[1]周桂法,王坚.基于神经网络的机车速度传感器故障诊断方法研究[J].机车电传动,2010,(01):36-38.[doi:10.13890/j.issn.1000-128x.2010.01.027]
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基于神经网络的机车速度传感器故障诊断方法研究()
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机车电传动[ISSN:1000-128X/CN:43-1125/U]

卷:
期数:
2010年01期
页码:
36-38
栏目:
研究开发
出版日期:
2010-01-10

文章信息/Info

Title:
Research on Locomotive Speed Sensor Fault Diagnosis Method Based on Neural Network
文章编号:
1000-128X(2010)01-0036-03
作者:
周桂法12王坚2
1.同济大学交通运输工程学院 2.株洲南车时代电气股份有限公司技术中心
关键词:
机车RBF神经网络速度传感器故障诊断
Keywords:
locomotive RBF neural network speed sensor fault diagnosis
分类号:
TP212, TP277
DOI:
10.13890/j.issn.1000-128x.2010.01.027
摘要:
建立了RBF神经网络预测器模型,将其应用到机车双速度传感器的故障诊断中,并提出了诊断决策方法。利用MATLAB实现了RBF神经网络预测器的仿真,并模拟了机车速度传感器输出的3种故障模式进行了故障诊断辨识。仿真结果表明文中提出的方法能够准确地进行速度传感器在线故障诊断,为机车速度传感器故障诊断提供了新的思路。
Abstract:
For fault diagnosis of locomotive speed sensor, a predictor method based on RBF neural network is established, and diagnostic decision method is also proposed. The RBF neural network predictor and three kinds of fault mode of locomotive speed sensor are simulated by MATLAB. The simulation results indicate that this method can diagnose faults of the speed sensor online exactly, and provides a new idea for locomotive speed sensor fault diagnosis.

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更新日期/Last Update: 2010-01-10