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《Journal of University of Science and Technology Beijing》 2011-10
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Railway bearing fault diagnosis with the pattern recognition method of interface geometric discriminant

TANG Ying,LI Ying-zhen School of Mechanical Engineering,University of Science and Technology Beijing,Beijing 100083,China  
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.
【CateGory Index】: TH165.3;TP183
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