摩擦学故障种类诊断的D-S信息融合研究  

Research on Data Fusion for Diagnosing Types of Tribological Failures by Dampster Shafer

作　　者：严新平[1,2] 谢友柏[1,2] 萧汉梁[1,2] 

机构地区：[1]武汉交通科技大学 [2]西安交通大学

出　　处：《摩擦学学报》1999年第2期145-150,共6页Tribology

基　　金：交通部跨世纪人才基金

摘　　要：利用光谱油料分析、铁谱监测、红外光谱分析等，对８ＮＶＤ４８Ａ－２ｕ型柴油机进行了现场运行油液监测试验．根据试验结果和收集到的应用实例，总结了缸套活塞组的划伤、拉缸和腐蚀；轴承的擦伤、烧损、剥落和腐蚀；齿轮的点蚀、胶合和剥离等摩擦学故障种类及其油液监测的信息描述．利用领域专家经验给出了Ｄ－Ｓ证据组合理论的基本概率分配函数，确定了每种油液监测方法对上述摩擦学故障的支持程度，以柴油机缸套活塞组的“拉缸”故障为例，给出了Ｄ－Ｓ方法的组合支持程度的计算过程．The diesel engines model 8NVD48A 2u were monitored under running condition by spectrometric oil analysis, ferrographic monitoring, infrared spectrum analysis and oil quality testing. According to the results from the monitoring experiment, the types of worn parts and the relevant information descriptors are summarized. The worn parts are mainly subject to scoring, seizure and corrosion between piston (or piston ring) and cylinder liner; scratching, seizure, spalling and corrosion in gear; pitting, seizure and fatigue in gear. Based on the experiences and rules of some experts, the basic probability assignment for Dampster Shafer is given, and the applicability of different oil monitoring for different wear types is also discussed. The analysis and calculation show that data fusion is useful for information process in oil monitoring.

关 键 词：磨损 油液监测 信息融合 证据组合理论 柴油机 

分 类 号：TK428[动力工程及工程热物理—动力机械及工程] TH117[机械工程—机械设计及理论]