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溃口下游河道水动力特征实时监测技术研究OA

Study on real-time monitoring technology for hydrodynamics of river channel flow downstream of breached dams

中文摘要英文摘要

溃口下游河道水动力特征的实时、精准监测是水利工程安全防护与防洪减灾决策的关键支撑,传统接触式监测技术存在响应滞后、精度不足等问题,难以满足应急监测需求.本文通过融合图像识别技术、LSPIV和PTV技术,研发了高效的HAIT算法引擎,有效提高了溃口水流速度分布的测量精度和效率.同时,针对复杂场景下的测量问题,引入L-K金字塔光流算法和图像金字塔构建方法,解决了大运动不连贯情况下的光流计算难题.此外,还构建了河道视频智能流速监测技术体系,包括监测系统组成和工作流程,并通过实际应用测试验证了该技术的可靠性与有效性,为溃口下游河道水动力监测提供了新的技术手段.

Real-time and accurate monitoring of the hydrodynamic characteristics of river channel flow downstream of a breached dam is fundamental to the safety protecting performance of a hydraulic project and the decision-making of flood control and disaster mitigation.Traditional contact-based monitoring technologies suffer from response delays and low accuracy,failing to meet emergency monitoring demands.By integrating image recognition technology,LSPIV,and PTV techniques,this study develops an efficient HAIT algorithm engine that significantly enhances accuracy and efficiency in the velocity measurement of the flow passing through the breach and its distribution.Aiming at the challenges in the monitoring in complex scenarios,we adopt the L-K pyramid optical flow algorithm and the image pyramid construction method to resolve optical flow calculation issues in the case of large-scale motion discontinuities.And,we develop a comprehensive technology framework-comprising the composition of the system and its workflow-for river video-based intelligent flow velocity monitoring,and validate its reliability and effectiveness through testing its practical application,as a new tool for riverine hydrodynamic characteristics downstream of a breached dam.

郭秋歌;杨洋;介玉新

河南黄河河务局信息中心,郑州 450003||河南智慧黄河研究院,郑州 450003清华大学 水圈科学与水利工程全国重点实验室,北京 100084||清华大学 水利部水圈科学重点实验室,北京 100084||清华大学 水利水电工程系,北京 100084清华大学 水圈科学与水利工程全国重点实验室,北京 100084||清华大学 水利部水圈科学重点实验室,北京 100084||清华大学 水利水电工程系,北京 100084

信息技术与安全科学

溃口水动力实时监测视频智能流场识别LSPIVPTV

breach hydraulicreal-time monitoringvideo intelligent flow field identificationLSPIVPTV

《水力发电学报》 2026 (5)

16-29,14

国家重点研发计划项目(2023YFC3011401)

10.11660/slfdxb.20260502

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