独立电源多智能体信息融合故障诊断方法

张莉; 袁海文; 吕弘; 袁海斌

独立电源多智能体信息融合故障诊断方法

北京航空航天大学自动化科学与电气工程学院, 北京 100191

基金项目: 国家自然科学基金资助项目(60974058); 航空科学基金项目(2008ZD51060); 航空科学基金项目(2009ZD51041)

详细信息

中图分类号: TP 181
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出版历程
- 收稿日期: 2009-06-11
- 网络出版日期: 2010-08-30

Fault diagnosis for independent power-supply system using multi-agent information fusion

School of Automation Science and Electrical Engineering, Beijing University of Aeronautics and Astronautics, Beijing 100191, China

摘要

摘要: 对独立电源系统进行故障诊断与预测研究是保证整个复杂运动装置系统安全性工程的重要环节.分析了目前独立电源故障诊断系统中存在的问题,提出采用多传感器信息融合和多智能体技术相结合的方法来提高故障诊断的可靠性和系统的扩展性.利用智能体的自主性、分布性和协作性,构建了独立电源多智能体信息融合故障诊断系统.根据独立电源故障征兆的特点,将D-S(Dempster-Shafer)证据理论引入到多神经网络的诊断结果融合技术中,阐述了多神经网络局部诊断智能体和D-S证据理论融合诊断智能体的具体实现方法.最后,以某型航空电源故障诊断为例,给出了故障实例的诊断仿真,结果表明该方法可有效提高诊断可信度.
- 独立电源 /
- 故障诊断 /
- 智能体 /
- 传感器信息融合 /
- 证据理论
Abstract: The fault diagnosis and prognosis research for Independent power-supply system(IPSS) was an important step to ensure the safety for the complex moving devices system. Current fault diagnosis system problems for IPSS were analyzed. The method of combining multi-sensor information fusion with multi-Agent was put forward to improve the diagnosis reliability and the system expansibility. A fault diagnosis system for IPSS using multi-Agent and information fusion was established based on Agent automation, distribution and collaboration. According to the fault symptom feature, Dempster-Shafer evidential theory was introduced into diagnosis result fusion. The multi-neural network local diagnosis Agent and the Dempster-Shafer evidential reasoning Agent implementation were disserted in detail. Finally, taking an aircraft electric power system as an example, the diagnostic process was simulated. The results indicate that the method can improve the diagnosis reliability.
- independent power-supply /
- diagnosis /
- agents /
- sensor data fusion /
- evidential theory

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参考文献(1)

[1] Elbaluk M E,Kankam M D.Potential starter/generator technologies for future aerospace application[J].IEEE AES System Magazine,1997,12(5):24-31 [2] 孙博,康锐,谢劲松.故障预测与健康管理系统研究和应用现状综述[J].系统工程与电子技术,2007,29(10):1762-1767 Sun Bo,Kang Rui,Xie Jinsong.Research and application of the prognostic and health management system[J].Systems Engineering and Electronics,2007,29(10):1762-1767(in Chinese) [3] Keller K,Swearingen K,Sheahan J,et al.Aircraft electrical power systems prognostics and health management[J].IEEE Aerospace Conference,2006,1(9):3737-3748 [4] 朱新宇,沈颂华.飞机电源系统故障诊断专家系统[J].北京航空航天大学学报,2001,27(6):706-708 Zhu Xinyu,Shen Songhua.Fault diagnosis expert system for aircraft electric power system[J].Journal of Beijing University of Aeronautics and Astronautics,2001,27(6):706-708(in Chinese) [5] 牛星岩,沈颂华,董世良.基于模糊推理的飞机电源系统故障诊断专家系统[J].电子测量技术,2007,30(12):59-62 Niu Xingyan,Shen Songhua,Dong Shiliang.Fuzzy fault diagnosis expert system in aircraft power system[J].Electronic Measurement Technology,2007,30(12):59-62(in Chinese) [6] 安若铭,谷吉海,何传严,等.粗糙集在卫星电源系统故障诊断中的应用研究[J].中国空间科学技术,2008(4):59-64 An Ruoming,Gu Jihai,He Chuanyan,et al.Research on rough set applied to satellite power system fault diagnosis[J].Chinese Space Science and Technology,2008(4):59-64(in Chinese) [7] Hall D L,Llinas J.Handbook of multisensor data fusion[M].NewYork:CRC Press,2001 [8] 滕召胜,罗隆福,童调生.智能检测系统与数据融合[M].北京:机械工业出版社,2000:246-247 Teng Zhaosheng,Luo Longfu,Tong Tiaosheng.Intelligent detecting system and data fusion[M].Beijing:China Machine Industry Press,2000:246-247 (in Chinese) [9] Dempster A.Upper and lower probabilities induced by a multivalued mapping[J].Am Math Statist,1967,38:325-339 [10] Zhang Li,Yuan Haiwen,Yuan Haibin,et al.Research and application of atml for aircraft electric power diagnosis and prognostic system[C]// Proceeding of 8th International Conference on Electronic Measurement and Instruments.Beijing:IEEE Press,2007:3615-3618

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