消力池底板上举力的神经网络模型预测  

Neural network model based prediction on uplift force acting on bottom slab of stilling basin

作　　者：辜晋德[1] 练继建[1] 

机构地区：[1]天津大学建筑工程学院,天津300072

出　　处：《水利水电技术》2011年第1期54-57,共4页Water Resources and Hydropower Engineering

基　　金：国家杰出青年科学基金(50725929);国家科技支撑项目(2008BAB29B04);水利部公益性行业科技专项(200901081)

摘　　要：利用BP人工神经网络的非线性映射功能,结合水槽中两种主要消能形式的模型试验,以流场中作用在板块上表面实测脉动压力为变量,构建了一个简单的上举力预测系统。经过实测资料验证,该系统预测效果较好。本文的研究成果对消力池安全实时监测具有一定的意义。Based on the nonlinear mapping function of the BP artificial neural network and combined with the model test with two forms of energy dissipation in sink, a simple system of the uplift force prediction is made up by taking the measured fluctuating pressures acting on the surface of the bottom slab in the flow field as the variables concerned. It is demonstrated by the relevant measured data that better predicting effect can be obtained by the system, and then the study result has certain significance to the real-time safetv monitoring on stilling basin.

关 键 词：消力池 底板 神经网络 上举力 预测 

分 类 号：TV653.1[水利工程—水利水电工程]