同济大学学报（自然科学版）2026，Vol.54Issue(4)：473-482,10.DOI:10.11908/j.issn.0253-374x.25048
基于无线传感与XGBoost模型的供水管网监测与分析
Integrated Monitoring and Analysis of Water Supply Network Based on Wireless Sensing and XGBoost Model
摘要
Abstract
In this study,a self-developed wireless monitoring system was deployed at 25 monitoring sites in the central urban area of Shanghai to collect real-time multi-source data on pipeline structural conditions and surrounding environmental factors.The XGBoost(eXtreme Gradient Boosting)algorithm was applied for quantitative analysis to reveal the influence mechanisms of various environmental factors on pipeline structural changes.The results indicate that soil pressure,soil displacement,pipe crown and invert temperatures,and pore water pressure exhibit significant variations during pipeline operation,reflecting characteristics such as soil backfilling processes,foundation settlement,and groundwater dynamics.The XGBoost model trained on the monitoring data demonstrated excellent predictive performance,with a 98%overlap between predicted and observed values,confirming the model's high accuracy and robustness.Furthermore,feature importance analysis showed that soil displacement changes accounted for 77.8%of the total feature weight,making it the dominant driving factor influencing changes in pipeline structural angles.Therefore,monitoring points for water supply networks should be preferentially installed in areas where the tri-cross junction is prone to change.关键词
供水管网/无线监测/管道结构/机器学习Key words
water supply network/wireless monitoring/pipeline structure/machine learning分类
建筑与水利引用本文复制引用
胡群芳,聂爽,王飞,海倩,李荣帅,毛源康,刘洋河..基于无线传感与XGBoost模型的供水管网监测与分析[J].同济大学学报（自然科学版）,2026,54(4):473-482,10.基金项目
国家重点研发计划(2022YFC3801000) （2022YFC3801000）
上海市自然基金(24ZR1470300) （24ZR1470300）
上海城投水务集团公司资助项目(KY.WB.23.012) （KY.WB.23.012）
