期刊文献+

高拱坝施工期垂直向温度分布智能动态预测

Intelligent Dynamic Prediction about the Vertical Temperature Distribution of High Arch Dam during Construction Period
下载PDF
导出
摘要 针对当前特高拱坝施工期混凝土温控采取分区分时段通水冷却难以实时掌握并准确预测垂直向温度分布的问题,利用分布式光纤实时在线监测采集数据量大的优势,发掘其线空间内的数据关系,基于广义回归神经网络建立隐式垂直向温度分布模型,并对某处于建设期的高拱坝垂直向温度分布进行动态预测分析。结果表明,建立的垂直向温度预测模型的预测温度与实测温度之间存在良好的相关性,能很好地反映各温控因素与监测数据的非线性关系,能够准确、合理地预测垂直向温度。 The concrete temperature control in construction period of high arch dam always adopts water cooling in different time and space, but it is difficult to grasp and predict the vertical temperature distribution. By using abundant online monitoring data obtained from distributed optical fiber, the relationship of data in line space is explored based on generalized regression neural network to set up an implicit expression model about the vertical temperature distribution. The model is used to predict the vertical temperature distribution of a high arch dam in construction period. The results show that the predicted temperature of model has a good relation with actual online monitor temperature and it can reflect the non-linear relationship between temperature control factors and monitoring data. The model can accurately and reasonably predict vertical temperature distribution.
出处 《水力发电》 北大核心 2015年第12期54-57,共4页 Water Power
基金 国家自然科学基金(51079079 51209124)
关键词 高拱坝 施工期 广义回归神经网络 垂直向温度分布 智能动态预测 high arch dam construction period generalized regression neural network vertical temperature distribution intelligent dynamic prediction
  • 相关文献

参考文献6

二级参考文献13

  • 1陈德祥,许勇.普定水电站碾压混凝土拱坝裂缝成因探讨[J].贵州水力发电,2000,14(1):34-36. 被引量:9
  • 2[3]Kennecly M,Pchua L O. Neural networks for nonlinear programming[J]. IEE E,Trans,Circuits,1988,35:554-562.
  • 3[4]Aribshahi P. Fuzzy control of backpropagation[A]. IEEE Fuzzy’96,1996.96 7-972.
  • 4[5]Derrick H,Widrow B. Neural networks for self-learning control system[J ]. IEEE Control Systems Mangzine,1990,4(1):18-23.
  • 5[6]Khalid M,Omatu S. A neural network based control scheme with an adaptive neural model reference structure[A]. IJCNN,Singapore,1991.2128-2133.
  • 6[7]Wilis N J. Artificial neural networks in process estimation and control[ J]. Automatica,1992,28:1181-1187.
  • 7[8]Luo Li,Luo Qiang,Hu Shouren. A high-speed learning algorithm for BP ne ural networks[A]. International Conference on Neural Networks and Signal Proce ssing(Vol.1)[C]. ICNNSP’95, Nanjing,1995.202-205.
  • 8[9]Aoki K,Kanezashi M. Learning algorithm for neural networks by solv ing nonlinear equations[A]. Japan:Proc of ANNPS’93,1993,461-466.
  • 9张国新.大体积混凝土结构施工期温度场、温度应力分析程序包SAPTIS编制说明及用户手册[Z].,1994~2004..
  • 10朱伯芳,吴龙珅,杨萍,张国新.利用塑料水管易于加密以强化混凝土冷却[J].水利水电技术,2008,39(5):36-39. 被引量:13

共引文献161

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部