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基于改进D-S信息融合方法的发动机故障诊断

, PP. 146-151

Keywords: 汽车工程,发动机,证据理论,信息融合,组合方法,故障诊断

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Abstract:

为提高发动机故障诊断的精确度和准确性,将信息融合技术应用于发动机非电控单元的故障诊断。针对经典D-S理论方法所存在的对高度冲突证据融合失效的问题,提出一种基于D-S证据理论的改进信息融合方法首先将不同类型的故障诊断模型给出的诊断结果组成证据组,计算证据组各证据之间冲突的程度;利用证据冲突系数对证据组进行分类,计算各高冲突证据的重要度,应用证据间距离函数来判定各证据的可信度;根据重要度和可信度来修正证据的权重,并通过Dempster组合规则实现故障诊断信息融合。通过理论分析和发动机实车试验研究验证了新方法的有效性,与经典D-S组合方法和改进合成规则公式法比较,新组合方法可提高故障诊断的准确率和确定度。

References

[1]  FAN Xianfeng,ZUO M J,Fault Diagnosis of Machines Based on D-S Evidence Theory,Part 1:D-S Evidence Theory and Its Improvement[J],Pattern Recognition Letters,2006,27(5):366-376.
[2]  BASIR O,YUAN Xiaohong,Engine Fault Diagnosis Based on Multi-sensor Information Fusion Using Dempster-Shafer Evidence Theory[J],Information Fusion,2007,8(4):379-386.
[3]  郭惠勇,张陵,基于遗传算法和加权 D-S 信息融合的结构多损伤位置识别[J],机械工程学报,2004,40(9):148-153,GUO Huiyong,ZHANG Ling,Identification of Structural Multiple Damaged Locations Based on Genetic Algorithms and Dempster-Shafer Fusion Theory[J],Chinese Journal of Mechanical Engineering,2004,40(9):148-153.
[4]  张清华,李乔,唐亮,基于证据理论的结构损伤识别研究[J],振动工程学报,2007,20(2):200-205,ZHANG Qinghua,LI Qiao,TANG Liang,Study of Structural Damage Identification Based on Evidence Theory[J],Journal of Vibration Engineering,2007,20(2):200-205.
[5]  ZHANG Jie,Improved On-line Process Fault Diagnosis through Information Fusion in Multiple Neural Networks[J],Computers and Chemical Engineering,2006,30(3):558-571.
[6]  邓勇,施文康,朱振福,一种有效处理冲突证据的组合方法[J],红外与毫米波学报,2004,23(1):27-32,DENG Yong,SHI Wenkang,ZHU Zhenfu,Efficient Combination Approach of Conflict Evidence[J],Journal Infrared Millimeter and Waves,2004,23(1):27-32.
[7]  陈恬,孙健国,郝英,基于神经网络和证据融合理论的航空发动机气路故障诊断[J],航空学报,2006,27(6):1014-1017,CHEN Tian,SUN Jianguo,HAO Ying,Neural Network and Dempster-Shafer Theory Based Fault Diagnosis for Aeroengine Gas Path[J],Acta Aeronautica Et Astronautica Siniga,2006,27(6):1014-1017.
[8]  DENG Yong,SHI Wenkang,ZHU Zhenfu,Combining Belief Functions Based on Distance of Evidence[J],Decision Support Systems,2004,38(3):489-493.
[9]  LU Y H,YEH F H,Study of Using ANFIS to the Prediction in the Bore-expanding Process[J],The International Journal of Advanced Manufacturing Technology,2005,26:544-551.
[10]  刘海燕,赵宗贵,刘熹,D-S 证据理论中冲突证据的合成方法[J],电子科技大学学报,2008,37(5):148-153,LIU Haiyan,ZHAO Zonggui,LIU Xi,Combination of Conflict Evidences in D-S Theory[J],Journal of University of Electronic Science and Technology of China,2008,37(5):148-153.
[11]  吴玉彬,张合新,吕永佳,基于 D-S 证据理论的某飞行器地面电源故障诊断研究[J],航天控制,2011,29(6):69-74,WU Yubin,ZHANG Hexin,Lv Yongjia,Research of Certain Aircraft Ground Power Fault Diagnosis Based on D-S Evidence Theory[J],Aerospace Control,2011,29(6):69-74.
[12]  朱健,曹红兵,徐华安,等,基于多传感器信息融合的智能交通信息语义描述[J],现代电子技术,2011,34(24):48-53,ZHU Jian,CAO Hongbing,XU hua'an,et al,Semantic Description of Intelligent Traffic Information Based on Multi-sensor Information Fusion[J],Modern Electronics Technique,2011,34(24):48-53.
[13]  程华,杜思伟,徐萃华,等,基于DS 证据的信息融合算法多指标融合[J],华东理工大学学报:自然科学版,2011,37(4):133-137,CHENG Hua,DU Siwei,XU Cuihua,et al,A D-S-based Multi-index Fusion of Information Fusion Algorithm[J],Journal of East China University of Science and Technology:Natural Science Edition,2011,37(4):133-137.
[14]  苏广宁,张沛超,胡炎,等,基于多源信息的电网故障诊断新方法[J],电力系统自动化,2012,36(1):61-65,SU Guangning,ZHANG Peichao,HU Yan,et al,A Novel Fault Diagnosis Method Based on Information Fusion of Multi-resources for Power Grids[J],Automation of Electric Power Systems,2012,36(1):61-65.
[15]  成波,冯睿嘉,张伟,等,基于多源信息融合的驾驶人疲劳状态监测及预警方法研究[J],公路交通科技,2009,26(增):13-18,CHENG Bo,FENG Ruijia,ZHANG Wei,et al,Driver Drowsiness Detection and Warning System Based on Multi-source Information Fusion[J],Journal of Highway and Transportation Research and Development,2009,26(S1):13-18.

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