[1]范旭红,章立栋,杨 帆,等.基于BA-Elman算法的预应力钢筋混凝土梁损伤识别研究[J].西安建筑科技大学学报(自然科学版),2023,55(03):332-341.[doi:10.15986/j.1006-7930.2023.03.003 ]
　FAN Xuhong,ZHANG Lidong,YANG Fan,et al.Research on damage identification of prestressed reinforced concrete beams based on BA-Elman algorithm[J].J. Xi'an Univ. of Arch. & Tech.(Natural Science Edition),2023,55(03):332-341.[doi:10.15986/j.1006-7930.2023.03.003 ]
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基于BA-Elman算法的预应力钢筋混凝土梁损伤识别研究()
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西安建筑科技大学学报（自然科学版）[ISSN:1006-7930/CN:61-1295/TU]

卷:
55
期数:
2023年03期
页码:
332-341
栏目:
出版日期:
2023-06-28

文章信息/Info

Title:
Research on damage identification of prestressed reinforced concrete beams based on BA-Elman algorithm
文章编号:
1006-7930(2023)03-0332-10
作者:
范旭红1; 章立栋1; 杨 帆1; 李 青2; 郁董凯3
(1.江苏大学 力学与土木工程学院, 江苏 镇江 212013; 2.河南省公路工程局集团 第二公路工程有限公司,河南 郑州 450015; 3.中国葛洲坝集团 第二工程有限公司,四川 成都 610091)
Author(s):
FAN Xuhong1; ZHANG Lidong1; YANG Fan1; LI Qing2; YU Dongkai3
(1.College of Mechanics and Civil Engineering, Jiangsu University, Jiangsu Zhenjiang 212013,China; 2.Henan Highway Engineering Bureau Group Second Highway Engineering Co. Ltd., Zhengzhou 450015, China; 3.China Gezhouba Group Second Engineering Co., Ltd., Chengdu 610091, China)
关键词:
声发射;  预应力混凝土结构;  损伤识别;  Elman神经网络;  蝙蝠算法
Keywords:
acoustic emission;  prestressed concrete structure;  damage identification;  Elman neural network;  bat algorithm
分类号:
TU378.2
DOI:
10.15986/j.1006-7930.2023.03.003
文献标志码:
A
摘要:
为了准确识别预应力混凝土结构的损伤程度,制作预应力钢筋混凝土实验梁,进行三点弯曲加载实验,收集损伤全过程声发射(AE)信号.绘制声发射振铃计数与持续时间的特征参数关联分布图,以揭示梁的损伤演化过程.借鉴加卸载响应比理论进一步将梁的损伤破坏过程划分为4个典型阶段.构建Elman神经网络,基于Elman神经网络采用局部搜索算法,难以达到全局最优的缺点,提出用蝙蝠算法(BA)对其进行优化.设计BA-Elman神经网络模型训练识别试验梁各损伤阶段AE信号特征参数数据,准确率达到93%,相较于基础Elman神经网络准确率提高了6%左右.定型BA-Elman网络结构并识别同种工况下的其他梁AE信号,识别准确率达到92%左右.
Abstract:
In order to accurately identify the damage degree of prestressed concrete structure, the prestressed reinforced concrete experimental beam was made, and the three-point bending loading experiment was carried out to collect the acoustic emission( AE )signal of the whole damage process. The correlation distribution diagram of characteristic parameters of acoustic emission ringing count and duration was drawn to reveal the damage evolution process of the beam. According to the load-unload response ratio theory, the damage process of the beam was further divided into four typical stages. The Elman neural network was constructed, but based on the local search algorithm adopted by the Elman neural network, it was difficult to achieve the global optimum, so the bat algorithm( BA )was proposed to optimize it. The BA-Elman neural network model was designed to train and identify the AE signal characteristic parameter data of experimental beam at various damage stages, and the accuracy rate reached 93%, which was about 6% higher than that of the basic Elman neural network. The BA-Elman network structure was established and AE signals of other beams under the same working condition were identified with an accuracy of about 92%.

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相似文献/References:

[1]门进杰,朱 乐,李 欢,等.钢筋混凝土梁声发射检测参数设置和受力特征试验研究[J].西安建筑科技大学学报(自然科学版),2015,47(06):793.[doi:10.15986/j.1006-7930.2015.06. 005]
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备注/Memo

备注/Memo:
收稿日期:2022-02-22修回日期:2023-05-03
基金项目:国家自然科学基金青年项目(52108148)
第一作者:范旭红(1969—),女,硕士,副教授,主要从事防灾与减灾等方面的研究.E-mail:55358319@qq.com
更新日期/Last Update: 2023-06-28