摘要
灰色理论应用于滑油光谱分析的方法已经成为设备状态监测中油液监测的一种有效的建模手段。对取样时间间隔较长的机械设备磨损进行监测 ,以便得到设备磨损状态的预测信息。本文提出了基于灰色理论的GM(2 ,1 )模型 ,对设备磨损状态进行预测和诊断分析 ,并与以往常用的GM(1 ,1 )模型进行了比较 ,分析讨论这两种模型应用于设备磨损光谱元素浓度预测的精度 ,通过实例验证了GM(2 ,1 )模型具有简单、准确和实用的特点。并在此基础上 ,又提出了应用灰色理论对设备磨损状态进行参数辨识 ,进而运用参数监测来对设备进行状态监测的方法 ,可以准确地发现系统的变化 。
A practical model of GM(2,1) based on Grey Theory was built to predict and diagnose the wear of oil lubricated mechanical equipment and compared with usual GM(1,1). Through the analysis and discussion of an example of spectral analysis data, the precision and practicality were validated. Moreover, a method for recognized parameters of the wear state monitoring based on Grey Theory has been brought forward. This method through recognition of spectral analysis data by GM(2,1) convert original data to be processed parameters to monitor the wear state of mechanic equipment, and it can discover the changes of oil system monitored exactly and distinctly, and provide us a forceful instrument to determine the state and analyze the trend of wear.
出处
《润滑与密封》
CAS
CSCD
北大核心
2003年第6期66-68,70,共4页
Lubrication Engineering
