人民珠江2024，Vol.45Issue(3)：138-145,8.DOI:10.3969/j.issn.1001-9235.2024.03.015
基于稳健估计和变量分离的大坝监测数据异常值识别方法
Outlier Detection Method of Dam Monitoring Data Based on Robust Estimation and Variable Separation
摘要
Abstract
The original monitoring data of dams is the most important data to grasp the operation behavior of the dams,and the outliers in the data are the focus during the analysis.Outliers are divided into two categories.One category is caused by measurement errors and should be eliminated or supplemented to avoid affecting subsequent analysis.The other is caused by structural mutations and should be highly valued.At present,main outlier recognition methods in dam engineering are based on traditional mathematical statistics and do not consider the influence of structural anomalies,which results in low recognition accuracy.Therefore,based on an in-depth study of dam monitoring data and outlier characteristics,this paper first employs robust MM estimation to eliminate the normal influence of internal and external factors and then adopts the residual measured value to eliminate the stable abnormal influence by difference before and after.Finally,according to the minimum value method,outlier identification is conducted on the residual values.The application of the measured dam data proves that the proposed method can identify the measurement outliers more effectively and robustly,and avoid the interference of structural stability anomalies.关键词
异常值识别/时间序列数据/稳健估计/大坝监测/变量分离Key words
outlier detection/time series data/robust estimation/dam monitoring/variable separation分类
建筑与水利引用本文复制引用
梁汇彬,张瀚,张林松,曹宇鑫,周靖人..基于稳健估计和变量分离的大坝监测数据异常值识别方法[J].人民珠江,2024,45(3):138-145,8.基金项目
四川省科技厅重点研发项目(2022YFS0535) （2022YFS0535）
