专栏文章速递|污水管网重大缺陷快速识别方法研究

题目：污水管网重大缺陷快速识别方法研究作者：王福芝、尹 炜、王殿常、彭寿海、王万琼、陈晓龙Abstract:The current periodic detection mechanism for pipelines has issues, including highcosts and an inability to detect major defects that could impact the safety of the pipelines in a timelymanner. Therefore, it is imperative to develop a rapid identification method for major defects insewage pipelines, In this paper, a rapid identification method for major defects in sewerage pipelines is proposed by integrating various advanced technologies, Firstly, taking the sewage pipelinesin the district and county area as the research object，relying on the multi-source big data analysis technology, the pipe network defect prediction model is built to screen the high-risk areas. Then，advanced technologies such as water quality and quantity analysis and detection, UAV aerial remote sensing, logistic regression prediction model, and vehicle-mounted ground penetrating radarare used to comprehensively and quickly detect the pipelines in high-risk areas to accurately identifypipelines with major defects. Finally, a variety of advanced physical exploration techniques are usedin combination to carry out rapid pipeline internal inspection, in order to accurately obtain the typeand level of pipeline defects, so as to provide a scientific basis for the later repair.摘要：当前污水管网周期性检测机制存在成本高且无法及时发现影响管网正常运行的重大缺陷等问题，亟需开发重大缺陷快速识别方法。通过整合各类先进技术提出了一种污水管网重大缺陷快速识别方法。首先，以区县级片区内的污水管网为研究对象，依托多源大数据分析技术，构建管网缺陷预测模型，筛选高风险区域。然后，综合采用水质水量分析检测、无人机航拍遥感、逻辑回归预测模型、车载探地雷达等先进技术对高风险区域的管网进行全方位、快速的检测，以精确识别出存在重大缺陷的管道。最后，采用多种先进物探技术相结合的方式开展管道内部快速检测，精准获取缺陷类型和缺陷等级，从而为后期的修复提供科学依据。通讯作者：王殿常，男，1973年出生，山东梁山人，博士，正高级工程师。主要研究方向为流域生态环境保护、城市水环境治理等研究和实践。