摘要
Abstract
Water supply pipe networks serve as vital infrastructures in urban and rural areas.However,leakage issues offen appear during prolonged operation.Among these concerns,dark leakage within the garden pipe network stands out as a complex and elusive problem,characterized by a multitude of causes,challenging detection,prolonged leakage periods,and substantial water loss.These characteristics result in immeasurable losses for water supply enterprises,making the control of pipe network leakage a pressing and longstanding issue in the water supply industry.Regrettably,the leakage within the garden pipe network,considered the"last mile"of the secondary water supply,has often been overlooked by water companies and property management firms.To address this problem,this paper proposed a novel"curve fit"algorithm,which leveraged big data and computer technology to achieve accurate prediction of garden pipe network leakage events.The algorithm's effectiveness was demonstrated through its application and validation over a span of more than three years by a water supply company.The results show the algorithm's accuracy and practicality in predicting leakage events,providing invaluable technical support to effectively mitigate courtyard pipe network leakage.关键词
二次供水/庭院管道漏损/大数据/二次移动平均法/曲线吻合度Key words
secondary water supply/leakage of courtyard pipelines/big data/double moving average/curve-fitting degree分类
土木建筑
