本文采用FPGA实现四通道传感器的高速数据采集、同步转换和LMS自适应降噪,使用ARM搭建了边缘计算平台,进而实现了一种云-边-端协同的测试流式大数据处理系统,并且在磨床设备检测中得到了应用。实验和现场测试结果表明,本系统可以满足实际应用的需求,为基于工业物联网的设备监测提供了一种可行的方法。
Abstract
In the paper,FPGA is used to realize high-speed data acquisition,synchronous conversion and LMS adaptive noise reduction of four-channel sensors,an edge computing platform is built using ARM,and then a cloud-side-end collaborative test streaming big data processing system is realized,and it has been applied in the detection of grinding machine equipment.The experiment and field test results show that it can meet the needs of practical applications and provide a feasible method for equipment monitoring based on the industrial internet of things.
关键词
多核异构平台 /
流式大数据处理系统 /
磨床砂轮状态在线监测 /
Zynq-7045 /
Netty框架
Key words
multi-core heterogeneous platform /
streaming big data processing system /
on line monitoring of grinding wheel condition of grinder /
Zynq-7045 /
Netty framework
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参考文献
[1] 王其朝,金光淑,李庆,等.工业边缘计算研究现状与展望[J].信息与控制,2021,50(3):257-274.
[2] K Anitha Kumari.Edge Computing:Fundamentals,Advances and Applications[M].CRC Press,2021.
[3] 魏化雨.基于FPGA的无线声发射桥梁结构健康检测仪设计[D].深圳:深圳大学,2018.
[4] 欧阳旻,郭玉超,王桓,等.工业物联网环境下设备数据采集研究与实现[J].软件工程,23(12):4.
基金
*科技创新人才服务企业项目(2020KJRC0122);基于“云-边-端”的工业测量装备自主保障技术及应用示范(2019ZDLGY17-05-02)。