Energy Analysis of Piezoelectric Stacked Transducers for Damage Detection in Large-Scale Structures

Lamb wave based monitoring technology has the advantages of fast response, wide coverage, and high cost-effectiveness, making it a prominent focus in the field of structural health monitoring. However, the wave energy attenuation can affect the reliability of damage detection for large-scale structures. Increasing the excitation energy of Lamb waves is an effective strategy to reduce the effect of Lamb wave attenuation, which can further improve signal-to-noise ratio. In order to improve the energy of the excitation wave, this study designed a piezoelectric stacked transducer with high excitation energy by a finite element analysis model using ABAQUS. The comparative analysis of the excitation energy results of piezoelectric stacked transducers confirms their high excitation energy characteristics. Subsequently, a thorough comparison is undertaken to analyze the differences in damage scattering waves between the stacked piezoelectric transducer and its single-layer counterpart within the framework of damage monitoring. The results robustly demonstrate that stacked piezoelectric sensors have the advantages of a high signal-to-noise ratio and excitation energy in damage detection. Furthermore, a damage monitoring model with stacked piezoelectric sensors was established by simulation method, and the calculated results from the model closely correlate with the experimental results. The results show that the designed stacked piezoelectric sensors are more sensitive to damage signals, anticipating their application in future damage detection efforts for large-scale structures with high attenuation.

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Published
2024-10-18
DOI
https://doi.org/10.1109/meae62008.2024.11026168
Primary Topic
Ultrasonics and Acoustic Wave Propagation
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article
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article

Energy Analysis of Piezoelectric Stacked Transducers for Damage Detection in Large-Scale Structures

Jitong Ma, Rui Xu, Yu Hu, Zhengyan Yang
Ultrasonics and Acoustic Wave Propagation
article

Energy Analysis of Piezoelectric Stacked Transducers for Damage Detection in Large-Scale Structures

Jitong Ma, Rui Xu, Yu Hu, Zhengyan Yang
article en

Abstract

Lamb wave based monitoring technology has the advantages of fast response, wide coverage, and high cost-effectiveness, making it a prominent focus in the field of structural health monitoring. However, the wave energy attenuation can affect the reliability of damage detection for large-scale structures. Increasing the excitation energy of Lamb waves is an effective strategy to reduce the effect of Lamb wave attenuation, which can further improve signal-to-noise ratio. In order to improve the energy of the excitation wave, this study designed a piezoelectric stacked transducer with high excitation energy by a finite element analysis model using ABAQUS. The comparative analysis of the excitation energy results of piezoelectric stacked transducers confirms their high excitation energy characteristics. Subsequently, a thorough comparison is undertaken to analyze the differences in damage scattering waves between the stacked piezoelectric transducer and its single-layer counterpart within the framework of damage monitoring. The results robustly demonstrate that stacked piezoelectric sensors have the advantages of a high signal-to-noise ratio and excitation energy in damage detection. Furthermore, a damage monitoring model with stacked piezoelectric sensors was established by simulation method, and the calculated results from the model closely correlate with the experimental results. The results show that the designed stacked piezoelectric sensors are more sensitive to damage signals, anticipating their application in future damage detection efforts for large-scale structures with high attenuation.

Jiangnan University (CN), Dalian Maritime University (CN)
Affordable and clean energy
Openalex Percentile: Top 68%
Ultrasonics and Acoustic Wave Propagation
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Energy Analysis of Piezoelectric Stacked Transducers for Damage Detection in Large-Scale Structures — Jitong Ma, Rui Xu, et al. · (2024) | TGRS Research Map | TGRS