| 基于神经网络的超声波乳化液质量分数测量 |
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| 引用本文： | 陈琳,朱士明,梁军汀,卢杰.基于神经网络的超声波乳化液质量分数测量[J].同济大学学报(自然科学版),2007,35(2):257-261. |
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| 作者姓名： | 陈琳 朱士明 梁军汀 卢杰 |
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| 作者单位： | 同济大学,声学研究所,上海,200092 |
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| 摘 要： | 通过反向传播（BP）神经网络及径向基函数（RBF）神经网络，构建了一个实时的超声波乳化液质量分数测量模型，对结果进行了处理和分析，并对比了两者的优缺点．在此基础上，实现了对某些生产过程中乳化液质量分数的检测和控制．
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| 关 键 词： | 乳化液 超声 质量分数 测量 反向传播神经网络 径向基函数网络 |
| 文章编号： | 0253-374X（2007）02-0257-05 |
| 修稿时间： | 2005-06-24 |
Ultrasonic Rolling-Oil Concentration Measurement Based on ANN |
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| CHEN Lin,ZHU Shiming,LIANG Junting,LU Jie.Ultrasonic Rolling-Oil Concentration Measurement Based on ANN[J].Journal of Tongji University(Natural Science),2007,35(2):257-261. |
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| Authors: | CHEN Lin ZHU Shiming LIANG Junting LU Jie |
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| Institution: | Institute of Aooustics, Tongji University, Shanghai 200092, China |
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| Abstract: | Two systems based on back propagation(BP) neural network and RBF(radial basis function) neural network for rollingoil concentration measurement are presented respectively,and the measurement results are analyzed with the models.The merits and demerits of these two modeling methods are compared in this paper. |
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| Keywords: | rolling oil ultrasonic mass fraction measurement back propagation(BP) neural network radial basis function(RBF) neural network |
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