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针对磨损监测过程中获得的大量参数之间存在冗余及关联影响自动识别这一问题,首先运用粗糙集理论和主元分析2种不同的数据约简方法对监测数据进行约简,然后采用支持向量机建立滑动轴承磨粒信息和磨损表面信息之间的映射关系识别器。应用示例表明建立的模型对识别滑动轴承的磨损表面信息和磨粒信息映射关系具有较好的效果。
Aiming at the problem of redundancy and associated influence automatic identification among the large number of parameters obtained during wear monitoring, the monitoring data is reduced by using two different data reduction methods of rough set theory and principal component analysis, and then the support The vector machine establishes a mapping relationship between the bearing information of the sliding bearing and the worn surface information. The application examples show that the established model has a good effect in identifying the relationship between the wear surface information and the wear information of the sliding bearing.