基于云技术的弹簧疲劳试验机远程实时监测和控制系统

Machines Pub Date : 2024-07-09 DOI:10.3390/machines12070462
Guoshuai Wang, Tonghui Xu, Decheng Wang, Peng Cheng, Chenxi Shao, Feng Feng, Peng Zhou
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引用次数: 0

摘要

近年来,云技术的应用方兴未艾,尤其是在工业自动化和智能场景领域。然而,目前普遍使用的弹簧疲劳试验机仍是传统的单机工作模式。在这种模式下,存在测试设备自动化程度低、实验现场环境差、实验人员需要长时间值守等诸多问题。为解决上述问题,本文基于高温恒力弹簧疲劳试验机,构建了基于云计算的远程监测与控制系统。该系统基于浏览器/服务器架构,客户端可在公共网络环境下使用浏览器随时随地访问该系统。服务器托管在公共云平台上,包括网站服务、数据存储服务、WebSocket 实时通信服务和远程视频监控服务。客户端可以通过云端对试验机进行远程实时监控。经过实验验证,实时监控信息时延为 11 毫秒,视频监控时延为 291 毫秒,能够满足远程弹簧疲劳试验的实际需求。该远程监控系统提高了弹簧疲劳试验机的自动化程度,改善了实验人员的工作环境。此外,该系统还可应用于实验室的其他可靠性试验机,进一步帮助建立车间级远程监控平台。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Cloud-Based Remote Real-Time Monitoring and Control System for Spring Fatigue Testing Machine
In recent years, the utilization of cloud technology has witnessed a surge, particularly in the domains of industrial automation and intelligent scenarios. However, the prevailing spring fatigue testing machine is still in the traditional single-machine working mode. In this mode, there are many problems such as low automation of testing equipment, poor experimental site environment, and the need for experimenters to be on duty for a long time. In order to solve the above problems, this paper builds a cloud-based remote monitoring and control system based on the high-temperature constant-force spring fatigue testing machine. The system is based on Browser/Server architecture, and clients can access it anytime and anywhere using a browser in a public network environment. The server is hosted on a public cloud platform and includes website service, data storage service, WebSocket real-time communication service, and remote video monitoring service. Clients can remotely monitor and control the testing machine in real time through the cloud. After experimental verification, the real-time monitoring and control messages delay is 11 ms, and the video monitoring delay is 291 ms, which can meet the actual needs of remote spring fatigue testing. This remote monitoring and control system improves the automation of the spring fatigue testing machine and improves the working environment of the experimenters. In addition, it can be applied to other reliability testing machines in the laboratory, and can further help build a workshop-level remote monitoring and control platform.
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