Damage Identification in Reinforced Concrete Beams Using Wavelet Transform of Modal Excitation Responses

Author:

Soleymani Atefeh1ORCID,Jahangir Hashem2ORCID,Rashidi Maria3ORCID,Mojtahedi Farid Fazel4,Bahrami Michael5ORCID,Javanmardi Ahad36ORCID

Affiliation:

1. Department of Civil Engineering, Shahid Bahonar University of Kerman, Kerman 7616913439, Iran

2. Department of Civil Engineering, University of Birjand, Birjand 9717434765, Iran

3. Centre for Infrastructure Engineering, Western Sydney University, Sydney, NSW 2000, Australia

4. Department of Infrastructure Engineering, University of Melbourne, Parkville, VIC 3010, Australia

5. Department of Civil Engineering, Sharif University of Technology, Tehran 1458889694, Iran

6. College of Civil Engineering, Key Lab of Fujian Province, Fuzhou University, University Town, 2 Xueyuan Road, Fuzhou 350108, China

Abstract

This study focuses on identifying damage in reinforced concrete (RC) beams using time-domain modal testing and wavelet analysis. A numerical model of an RC beam was used to generate various damage scenarios with different severities and locations. Acceleration time histories were recorded for both damaged and undamaged structures. Two damage indices, DI_MW and DI_SW, derived from the wavelet analysis, were employed to determine the location and severity of the damage. The results showed that different wavelet families and specific mother wavelets had varying effectiveness in detecting damage. The Daubechies wavelet family (db2, db6, and db9) detected damage at the center and sides of the RC beams due to good time and frequency localization. The Biorthogonal wavelet family (bior2.8 and bior3.1) provided improved time–frequency resolution. The Symlets wavelet family (sym2 and sym7) offered a balanced trade-off between time and frequency localization. The Shannon wavelet family (shan1-0.5 and shan1-0.1) exhibited good time localization, while the Frequency B-Spline wavelet family (fbsp2-1-0.1) excelled in frequency localization. Certain combinations of mother wavelets, such as shan1-0.5 with the DI_SW index, were highly effective in detecting damage. The DI_SW index outperformed DI_MW across different numerical models. Selecting appropriate wavelet analysis techniques, particularly utilizing shan1-0.5 in the DI_SW, proved effective for detecting damage in RC beams.

Publisher

MDPI AG

Subject

Building and Construction,Civil and Structural Engineering,Architecture

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3