基于时空聚类和深度学习的混凝土坝变形异常值识别方法  

A method for identifying deformation outliers in concrete dams based on spatio-temporal clustering and deep learning

作　　者：宋锦焘 葛佳豪 杨杰[1,2] 徐笑颜 陈家敏 孟庆耀 SONG Jintao;GE Jiahao;YANG Jie;XU Xiaoyan;CHEN Jiamin;MENG Qingyao(Institute of Water Resources and Hydro-electric Engineering,Xi’an University of Technology,Xi’an 710048,China;State Key Laboratory of Eco-hydraulics in Northwest Arid Region,Xi’an University of Technology,Xi’an 710048,China)

机构地区：[1]西安理工大学水利水电学院,陕西西安710048 [2]西安理工大学省部共建西北旱区生态水利国家重点实验室,陕西西安710048

出　　处：《水利水电科技进展》2024年第4期65-71,共7页Advances in Science and Technology of Water Resources

基　　金：国家自然科学基金青年科学基金项目(52109166);国家自然科学基金面上项目(52279140)。

摘　　要：针对传统大坝异常值识别方法多依靠单测点模型,未充分考虑测点间变形的时空关联特性,易造成异常值误诊断的问题,提出了基于时空聚类和深度学习的混凝土坝变形异常值识别方法。该方法利用测点间变形的时空关联特性对混凝土坝测点变形数据进行时空聚类分区,基于新型蜜獾优化算法(HBA)与双向长短时记忆(BiLSTM)神经网络构建HBA-BiLSTM变形预测模型,根据模型输出的变形值以及异常值判别指标识别混凝土坝变形异常值。实例验证结果表明,该方法比传统异常值识别方法准确率更高。In order to solve the problem that traditional dam outlier identification methods mostly rely on single measuring point models and fail to fully consider the spatio-temporal correlation characteristics of deformation between measuring points,which easily leads to misdiagnosis of outliers,a method for identifying concrete dam deformation outliers based on spatio-temporal clustering and deep learning is proposed.This method utilizes the spatio-temporal correlations of deformations between measurement points to perform spatio-temporal clustering and partitioning of the deformation data from the measurement points of concrete dams.Based on the new honey badger algorithm(HBA)and the bidirectional long short-term memory(BiLSTM)neural networks,the HBA-BiLSTM deformation prediction model is established.Deformation outliers in concrete dams are identified based on the deformation values output by the established model and outlier discrimination indices.The results of case validation show that this method has higher accuracy than traditional outlier identification methods.

关 键 词：混凝土坝 变形 异常值识别 监控模型 时空聚类 

分 类 号：TV698.11[水利工程—水利水电工程]