The Application of BP Neural Network on Mechanical Failure Classification

Fang Zhou, Jianheng Ji, De-zhen Feng
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引用次数: 1

Abstract

Based on the fuzzy classifying approach, the paper puts forwards a diagnosis algorithm of Back-propagation Neural Network. For some complexity environments, the traditional Backpropagation Neural Network has some limitations on classification. The paper applies fuzzy model on Neural Network structure, by using classifying variance and energy function to adjust the convergence of the Neural Network. With the improved nonlinear mapping property, the diagnostic processing shows perfect results with identifying ratio of 100 percent, while the traditional method is 65 percent only. Keywords—Classification, Neural network, Diagnosis, Back propagation
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BP神经网络在机械故障分类中的应用
在模糊分类方法的基础上,提出了一种反向传播神经网络诊断算法。对于一些复杂的环境,传统的反向传播神经网络在分类上存在一定的局限性。本文将模糊模型应用于神经网络结构,利用分类方差和能量函数来调节神经网络的收敛性。利用改进的非线性映射特性,该诊断处理的准确率达到100%,而传统方法的识别率仅为65%。关键词:分类,神经网络,诊断,反向传播
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