学术论文

      基于判别域界面几何法模式识别的铁路轴承故障诊断

      Railway bearing fault diagnosis with the pattern recognition method of interface geometric discriminant

      摘要:
      基于最优分类线的概念,提出了一种新的模式识别分类器构建方法——判别域界面几何法.该方法利用BP神经网络的高度非线性,将模式类样本数据从高维输入空间映射至二维判别域空间后,采用多边形中轴提取方法,构造模式类间隙多边形的中轴线,延伸至整个二维判别域空间,生成模式类决策边界.以铁路货车车轮用双列圆锥滚子轴承的故障诊断为例,介绍了判别域界面几何法的应用过程.结果表明,判别域界面几何法能在二维判别域空间上给出各不同故障模式类之间明确的界限,这就给操作者直观判断故障模式类别提供了条件.
      Abstract:
      With the concept of optimal classification lines,a pattern recognition method,which uses interface geometric discriminant to generate a pattern classifier,was proposed.Major procedures of the method include: mapping multidimensional inputted characteristic vectors of different pattern classes to a 2-dimensional(2D) discriminant space with a BP neural network which is characterized by its high nonlinear mapping capability,extracting a polygon axis of the polygon which is formed at the interval clearance space among pattern classes,and constructing a decision-making boundary for pattern recognition by extending polygon axes to all discriminating domains.The method was tested in a case study of fault diagnosis for double row tapered roller-bearings used in railway wheels.The result shows that the proposed method can construct decision-making boundaries for different fault patterns on a 2D discriminant space,which provides a condition to operators for intuitive recognition of fault classifications in practice.
      作者: 唐英 李应珍
      作者单位: 北京科技大学机械工程学院,北京,100083
      刊 名: 北京科技大学学报 ISTICEIPKU
      年,卷(期): 2011, 33(10)
      分类号: TP206.3
      机标分类号: TH1 U22
      在线出版日期: 2012年4月21日