Live drilling data updates a rock mass model to estimate hole hardness and set blasting parameters for more uniform fragmentation.
Real-time sensor scales on a machine chisel replace interrupted visual ore checks, enabling selective extraction with lower dilution and cost.
Sensor-guided drilling feedback adjusts bolter miner cutting angles to stay within the coal seam and reduce rock damage.
LIBS and hyperspectral sensors mounted on an excavator boom analyze ore grade and mineralogy during digging while avoiding bucket damage.
Drilling data from the first hole is used to tune later holes, improving rock fragmentation accuracy and vibration control for blasting.
Drilling equipment data enables rapid soil classification during borehole creation, reducing reliance on expert sample analysis for construction planning.
Localized adhesive coupling enables multi-point stress sensing in one borehole.
Cutting-wheel sensors detect material consistency to limit adhesion and tool wear.
A tracking system links milled material properties to storage locations using separate detection devices.
An automatic numerical simulation model using CNN-LSTM and Lorenz chaotic systems predicts coal and gas outbursts while maintaining operational simplicity.
Vehicle-mounted platform fuses laser radar and ground penetrating radar data to generate high-precision 3D navigation maps for fully mechanized mining surfaces.
Accelerometer detects formation hardness changes via vibration signals, allowing the system to adjust drum elevation and speed to reduce tool wear.