Geomechanics and Engineering

  • 제36권1호
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  • Pages.1-8
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  • 2024
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  • 2005-307X(pISSN)
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  • 2092-6219(eISSN)
테크노프레스 (Techno-Press)
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DOI QR코드

DOI QR Code

Void detection for tunnel lining backfill using impact-echo method based on continuous wavelet transform and convolutional neural network

  • 투고 : 2022.12.15
  • 심사 : 2023.11.10
  • 발행 : 2024.01.10
⟨ 이전 논문 다음 논문 ⟩

초록

We propose a new method for detecting voids behind tunnel concrete linings using the impact-echo method that is based on continuous wavelet transform (CWT) and a convolutional neural network (CNN). We first collect experimental data using the impact-echo method and then convert them into time-frequency images via CWT. We provide a CNN model trained using the converted images and experimentally confirm that our proposed model is robust. Moreover, it exhibits outstanding performance in detecting backfill voids and their status.

키워드

과제정보

This work is supported by the Korea Agency for Infrastructure Technology Advancement(KAIA) grant funded by the Ministry of Land, Infrastructure and Transport (Grant 22TBIP-C162312-02).

참고문헌

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