DNA优化的BP神经网络在故障诊断中的应用
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TP183

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基金项目:铁道部科研课题《客运专线信号列控设备维修技术及标准》(2009X001-B)


Fault diagnosis using a BP neural network-based DNA algorithm
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    摘要:

    针对BP神经网络收敛速度慢和容易陷入局部极小值问题,将DNA算法和神经网络有机结合,利用DNA算法的全局搜索能力,优化网络的初始权值和阈值,解决其本身固有的两个缺陷,进而提高了BP神经网络诊断故障时的准确性和快速性。以道岔控制电路的故障诊断为研究对象,建立了基于DNA优化的BP神经网络的故障诊断优化模型,使用MATLAB仿真软件对故障诊断模型进行了仿真分析。结果表明,DNA算法优化的BP神经网络的泛化能力、诊断精确性都要优于BP神经网络。

    Abstract:

    In order to solve the problem of BP neural network, like local minimum and convergence rate, the author effectively combined DNA algorithm and neural network. By utilizing global searching ability of DNA algorithm and optimizing the initial weights and threshold value of the optimized network, the two problems of the BP neural network would be solved and the accuracy and rapidity of BP neural network diagnosis would be further improved. Taking the fault diagnosis of switch control circuit as the object of the study, this paper establishes fault diagnosis model of BP neural network optimized by DNA algorithm and conducts simulation analysis for fault diagnosis model with MATLAB software. The result demonstrates that the generalization ability and the accuracy of BP neural network optimized by DNA algorithm are better than BP neural network.

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付琴. DNA优化的BP神经网络在故障诊断中的应用[J]. 科学技术与工程, 2012, 12(29): .
fuqin. Fault diagnosis using a BP neural network-based DNA algorithm[J]. Science Technology and Engineering,2012,12(29).

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历史
  • 收稿日期:2012-06-08
  • 最后修改日期:2012-06-08
  • 录用日期:2012-06-26
  • 在线发布日期: 2012-09-10
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