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文章摘要
基于LMS自适应滤波的电能计量箱数据采集与处理方法研究*
Research on data acquisition and processing method of electric energy metering box based on LMS adaptive filtering
Received:October 12, 2019  Revised:October 12, 2019
DOI:10.19753/j.issn1001-1390.2020.04.022
中文关键词: 数据采集  LMS滤波  电能计量箱  主-辅处理器
英文关键词: data  acquisition, LMS  filtering, electric  energy metering  box, main-auxiliary  processor
基金项目:国家电网有限公司项目,JL71-17-006电能计量箱检测及质量评价关键技术研究(5442JL70007)
Author NameAffiliationE-mail
Chen Hui* Electric Power Research Institute of Fujian power co LTD phoebehui@163.com 
Zhang Ying Electric Power Research Institute of Fujian power co LTD 13609557640@163.com 
Wei Xiaoying Electric Power Research Institute of Fujian power co LTD 147804009@qq.com 
Wang Sun’an School of Mechanical Engineering, Xi''an Jiaotong University 727166585@qq.com 
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中文摘要:
      为了解决电能计量箱多传感器数据同步采集,并消除或减小数据噪声的问题,文章研究设计了电能计量箱多特征量采集系统。该方法首先采用STM32F7和STM32F1单片机作为主-辅处理器,设计了多传感器数据滤波和扩展IO资源采集系统;其次,设计并采用了标准化的通信协议使传感器数据实现同步采集;最后,采用基于LMS自适应滤波的方法对采集的数据进行降噪处理和分析。文章以温度传感器ADT7320为例做了数据采集与滤波处理实验,通过数据降噪处理后,基本消除了频率在1Hz以上的噪声且小于1Hz的噪声幅值也减少为原来的50-90%。通过与传统的低通滤波器相比,本文方法能根据噪声频率进行自适应滤波,从而得到较为纯净准确的传感器数据。
英文摘要:
      In order to solve the problem of multi-sensor data synchronous acquisition and data noise elimination or reduction in electric energy metering box, this paper studies and designs a multi-feature data acquisition system. In this method, the MCU STM32F7 and STM32F1 are used as the main-auxiliary processor, and the multi-sensor data filtering and extended IO resource acquisition system are designed. Secondly, a standardized communication protocol is designed and adopted to realize synchronous acquisition of sensor data. Finally, an adaptive filtering method based on LMS is adopted to deal with and analyze the noise reduction of the collected data. In this paper, the temperature sensor ADT7320 is taken as an example to conduct data acquisition and filtering processing experiments. After data noise reduction processing, the noise with the frequency above 1Hz is basically eliminated and the noise less than 1Hz is basically reduced to 50-90%. Comparing with the traditional low-pass filter, the method in this paper can perform filtering adaptively according to the noise frequency, so that it can obtain the relatively pure and accurate sensor data.
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