|Table of Contents|

Neural Network Method of Diameter Detection of Rebar in Concrete by Using GPR(PDF)

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

Issue:
2008年04期
Page:
105-110
Research Field:
Publishing date:
2008-12-20

Info

Title:
Neural Network Method of Diameter Detection of Rebar in Concrete by Using GPR
Author(s):
YE Ai-wen12 XIE Hui-cai12
1. School of Civil Engineering, Shenzhen University, Shenzhen 518060, Guangdong, China; 2. Shenzhen Municipal Key Lab on Durability of Civil Engineering, Shenzhen University, Shenzhen 518060, Guangdong, China)
Keywords:
GPR diameter detection of rebar neural network wavelet packet analysis
PACS:
TU311.41
DOI:
-
Abstract:
The basic theory of neural network was introduced,and a new method using neural network to estimate the diameter of rebar in concrete by processing ground penetrating radar(GPR)signal was presented. The models of back propagating(BP)and Elman neural network were employed, and feature parameters were extracted using wavelet packet. Authors detailed alternative synthetic data generation by fitting polynomial, which could reduce the volume of data collection. The results show that the method to estimate diameter of rebar is satisfactory.

References:

[1] MOLYNEAUX T C K,MILLARD S G,BUNGEY J H,et al.Radar Assessment of Structural Concrete Using Neural Networks[J].NDT & E International,1995,28(5):281-288.
[2]NEWNHAM L,GOODIER A.Using Neural Networks to Interpret Sub-surface Radar Imagery of Reinforced Concrete[C]//NOON D A,STICKLEY G F,LONGSTAFF D I D.Proceedings of the Eighth International Conference on Ground Penetrating Radar.Bellingham:SPIE,2000:434-440.
[3]SHAW M R,MILLARD S G,MOLYNEAUX T C K,et al.Bungey Location of Steel Reinforcement in Concrete Using Ground Penetrating Radar and Neural Networks[J].NDT & E International,2005,38(3):203-212.
[4]谢慧才,徐茂辉.钢筋混凝土雷达信号的BP人工神经网络识别[J].华中科技大学学报:城市科学版,2007,24(1):1-4. XIE Hui-cai,XU Mao-hui.Radar Signal Interpretation of Structural Concrete by BP Neural Network[J].Journal of Huazhong University of Science and Technology:Urban Science Edition,2007,24(1):1-4.
[5]UTSI V,UTSI E.Measurement of Reinforcement Bar Depths and Diameters in Concrete[C]//SLOB E C,YAROVOY A G,RHEBERGEN J B.Proceedings of Tenth Inter-national Conference on Ground Penetrating Radar.Delft:SPIE,2004:659-662.
[6]王 唯,郑正奇,王晓华,等.小波包特征提取法在探地雷达回波信号分析中的应用[J].物探与化探,2005,29(2):149-152. WANG Wei,ZHENG Zheng-qi,WANG Xiao-hua,et al.The Application of Wavelet Packet Transform to the Analysis of Radar Signals[J].Geophysical & Geochemical Exploration,2005,29(2):149-152.
[7]韩力群.人工神经网络教程[M].北京:邮电大学出版社,2006. HAN Li-qun.Artificial Neural Networks Guide[M].Beijing:Beijing University of Posts and Telecommunications Press,2006.
[8]陈善广,鲍 勇.BP神经网络学习算法研究[J].应用基础与工程科学学报,1995,3(4):105-110. CHEN Shan-guang,BAO Yong.Studies on Learning Algorithms for BP Net[J]. Journal of Basic Science and Engineering,1995,3(4):105-110.
[9]刘怀智,姚运仕,赵 悟,等.基于BP网络的道路水泥再生混凝土性能的评价[J].筑路机械与施工机械化,2007,24(9):23-24. LIU Huai-zhi,YAO Yun-shi,ZHAO Wu,et al.Evalu-ation of Road Recycled Concrete Performance Based on BP Neural Network[J].Road Machinery & Construction Mechanization,2007,24(9):23-24.
[10]任更锋,徐 岳,王春生.大跨径PC连续刚构桥神经网络控制系统[J].长安大学学报:自然科学版,2007,27(2):38-41. REN Geng-feng,XU Yue,WANG Chun-sheng.Construction Control System of Long-span Prestressed Concrete Continuous Rigid-frame Bridge Based on Artificial Neural Network[J].Journal of Chang'an University:Natural Science Edition,2007,27(2):38-41.
[11]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.
[12]王桂萱,中村秀明,晏班夫,等.基于模糊神经网络的桥梁诊断辅助系统研究[J].中国公路学报,2005,18(2):45-50. WANG Gui-xuan,NAKAMURA H,YAN Ban-fu,et al.Research on Bridge Diagnosis System with Fuzzy-neural Network[J].China Journal of Highway and Transport,2005,18(2):45-50.
[13]丁幼亮,李爱群,缪长青,等.基于小波包能量谱的大跨桥梁结构损伤预警指标[J].中国公路学报,2006,19(5):34-40. DING You-liang,LI Ai-qun,MIAO Chang-qing,et al.Structural Damage Alarming Indices for Long-span Bridges Based on Wavelet Packet Energy Spectrum[J].China Journal of Highway and Transport,2006,19(5):34-40.
[14]王晓伟.基于RBF网络的混凝土抗压强度的预测[J].筑路机械与施工机械化,2006,23(10):23-24. WANG Xiao-wei.Predication of Concrete Compression Strength Based on RBF Neural Network[J].Road Machinery & Construction Mechanization,2006,23(10):23-24.

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Last Update: 2008-12-20