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基于矩阵奇异值分解约束型无迹粒子滤波的滑坡位移预测模型研究
李丽敏, 温宗周, 董勋凯, 王真, 张阳阳, 李璐
西安工程大学 电子信息学院, 陕西 西安 710048
摘要:
[目的]通过对滑坡位移预测模型进行研究,为政府部门实施更加可靠的灾害防治决策提供科学依据。[方法]提出了一种矩阵奇异值分解(SVD)约束型无迹粒子滤波(IUPF)方法,建立基于位移参数的滑坡位移预报模型。[结果]利用改进的SVD方法有效提升了无迹粒子滤波方法中Sigma点计算的鲁棒性,从而提升了算法的预测精度,对滑坡的稳定趋势能够做出更准确的预报。将该算法在镇江市跑马山滑坡体监测工程、京港澳高速公路雨花互通南侧护坡体滑坡监测工程相关数据进行了应用和分析验证。[结论]实例验证结果表明,加入SVD约束后的无迹粒子滤波算法,能够使得滑坡位移预测更加准确,预测的数据更加准确地反映了滑坡的变形趋势。
关键词:  SVD约束  UPF算法  滑坡位移预测  鲁棒性
DOI:10.13961/j.cnki.stbctb.2019.01.021
分类号:
基金项目:陕西省教育厅科学研究项目"陕西地区降雨型滑坡形成机理与监测预警系统研究"(17JK0346);西安工程大学博士科研启动项目"基于深度学习的轴承故障诊断方法研究"(BS1506)
Landslide Displacement Prediction Model Based on Singular Value Decomposition Constrained Unscented Particle Filter
Li Limin, Wen Zongzhou, Dong Xunkai, Wang Zhen, Zhang Yangyang, Li Lu
College of Electronics and Information, Xi'an Polytechnic University, Xi'an, Shaanxi 710048, China
Abstract:
[Objective] To study the landslide displacement prediction model, in order to provide a scientific basis for government departments to implement more reliable disaster prevention and control decisions. [Methods] An iterative unscented particle filter (IUPF) method based on singular value decomposition (SVD) constrain was proposed to establish a landslide displacement prediction model based on displacement parameters. [Results] The SVD method was effectively improved the robustness of Sigma point calculation in the unscented particle filtering method, thereby improving the prediction accuracy of the algorithm and making a more accurate prediction of the landslide stability trend. The algorithm was applied to the application and analysis of the data related to the monitoring project of the Paomashan landslide in Zhenjiang City and the landslide monitoring project on the south side of the Yuhua Interchange in Beijing-Hong Kong-Macao Expressway. [Conclusion] The prediction in landslide displacement with the unscented particle filtering algorithm with SVD constraint can be more accurate, and the predicted data can reflect the deformation trend of the landslide more accurately.
Key words:  singular value decomposition (SVD) constraint  unscented particle filter (UPF) algorithm  landslide displacement prediction  robustness