Intelligent Recognition of Muffled Blasting Sounds and Lithology Prediction in Coal Mines Based on RDGNet
Gengxin Li, Hua Ding, Kai Wang, Xiaoqiang Zhang, Jiacheng Sun, Luca De Marchi · 2025
Read Intelligent Recognition of Muffled Blasting Sounds and Lithology Prediction in Coal Mines Based on RDGNet by Gengxin Li, Hua Ding, Kai Wang, Xiaoqiang Zhang, Jiacheng Sun, Luca De Marchi (2025) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/pmc-12737104.txt.
Description
Gengxin Li and co-authors teach a computer to read blast sounds in coal mines in this 2025 study. Dull booms from rock layers signal growing cracks underground, yet spotting them by hand is slow and uneven. Their network, RDGNet, reads both sound waves and sound pictures at once.
The design blends sequence memory, lean filtering, and a gating step that merges the two streams. It names blast sounds and rock types in real time. Scores stayed high even with noise and mixed sources mixed in. The authors pitch the tool for live rock stability watching in mines and tunnels.
Catalog record
| CREATOR | Gengxin Li, Hua Ding, Kai Wang, Xiaoqiang Zhang, Jiacheng Sun, Luca De Marchi |
|---|---|
| YEAR | 2025 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 45 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |