人民黄河2025，Vol.47Issue(3)：141-145,5.DOI:10.3969/j.issn.1000-1379.2025.03.022
基于平滑阈值与孤立森林的大坝监测数据异常检测
Anomaly Detection of Dam Monitoring Data Based on Smoothing Threshold and Isolated Forest
摘要
Abstract
In order to solve the issue of data misjudgment caused by the inability to identify the trend and correlation between data when the isolated forest algorithm detected dam abnormal data,an anomaly detection algorithm based on smooth threshold and isolated forest was pro-posed.Firstly,the trend term of time series data was extracted by wavelet transform.Secondly,ARMA model was used to determine the dy-namic threshold interval of the extracted trend item data.Finally,isolated forest algorithm was used to detect the outliers scattered outside the threshold interval.Taking the concrete faced rockfill dam of Jiayan Key Water Control Project in Bijie City,Guizhou Province as an example,the monitoring data of four parts of the dam foundation,dam body,peripheral joint and panel were tested respectively to verify the effective-ness of the algorithm.The results show that comparing with the traditional isolated forest algorithm,the algorithm based on smooth threshold and isolated forest reduces the misjudgment rates of pressure,observation room settlement,opening and closing degree,and stress have been reduced by 12.2,13.4,7.1,and 8.0 percentage points,respectively.关键词
小波变换/ARMA模型/孤立森林/异常检测/大坝/毕节市夹岩水利枢纽工程Key words
wavelet transform/ARMA model/isolated forest/anomaly detection/dam/Jiayan Key Water Control Project in Bijie City分类
建筑与水利引用本文复制引用
张瑜,秦学,彭浩..基于平滑阈值与孤立森林的大坝监测数据异常检测[J].人民黄河,2025,47(3):141-145,5.基金项目
贵州省科技计划项目(黔科合支撑[2023]一般251) （黔科合支撑[2023]一般251）
