Void detection for tunnel lining backfill using impact-echo method based on continuous wavelet transform and convolutional neural network - Lee, Jiyun; Kim, Kyuwon; Kang, Meiyan; Hong, Eun Soo; Choi, Suyoung (Geomechanics and Engineering, 2024)
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.
Keywords: Concrete linings; Continuous Wavelet Transform; Convolutional neural network; Impact echo methods; Lining backfill; Neural network model; Performance; Time-frequency images; Voids detection; continuous wavelet transform; convolutional neural network; impact-echo method; lining backfill; nondestructive testing; void detection