首页> 外文会议>第一届现代铁路创新与可持续发展国际会议(The First International Symposium on Innovation amp; Sustainability of Modern Railway) >RESEARCH ON AUTOMATIC DETECTION SYSTEM DESIGN OF ROLLING BEARING'S SURFACE DEFECTS BASED ON NEURAL NETWORK
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RESEARCH ON AUTOMATIC DETECTION SYSTEM DESIGN OF ROLLING BEARING'S SURFACE DEFECTS BASED ON NEURAL NETWORK

机译:基于神经网络的滚动轴承表面缺陷自动检测系统设计研究

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摘要

The paper describes rolling bearing's surface defects images definition and the classification research by the connected domain's geometry features and moment invariants features. It applies BP neural network technology to surface quality analysis processing. And it also compare Minimum distance classification method to BP neural network method. Result proved that BP neural network method have a better discrimination. Finally, it carries on the discussion to the bearing surface defects images recognition system software design technology.
机译:本文通过连通域的几何特征和不变矩特征描述了滚动轴承的表面缺陷图像定义和分类研究。它将BP神经网络技术应用于表面质量分析处理。并将最小距离分类法与BP神经网络法进行了比较。结果证明,BP神经网络方法具有较好的判别能力。最后,对轴承表面缺陷图像识别系统软件设计技术进行了探讨。

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