井下机车调度与故障信息物理系统模型研究

IF 1.9 4区 工程技术 Q3 ENGINEERING, MECHANICAL
Jinyu Ma, Jianzhi Zheng, Boyun Li, Wenhong Li
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引用次数: 0

摘要

故障诊断对于事故发生后系统的快速恢复具有重要意义。本工作发展多控制器间智能调度,提高井下机车调度效率,最终实现无人驾驶的智能机车调度。基于信息物理系统(CPS)模型理论,建立了带信号灯、车辙机、机车等设备的机车调度逻辑处理模型。该系统中的模型任务与嵌入式控制器任务相结合,便于使用托勒密II软件对逻辑处理过程进行优化。研究结果表明,该模型可以使机车调度过程无死锁,使处理过程更加合理。仿真和实际实验表明,建立CPS模型后,可以提高控制器的协同速度,实现更安全、更有效的机车自动调度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research on cyber-physical system models of downhole locomotive dispatching and fault
Fault diagnosis is of great significance for the rapid recovery of the system after the accident. Intelligent dispatching among multiple controllers is developed in this work to improve the efficiency of downhole locomotive dispatching, finally realizing unmanned intelligent locomotive dispatching. The locomotive dispatching logic processing model of with signal lights, rutting machine, locomotives, and other equipment is established based on the model theory of Cyber-physical systems (CPS). The model tasks in this system are combined with the embedded controller tasks which make it convenient to optimize the logic processing procedures using Ptolemy II software. Our key findings indicate that the proposed model can make the locomotive dispatching process without deadlock and make the processing procedure more reasonable. Simulation and practical experiments demonstrate that the controller cooperation speed can be improved after the CPS model is built, which can realize safer and more effective automatic locomotive dispatching.
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来源期刊
Advances in Mechanical Engineering
Advances in Mechanical Engineering 工程技术-机械工程
CiteScore
3.60
自引率
4.80%
发文量
353
审稿时长
6-12 weeks
期刊介绍: Advances in Mechanical Engineering (AIME) is a JCR Ranked, peer-reviewed, open access journal which publishes a wide range of original research and review articles. The journal Editorial Board welcomes manuscripts in both fundamental and applied research areas, and encourages submissions which contribute novel and innovative insights to the field of mechanical engineering
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