Structural Monitoring and Maintenance

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An approach for structural damage identification using electromechanical impedance

  • Yujun Ye (College of Civil Engineering and Architecture, Zhejiang University) ;
  • Yikai Zhu (College of Civil Engineering and Architecture, Zhejiang University) ;
  • Bo Lei (China Construction Third Engineering Bureau Co., Ltd.) ;
  • Zhihai Weng (Huzhou City Investment and Development Group Co., Ltd.) ;
  • Hongchang Xu (China Construction Third Engineering Bureau Co., Ltd.) ;
  • Huaping Wan (College of Civil Engineering and Architecture, Zhejiang University)
  • Received : 2023.11.19
  • Accepted : 2024.03.13
  • Published : 2024.09.25
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Abstract

Electro-mechanical impedance (EMI) technique is a low-cost structural damage detection method. It reflects structural damage through the change in admittance signal which contains the structural mechanical impedance information. The ambient temperature greatly affects the admittance signal, which hides the changes caused by structural damage and reduces the accuracy of damage identification. This study introduces a convolutional neural network to compensate for the temperature effect. The proposed method uses a framework that consists of a feature extraction network and a decoding network, and the original admittance signal with temperature information is used as the input. The output admittance signal is eliminated from the temperature effect, improving damage identification robustness. The admittance data simulated by the finite element model of the spatial grid structure is used to verify the effectiveness of the proposed method. The results show that the proposed method has advantages in identification accuracy compared with the damage index minimization method and the principal component analysis method.

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References

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