人民长江2024，Vol.55Issue(1)：236-241,6.DOI:10.16232/j.cnki.1001-4179.2024.01.033
基于LV-DBSCAN算法的大坝安全监测数据异常检测
Detection of abnormal values in dam safety monitoring data based on LV-DBSCAN algorithm
摘要
Abstract
There are often abnormal measurements in the original observation sequence of dam safety monitoring,which greatly affects the reliability and accuracy of dam safety monitoring data analysis.Therefore,based on the analysis of the abnormal values characteristics and the advantages and disadvantages of traditional anomaly detection methods,this paper studied the detection methods of abnormal values in monitoring data from the local and overall perspectives.Firstly,aiming at the defects of multiple lo-cal anomaly coefficient methods requiring data with long sequence and equal time interval,a local change anomaly coefficient method(LV)and a collaborative discrimination strategy of local method and overall method were proposed.Furthermore,the densi-ty clustering algorithm(DBSCAN)was introduced,and a LV-DBSCAN anomaly detection method considering the overall and lo-cal characteristics of the data was proposed.Taking the downstream displacement monitoring data of two vertical measuring points of a concrete gravity dam as an example,the detection accuracy of different methods on different types of data sets was compared and analyzed.The results showed that the LV-DBSCAN method proposed in this paper has wider applicability,higher accuracy and lower misjudgment rate.关键词
大坝安全监测/异常值/局部变化异常系数法(LV)/密度聚类算法(DBSCAN)/置信度Key words
dam safety monitoring/abnormal value/local change anomaly coefficient method/density clustering algorithm/con-fidence degree分类
建筑与水利引用本文复制引用
戴领,李少林,刘光彪,纪传波,段国学..基于LV-DBSCAN算法的大坝安全监测数据异常检测[J].人民长江,2024,55(1):236-241,6.基金项目
湖北省博士后创新实践岗位项目(2022CXGW003) （2022CXGW003）
长江勘测规划设计研究有限责任公司自主创新项目(CX2019Z18,CX2020Z46) （CX2019Z18,CX2020Z46）
