基于Kalman滤波融合算法的某坝基水平位移综合信息提取

已有坝基水平位移监测模型只能利用一个关键监测点的监测数据,而关键点选取往往具有人为性;直接利用多个监测点的监测信息,往往会出现各个监测点采集数据不一致的现象。为消除这类现象,且充分利用多点监测信息,采用基于Kalman滤波融合方法,分别根据集中式和有无反馈分布式融合算法进行计算,对比分析了其可行性,最后给出融合结果。将其应用于某坝8坝段坝基水平位移的分析,结论较为符合规律,表明3种方法均有很高的识别精度。同时,也为水工建筑基础多点监测提供一个有效的理论方法。

Extraction of Comprehensive Information of Dam Foundation Horizontal Displacement Based on Kalman Filter Fusion Algorithm

Existed monitoring models of dam foundation horizontal displacement adopt only one key monitoring point＇s data,while the choice of the key point is subjective.Traditional multi-sensors method is inclined to result in inconsistency between different monitoring points.Kalman filter fusion algorithm is adopted to eliminate the inconsistency and make full use of the multi-point monitoring information.Fusion algorithm is calculated according to centralized method and distributed method with and without feedback separately.Finally,fusion result is presented.feasibility is comparatively analyzed.The feasibility is also analyzed.Finally,an example simulation is given in order to illustrate the effectiveness of the method in application.Meanwhile,an effective theoretical method is provided for the multi-point monitoring of the hydraulic structure foundation as well.