北京科技大学学报2011，Vol.33Issue(10)：1293-1300,8.
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
唐英 1李应珍1
作者信息
- 1. 北京科技大学机械工程学院,北京100083
- 折叠
摘要
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.关键词
滚动轴承/故障诊断/模式识别/铁路车轮/神经网络Key words
roller bearings/fault diagnosis/pattern recognition/railway wheels/neural networks分类
信息技术与安全科学引用本文复制引用
唐英,李应珍..基于判别域界面几何法模式识别的铁路轴承故障诊断[J].北京科技大学学报,2011,33(10):1293-1300,8.
