基于云的矢量网络分析仪在线系统软件设计
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1.中国计量大学信息工程学院  2.杭州;3.浙江省电磁波信息技术与计量重点实验室  

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TN98?

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浙江省基础公益研究计划项目(LGF19F010003)资助


Design of cloud-based vector network analyzer online system software
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    摘要:

    矢量网络分析仪是射频与微波检测领域中不可或缺的现代电子测量设备。传统的矢量网络分析仪检测方法主要依靠工作人员驻守在仪器旁操作控制,这种方法效率低且灵活性不强,无法满足现代电子测量所需要的智能化与便捷性需求。针对传统矢量网络分析仪检测中的难题,设计了一种基于云服务器的矢量网络分析仪在线软件系统。系统通过SCPI协议实现矢量网络分析仪与本地电脑进行连接,本地电脑通过SSH协议上传矢量网络分析仪检测到的S参数以频率点、实部与虚部的数据格式至云服务器的MySQL数据库中,使用Django开发的网站可以使用户通过任意设备登陆网站实时获取S参数的可视化数据,包括频域、时域和驻波比等相关波形图。将系统应用于矢量网络分析仪E5071C对矩形不锈钢管10GHz至12GHz的双端口S参数检测中进行试验,结果表明检测数据在仪器与本地电脑短时间内多次传输中无数据损失,相关S参数数据与仪器检测结果的误差小于0.01%,用户可通过多个设备同时访问网站获取实时S参数波形图,证明了该系统的实用性,为矢量网络分析仪的检测提供了新的可靠方案。

    Abstract:

    The vector network analyzer is an essential instrument in RF and microwave testing. The traditional methods of detection necessitate the presence of on-site personnel for operation and control, which is inefficient and inflexible, failing to meet the contemporary requirements for intelligent and convenient electronic measurement. To address these challenges, an online software system based on a cloud server was designed for vector network analyzer. The system connects the vector network analyzer to a local computer via the SCPI protocol. The local computer uploads the S-parameters, comprising frequency points, real and imaginary components, to the cloud server's MySQL database via SSH. The Django-developed website allows users to access real-time visual data of S-parameters, including frequency domain, time domain, and standing wave ratio graphs, from any device. The system was tested on the E5071C vector network analyzer for dual-port S-parameter detection of rectangular stainless steel tubes from 10GHz to 12GHz. Results showed no data loss during multiple transmissions between the instrument and the local computer. The error between S-parameter data and the instrument's detection results was less than 0.01%. Users could access real-time S-parameter waveforms simultaneously from multiple devices, proving the system's practicality and providing a reliable solution for vector network analyzer detection.

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  • 收稿日期:2024-04-11
  • 最后修改日期:2024-07-19
  • 录用日期:2024-07-22
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