Efficiency of electromechanical impedance for load and damage assessment along the thickness of lead zirconate titanate transducers in structural monitoring-Reference-Cited by-同舟云学术

Efficiency of electromechanical impedance for load and damage assessment along the thickness of lead zirconate titanate transducers in structural monitoring

Published:2013-06-07 Issue:16 Volume:24 Page:2008-2022
ISSN:1045-389X
Container-title:Journal of Intelligent Material Systems and Structures
language:en
Short-container-title:Journal of Intelligent Material Systems and Structures

Author:

Annamdas Venu GM¹²,Pang John HL¹²,Zhou Kun¹²,Song Bin¹³

Affiliation:

1. SIMTech-NTU Joint Laboratory on Reliability, Nanyang Technological University, Singapore

2. School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore

3. Singapore Institute of Manufacturing Technology (SIMTech), Division of A*STAR, Singapore

Publisher

SAGE Publications

Subject

Mechanical Engineering,General Materials Science

Link

http://journals.sagepub.com/doi/pdf/10.1177/1045389X13488252

Reference43 articles.

1. Annamdas VGM (2007) Characterization of smart PZT transducer and admittance signatures using PZT-structure interaction models for structural health monitoring. PhD Thesis, Nanyang Technological University, Singapore.

2. Monitoring concrete by means of embedded sensors and electromechanical impedance technique

3. Embedded piezoelectric ceramic transducers in sandwiched beams

Cited by 22 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. Shear stress identification in plate rubber bearing using surface-bonded piezoelectric transducer: A feasibility study;Measurement;2024-09

2. Flexure-critical stress and damage identification in RC beam structure using embedded piezoelectric transducers: 2D modelling and experimental investigations;Construction and Building Materials;2023-12

3. A novel data-based approach for monitoring fatigue crack propagation in welded joints under varying ambient temperature using the electromechanical admittance;Structural Health Monitoring;2023-01-30

4. Automated identification of compressive stress and damage in concrete specimen using convolutional neural network learned electromechanical admittance;Engineering Structures;2022-05

5. A cost-effective approach for assessment of pre-stressing force in bridges using piezoelectric transducers;Measurement;2021-01