基于BDS/GNSS的高精度变形监测和智能预警
1Yong Coal Company Geological Survey Department, Henan Energy Group, Yongcheng, Henan, China.
PloS one
|June 23, 2025
概括
这项研究使用了北斗系统和全球导航卫星系统 (BDS/GNSS),使用先进的算法来精确监测井口变形. 智能预警系统达到毫米级准确度,提高了矿山的安全性.
科学领域:
- 地测和地质工程的工程.
- 地质技术工程 地质技术工程
- 在工程领域的人工智能.
背景情况:
- 煤矿开采造成的井口变形对地下基础设施和安全构成重大风险.
- 传统的监测方法往往缺乏复杂地质环境所需的精度和动态能力.
- 整合多个星座的全球导航卫星系统 (GNSS) 提供了增强变形监测的潜力.
研究的目的:
- 开发和评估使用北斗系统和全球导航卫星系统 (BDS/GNSS) 的高精度井口变形监测系统.
- 评估联合BDS/GNSS系统的性能,以及基线长度对监测准确性的影响.
- 使用深度学习建立一个智能早期预警模型,用于采用深度学习的井口变形.
主要方法:
- 采用了一种改进的修改最小平方模两可关系 (MLAMBDA) 算法,用于动态BDS/GNSS数据处理的双差异模型.
- 量化分析了各种BDS/GNSS组合的性能,并评估了不同基线长度 (1-6公里) 的影响.
- 开发了一个Bi-LSTM深度学习模型,用于基于高精度变形序列的智能预警系统.
主要成果:
- BDS/GNSS多系统组合在东,北和上方向实现了2毫米的监控精度,优于单一的全球定位系统 (GPS).
- 随着基线长度的增加,观察到精度下降;然而,在6公里内,水平精度仍然为<3毫米,垂直精度为<6毫米.
- Bi-LSTM早期预警模型展示了适应特定场所条件和干扰的适应性,准确地捕捉了非线性时间变化的变形特征.
结论:
- 结合BDS/GNSS系统为高精度井口变形监测提供了强大而准确的解决方案,满足了关键的安全要求.
- 开发的智能预警系统提供了可靠的毫米级预测 (例如,<1mm用于一个月的预测),增强了矿山安全协议.
- 该方法可扩展到其他大型工程基础设施,如桥梁,大和铁路,用于每小时的变形监测和早期预警.
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