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Research on an Adaptive Progressive Point Cloud Filtering Algorithm for Deformation Monitoring of Mine Roadways
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Lei Wang1, Jingjing Zhang2, Junyan Qi2, Zhuli Ren3
Mining Research and Development | 2026, 46(6) : 218 - 224
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Mining Research and Development | 2026, 46(6): 218-224
Research on an Adaptive Progressive Point Cloud Filtering Algorithm for Deformation Monitoring of Mine Roadways
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Lei Wang1, Jingjing Zhang2, Junyan Qi2, Zhuli Ren3
Affiliations
  • 1.School of Computer Science and Technology, Henan Polytechnic University, Jiaozuo, Henan 454003, China
  • 2.School of Software, Henan Polytechnic University, Jiaozuo, Henan 454003, China
  • 3.School of Energy Science and Engineering, Henan Polytechnic University, Jiaozuo, Henan 454003, China
Published: 2026-06-18
Outline
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Point cloud data of mine roadways acquired by three-dimensional laser scanning often contain noise interference. Existing filtering methods struggle to balance point cloud data simplification with the accurate preservation of roadway geometric features. In contrast, adaptive filtering can dynamically adjust filtering parameters based on the characteristics of the original data, thereby providing a high-quality data foundation for subsequent roadway deformation monitoring. An adaptive progressive point cloud filtering algorithm was proposed, which integrated an improved adaptive voxel filter and a layer-constrained dynamic radius filter to achieve precise point cloud denoising. Specifically, the improved voxel filter can adaptively adjust voxel grid sizes according to the geometric complexity of the roadway, effectively simplifying the point cloud while better preserving its geometric features. The layered constraint dynamic radius filter optimized the dynamic radius parameters through a layered constraint model, enabling the accurate elimination of residual noise. Experimental results show that, compared with traditional voxel filtering, the improved voxel filter, and their conventional combinations, the proposed algorithm achieves a point cloud simplification rate exceeding 92% while controlling the change rates of point cloud volume and surface area within 3%. It can provide reliable data preprocessing technical support for mine roadway deformation monitoring.

Roadway deformation  /  Point cloud denoising  /  Adaptive voxel filtering  /  Point cloud slicing  /  Layered constraint
王磊, 张晶晶, 齐俊艳, 任助理. 面向矿井巷道变形监测的自适应递进点云滤波算法研究. 矿业研究与开发, 2026 , 46 (6) : 218 -224 .
Lei Wang, Jingjing Zhang, Junyan Qi, Zhuli Ren. Research on an Adaptive Progressive Point Cloud Filtering Algorithm for Deformation Monitoring of Mine Roadways[J]. Mining Research and Development, 2026 , 46 (6) : 218 -224 .
Year 2026 volume 46 Issue 6
33
11
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  • Receive Date:2025-07-04
  • Online Date:2026-10-27
  • Published:2026-06-18
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  • Received:2025-07-04
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Affiliations
    1.School of Computer Science and Technology, Henan Polytechnic University, Jiaozuo, Henan 454003, China
    2.School of Software, Henan Polytechnic University, Jiaozuo, Henan 454003, China
    3.School of Energy Science and Engineering, Henan Polytechnic University, Jiaozuo, Henan 454003, China
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表12种不同金属材料的力学参数
科
Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
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属
Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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