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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...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
MDPI
2022
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| Materias: | |
| 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 |