摘要
针对传统“黑箱”模型可以预测却无法解释拱坝变形的缺陷,利用Shapley Additive Explanation(SHAP)理论对特高拱坝的机器学习变形预测模型进行解构分析,分析水压、温度、时效对特高拱坝不同部位径向水平位移的影响规律。构建特高拱坝变形监测数据的轻量梯度提升算法(Light Gradient Boosting Machine,LightGBM)黑箱预测模型,利用SHAP对存在多重共线性的因子进行剔除,再从整个因子集和单个样本两个角度分析不同影响因子对模型变形预测的贡献度;通过分析拉西瓦特高拱坝坝肩、坝基、拱冠等不同部位的径向水平位移与影响因子间的关系,发现时效因子对高程越高、越靠近拱冠位置的径向水平位移影响越大,温度因子主要影响靠近拱冠位置的径向水平位移,水压因子主要影响高程较高位置的径向水平位移,而坝基和深入坝肩岩体测点的径向水平位移几乎不受水位、温度的影响。解决了以往“黑箱”变形预测模型可视性差、内部机理不明的问题,根据可解释模型得到的相关规律可为特高拱坝的工作性态分析和运行管理提供借鉴。
Aimed at the limitation of the traditional intelligent black box model that cannot explain the deformation mechanism of arch dams,we apply the Shapley Additive Explanation(SHAP)theory and deconstruct a machine learning deformation prediction model for a super high arch dam,focusing on analysis of the influence of water pressure,temperature and aging on the radial horizontal displacement of its different parts.From the deformation monitoring data of the dam,we construct a Light Gradient Boosting Machine(LightGBM)black box prediction model that uses SHAP to eliminate the factors with multicollinearity,and analyze the contribution of different influencing factors to model deformation prediction for the whole factor set and a single sample.In a case study of the dam abutment of a super high arch,we examine the relationship of the influencing factors versus its radial horizontal displacements at dam foundation,arch crown,and other dam parts.We find the aging factor has a greater influence on the displacements at the higher elevations close to the arch crown.The temperature factor mainly affects the displacements near the arch crown,and the water pressure factor mainly affects those at higher elevations;while neither of both factors has a considerable effect on the displacements at the measuring points in the dam foundation and the rock mass deep into the abutment.Our method overcomes the shortcoming of poor visibility and unclear internal mechanism of the previous intelligent'black box'deformation prediction model.Thus,this interpretable model yields the relevant laws that help working performance analysis and operation management of super high arch dams.
作者
马春辉
余飞
程琳
杨杰
MA Chunhui;YU Fei;CHENG Lin;YANG Jie(State Key Laboratory of Eco-hydraulics in Northwest Arid Region of China,Xi’an University of Technology,Xi’an 710048,China;Institute of Water Resources and Hydro-electric Engineering,Xi’an University of Technology,Xi’an 710048,China)
出处
《水力发电学报》
CSCD
北大核心
2024年第10期107-120,共14页
Journal of Hydroelectric Engineering
基金
国家自然科学基金(52279140)
陕西省自然科学基础研究计划一般项目(2023-JC-QN-0562)。
