基于贝叶斯分层模型的数字孪生明渠流量计量方法研究

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关键词：智能精准计量；贝叶斯分层模型；时间序列预测；数字孪生；黄河流域

中图分类号：TV67;P332.4;TV882.1 文献标志码：A

doi：10.3969/j.issn.1000-1379.2026.01.021

Research on Flow Measurement Method of Digital Twin Open Channel Based on Bayesian Hierarchical Model

YANG Hang， GUO Qiuge， YANG Ruixin，WANG Junliang

（1.YellowRiverEngineeringConsultingCo.d.Zhengzhou45O3，China；2.KeyLaboratoryofWaterManagementand WaterScurity forYellow River Basin（Under Construction），Ministryof Water Resources，Zhengzhou450o03，China；3.Information Center，

HenanYellow River BureauZhengzhou 450o03，China;4.Henan Yelow River Wisdom Research Institute，Zhengzhou4503，China; 5.Zhongyuan University of Technology，Zhengzhou 45ooo7，China）

Abstract：Inesposetoecomplexcharacteristicsofrverswithaundantsdimentinthenorth，suchasteYellRivertraditioalfow measurementtecholoiesfacecallngssuchasmeasurement inaccraciesandusceptibilityofmeasurementcapabiltistviotal factors.Toaddresstsehallege，tspaperproosedaovelitellitandprecisemeasurementethodfooncelflowbasedon theconceptofdigitaltwinandtheBayesianherarcicalodel.Thismetodintegratedieseriespredictionndinteligentmanagement technology.Fieldtestsconductedinth“YelowRiverWaterDiversiontoHebeiProvinceforReplenishingBaiyangdianLake”projectinthe UpperYellowRiverdemonstratedsignificantadvantagesof hisetod.Comparedithexistingtecologies，tisethodnotolysolvesthe problemofinaccurateflowmeasurementunderconditiosofunstableflowvelocityandscouringanddepositionchangesbutalsoacievepre cise prediction of flow data over small time scales in the future.

Keywords：intellgentandprecisemeasurement；Baysianhierarchicalmodel；timeseresprediction；digitaltwin；elowRiverasir

0 引言

数字孪生作为一种在信息世界刻画物理世界、仿真物理世界、优化物理世界、可视化物理世界的重要技术，为实现数字化、智能化（如智慧城市、智能制造）、服务化、绿色可持续等全球工业和社会发展提供了有效途径[1-3]。（剩余5961字）