[1]汤攀,张厚武,何勇.基于神经网络的光栅信号软件细分技术的研究[J].计算机技术与发展,2018,28(06):156-160.[doi:10.3969/ j. issn.1673-629X.2018.06.035]
　TANG Pan,ZHANG Hou-wu,HE Yong. Research on Grating Signal Software Subdivision Technology Based on Neural Network[J].,2018,28(06):156-160.[doi:10.3969/ j. issn.1673-629X.2018.06.035]
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基于神经网络的光栅信号软件细分技术的研究()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
28
期数:
2018年06期
页码:
156-160
栏目:
应用开发研究
出版日期:
2018-06-10

文章信息/Info

Title:
 Research on Grating Signal Software Subdivision Technology Based on Neural Network
文章编号:
1673-629X(2018)06-0156-05
作者:
汤攀; 张厚武; 何勇
贵州大学 计算机科学与技术学院,贵州 贵阳 550025
Author(s):
TANG Pan; ZHANG Hou-wu; HE Yong
School of Computer Science and Technology,Guizhou University,Guiyang 550025,China
关键词:
FPGA; 神经网络; 遗传算法; 四细分
Keywords:
FPGA; neural network; genetic algorithm; four subdivision
分类号:
TP399
DOI:
10.3969/ j. issn.1673-629X.2018.06.035
文献标志码:
A
摘要:
随着精密加工技术与超精密加工技术的发展,对测量精度的要求越来越高,而常用的 50 线/ 毫米经济型的光栅传感器,它的精度为 20 μm,难以达到精密测量的要求。 因此需要对光栅传感器输出的信号进行细分来提高测量的精度。 首先,应用硬件四细分的方法提高光栅测量的精度;其次,在四细分的基础上运用神经网络算法的软件细分技术提高光栅测量的精度;然后,再运用遗传算法对神经网络算法的权值和阈值进行优化,提高光栅测量的准确度;最后,验证了神经网络将光栅信号进行软件细分技术方案的可行性,并通过实验证明改进的 BP 神经网络细分方法使测量精度提高了 0.1 μm。
Abstract:
With the development of precision machining technology and ultra-precision machining technology,the requirement of measuring precision is increasingly high. Precision of 50-wire/ millimeter-economical grating sensor frequently used is 20 μm,which is difficult to meet the requirements of precise measurement. Therefore,it is necessary to fractionize the output signals of grating sensors to improve the measurement accuracy. Firstly,the accuracy of grating measurement is improved by using the hardware four-subdivision method. Secondly genetic algorithm is used to optimize weights and thresholds of neural network algorithm. Finally,it is proved that technical scheme of grating signal is fractionized by neural network. Experiment shows that the accuracy of improved BP neural network subdivision method is improved by 0.1 μm.

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更新日期/Last Update: 2018-08-22