A novel coal-rock recognition method in coal mining face based on fusing laser point cloud and images

IF 11.7 1区 工程技术 Q1 MINING & MINERAL PROCESSING
Yang Liu, Lei Si, Zhongbin Wang, Miao Chen, Xin Li, Dong Wei, Jinheng Gu
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引用次数: 0

Abstract

Rapid and accurate recognition of coal and rock is an important prerequisite for safe and efficient coal mining. In this paper, a novel coal-rock recognition method is proposed based on fusing laser point cloud and images, named Multi-Modal Frustum PointNet (MMFP). Firstly, MobileNetV3 is used as the backbone network of Mask R-CNN to reduce the network parameters and compress the model volume. The dilated convolutional block attention mechanism (Dilated CBAM) and inception structure are combined with MobileNetV3 to further enhance the detection accuracy. Subsequently, the 2D target candidate box is calculated through the improved Mask R-CNN, and the frustum point cloud in the 2D target candidate box is extracted to reduce the calculation scale and spatial search range. Then, the self-attention PointNet is constructed to segment the fused point cloud within the frustum range, and the bounding box regression network is used to predict the bounding box parameters. Finally, an experimental platform of shearer coal wall cutting is established, and multiple comparative experiments are conducted. Experimental results indicate that the proposed coal-rock recognition method is superior to other advanced models.
基于激光点云和图像融合的采煤工作面煤岩识别新方法
快速准确地识别煤岩是煤矿安全高效开采的重要前提。本文提出了一种基于激光点云和图像融合的煤岩识别新方法——多模态截点网(MMFP)。首先,利用MobileNetV3作为Mask R-CNN的骨干网,减少网络参数,压缩模型体积;将扩展卷积块注意机制(dilated CBAM)和初始结构与MobileNetV3相结合,进一步提高了检测精度。随后,通过改进的Mask R-CNN算法计算二维目标候选框,提取二维目标候选框中的视锥点云,减小计算规模和空间搜索范围。然后,构造自关注点网(PointNet)对融合点云在视台范围内进行分割,并利用边界框回归网络对边界框参数进行预测;最后,建立了采煤机煤壁截割实验平台,并进行了多次对比实验。实验结果表明,本文提出的煤岩识别方法优于其他先进模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
International Journal of Mining Science and Technology
International Journal of Mining Science and Technology Earth and Planetary Sciences-Geotechnical Engineering and Engineering Geology
CiteScore
19.10
自引率
11.90%
发文量
2541
审稿时长
44 days
期刊介绍: The International Journal of Mining Science and Technology, founded in 1990 as the Journal of China University of Mining and Technology, is a monthly English-language journal. It publishes original research papers and high-quality reviews that explore the latest advancements in theories, methodologies, and applications within the realm of mining sciences and technologies. The journal serves as an international exchange forum for readers and authors worldwide involved in mining sciences and technologies. All papers undergo a peer-review process and meticulous editing by specialists and authorities, with the entire submission-to-publication process conducted electronically.
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