|本期目录/Table of Contents|

[1]尤杰,车轶,仲伟秋.基于BP神经网络的既有建筑混凝土强度预测[J].建筑科学与工程学报,2011,28(01):70-75.
　YOU Jie,CHE Yi,ZHONG Wei-qiu.Predition of Concrete Strength of Existing Buildings Based on BP Neural Networks[J].Journal of Architecture and Civil Engineering,2011,28(01):70-75.
点击复制

基于BP神经网络的既有建筑混凝土强度预测(PDF)
分享到：

《建筑科学与工程学报》[ISSN:1673-2049/CN:61-1442/TU]

卷:
28卷
期数:
2011年01期
页码:
70-75
栏目:
出版日期:
2011-03-20

文章信息/Info

Title:
Predition of Concrete Strength of Existing Buildings Based on BP Neural Networks
作者:
尤杰,车轶,仲伟秋
大连理工大学 土木工程学院,辽宁 大连 116024
Author(s):
YOU Jie, CHE Yi, ZHONG Wei-qiu
YOU Jie, CHE Yi, ZHONG Wei-qiu
关键词:
BP神经网络;  既有建筑;  混凝土强度;  动量法;  自适应调整法
Keywords:
BP neural network;  existing building;  concrete strength;  momentum method;  adaptive adjustment method
分类号:
TU375
DOI:
-
文献标志码:
A
摘要:
在分析检测数据的基础上,提取了结构服役时间、结构建造时间、结构检测时间、混凝土设计强度和混凝土碳化深度等特征参数,建立了预测既有建筑混凝土强度退化的人工神经网络模型。采用动量法和自适应调整法改进了BP算法; 采用训练好的BP神经网络对既有混凝土强度最小值和混凝土强度最大值进行了预测,并与实测值进行了对比。结果表明:利用BP神经网络对既有建筑混凝土强度退化进行预测是可行的,该研究成果可为既有建筑大面积的抗震性能普查提供参考。
Abstract:
Based on the test data analysis method, characteristic parameters of the existing buildings, i.e. service time, construction time, in-situ inspection time of structure, design value of concrete strength, and carbonation depth of concrete were extracted, and the artificial neural network model was developed to predict the degradation of concrete strength of the existing buildings. The back propagation(BP)algorithm was improved by using the momentum method and adaptive adjustment method. Both minimum and maximum values of concrete strength were predicted using the trained BP neural network and were compared with the measured values. Results show that using BP neural network to predict the degradation of concrete strength of existing buildings is feasible. Results of this study can provide references for the existing building seismic performances of large area surveys.

参考文献/References:

[1] 刘青峰.神经网络智能诊断系统在混凝土结构中的应用研究[D].湘潭:湘潭大学,2006. LIU Qing-feng.Applicative Research of the Neural Network Intelligent Diagnosis System in Concrete Structure[D].Xiangtan:Xiangtan University,2006.
[2]姜绍飞,钟善桐.神经网络在结构工程中的应用[J].哈尔滨建筑大学学报,1998,31(6):129-134. JIANG Shao-fei,ZHONG Shan-tong.The Application of Neural Networks in Structural Engineering[J].Journal of Harbin University of Civil Engineering and Architecture,1998,31(6):129-134.
[3]REN L Q,ZHAO Z Y.An Optimal Neural Network and Concrete Strength Modeling[J].Advances in Engineering Software,2002,33(3):117-130.
[4]DIAS W P S,POOLIYADDA S P.Neural Networks for Predicting Properties of Concretes with Admixtures[J].Construction and Building Materials,2001,15(7):371-379.
[5]赵复笑,杨殿海,陈 宏.基于神经网络的沥青混凝土路面使用性能预测[J].沈阳建筑工程学院学报:自然科学版,2004,20(2):121-123,146. ZHAO Fu-xiao,YANG Dian-hai,CHEN Hong.Asphalt Concrete Pavement Performance Forecast Based on Neural Network[J].Journal of Shenyang Architectural and Civil Engineering University:Natural Science,2004,20(2):121-123,146.
[6]SEBASTIA M,OLMO I F,IRABIEN A.Neural Network Prediction of Unconfined Compressive Strength of Coal Fly Ash-cement Mixtures[J].Cement and Concrete Research,2003,33(8):1137-1146.
[7]丁声荣,余巍伟.混凝土的强度预测及其配合比优化设计研究[J].山西建筑,2008,34(34):1-2. DING Sheng-rong,YU Wei-wei.Forecast of Concrete Strength and Its Optimal Mixture Rate Design Research[J].Shanxi Architecture,2008,34(34):1-2.
[8]余雪娟.基于神经网络的混凝土强度预测[J].工程质量,2008(7):40-42,46. YU Xue-juan.Prediction Model of Concrete Strength by Artificial Neural Network[J].Quality of Civil Engineering and Construction,2008(7):40-42,46.
[9]韩 越,张新东.再生混凝土强度预测的神经网络模型[J].混凝土,2008(4):22-23,26. HAN Yue,ZHANG Xin-dong.Neural Network Model of the Recycled Concrete Strength[J].Concrete,2008(4):22-23,26.
[10]陈 强,王新刚.人工神经网络在混凝土强度预测中的应用[J].工业建筑,2007,37(增1):1013-1016. CHEN Qiang,WANG Xin-gang.The Application of ANN in Forecast to Concrete Strength[J].Industrial Construction,2007,37(S1):1013-1016.
[11]崔 猛,王新刚.混凝土强度预测的人工智能方法[J].山西建筑,2008,34(27):99-101. CUI Meng,WANG Xin-gang.Artificial Intelligent Method for Strength Prediction of Concrete[J].Shanxi Architecture,2008,34(27):99-101.
[12]周开利,康耀红.神经网络模型及其MATLAB仿真程序设计[M].北京:清华大学出版社,2005:88-89. ZHOU Kai-li,KANG Yao-hong.Neural Network Model and MATLAB Simulated Program Design[M].Beijing:Tsinghua University Press,2005:88-89.
[13]张艳梅,王 锋,仲伟秋.基于神经网络的混凝土构件质量识别[J].鞍山钢铁学院学报,2002,25(1):29-32. ZHANG Yan-mei,WANG Feng,ZHONG Wei-qiu.Quality Examination for Concrete Members Based on Neural Network Technique[J].Journal of Anshan Institute of Iron and Steel Technology,2002,25(1):29-32.
[14]高大启.有教师的线性基本函数前向三层神经网络结构研究[J].计算机学报,1998,21(1):80-86. GAO Da-qi.On Structures of Supervised Linear Basis Function Feed Forward Three-layered Neural Networks[J].Chinese Computers,1998,21(1):80-86.
[15]MIRCHANDANI G,CAO W.On Hidden Nodes for Neural Nets[J].IEEE Transactions on Circuits and Systems,1992,36(5):661-664.
[16]叶爱文,谢慧才.混凝土中钢筋直径雷达检测的神经网络方法[J].建筑科学与工程学报,2008,25(4):105-110. YE Ai-wen,XIE Hui-cai.Neural Network Method of Diameter Detection of Rebar in Concrete by Using GPR[J].Journal of Architecture and Civil Engineering,2008,25(4):105-110.
[17]刘义艳,段晨东,巨永锋,等.基于神经网络与特征融合的损伤诊断方法[J].长安大学学报:自然科学版,2008,28(6):106-110. LIU Yi-yan,DUAN Chen-dong,JU Yong-feng,et al.Diagnosis Method of Structure Damage Using Neural Network and Feature Fusion[J].Journal of Chang'an University:Natural Science Edition,2008,28(6):106-110.
[18]杨文娟.神经网络和主元分析-神经网络软测量技术在污水处理系统中的应用[J].地球科学与环境学报,2008,30(1):101-106. YANG Wen-juan.Soft Sensors with ANN and PCA-ANN for Wastewater Treatment System[J].Journal of Earth Sciences and Environment,2008,30(1):101-106.
[19]董贤哲,张军平.补偿模糊神经网络在砂土液化势评价中的应用[J].地球科学与环境学报,2008,30(1):64-68. DONG Xian-zhe,ZHANG Jun-ping.Application of Compensative Fuzzy Neural Network in Assessment of Sand Liquefaction Potential[J].Journal of Earth Sciences and Environment,2008,30(1):64-68.
[20]潘文超.以广义回归神经网络预测共同基金报酬[J].长安大学学报:社会科学版,2007,9(4):55-58. PAN Wen-chao.Forecast for Mutual Fund Returns with Gerenal Regression Neural Network[J].Journal of Chang'an University:Social Science Edition,2007,9(4):55-58.
[21]郭 琦,贺拴海,白 云.基于神经网络的简支梁桥预应力衰减评估模型[J].长安大学学报:自然科学版,2007,27(6):53-57. GUO Qi,HE Shuan-hai,BAI Yun.Evaluation Model on Prestress Attenuation of Simple Span Bridges Based on Neural Networks[J].Journal of Chang'an University:Natural Science Edition,2007,27(6):53-57.
[22]牛荻涛,王庆霖.一般大气环境下混凝土强度经时变化模型[J].工业建筑,1995,25(6):36-38. NIU Di-tao,WANG Qing-lin.Models of Concrete Strength Changing with Time in General Air Environment[J].Industrial Construction,1995,25(6):36-38.

相似文献/References:

备注/Memo

备注/Memo:
收稿日期:2010-12-10
基金项目:国家重点基础研究发展计划(“九七三”计划)项目(2007CB714202)
作者简介:尤 杰(1984-),男,内蒙古呼和浩特人,工学硕士研究生,E-mail:youjie2003@hit.edu.cn。
更新日期/Last Update: 2011-03-20