|本期目录/Table of Contents|

[1]刘喜梅,吕文韬.基于AD7606的树莓派多通道数据采集系统设计[J].工业仪表与自动化装置,2021,(04):98-101.[doi:10.19950/j.cnki.cn61-1121/th.2021.04.020]
 LIU Ximei,L? Wentao.Design of Raspberry Pi multi-channel data acquisition system based on AD7606[J].Industrial Instrumentation & Automation,2021,(04):98-101.[doi:10.19950/j.cnki.cn61-1121/th.2021.04.020]
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基于AD7606的树莓派多通道数据采集系统设计

《工业仪表与自动化装置》[ISSN:1000-0682/CN:61-1121/TH]

卷:
期数:
2021年04期
页码:
98-101
栏目:
出版日期:
2021-08-15

文章信息/Info

Title:
Design of Raspberry Pi multi-channel data acquisition system based on AD7606
作者:
刘喜梅吕文韬
青岛科技大学 自动化与电子工程学院,山东 青岛 266000
Author(s):
LIU XimeiL? Wentao
School of Automation and Electronic Engineering, Qingdao University of Science and Technology, Shandong Qingdao 266000
关键词:
数据采集多通道AD转换接口电路AD7606树莓派
Keywords:
data acquisition multi-channel AD conversion interface circuit AD7606 Raspberry Pi
分类号:
TP274.2
DOI:
10.19950/j.cnki.cn61-1121/th.2021.04.020
文献标志码:
A
摘要:
针对传统AD模块因精度或输入通道数量不足,不能满足同步采集电流和电压参数要求的问题,设计了一种基于AD7606的树莓派多通道数据采集系统。文章详细介绍了系统中电压/电流输入电路、输入滤波电路、AD7606与树莓派接口电路、AD转换程序的设计,并对转换结果进行了误差分析。测试结果表明,用标准输入电压测试AD7606进行AD转换的结果准确,采用AD7606进行AD转换的结果精度高、误差小,适合高精度测量的AD转换电路。
Abstract:
Aiming at the problem that the traditional AD module cannot meet the requirements of synchronous acquisition current and voltage parameters due to insufficient accuracy or the number of input channels, a Raspberry Pi multi-channel data acquisition system based on AD7606 is designed. The article introduces the design of voltage/current input circuit, input filter circuit, AD7606 and Raspberry Pi interface circuit, AD conversion program in the system in detail, and analyzes the error of the conversion result. The test results show that the AD7606 is tested with standard input voltage and the result of AD conversion is accurate, and the result of AD conversion with AD7606 is high in accuracy and small in error, which is suitable for AD conversion circuits for high-precision measurement.

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期:2020-09-30

作者简介:
刘喜梅(1961),女,辽宁新金人,教授、博士生导师,主要研究领域为工业过程建模仿真与优化控制、系统辨识。
更新日期/Last Update: 1900-01-01