|Table of Contents|

Ultrasonic-rebound and Core-drilling Synthetic Method in Strength Testing Based on BP Neural Network(PDF)

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

Issue:
2009年01期
Page:
68-74
Research Field:
Publishing date:
2009-03-20

Info

Title:
Ultrasonic-rebound and Core-drilling Synthetic Method in Strength Testing Based on BP Neural Network
Author(s):
Ultrasonic-rebound and Core-drilling Synthetic Method in Strength Testing Based on BP Neural Network
1. Nanjing Chixia Development Co., Ltd., Nanjing 210037,Jiangsu, China; 2. China Railway Sixth Group Co., Ltd., Beijing 100036, China; 3. Key Laboratory of Concrete and Prestressed Concrete Structure of Ministry of Education, Southeast University, Nanjing 210096, Jiangsu, China
Keywords:
ultrasonic;  rebound;  core-drilling;  large-scale concrete;  synthetic method in strength testing;  BP neural network
PACS:
TU528
DOI:
-
Abstract:
Comparison analyses were conducted on the principles, excellences and limitations of ultrasonic-rebound synthetic method and core-drilling technique for strength testing of large-scale concrete structures, and the significance of ultrasonic-rebound and core-drilling synthetic method(URCDSM)on large-scale concrete strength testing was pointed out. The BP neural network technology was then introduced and was used to determine the optimal core-drilling number in the URCDSM. The results from calculation were compared with results from statistic methods. Results show that the proposed URCDSM has low expenses and little damage, and the BP neural network technology can further increase the analysis accuracy, so the method can be popularized in large-scale concrete structures.

References:

[1] 吴慧敏.结构混凝土现场检测新技术[M].长沙:湖南大学出版,1998.WU Hui-min.New Techniques for Testing Concrete of Structures[M].Changsha:Hunan University Press,1998.
[2]CECS 02:2005,超声回弹综合法检测混凝土强度技术规程[S].CECS 02:2005,Technical Specification for Testing Concrete Strength with Ultrasonic-rebound Synthetic Method[S].
[3]CECS 03:88,钻芯法检测混凝土强度技术规程[S].CECS 03:88,Technical Specification for Testing Concrete Strength with Drilled Core Method[S].
[4]邸小坛,徐 骋,陶 里,等.钻芯检测结构混凝土强度技术的改善与提高[J].施工技术,2001,30(2):32-34.DI Xiao-tan,XU Cheng,TAO Li,et al.Improvement and Increase of Core-drilling Structural Concrete Strength Detection Technique[J].Construction Technique,2001,30(2):32-34.
[5]张竞男,王 浩,乔建东.超声-回弹-钻芯综合法测强初探[J].材料科学与工程学报,2003,21(6):886-889.ZHANG Jing-nan,WANG Hao,QIAO Jian-dong.Preliminary Investigation on Strength Testing Method with Combined Ultrasonic-rebound and Core-drilling Technique[J].Journal of Materials Science & Engin-eering,2003,21(6):886-889.
[6]HOLLAND J H.Adaptation in Natural and Artificial System[M].Ann Arbor:University of Michigan Press,1975.
[7]楼顺天.基于MATLAB的系统分析与设计--神经网络[M].西安:西安电子科技大学出版社,1998.LOU Shun-tian.System Analysis and Design Based on MATLAB-Neural Networks[M].Xi’an:Xidian University Press,1998.
[8]柳成荫,陈政清,黄方林,等.基于神经网络的加速度时程积分方法[J].中南大学学报:自然科学版,2004,35(1):162-166.LIU Cheng-yin,CHEN Zheng-qing,HUANG Fang-lin,et al.Time History Integral Method of Acceler-ation Based on Artificial Neural Networks[J].Journal of Central South University:Natural Science,2004,35(1):162-166.
[9]李 萍,曾令可,税安泽.基于MATLAB的BP神经网络预测系统的设计[J].计算机应用与软件,2008,25(4):149-184.LI Ping,ZENG Ling-ke,SHUI An-ze.Design of Forecast System of Back Propagation Neural Network Based on MATLAB[J].Computer Applications and Software,2008,25(4):149-184.

Memo

Memo:
-
Last Update: 2009-03-20