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Cited by 336

The DOI matches its Crossref record; 40 of the 40 references it cites were found in a registry or an index.

A Review of the Piezoelectric Electromechanical Impedance Based Structural Health Monitoring Technique for Engineering Structures

Open access
Na, Wongi S., Baek, Jongdae·2018·Sensors

Abstract

The birth of smart materials such as piezoelectric (PZT) transducers has aided in revolutionizing the field of structural health monitoring (SHM) based on non-destructive testing (NDT) methods. While a relatively new NDT method known as the electromechanical (EMI) technique has been investigated for more than two decades, there are still various problems that must be solved before it is applied to real structures. The technique, which has a significant potential to contribute to the creation of one of the most effective SHM systems, involves the use of a single PZT for exciting and sensing of the host structure. In this paper, studies applied for the past decade related to the EMI technique have been reviewed to understand its trend. In addition, new concepts and ideas proposed by various authors are also surveyed, and the paper concludes with a discussion of the potential directions for future works.

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Metadata

Authors
Na, W. S., & Baek, J.
Venue
Sensors
Publisher
MDPI AG
Published
2018-04-24
Volume
18
Issue
5
Pages
1307
ISSN
1424-8220 (ISSN-L)
OpenAlex
W2801443543
Cited by
336
References
40
FWCI
19.73
Type
journal article
Language
en
Open access
gold

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CoChat. (2026). Citation check: A Review of the Piezoelectric Electromechanical Impedance Based Structural Health Monitoring Technique for Engineering Structures. https://app.cochat.ai/papers/10.3390/s18051307
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Na, W. S., & Baek, J. (2018). A Review of the Piezoelectric Electromechanical Impedance Based Structural Health Monitoring Technique for Engineering Structures. Sensors. https://doi.org/10.3390/s18051307

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.