An Unsupervised Tunnel Damage Identification Method Based on Convolutional Variational Auto-Encoder and Wavelet Packet Analysis

Finding a low-cost and highly efficient method for identifying subway tunnel damage can greatly reduce catastrophic accidents. At present, tunnel health monitoring is mainly based on the observation of apparent diseases and vibration monitoring, which is combined with a manual inspection to perceive...

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Detalles Bibliográficos
Autores principales: Zhang, Yonglai, Xie, Xiongyao, Li, Hongqiao, Zhou, Biao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8953544/
https://www.ncbi.nlm.nih.gov/pubmed/35336582
http://dx.doi.org/10.3390/s22062412

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8953544/
https://www.ncbi.nlm.nih.gov/pubmed/35336582
http://dx.doi.org/10.3390/s22062412

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