Physical diagnostic for profibus DP networks based on Artificial Neural Network

R. C. Souza, E. A. Mossin, D. Brandão
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引用次数: 2

Abstract

PROFIBUS (Process Field Bus) DP is the most used field communication bus in the worldwide industry. The increasing use of this fieldbus network protocol in industrial plants has made quick diagnostics for fails extremely necessary and important in order to minimize halt time during installation and the consequent financial losses in the production process. This work describe a tool based on Artificial Neural Networks (ANN), which will be used to promptly diagnose the physical layer of a PROFIBUS network in case of a failure, providing a criterial performance analysis through the basic concepts presented. In this context, this paper will briefly describe the physical layer of the mentioned protocol and the related problems, as well as the results from the performed ANN training.
基于人工神经网络的profibus DP网络物理诊断
PROFIBUS(过程现场总线)DP是目前世界范围内应用最广泛的现场通信总线。这种现场总线网络协议在工业工厂中的使用越来越多,这使得快速诊断故障变得非常必要和重要,以便最大限度地减少安装期间的停机时间和生产过程中随之而来的经济损失。本工作描述了一种基于人工神经网络(ANN)的工具,该工具将用于在故障情况下快速诊断PROFIBUS网络的物理层,通过提出的基本概念提供标准性能分析。在此背景下,本文将简要描述上述协议的物理层和相关问题,以及所执行的人工神经网络训练的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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