净水技术2025，Vol.44Issue(5)：34-43,10.DOI:10.15890/j.cnki.jsjs.2025.05.005
城镇排水管道健康评估研究进展
Research Progress of Health Assessment for Urban Drainage Pipelines
摘要
Abstract
[Objective]Urban drainage pipelines are crucial parts of urban infrastructure,and their health conditions are related to urban safety and operation & maintenance.The health conditions of drainage pipelines are aimed to be analyzed by this study,so as to provide a basis for ensuring the stable operation of the drainage system.[Methods]Relevant studies at home and abroad are integrated.The health influencing factors are analyzed from aspects of the pipelines themselves,the external environment,usage and maintenance.Various risk events and their causes are sorted out.Intuitive inspection and equipment detection means are introduced.The evaluation process and common evaluation method are elaborated,and pipeline prediction models such as artificial neural networks are explored.[Results]Risk events are caused by factors such as the aging of pipelines,the complex external environment,improper operation and maintenance.Each detection technology has its own advantages and disadvantages.Multiple method coexist in the evaluation process.Although progress has been made in prediction models,their application is limited by data.[Conclusion]The health assessment of urban drainage pipelines has shifted from traditional to comprehensive assessment,and certain achievements have been made.However,challenges still remain,such as the lack of unified evaluation standards,difficulties in data fusion,and the need to optimize cost-effectiveness.In future,multi-disciplinary integration and the application of intelligent robot technology need to be promoted to strengthen pipeline health management and enhance urban resilience and sustainable development capabilities.关键词
排水管道/风险事件/检测手段/评估流程/预测模型/健康评估Key words
drainage pipeline/risk event/detection means/evaluation process/prediction model/health assessment分类
土木建筑引用本文复制引用
周毅,刘旭辉,沈加子,李继,张小磊..城镇排水管道健康评估研究进展[J].净水技术,2025,44(5):34-43,10.基金项目
深圳市科技创新委员会科技重大专项(KJZD20230923114800002) （KJZD20230923114800002）
