|本期目录/Table of Contents|

[1]林峰,李庶林,薛云亮,等.混凝土受压过程中声发射数的灰色模型研究[J].建筑科学与工程学报,2008,25(03):42-46.
 LIN Feng,LI Shu-lin,XUE Yun-liang,et al.Study of Number of Acoustic Emission with Gray Model in Compression Process of Concrete[J].Journal of Architecture and Civil Engineering,2008,25(03):42-46.
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混凝土受压过程中声发射数的灰色模型研究(PDF)
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《建筑科学与工程学报》[ISSN:1673-2049/CN:61-1442/TU]

卷:
25卷
期数:
2008年03期
页码:
42-46
栏目:
出版日期:
2008-09-20

文章信息/Info

Title:
Study of Number of Acoustic Emission with Gray Model in Compression Process of Concrete
作者:
林峰李庶林薛云亮王明
厦门大学建筑与土木工程学院,福建厦门361005
Author(s):
LIN Feng, LI Shu-lin, XUE Yun-liang, WANG Ming
School of Architectural and Civil Engineering, Xiamen University, Xiamen 361005, Fujian, China
关键词:
混凝土 灰色模型 声发射 折减系数 预测精度
Keywords:
concrete gray model acoustic emission reduced coefficient precision of prediction
分类号:
TU37
DOI:
-
文献标志码:
A
摘要:
针对在混凝土单轴受压破坏全过程的声发射试验中,采用传统GM(1,1)灰色模型多步预测分析所得预测值普遍较实测值偏大、预测精度偏低的问题,通过引进预测值折减系数,重点探讨了折减系数的特点。结果表明,折减系数在预测曲线起点处基本为一常数,在终点处基本与已知数据百分数呈线性关系。基于上述特点通过插值求其折减系数来合理修正传统的灰色模型,建立起折减修正GM(1,1)灰色模型。通过该修正GM(1,1)灰色模型对室内声发射试验建立的预测模型,其精度较传统GM(1,1)灰色模型有较大提高。
Abstract:
The whole compression failure process of acoustic emission test in single axial of concrete was established using GM(1,1)gray model multi-step prediction. The prediction values were larger than the real values and the precision of prediction was not enough. The characteristics of the reduced coefficients were emphatically discussed by introducing the prediction value reduced coefficients. Results show that the reduced coefficients are almost constant at the beginning of prediction curves and linear relation between the reduced coefficients and known data percent is assumed in the end point. Based on above characteristics, the interpolation method is used to solve the reduced coefficients in order to correctly modify traditional gray model, and the reduced modified GM(1,1)gray model can be built. Through modifying GM(1,1)gray model, a prediction model is set up in indoor acoustic emission test, and the precision of prediction by the correct model of GM(1,1)gray model is more advanced than the precision of prediction by the traditional GM(1,1)gray model.

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期:2008-06-02
基金项目:国家高技术研究发展计划(“八六三”计划)项目(2006AA06Z117); 国家自然科学基金项目(10572122); 厦门大学人才引进基金项目(xk1005)
作者简介:林 峰(1984-),男,福建福清人,工学硕士研究生,E-mail:linfeng840202@163.com。
更新日期/Last Update: 2008-09-20