Performance evaluation of piezo sensors with respect to accelerometers for 3D modal analysis of structures

Author:

Aulakh Dattar SinghORCID,Bhalla Suresh

Abstract

Abstract Strain modal analysis, as a new domain in the health monitoring field, needs to be studied in depth for experimental modal testing. Towards this purpose, this paper experimentally investigates the efficacy of piezo sensors for structural identification for structural health monitoring under different excitations applicable to large-scale structures. The piezo sensors are evaluated against industry-standard accelerometers by experimental modal testing of a scaled-down model of a pedestrian foot over bridge. The model is excited under the impact hammer, electro-dynamic shaker-based sweep and random excitations, and pedestrian motion (PM)-based low-amplitude excitations. Piezo sensors are found to be capable of capturing the modal parameters (modal frequencies, damping ratios and mode shape vector) under all the excitations with excellent correlation with respect to accelerometer-based parameters. However, some modes are missed under the shaker and PM-based excitations compared to the impact hammer-based excitations for both accelerometers and piezo sensors. Modal parameters of lower modes are successfully extracted under low-level pedestrian excitations, the most efficient type of excitation acting in operational conditions. High modal assurance criteria values between the strain and the displacement mode shapes establish the piezo sensors as effective for strain-based vibration testing and structural identification.

Publisher

IOP Publishing

Subject

Electrical and Electronic Engineering,Mechanics of Materials,Condensed Matter Physics,General Materials Science,Atomic and Molecular Physics, and Optics,Civil and Structural Engineering,Signal Processing

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

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