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基于集合卡尔曼滤波的海洋土孔隙率预测研究

汪明元 张国 潘孙珏徐 陶袁钦

汪明元, 张国, 潘孙珏徐, 陶袁钦. 基于集合卡尔曼滤波的海洋土孔隙率预测研究[J]. 工业建筑, 2023, 53(6): 37-42. doi: 10.13204/j.gyjzG22052707
引用本文: 汪明元, 张国, 潘孙珏徐, 陶袁钦. 基于集合卡尔曼滤波的海洋土孔隙率预测研究[J]. 工业建筑, 2023, 53(6): 37-42. doi: 10.13204/j.gyjzG22052707
WANG Mingyuan, ZHANG Guo, PAN Sunjuexu, TAO Yuanqin. Prediction of Marine Soil Porosity Based on Ensemble Kalman Filters[J]. INDUSTRIAL CONSTRUCTION, 2023, 53(6): 37-42. doi: 10.13204/j.gyjzG22052707
Citation: WANG Mingyuan, ZHANG Guo, PAN Sunjuexu, TAO Yuanqin. Prediction of Marine Soil Porosity Based on Ensemble Kalman Filters[J]. INDUSTRIAL CONSTRUCTION, 2023, 53(6): 37-42. doi: 10.13204/j.gyjzG22052707

基于集合卡尔曼滤波的海洋土孔隙率预测研究

doi: 10.13204/j.gyjzG22052707
详细信息
    作者简介:

    汪明元,男,1972年出生,博士,正高级工程师。

    通讯作者:

    陶袁钦,女,1995年出生,博士,taoyuanqin@zju.edu.cn。

Prediction of Marine Soil Porosity Based on Ensemble Kalman Filters

  • 摘要: 正确评估海洋土的物理力学性质是保障海洋工程安全的关键。基于集合卡尔曼滤波结合波阻抗测量数据和波阻抗-孔隙率转换式,提出了一种海洋土孔隙率的概率预测及不确定性量化的方法。它可同时考虑转换模型和状态转移的不确定性,提供孔隙率沿深度的取值及其不确定性。首先基于先验信息生成海洋土孔隙率估计的初始集合;然后通过由多传感器岩心记录仪取样测量的波阻抗数据和概率转换模型,对海洋土孔隙率进行预测和更新;最后分析转换模型误差、初始集合和观测数据量对孔隙率估计的影响,通过工程实例的验证,表明该方法可有效地估计海洋土孔隙率随深度的空间分布,并量化不确定性。
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出版历程
  • 收稿日期:  2022-05-27
  • 网络出版日期:  2023-08-18

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