• 论文
主办单位:煤炭科学研究总院有限公司、中国煤炭学会学术期刊工作委员会
煤岩识别技术发展综述
  • Title

    Overview of the development of coal rock recognition technology

  • 作者

    贺艳军李海雄胡淼龙薛竞飞

  • Author

    HE Yanjun;LI Haixiong;HU Miaolong;XUE Jingfei

  • 单位

    国能包头能源有限责任公司榆林市能源局浙江维思无线网络技术公司西安科技大学电气与控制工程学院

  • Organization
    CHN Energy Baotou Energy Co., Ltd.
    Yulin Energy Bureau
    Wins Wireless Network Technology Ltd.
    College of Electrical and Control Engineering,Xi'an University of Science and Technology
  • 摘要
    煤岩识别技术可为采煤机自动调高提供依据,是实现煤矿智能无人化开采的关键。现有煤岩识别技术包括图像识别、过程信号监测识别、电磁波识别、超声波探测识别、多传感器融合识别等。详细介绍了上述几种技术原理及应用现状:①图像识别技术目前处于实验阶段,主要涉及大规模煤岩图像数据标注和复杂地质条件下的识别问题。②过程信号监测识别技术可分析煤矿开采过程中的相关信号,识别潜在的煤岩界面信息,但需要解决信号噪声干扰和复杂煤岩界面识别问题。③电磁波识别技术和超声波探测识别技术已在实际煤岩界面探测中应用,但仍需要提高识别准确性和可靠性,尤其是对于复杂煤岩结构和界面情况。④多传感器融合识别技术需解决数据融合和匹配的难题,确保不同传感器之间的精确校准和可靠性,并验证其在实际应用中的可行性和实用性。针对上述问题,指出煤岩识别技术发展方向:①煤岩识别研究应着重提高算法的实时性和抗干扰能力,确保在特定条件下并兼有复杂环境干扰下也能准确识别煤岩,满足井下实际开采需求。②加强矿用传感器的研究,以提高其抗干扰性能,同时采用先进的视觉相机和智能设备,与传感器相结合,提高煤岩识别的精度和效率。③多种煤岩识别技术交叉融合使用:对于不同硬度的煤岩,可采用过程信号监测识别和多传感器融合技术;对于硬度接近的情况,可结合图像识别和电磁波识别技术,实现煤岩壁界面和煤层厚度的准确识别。
  • Abstract
    Coal rock recognition technology can provide a basis for automatization improvement of shearerand is the key to achieving intelligent unmanned mining in coal mines. The existing coal rock recognitiontechnologies include image recognition, process signal monitoring recognition, electromagnetic wave recognition,and ultrasonic detection recognition, multi-sensor fusion recognition. This article provides a detailed introductionto the principles and application status of the above-mentioned technologies. ① Image recognition technology iscurrently in the experimental stage, mainly involving large-scale coal rock image data annotation and recognitionproblems under complex geological conditions. ② Process signal monitoring and recognition technology can analyze relevant signals during coal mining and recognize potential coal rock interface information. But it needs tosolve the problems of signal noise interference and complex coal rock interface recognition. ③ Electromagneticwave recognition technology and ultrasonic detection recognition technology have been applied in actual coalrock interface detection. But there is still a need to improve recognition accuracy and reliability, especially forcomplex coal rock structures and interface situations. ④ Multi sensor fusion recognition technology needs tosolve the problem of data fusion and matching, ensure accurate calibration and reliability between differentsensors, and verify its feasibility and practicality in practical applications. In order to solve the above problems,the development directions of coal rock recognition technology are pointed out. ① Research on coal rockrecognition should focus on improving the real-time performance and anti-interference capability of algorithms. Itwill ensure accurate recognition of coal rock under specific conditions and complex environmental interference,and meet the actual mining needs underground. ② Research on coal rock recognition should strengthen theresearch on mining sensors to improve their anti-interference performance. It is suggested to adopt advancedvisual cameras and intelligent devices to combine with sensors to improve the precision and efficiency of coalrock recognition. ③ Research on coal rock recognition should focus on the cross fusion of multiple coal and rockrecognition technologies. For coal and rock with different hardness, process signal monitoring recognition andmulti-sensor fusion technology can be adopted. For cases with similar hardness, image recognition andelectromagnetic wave recognition techniques can be combined to achieve accurate recognition of coal rock wallinterfaces and coal seam thickness.
  • 关键词

    煤岩识别采煤机滚筒图像识别过程信号监测识别电磁波识别超声波探测识别多传感器融合识别

  • KeyWords

    coal rock recognition;shearer drum;image recognition;process signal monitoring andrecognition;electromagnetic wave recognition;ultrasonic detection and recognition;multi sensor fusionrecognition

  • 基金项目(Foundation)
    陕西省秦创原“科学家+工程师”队伍建设项目(2022KXJ-38)
  • DOI
  • 引用格式
    贺艳军,李海雄,胡淼龙,等. 煤岩识别技术发展综述[J]. 工矿自动化,2023,49(12):1-11.
  • Citation
    HE Yanjun, LI Haixiong, HU Miaolong, et al. Overview of the development of coal rock recognition technology[J]. Journal ofMine Automation,2023,49(12):1-11.
  • 相关专题
相关问题

主办单位:煤炭科学研究总院有限公司 中国煤炭学会学术期刊工作委员会

©版权所有2015 煤炭科学研究总院有限公司 地址:北京市朝阳区和平里青年沟东路煤炭大厦 邮编:100013
京ICP备05086979号-16  技术支持:云智互联