|本期目录/Table of Contents|

[1]张竞男,孙福洋,王浩.基于BP神经网络的超声-回弹-钻芯综合测强法[J].建筑科学与工程学报,2009,26(01):68-74.
 Ultrasonic-rebound and Core-drilling Synthetic Method in Strength Testing Based on BP Neural Network.Ultrasonic-rebound and Core-drilling Synthetic Method in Strength Testing Based on BP Neural Network[J].Journal of Architecture and Civil Engineering,2009,26(01):68-74.
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基于BP神经网络的超声-回弹-钻芯综合测强法(PDF)
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《建筑科学与工程学报》[ISSN:1673-2049/CN:61-1442/TU]

卷:
26卷
期数:
2009年01期
页码:
68-74
栏目:
出版日期:
2009-03-20

文章信息/Info

Title:
Ultrasonic-rebound and Core-drilling Synthetic Method in Strength Testing Based on BP Neural Network
作者:
张竞男1,孙福洋2,王浩3
1.南京栖霞建设股份有限公司,江苏南京210037;2.中国中铁六局集团有限公司,北京100036;3.东南大学混凝土及预应力混凝土结构教育部重点实验室,江苏南京210096
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
关键词:
超声 回弹 钻芯 大体积混凝土 综合测强法 BP神经网络
Keywords:
ultrasonic rebound core-drilling large-scale concrete synthetic method in strength testing BP neural network
分类号:
TU528
DOI:
-
文献标志码:
-
摘要:
对超声-回弹综合法和钻芯法检测结构混凝土强度的原理、优点及其局限性进行了对比分析,阐述了将超声-回弹综合法和钻芯取样技术进行联合测强对于大体积混凝土强度检测的重要意义。在此基础上将BP神经网络技术引入到超声-回弹-钻芯综合法中,用以确定最优钻芯数量,并将所得结果与传统基于数理统计理论的分析结果进行了比较。结果表明:超声-回弹-钻芯综合法费用合理、损伤较小,与BP神经网络技术结合后进一步提高了其分析精度,可在各类大体积混凝土工程结构的强度检测中推广应用。
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.

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期:2008-09-08
作者简介:张竞男(1979-),女,浙江衢州人,工程师,工学硕士,E-mail:zjn215@163.com。
更新日期/Last Update: 2009-03-20