System-Level BITs Fault Diagnosis and Isolation Based on Diagnostic Tree and Bayesian Network

Qi Yu He; Jing Qiu; Guan Jun Liu; Ke Hong Lv; Peng Yang

doi:10.4028/www.scientific.net/KEM.584.102

Paper Titles

Centralized Monitoring Method for Isomeric Heat Treatment Equipments
p.81

Double Phase Differences Correction Method for Frequency and Phase in Spectrum Analysis
p.87

Dynamic Analysis and Various Mode Strategy Comparisons of the Two-Mode Hybrid Transmission
p.92

Intermittent Fault Diagnosis under Extreme Vibration Environment Based on EMD and Neural Network
p.97

System-Level BITs Fault Diagnosis and Isolation Based on Diagnostic Tree and Bayesian Network
p.102

The Performance Analysis of Double Beam Bridge Crane Based on Computer Simulation Technology
p.107

Weak-Points Diagnosis of Gas Turbine Disk by Modal Parameter Identification
p.112

Design of Key Parts of a Pneumatic Conveying System Used in a New Small Trenchless Drilling Robot
p.117

Development of Characteristic Points Recognition and its Application in Cloth Hot-Beads Processing
p.121

HomeKey Engineering MaterialsKey Engineering Materials Vol. 584System-Level BITs Fault Diagnosis and Isolation...

System-Level BITs Fault Diagnosis and Isolation Based on Diagnostic Tree and Bayesian Network

Abstract:

Large systems have complex structures and functions, which makes it more difficult in fault isolation. Given the design features of BITs (built-in test) of large complex systems, a method, based on the diagnostic tree and Bayesian network, has been proposed for fault diagnosis and isolation of System-level BITs. First, faults are rapidly isolated in accordance with the diagnostic tree as well as the information of periodic BITs and maintenance BITs. Then, a diagnostic method based on the Bayesian network has been put forward to solve the problems of ambiguity groups of three LRUs or more and to accomplish further diagnosis and isolation. Finally, a certain subsystem of radar has been exemplified to verify the effectiveness of the method proposed by this study.

You might also be interested in these eBooks

Progress in Functional Manufacturing Technologies III

View Preview

Info:

Periodical:

Key Engineering Materials (Volume 584)

Pages:

102-106

DOI:

https://doi.org/10.4028/www.scientific.net/KEM.584.102

Citation:

Cite this paper

Online since:

September 2013

Authors:

Qi Yu He, Jing Qiu, Guan Jun Liu, Ke Hong Lv, Peng Yang

Keywords:

Ambiguity Group, Bayesian Network (BN), Bit, Diagnostic Tree, Fault Isolation

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

References

[1] Zhong Tian, Junyou Shi. Testability Analysis for Design and Verification of System, Beijing: The Press of Aeronautics and Astronautics in Beijing, (2003).

Google Scholar

[2] Daqi Zhu. The Principle and Practice of Fault Diagnosis of Electronic Equipment, Beijing: The Press of Electronic Industry, (2004).

Google Scholar

[3] Byon J, Deight L. Stratton G. RADC Testability Notebook, ADA, 1982, pp.150-156.

DOI: 10.21236/ada118881

Google Scholar

[4] Yugang Wang, Haidong Wang. The Expert System of Fault Diagnosis in A Certain Equipment Based on Fault Tree, Users of Instrumentation, vol. 19, no. 2, (2012).

Google Scholar

[5] Dongyang Dou, Yingkai Zhao. The Expert System in Fault Diagnosis of Rotating Machinery Based on The Priority of Diagnostic Tree, Journal of Electrical Engineering, vol. 19, no. 2, (2008).

Google Scholar

[6] Jianghua Luo. Bayesian Network in Mechanical Fault Diagnosis, Chongqing: University of Chongqing, 2006, pp.90-96.

Google Scholar

[7] Binghong Cao, Jinyan Cai, Yunhua Huang. The Applications of Smart BITs in Radar Systems, vol. 23, no. 3, (2001).

Google Scholar