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Feature-preserving denoising of low-SNR microseismic signals in deep underground engineering using U-BiLSTM-CA-DDNet with explicit signal–noise separation

https://doi.org/10.2139/ssrn.7438632
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Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/s00024-023-03365-0openalex-snapshot
Microseismic Signal Denoising Based on Variational Mode Decomposition With Adaptive Non-local Means Filtering
inferredcites →https://doi.org/10.1007/s11589-001-0044-0openalex-snapshot
Automatic onset phase picking for portable seismic array observation
inferredcites →https://doi.org/10.1007/s11600-024-01518-wopenalex-snapshot
RETRACTED ARTICLE: Efficient seismic noise suppression for microseismic data using an adaptive TMSST approach
inferredcites →https://doi.org/10.1016/j.aiig.2023.02.002openalex-snapshot
Research on microseismic denoising method based on CBDNet
inferredcites →https://doi.org/10.1016/j.earscirev.2023.104371openalex-snapshot
Machine learning in microseismic monitoring
inferredcites →https://doi.org/10.1016/j.ijmst.2018.08.007openalex-snapshot
Comprehensive early warning of rock burst utilizing microseismic multi-parameter indices
inferredcites →https://doi.org/10.1016/j.ijmst.2019.06.009openalex-snapshot
Machine learning methods for rockburst prediction-state-of-the-art review
inferredcites →https://doi.org/10.1016/j.ijmst.2020.04.009openalex-snapshot
A comprehensive geomechanical method for the assessment of rockburst hazards in underground mining
inferredcites →https://doi.org/10.1016/j.ijmst.2023.07.006openalex-snapshot
Rock dynamics in deep mining
inferredcites →https://doi.org/10.1016/j.ijmst.2023.09.003openalex-snapshot
Microseismic event waveform classification using CNN-based transfer learning models
inferredcites →https://doi.org/10.1016/j.jappgeo.2024.105355openalex-snapshot
Seismic signal denoising using Swin-Conv-UNet
inferredcites →https://doi.org/10.1016/j.tust.2015.04.016openalex-snapshot
Rockburst characteristics and microseismic monitoring of deep-buried tunnels for Jinping II Hydropower Station
inferredcites →https://doi.org/10.1016/j.tust.2018.08.028openalex-snapshot
Stability evaluation of deep-buried TBM construction tunnel based on microseismic monitoring technology
inferredcites →https://doi.org/10.1016/j.tust.2021.104025openalex-snapshot
A path for evaluating the mechanical response of rock masses based on deep mining-induced microseismic data: A case study
inferredcites →https://doi.org/10.1016/j.undsp.2017.05.002openalex-snapshot
Microseismic monitoring and analysis of induced seismicity source mechanisms in a retreating room and pillar coal mine in the Eastern United States
inferredcites →https://doi.org/10.1038/s41598-019-45748-1openalex-snapshot
CRED: A Deep Residual Network of Convolutional and Recurrent Units for Earthquake Signal Detection
inferredcites →https://doi.org/10.1038/s41598-022-26576-2openalex-snapshot
Investigation of microseismic signal denoising using an improved wavelet adaptive thresholding method
inferredcites →https://doi.org/10.1093/gji/ggac290openalex-snapshot
A multitask encoder–decoder to separate earthquake and ambient noise signal in seismograms
inferredcites →https://doi.org/10.1093/gji/ggad460openalex-snapshot
DAS-N2N: machine learning distributed acoustic sensing (DAS) signal denoising without clean data
inferredcites →https://doi.org/10.1093/gji/ggy079openalex-snapshot
Non-stationary least-squares complex decomposition for microseismic noise attenuation
inferredcites →https://doi.org/10.1093/jge/gxad076openalex-snapshot
Seismic random noise attenuation using DnCNN with stratigraphic dip constraint
inferredcites →https://doi.org/10.1109/tgrs.2019.2926772openalex-snapshot
Seismic Signal Denoising and Decomposition Using Deep Neural Networks
inferredcites →https://doi.org/10.1190/geo2015-0598.1openalex-snapshot
Automatic microseismic denoising and onset detection using the synchrosqueezed continuous wavelet transform
inferredcites →https://doi.org/10.32604/cmes.2024.051402openalex-snapshot
A Microseismic Signal Denoising Algorithm Combining VMD and Wavelet Threshold Denoising Optimized by BWOA
inferredcites →https://doi.org/10.3390/app10186621openalex-snapshot
Microseismic Signal Denoising and Separation Based on Fully Convolutional Encoder–Decoder Network
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