Python 在 ＲLC 串联谐振实验数据处理中的应用

doi:10.14139/j.cnki.cn22-1228.2022.06.018

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摘要

ＲLC 串联谐振实验是电学的实验之一，以加强对串联谐振电路谐振特性的理解。Python语言在数据分析与处理等方面有很好的应用。首先利用 Python 的第三方库 numpy 对数据进行预处理;其次基于 scikit-learn 建立线性回归模型，通过数据训练、机器学习拟合数据并求解;为判定测试数据的质量，通过 sklearn 对拟合曲线进行均方误差回归损失分析，最后采用 matplotlib 绘制图形，实现数据的可视化。引入 Python 进行数据处理，能快速处理实验数据，绘制拟合曲线并分析测试数据的优劣，形象且直观，对教师评判实验报告的测试数据质量也具有一定的辅助作用。

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	赵文来
	杨俊秀
	陈秋妹

关键词: ＲLC 串联谐振归一化幅频特性拟合 Python numpy sklearn

Abstract:

ＲLC series resonant is one of circuit experiments，in order to strengthen the understanding of impedance，current and voltage resonance characteristics．Python language has wide application in data analysis and processing because of concise statements，rich library classes，open source code and etc．Some measurement data of ＲLC series resonance are analyzed．Firstly，data are preprocessed by numpy library of Python．Secondly，linear regression model is established based on scikit-learn，and data are fitted and solved through data training and machine learning． In order to measure data quality，the mean square error regression loss is analyzed through sklearn． Finally，using matplotlib to achieve data visualization． Python language is introduced for experiment data processing．Students can quickly process data，draw fitting curve and analyze data．It is vivid and intuitive，and it has a certain auxiliary for teachers to judge the quality of the experimental report．

Key words: series resonance normalization amplitude frequency characteristics fitting Python numpy sklearn

出版日期: 2022-12-25 发布日期: 2022-12-25 整期出版日期: 2022-12-25

ZTFLH:

TN 30

引用本文:

赵文来, 杨俊秀, 陈秋妹. Python 在ＲLC 串联谐振实验数据处理中的应用 [J]. 大学物理实验, 2022, 35(6): 85-90.
ZHAO Wenlai, YANG Junxiu, CHEN Qiumei. Application of Data Processing of ＲLC Series Ｒesonant Circuit Experiment by Python . Physical Experiment of College, 2022, 35(6): 85-90.

链接本文:

http://dawushiyan.jlict.edu.cn/CN/10.14139/j.cnki.cn22-1228.2022.06.018 或 http://dawushiyan.jlict.edu.cn/CN/Y2022/V35/I6/85

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