| 基于人工神经网络的柴油机故障诊断 |
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| 引用本文： | 汪小年,郑胜国,钱刚. 基于人工神经网络的柴油机故障诊断[J]. 移动电源与车辆, 2005, 0(3): 30-33 |
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| 作者姓名： | 汪小年 郑胜国 钱刚 |
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| 作者单位： | 1. 重庆通信学院研究生队,重庆,400035
2. 重庆通信学院电力工程系,重庆,400035 |
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| 基金项目： | 重庆市自然科学基金研究项目（2004-8495） |
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| 摘 要： | 故障诊断是计算机模式识别领域的一个活跃课题。文中提出了基于人工神经网络的柴油机故障诊断方法，设计了适合该诊断系统的BP网络结构，并给出了一种基于黄金分割法改进的BP算法，用来自适应调整网络学习速率。仿真结果表明：该算法具有很快的学习速度和较高的学习精度，完全适用于柴油机故障诊断系统。
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| 关 键 词： | 柴油机 故障诊断 人工神经网络 BP算法 |
| 文章编号： | 1003-4250(2005)03-0030-04 |
| 收稿时间： | 2005-05-10 |
| 修稿时间： | 2005-05-10 |
Diesel fault diagnosis method based on artificial neural network theory |
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| WANG Xiao-nian,ZHENG Sheng-guo,QIAN Gang. Diesel fault diagnosis method based on artificial neural network theory[J]. Movable Power Station & Vehicle, 2005, 0(3): 30-33 |
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| Authors: | WANG Xiao-nian ZHENG Sheng-guo QIAN Gang |
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| Abstract: | Fault diagnosis is an active subject in the area of computer pattern recognition, this paper puts forward a diesel engine fault diagnosis method designs BP networks form that fits the diagnosis system, and presents an improved BP algorithm, which can adapt learning speed using gold-segmentation. The simulation result indicates that the ANN algorithm has much faster learning speed and more superior learning precision compared with the standard BP algorithm, It is entirely practical in diesel fault diagnosis system. |
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| Keywords: | diesel engine fault diagnosis artificial neural networks BP algorithm |
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