高精度程控电阻网络生成算法设计
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作者单位:

(1. 海军工程大学 核科学技术学院, 湖北 武汉 430033;2. 海军工程大学 舰船综合电力技术国防科技重点实验室, 湖北 武汉 430033)

作者简介:

朱利文(1992—),男,湖南长沙人,博士研究生,E-mail:15172535460@163.com; 于雷(通信作者),男,教授,博士,博士生导师,E-mail:yulei301@163.com

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基金项目:

军内科研资助项目(HJ20182A070216)


Design of algorithm for high-precision programmable resistance network generation
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Affiliation:

(1. College of Nuclear Science and Technology, Naval University of Engineering, Wuhan 430033, China;2. National Key Laboratory of Science and Technology on Vessel Integrated Power System, Naval University of Engineering, Wuhan 430033, China)

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    摘要:

    为了提高高精度程控电阻的设计效率,建立高精度电阻网络的物理模型和数学模型,提出一种高精度程控电阻网络生成算法。该算法根据给定的量程和精度,基于主电阻网络、补偿电阻网络和偏移电阻的组合方式,自动生成高精度程控电阻网络。以量程90~250 Ω、精度5 mΩ的需求为例,在MATLAB平台上对算法进行仿真验证,仿真结果验证了算法的可行性。结果表明生成的程控电阻网络满足目标量程和精度的需求,算法解算时间仅为18.128 s。相比于人工设计的方式,该算法大大提高了设计效率。

    Abstract:

    In order to improve the design efficiency of the high-precision programmable resistance network, the physical and mathematical models of the high-precision resistance network were established, and a high-precision programmable resistance network generation algorithm was proposed. The algorithm automatically generates a high-precision programmable resistor network based on the combination of the main resistance network, compensation resistance network and offset resistance network, according to the given range and accuracy. Taking the requirement of measuring range 90~250 Ω and accuracy 5 mΩ as an example, the algorithm was simulated and verified on the MATLAB platform, and the simulation results verified the feasibility of the algorithm. The results show that the generated programmable resistor network meets the requirements of target range and accuracy, and the algorithm solution time only needs 18.128 s. Compared with the manual design, this algorithm greatly improves the design efficiency.

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引用本文

朱利文,于雷,金传喜,等.高精度程控电阻网络生成算法设计[J].国防科技大学学报,2021,43(6):95-101.
ZHU Liwen, YU Lei, JIN Chuanxi, et al. Design of algorithm for high-precision programmable resistance network generation[J]. Journal of National University of Defense Technology,2021,43(6):95-101.

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  • 收稿日期:2020-05-12
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  • 在线发布日期: 2021-12-04
  • 出版日期: 2021-12-28
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