基于深度学习模型的混凝土坝变形预测研究

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关键词：混凝土坝；变形监测；变形预测；LSTM；TCN中图分类号：TV642 文献标志码：A doi：10.3969/j.issn.1000-1379.2025.07.023引用格式：，，，等.基于深度学习模型的混凝土坝变形预测研究[J].人民黄河，2025，47（7）：144-149，155.

Research on Deformation Prediction of Concrete Dams Based on Deep Learning Models

SU Xiaojun¹，XU Zengguang¹， ZHANG Ye¹，KANG Xinyu'， ZHOU Tao²，YANG Tao³，LI Kangping4 （1.State KeyLaboratoryof WaterEngineering EcologyandEnvironment inAridArea，Xi’an Universityof Technology，Xi'an 710048，China；2.Huanghe Hydropower Development Co.，Ltd.， Xining 81000，China； 3.China Yangtze Power Co.，Ltd.，Yibin 644612，China；4.Power China Northwest Engineering Co.，Ltd.，Xi'an 710065，China） Abstract： Inordertoimprovetheacuracyofpredictingconcretedamdeformationsandensuredamstructuralsafety，thispaperproposeda predictionmodelcombiningTemporalConvolutionalNetworks（TCN）andLongShort-TermMemory（LSTM）networks，imingthelimitationsofexistingpredictionmodelsincaptuingcomplexdeformationfeaturesandlong-tedependencies.TCNwasusedtoextractteporal featuresfromdeformationdta，hileLSTMcapturedlongtedependenciesiscombinationsignificantlyehancedteodel’sabilityo predictomplexdeformationpatesExperimentalesultsemonstratetat，compaedwithvariousinteligentpedictionodels，eo posedmodelaccuratelysiulatestdadfaprocsndcheshigerpredictiouacyFurteore，eodelosates asignificantadvantageincapturigomplexdefoationcharacteisticsofconcretedams，providingaovelteciquefordamsafetoi ring.

Key words：concrete dam；deformation monitoring；deformation prediction；LSTM；TCN

0 引言

水库大坝作为重要的基础设施，直接关系到库区人民的生命财产安全，一旦发生事故，后果将极为严重[1-3]。（剩余10114字）