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作 者:李鹏飞 雷未 虞冬冬 吉同元 LI Pengfei;LEI Wei;YU Dongdong;JI Tongyuan(China Design Group Co.,Ltd.,Nanjing 210014,China;China Testing Technology Co.,Ltd.,Nanjing 210014,China;College of Water Conservancy and Hydropower Engineering,Hohai University,Nanjing 210098,China;Changzhou Class III Waterway Network Regulation Project Construction Headquarters Office,Changzhou 213003,China)
机构地区:[1]华设设计集团股份有限公司,江苏南京210014 [2]华设检测科技有限公司,江苏南京210014 [3]河海大学水利水电学院,江苏南京210098 [4]常州市三级航道网整治工程建设指挥部办公室,江苏常州213003
出 处:《人民长江》2023年第11期221-227,共7页Yangtze River
基 金:国家自然科学基金项目(52279099)。
摘 要:由于系统故障或外界环境扰动影响,工程监测数据常会出现漂移的现象。对于水工建筑物,由于结构的相似性和测点布置的相关性,其监测量往往具有显著的空间关联性,使得监测数据存在相似的变化规律,以此可为测点的漂移校正提供判别依据。依据上述原理,提出基于相似测点的密度聚类分析,并运用DBSCAN算法判定测点漂移区间和漂移量;同时为克服校正突变和类簇粘连等问题,引入滑动窗口模式建立监测量漂移的动态校正模型,其校正过程分为窗口内数据校正与窗口滑动校正两个部分。工程实例表明:该方法具有较强的适用性及较高精度,为结构中存在相似测点的数据漂移问题提供了新的自动校正思路。Due to the system fault or external disturbance,the drift phenomenon of monitoring data often occurs.As for hydraulic structures,because of the structure similarity and the correlation of measuring points arrangement,the monitoring data often have significant spatial correlation making them possess similar variation rules,so as to provide a discriminant basis for the drift correction of the measuring points.According to the above principle,the density clustering analysis based on similar measuring points was proposed,and the DBSCAN algorithm was used to determine the drift interval and drift amount of measuring points.At the same time,in order to overcome the problems of correction mutation and cluster adhesion,the sliding window mode was introduced to establish a dynamic correction model for monitoring data drift.The correction process was divided into two parts,data correction within window and window sliding correction.The engineering example showed that this method has strong applicability and high precision,which provides a new automatic correction idea for the data drift problem of similar measuring points in hydraulic structures.
分 类 号:TV698[水利工程—水利水电工程]
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