摘要
在油液监测过程中 ,信息表现形式多样 ,容量高 .监测智能化需具备高信息处理速度 ,以完成油液监测中的数据分析、趋势分析、故障诊断和状态预测等 ,这对处理中所用到的数学方法和模型提出了要求 .文中依据油液诊断策略的原理 ,从数据预处理、模式识别和趋势预测等环节分析了各种数学模型和方法的应用现状 。
Intelligent oil monitoring is one of important directions in current machine wear pattern recognition. In oil monitoring, the obtained data has characteristic of various types and high capability, and real-time diagnosis needs a quick speed in data analysis, trend analysis, fault diagnosis and condition monitoring. The paper discusses the mathematical methods and models which are used in oil monitoring in aspects of data processing, pattern cognition and trend prognosis, and gives the research direction of intelligent oil monitoring in the future.
出处
《武汉理工大学学报（交通科学与工程版）》
北大核心
2004年第3期326-329,共4页
Journal of Wuhan University of Technology（Transportation Science & Engineering）
基金
国家自然科学基金项目资助 (批准号 :5 0 2 75 111)
关键词
油液监测
模式识别
信息融合
故障诊断
预测
oil monitoring
pattern recognition
data fusion
fault diagnosis
prognosis
