基于神经网络的水电站厂房结构振动响应预测  

Vibration Response Prediction of Powerhouse Structure Based on Artificial Neural Network

作　　者：苗宗伟 马震岳[1] 王溢波[1] 职保平[1] 

机构地区：[1]大连理工大学建设工程学部水利工程学院,辽宁大连116024

出　　处：《水电能源科学》2010年第8期88-90,共3页Water Resources and Power

基　　金：辽宁省教育厅重点实验室科研基金资助项目(2008S045)

摘　　要：针对水电站厂房结构振动主要由水力、机械和电磁三大类振源引起,结合景洪水电站机组与厂房振动联合测试数据,在分析厂房结构与机组振动响应关系的基础上,应用径向基神经网络建立了厂房结构振动预测模型。实例结果表明,该方法简单、有效、预测精度较高,可供同类工程参考。The structural vibration of power house may be induced by hydraulics,mechanical and electromagnetic factors of generating unit.According to the joint vibration test data of generating unit and powerhouse structures in Jinghong Hydropower Station,the RBF neural network method is applied to establish prediction model of power house structural vibration on the basis of response relationship between power house structure and generating unit.The instance results show that the proposed method is effective and simple and it has high precision,which provides reference for similar engineering project.

关 键 词：神经网络建立 水电站机组 厂房结构振动 振动响应预测 Artificial NEURAL Network Based Structure 预测模型 预测精度 响应关系 机组振动 厂房振动 测试数据 振动主 径向基 振源 水力 结果 基础 机械 

分 类 号：TK79[动力工程及工程热物理—流体机械及工程] TV7[水利工程—水利水电工程]