A New Knowledge Representation and Processing Method of Radar Fault Diagnosis

Abstract:

In order to solve the problem of complex faults of radar and bottleneck problem in the expert system, a fault diagnosis system based on hierarchical fault tree and a new method of knowledge storage for radar is developed. The radar faults are divided into subjective faults and objective faults through the analysis of knowledge for some types of radar faults. Aimed at objective faults, a knowledge base structure based on polychromatic sets theory is proposed, which solves the problems of inconvenient storage of fault tree and lacking unified mathematical model, puts forward the description method of knowledge base and realizes the intelligent knowledge reasoning. Aimed at subjective faults, a knowledge base structure based on the method of conventional production rule is founded. The system is verified using VC++6.0. The result shows that knowledge bases with different methods are built respectively according to different types of faults, which improves efficiency and accuracy of the location of faults, providing a new way on the research of radar fault diagnosis system.

• Periodical: Applied Mechanics and Materials (Volumes 110-116)
• Pages: 4358-4364
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.110-116.4358
• Online since: October 2011
• Authors: Shu Xing Du, Wen Jing Hu, Bao Mi Li
• Keywords: Hierarchical Fault Tree, Knowledge Processing, Polychromatic Sets, Radar Fault Diagnosis

References

[1] Xie Guangjun, Van Shiqiang, Tang Ziyue, and Rui Li, A PHM System for AEW Radar Based on AOPS-LSSVM Prognostic Algorithm and Expert Knowledge Database, Proc. IEEE. Prognostics and Health Management Conference (PHM 10), IEEE Press, Jan. 2010, pp.1-6.

DOI: 10.1109/phm.2010.5413478

[2] Xie Guangjun, Yan Shiqiang, Tang Ziyue, and Rui Li, Fault Diagnosis Platform for Radar Circuit Based on Virtual Instrument, Proc. IEEE. Measuring Technology and Mechatronics Automation (ICMTMA 10), IEEE Press, March. 2010, p.245.

DOI: 10.1109/icmtma.2010.470

[3] Dai Jianpeng, Wei Zhensheng, Wang Chunping, and Zhang Guangyuan, Expert System for Radar Equipment Faults Diagnosis Based on Rough Set Theory, Proc. IEEE. Electronic Measurement and Instruments(ICEMI 07), IEEE Press, Aug-July. 2007, pp.3-464.

DOI: 10.1109/icemi.2007.4350955

[4] J. Drabarek and R. Wirski, A Neural Expert System Concept Applied to Diagnostics. Proc. IEEE. Electronics, Circuits and Systems (ICECS 01), IEEE Press, Sep. 2001, pp.1301-1304 vol. 3, doi: 10. 1109/ICECS. 2001. 957454.

DOI: 10.1109/icecs.2001.957454

[5] Chen Wenqin, Wang Qiang and Li Bo, Fault tree-based knowledge storage and d iagnosis system, Journal of Guangxi University, Vol. 35, Apr. 2010, pp.324-329.

[6] Liu Chengxiang and Chen Li, Application of Fault Tree in Expert System, Mechanical Science and Technology, vol. 22, Nov. 2003, pp.8-15.

[7] 7. Li Dong, Construction of Bayesian Diagnostic Network Based on Polychromatic Sets, Computer Measurement & Control, Vol. 15, 2007, pp.496-505.

[8] Wang Hanzhong, Yang Jiangping, and Zhang Aiyuan, Design of an Intelligent Fault Diagnosis System for Modern Radar Equipment, Modern Radar, vol. 30, Nov. 2008, pp.18-25.

[9] Guan Chunping, Peng Heping, and Jang Lili, Research on IETM of Engine Diagnosis Based on Polychromatic Sets, Vehicle Engine, Jun. 2008, pp.55-57.

[10] Zongbin Li and Li Daxua, Polychromatic sets and its application in simulating complex, Computers & Operations Research, vol. 30, 2003, p.851–860.

DOI: 10.1016/s0305-0548(02)00038-2

[11] Tang Fengming and Li Zongbin, A New Approach to Conceptual Polychromatic Sets Design of Mechanical Products Using, Journal of Computer Aided Design & Computer Graphics, vol. 15, Feb. 2003, p.150–155.