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《工业仪表与自动化装置》[ISSN:1000-0682/CN:61-1121/TH]

卷:

期数:

2014年06期

页码:

67-69

栏目:

出版日期:

2014-12-15

文章信息/Info

Title:

The boom-type roadheader intelligent control system based on neural network and genetic algorithms

作者:

刘若涵; 赵振民; 赵 杰

（黑龙江科技大学 电气与控制工程学院，哈尔滨 150022）

Author(s):

LIU Ruohan;  ZHAO Zhenmin;  ZHAO Jie

(Institute of Electrical and Control Engineering, Heilongjiang University of Science and Technology，Harbin 150022 China)

关键词:

神经网络; 遗传算法; 悬臂式掘进机; 智能控制

Keywords:

artificial neural network;  genetic algorithms;  boom-type roadheader;  intelligent control

分类号:

TP273

DOI:

-

文献标志码:

A

摘要:

由于煤矿巷道内煤层的分布是不均匀的，并且是时时变化的，这就给高效开采带来了难度。悬臂式掘进机在巷道中作业时，会因为煤层分布的不确定性，导致所受的截割阻力不停地变化，因此，要求掘进机可以根据不同的工况，能够快速地、实时地调整悬臂的摆动速度。该文提出了基于神经网络与遗传算法的复合控制理论的悬臂式掘进机的控制模式。该控制系统能有效地提高生产效率，并且安全可靠。

Abstract:

Since the distribution of the coal seams is uneven and continual variation, it brings difficulty to excavate efficiently. When boom - type roadheader is working in the tunnel, because of the uncertainty of the distribution of coal seams, cutting resistance suffered by roadheader is changing constantly. So the roadheader should adjust boom swing speed quickly and in real time according to different conditions. This paper presents a composite control mode, that is a control theory of boom - type roadheader based on neural network and genetic algorithms, which can improve production efficiency effectively , and safety and reliability.

参考文献/References:

[1] 汪胜陆,孟国营,田劼,等.悬臂式掘进机的发展状况及趋势[J].煤矿机械,2007,28(6):1-3.[2] 刘建功,吴淼,魏景生,等.悬臂式掘进机自动截割控制关键技术[J].中国煤炭,2008,34(12):54-57.[3] 王慧,张笑,赵迪.基于PLC的掘进机恒功率变频调速系统仿真分析[J].电子测量与仪器学报,2013,27(10):951-956.[4] 李晓豁,吴志强.基于参数自适应模糊PID控制器的掘进机恒功率调速系统[J].制造业自动化,2009,31(1):45-47.[5] 许力.智能控制与智能系统[M].北京:机械工业出版社,2006.

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更新日期/Last Update: 1900-01-01