微型电脑应用2024,Vol.40Issue(3) :162-164,197.

基于大数据跨平台的半结构化实时数据采集技术

Semi-structured Real-time Data Acquisition Technology Based on Big Data Cross-platform

赵小凡 徐炫东 胡璇
微型电脑应用2024,Vol.40Issue(3) :162-164,197.

基于大数据跨平台的半结构化实时数据采集技术

Semi-structured Real-time Data Acquisition Technology Based on Big Data Cross-platform

赵小凡 1徐炫东 1胡璇1
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作者信息

  • 1. 广东电网有限责任公司广州供电局,广东广州 510610
  • 折叠

摘要

针对传统数据采集技术的功能单一、时钟频率低,满足不了现在发展需求的问题,设计半结构化实时数据采集系统,采用FPGA进行并行数据处理,并采用嵌套式乒乓缓存的方式进行数据缓存,实现了实时数据处理和FLASH存储,增强了数据传输和存储的可靠性及稳定性.设计半结构化实时数据远程采集系统,采用REMOTE进程,通过火灾大数据算法模型提高故障诊断能力.实验表明,所提系统在对20 000条数据进行采集时所花费的时间最少为22 s,并且采集的数据精确度最高达到了 98%,火灾故障诊断速度更快、准确率更高,大大提升了对火灾故障的诊断效率和应对能力.

Abstract

Aiming at the problem of the single function and low clock frequency of traditional data acquisition technology cannot meet the needs of current development,this paper designs a semi-structured real-time data acquisition system.It uses FPGA for parallel data processing,and adopts the nested ping-pong cache method for data caching,which realizes real-time data pro-cessing and FLASH storage,and enhance the reliability and stability of data transmission and storage.The remote collection system for semi-structured real-time data is designed.The REMOTE process is adopted to improve the fault diagnosis ability through the fire big data algorithm model.Experiments show that the proposed system takes at least 22 s to collect 20 000 pieces of data,the accuracy of the collected data reaches up to 98%.The fire fault diagnosis speed is faster and the auuracy is higher,which greatly improves the diagnosis efficiency and response ability of fire fault.

关键词

数据采集/大数据/FPGA/半结构化/远程采集/故障诊断

Key words

data acquisition/big data/FPGA/semi-structured/remote acquisition/fault diagnosis

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出版年

2024
微型电脑应用
上海市微型电脑应用学会

微型电脑应用

CSTPCD
影响因子:0.359
ISSN:1007-757X
参考文献量12
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