| 基于遗传神经网络的插铣铣削力建模与分析 |
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| 引用本文： | 张绍武,;孟宪立,;任宏斌,;冷建伟.基于遗传神经网络的插铣铣削力建模与分析[J].天津理工大学学报,2014(4):14-18. |
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| 作者姓名： | 张绍武 ;孟宪立 ;任宏斌 ;冷建伟 |
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| 作者单位： | [1]天特国际贸易有限公司,天津300230; [2]丹佛斯天津有限公司,天津300100; [3]天津理工大学自动化学院,天津300384 |
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| 摘 要： | 本文首先对插铣铣削力进行了理论分析,并基于正交试验方法对铣削力进行了测量试验,然后利用遗传算法对BP神经网络的权值和阈值进行优化,建立了预测铣削力的遗传神经网络模型,最后将经过遗传算法优化的BP网络与未优化的进行对比分析.结果表明,经遗传算法优化后BP网络模型预测误差明显减小,网络的计算精度和收敛速度有了显著提高.
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| 关 键 词： | 插铣 铣削力 BP神经网络 遗传算法 |
Modeling and analysis of plunge milling force based on genetic neural network |
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| Institution: | ZHANG Shao-wu, MENG Xian-li, REN Hong-bin, LENG Jian-wei (1. Tiante International Trade Co., Ltd., Tianjin 300230, China; 2. Danfoss ( Tianjin ) Co., Ltd., Tianjin 300100, China; 3. School of Electrical Engineering, Tianjin University of Technology, Tianjin 300384, China) |
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| Abstract: | First, plunge milling force was analyzed theoretically, and the milling force was measured based on the orthogonal experiment method. Then, the weights and thresholds of BP neural network was optimized using genetic algorithm, and the genetic neural network for predicting milling force was established. Finally, network optimized was compared and analyzed with unoptimized network. The results show that the prediction error of BP network optimized reduced significantly, and the network＆#39;s accuracy and convergence rate has been improved significantly. |
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| Keywords: | plunge milling milling force BP neural network genetic algorithm |
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