基于网络通信技术的机械手非线性远程监控系统

IF 2.4 Q2 ENGINEERING, MECHANICAL
Qing Liu, Liye Peng, K. Shang
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引用次数: 0

摘要

摘要为了研究基于网络通信技术的机械手非线性远程监控系统,提出了一种基于网络通信技术的机械手非线性远程监控系统的研究方法。本文在Visual c++环境下,采用传输控制协议/互联网协议技术构建了机械臂远程监控系统,主要实现了机械臂在远程中按轨迹运行的功能。在存储视频时,需要指定视频源的ID,即实时传输协议数据包头中的同步源识别机器人,这样可以更清晰地监控。远程监控技术在现代自动化工业中的广泛应用,不仅进一步扩展了人类的空间活动能力,而且使人类从危险复杂的工作环境中解脱出来。因此,远程监控技术具有广阔的应用前景。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Nonlinear remote monitoring system of manipulator based on network communication technology
Abstract In order to study the nonlinear remote monitoring system of the manipulator based on the network communication technology, a research method of the nonlinear remote monitoring system of the manipulator based on the network communication technology is proposed. In this article, in the Visual C++ environment, the transmission control protocol/internet protocol technology is used to build a remote monitoring system for the robotic arm, and it mainly realizes the function of the robotic arm running according to the trajectory in the remote. When storing video, you need to specify the ID of the video source, i.e., the synchronization source in the real-time transport protocol data packet header identifies the robot, which can monitor more clearly. The remote monitoring technology is widely used in the modern automation industry, which not only further extends the human space activity ability, but also removes the human from the dangerous and complex working environment. Therefore, the remote monitoring technology has broad application prospects.
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来源期刊
CiteScore
6.20
自引率
3.60%
发文量
49
审稿时长
44 weeks
期刊介绍: The Journal of Nonlinear Engineering aims to be a platform for sharing original research results in theoretical, experimental, practical, and applied nonlinear phenomena within engineering. It serves as a forum to exchange ideas and applications of nonlinear problems across various engineering disciplines. Articles are considered for publication if they explore nonlinearities in engineering systems, offering realistic mathematical modeling, utilizing nonlinearity for new designs, stabilizing systems, understanding system behavior through nonlinearity, optimizing systems based on nonlinear interactions, and developing algorithms to harness and leverage nonlinear elements.
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