| 基于BP神经网络的汽油机失火故障诊断方法的研究 |
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| 引用本文： | 胡杰,颜伏伍. 基于BP神经网络的汽油机失火故障诊断方法的研究[J]. 汽车工程, 2011, 33(2): 101-105 |
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| 作者姓名： | 胡杰 颜伏伍 |
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| 作者单位： | 武汉理工大学,现代汽车零部件技术湖北省重点实验室,武汉,430070 |
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| 基金项目： | 国家863计划项目(2007AA06Z341)资助 |
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| 摘 要： | 针对基于曲轴瞬时角加速度的一般失火故障诊断算法能诊断失火故障,但未能有效区分故障模式的缺陷,提出了一种基于做功时间和BP神经网络的失火诊断算法.根据不同模式下各缸做功时间的波动,提取诊断循环内各缸做功时间信号的特征参数,结合BP神经网络模式识别功能,实现不同模式下的失火故障诊断.通过台架试验,测试了在正常工作、第3缸单...
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| 关 键 词： | 电控汽油机 失火 故障诊断 特征参数 BP神经网络 |
A Research on the Misfire Diagnosis Method of Gasoline Engine Based on BP Neural Network |
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| Hu Jie,Yan Fuwu. A Research on the Misfire Diagnosis Method of Gasoline Engine Based on BP Neural Network[J]. Automotive Engineering, 2011, 33(2): 101-105 |
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| Authors: | Hu Jie Yan Fuwu |
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| Affiliation: | Hu Jie & Yan Fuwu Wuhan University of Technology,Hubei Key Laboratory of Advanced Technology of Automotive Parts,Wuhan 430070 |
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| Abstract: | In view of the defect of general misfire diagnosis algorithm based on instantaneous crankshaft angular acceleration that it can diagnose misfire,but can't effectively identify misfire fault mode,a new misfire diagnosis algorithm is proposed based on the time of work and BP neural network.According to the fluctuation of the time of work in each cylinder under different modes,the characteristic parameters of the time of work signal in each cylinder in a diagnostic cycle are extracted;and combining with the id... |
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| Keywords: | electronically-controlled gasoline engine misfire fault diagnosis characteristic parameters BP neural network |
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