Mining Publication: Neural Network Technology for Strata Strength Characterization
Original creation date: January 1999
The process of drilling and bolting the roof is currently one of the most dangerous jobs in underground mining, resulting in about 1,000 accidents with injuries each year in the United States. To increase the safety of underground miners, researchers from the Spokane Research Laboratory of the National Institute for Occupational Safety and Health are applying neural network technology to the classification of mine roof strata in terms of relative strength. In this project, the feasibility of using a monitoring system on a roof drill to assess the integrity of a mine roof and warn a roof drill operator when a weak layer is encountered is being studied. Using measurements taken while a layer is being drilled, one can convert the data to suitably scaled features and classify the strength of the layer with a neural network. The feasibility of using a drill monitoring system to estimate the strength of successive layers of rock was demonstrated in the laboratory.
Authors: WK Utt
Conference Paper - January 1999
NIOSHTIC2 Number: 20024659
Proc International Joint Conference on Neural Networks, Mount Royal, New Jersey. Middleton, WI: International Neural Network Society, 1999 Jan; :CD-ROM; 4pp
See Also
- Diagnosing and Controlling Moisture-Sensitive Roof in Coal Mines
- Drill Monitor With Strata Strength Classification in Near-Real Time
- Geologic Hazards and Roof Stability in Coal Mines
- Ground Monitoring
- Monitoring and Removal of CO in Blasting Operations
- New Developments with the Coal Mine Roof Rating
- Remote Monitoring of Mine Seismicity and Earthquakes Using Radio Telemetry, Computers, and the Internet
- Roof Monitoring Helps Prevent Injuries in Stone Mines
- Technology News 481 - Update: Roof Monitoring Safety System for Underground Stone Mines
- Time Dependent Roof Deterioration at a Central Ohio Coal Mine
- Page last reviewed: 9/21/2012
- Page last updated: 9/21/2012
- Content source: National Institute for Occupational Safety and Health, Mining Program