摘要
为了能够准确地对大型设备的性能退化过程进行描述,提出了一种基于支持向量数据描述(SVDD)和信息融合技术的评估方法。通过SVDD算法分别评估来自单个传感器的数据,然后运用D-S证据理论对来自多传感器的局部评估结果进行信息融合,最终给出设备的整体性能评估结果。实验分析表明,SVDD算法能够真实地反映设备局部性能退化状态的变化,而利用D-S证据理论得出的整体设备状态评估结果符合实际情况,同时有效地消除局部信息之间的矛盾,提高了设备整体评估的可靠性。
To improve the accuracy of description of equipment performance degradation process,a novel method for performance degradation assessment was proposed,it was based on two techniques: support vector data description (SVDD) and dempeter-shafer(D-S) theory. SVDD was used to assess the performance according to the data from a single sensor,and the performance assessment results based on multi-sensor were sent to D-S theory as input to obtain the assessment result of the whole system. As shown in experiments,SVDD could reflect the performance degradation of equipment parts,the results using D-S theory accorded with the practical situation,and the algorithms could deal with the evident conflict problem effectively,it improved the accuracy and reliability of the assessment results.
出处
《振动与冲击》
EI
CSCD
北大核心
2009年第9期21-24,共4页
Journal of Vibration and Shock
基金
国家自然科学基金资助项目(50675140)
国家高技术研究发展计划("863"计划
2006AA04Z175)
关键词
性能退化
支持向量数据描述
信息融合
D—S证据理论
performance degradation
support vector data description(SVDD)
information fusion
dempeter-shafer(D-S) theory