离子管李萨如图在线测量系统设计
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1.湖南师范大学信息科学与工程学院;2.湖南科技职业学院软件学院

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TN13

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湖南省教育厅科学研究项目(23B0098),湖南省普通本科高校教学改革研究项目(202401000496),湖南省大学生研究性学习和创新性实验计划项目(S202410542276、S202410542278)


Design of on-line measurement system for ion tube Lissajous figure
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    摘要:

    为实现离子管李萨如图的在线测量,本文采用BP神经网络拟合离子管变压器低压侧电压、电流信号到高压侧总电压、测量电压信号的非线性关系,通过设计数据采集电路得到用于训练及测试BP神经网络的样本数据,测试表明所构建BP神经网络的计算误差低于3%。在实际测量过程中,采用训练好的BP神经网络由离子管变压器低压侧信号计算高压侧信号,得到离子管的李萨如图。最后基于STM32单片机,设计了离子管李萨如图在线测量系统样机。实验分析表明:所设计的BP神经网络适用于同一离子管不同工作电压,以及不同离子管相同工作电压下的李萨如图计算;所设计的在线测量系统样机可以实现对离子管李萨如图的在线测量。

    Abstract:

    To realize the on-line measurement of the ion tube’s Lissajous figure. This article uses BP neural network to fit the nonlinear relationship between the voltage and current signal of low-voltage side and the total voltage and measurement voltage signal of high-voltage side of the ion tube transformer. A data acquisition circuit is designed to obtain the sample data used for training and testing the BP neural network, and the test result shows that the computational error of the constructed BP neural network is less than 3%. In the actual measurement process, in order to get the Lissajous figure of ion tube, the high-voltage signal is calculated from the low-voltage signal of the ion tube transformer by using the well-trained BP neural network. Finally, based on the STM32 microcontroller, an on-line measurement system prototype of ion tube Lissajous figure is designed. The experimental analysis shows that the designed BP neural network is suitable for calculating the Lissajous figure for the same ion tube with different working voltages and different ion tubes with the same working voltage, and the designed on-line measurement system prototype can realize the on-line measurement of ion tube’s Lissajous figure.

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  • 收稿日期:2024-10-24
  • 最后修改日期:2024-11-20
  • 录用日期:2024-11-20
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《国外电子测量技术》
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