[关键词]
[摘要]
针对燃气轮机轴承监测诊断中存在的多源监测数据利用不足、传感器信号不确定性难以消除、诊断精度待提高等问题,D-S证据理论(Dempster-Shafer Evidence Theory)作为一种简洁、高效的决策层多源信息融合方法,在燃气轮机状态监测与故障诊断中具有应用潜力。本文引入传统的D-S证据理论,并针对其存在的缺陷,系统总结了证据理论在燃气轮机轴承故障诊断领域的研究现状,围绕燃气轮机实际的工业应用场景,分析归纳了D-S证据理论的特点,并指出了未来D-S证据理论与燃气轮机轴承故障诊断的发展趋势。
[Key word]
[Abstract]
Due to the complex and changeable operating conditions of gas turbine bearings and insufficient utilization of measurement point information,the detection,diagnosis,operation and maintenance of gas turbine bearings have always been the focus of research.In recent years,multisource information fusion technology has been widely used,and gradually become the key to ensure the safe operation of industrial equipment.In view of the problems of the insufficient utilization of multisource monitoring data,the difficulty of eliminating sensor signal uncertainty,and the need to improve diagnosis accuracy existed in current gas turbine bearing monitoring diagnosis,DempsterShafer (DS) evidence theory is a concise and efficient decisionlevel multisource information fusion method,which has huge application potential in gas turbine condition monitoring and fault diagnosis.The traditional DS evidence theory is introduced,and in view of its shortcomings,the research status of evidence theory in the field of gas turbine fault diagnosis is systematically summarized.Focusing on the actual industrial application scenarios of gas turbines,the characteristics of DS evidence theory are analyzed and concluded,and the future development trend of DS evidence theory and gas turbine fault diagnosis is pointed out.
[中图分类号]
TP181
[基金项目]
国家科技重大专项(2017-I-0007-0008)