Discussion on disaster environment detection technology of coal mine rescue robot
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摘要: 在分析传统的煤矿救灾机器人突水水源、火灾及瓦斯浓度侦测技术原理和特点的基础上，提出了基于无线自组网的煤矿救灾机器人突水水源侦测方法、基于大数据的煤矿救灾机器人火灾侦测方法、基于多源信息融合的煤矿救灾机器人瓦斯浓度侦测方法，可有效提高煤矿救灾机器人突水水源、火灾及瓦斯浓度侦测的准确率。指出了煤矿救灾机器人灾变环境侦测技术将深度融合云计算、人工智能、物联网等现代信息技术，从而全面提升煤矿救灾机器人灾变环境侦测结果的可靠性。Abstract: Based on analysis of principle and characteristics of traditional water inrush source, fire and gas concentration detection technologies of coal mine rescue robot, water inrush source detection method of coal mine rescue robot based on wireless ad-hoc network, fire detection method of coal mine rescue robot based on big data and gas concentration detection method of coal mine rescue robot based on multi-source information fusion were proposed, which could effectively improve accuracy of water inrush water, fire and gas concentration detection of coal mine rescue robot. It was pointed out that disaster environment detection technology of coal mine rescue robot would deeply integrate modern information technologies such as cloud computing, artificial intelligence and Internet of things, so as to comprehensively improve reliability of disaster environment detection results of coal mine rescue robot.
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期刊类型引用(3)
1. 赵春雷，田中华，李航，舒爱国，朱红金，李明，李慧彤. 煤矿探巷机器人感测与控制系统研发与应用. 煤炭工程. 2022(05): 188-192 . 
百度学术
2. 杨佳，丁宗广. 应急管理科技支撑研究综述. 中国应急管理科学. 2021(01): 63-74 . 百度学术
3. 郑学召，童鑫，郭军，张铎. 煤矿智能监测与预警技术研究现状与发展趋势. 工矿自动化. 2020(06): 35-40 . 本站查看
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