentiating the arithmetic circuit. In addition, we incorporate sensors information into diagnosis process and propose the schemes on how to update the diagnostic importance factor and the minimal cut sequences. Finally, the example of a train-ground communication system is used to demonstrate the proposed method.
목차
1. Introduction
2. Dynamic Fault Tree Analysis
2.1 Qualitative Analysis of Dynamic Fault Tree
2.2 Quantitative Analysis of Dynamic Fault Tree
3. Inference based on Arithmetic Circuit
3.1 Compilation based Inference Approach
3.2 Compiling BN into Arithmetic Circuit with Local Structure
3.3 Online Inference Using Arithmetic Circuit
4. Implementation of the Proposed Real-Time Diagnosis Method
4.1 Sensors Diagnostic Model
4.2 Updating Reliability Results Using Sensors Data
4.3 Diagnosis Algorithm and its Evaluation
5. A Case Study
5.1 Train-ground Communication System
5.2 Application of Diagnostic Method
6. Conclusions
Acknowledgements
References