Multimodal structural health monitoring based on active and passive sensing

Author:

Nasrollahi Amir1,Deng Wen2,Ma Zhaoyun3,Rizzo Piervincenzo1

Affiliation:

1. Laboratory for Nondestructive Evaluation and Structural Health Monitoring Studies, Department of Civil and Environmental Engineering, University of Pittsburgh, Pittsburgh, PA, USA

2. School of Automation, Northwestern Polytechnical University, Xi’an, China

3. Department of Mechanical Engineering, University of South Carolina

Abstract

We present a structural health monitoring system based on the simultaneous use of passive and active sensing. The passive approach is based on acoustic emission, whereas the active approach uses the electromechanical impedance and the guided ultrasonic wave methods. As all these methods can be deployed with the use of wafer-type piezoelectric transducers bonded or embedded to the structure of interest, this article describes a unified structural health monitoring system where acoustic emission, electromechanical impedance, and guided ultrasonic wave are integrated in the same hardware/software unit. We assess the feasibility of this multimodal monitoring in a large flat aluminum plate instrumented with six transducers. Acoustic emission events are simulated by exciting a tone burst or by using the conventional pencil lead break test, and the detected signals are processed with a source localization algorithm to identify the position of the source. For the active sensing, damage is simulated by adding a small mass to the plate: the raw waveforms are processed with a delay-and-sum algorithm to create an image of the plate, whereas the electrical admittance of each transducer is analyzed using the statistical index of the root-mean-square deviation. The results presented in this article show that the proposed system is robust, mitigates the weaknesses of each method considered individually, and can be developed further to address the challenges associated with the structural health monitoring of complex structures.

Funder

American Society for Nondestructive Testing

Publisher

SAGE Publications

Subject

Mechanical Engineering,Biophysics

Cited by 38 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

1. An adaptive network model-based weighted similarity measure for CT image denoising;Soft Computing;2023-11-21

2. An Optimized Learning Model for Image Denoising using Modern Deep Learning Approaches;2023 International Conference on Research Methodologies in Knowledge Management, Artificial Intelligence and Telecommunication Engineering (RMKMATE);2023-11-01

3. Deep transfer learning-based damage detection of composite structures by fusing monitoring data with physical mechanism;Engineering Applications of Artificial Intelligence;2023-08

4. Inner damage identification and residual strength assessment of a 3D printed tunnel with marble-like cementitious materials using piezoelectric transducers;Journal of Rock Mechanics and Geotechnical Engineering;2023-04

5. Introduction;Synthesis Lectures on Biomedical Engineering;2023

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