| 基于神经网络的汽轮发电机组推力瓦块拆检周期改进 |
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| 引用本文： | 徐鲁杰,刘镇.基于神经网络的汽轮发电机组推力瓦块拆检周期改进[J].船海工程,2007,36(1):73-74. |
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| 作者姓名： | 徐鲁杰 刘镇 |
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| 作者单位： | 海军工程大学动力工程学院,武汉,430033 |
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| 摘 要： | 运用人工神经网络的方法对某舰用汽轮发电机组的滑油铜含量进行分析,找出铜含量的变化规律,然后与曲线拟合进行数据处理的方法作比较,结果表明,基于遗传算法的BP网络模型比曲线拟合模型的预报精度明显提高,预报结果稳定,且建立模型的过程较为简单。
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| 关 键 词： | 神经网络 磨损 铜含量 维修 |
| 文章编号： | 1671-7953（2007）01-0073-02 |
| 修稿时间： | 2006-03-03 |
A research of thrust bush inspection period based on neural network |
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| Authors: | XU Lu-jie LIU Zhen |
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| Institution: | XU Lu-jie LIU Zhen College of Power Engineering Naval University.of Engineering Wuhan 430033 |
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| Abstract: | The lubrication copper spectrum data was analyzed by the method of artificial neural network for the warships turbine generating set,in order to find the law of the change of copper contents.Comparative study shows that the results of BP network model based on genetic algorithms are more accurate than the ones of curve fitting model,and it is simpler to build up the BP network model with stable forecast result. |
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| Keywords: | neural network abrasionvcopper contents maintenance |
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