首页|综采机电设备智能化管控平台研究与应用

综采机电设备智能化管控平台研究与应用

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针对传统综采机电设备管理模式过度依赖人工方式存在的管理效率低下、反应迟缓、管理粒度较粗以及难以实现对综采机电设备的精细化管理与调度等问题,北京天玛智控科技股份有限公司运用物联网、大数据和人工智能等先进技术,构建了综采机电设备智能化管控平台,以实现对关键装备的状态监测、故障预测、寿命评估与精细化管理.介绍了综采机电设备智能化设备管控平台总体架构、数据采集、动态监测和故障预测以及智能调度与优化等关键技术,相关技术成果在国能神东煤炭有限责任公司上湾、榆家梁、保德等煤矿进行了应用.应用结果表明,该管控平台能够极大提高设备管理的智能化和科学决策水平,对企业安全生产与降本增效具有重要作用.
Research and application of intelligent management and control platform for mechanical and electrical equipment for fully mechanized mining
In response to the low management efficiency,slow response,coarse management granularity,and difficulties in achieving refined management and scheduling in the traditional management mode of the mechanical and electrical equipment for fully mechanized mining,CCTEG Beijing Tianma Intelligent Control Technology Co.,Ltd.used the Internet of Things,big data,artificial intelligence and other technologies to build an intelligent management and control platform for mechanical and electrical equipment for fully mechanized mining,so as to achieve status monitoring,fault prediction,life assessment,and refined management of the key equipment.The overall architecture,data collection,dynamic monitoring,fault prediction,intelligent scheduling and optimization,and other key technologies of the intelligent management and control platform were introduced.The relevant technical achievements have been applied in Shangwan Coal Mine,Yujialiang Coal Mine and Baode Coal Mine,and the application results showed that the platform could greatly improve the intelligent and scientific decision-making level of equipment management,and play an important role in the safety production,cost reduction and efficiency increase of enterprises.

mechanical and electrical equipment for fully mechanized miningintelligent management and controlequipment managementartificial intelligenceindustrial Internet of Things

秦泽宇、王伟涛、冯银辉、崔耀、王建兵、王帅

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北京天玛智控科技股份有限公司,北京市顺义区,101399

综采机电设备 智能化管控 设备管理 人工智能 工业物联网

中国煤炭科工集团有限公司科技创新创业资金专项项目山东省重大科技创新工程项目课题

2023-TD-QN0072020CXGC01150102

2024

中国煤炭
煤炭信息研究院

中国煤炭

CSTPCD北大核心
影响因子:0.736
ISSN:1006-530X
年,卷(期):2024.50(2)
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