Evaluation Of Coal Mine Roof Supports Using Artificial Intelligence

The U.S. Bureau of Mines is developing an intelligent system for roof' control that uses both an expert system and neural networks to improve the capability of mining engineers to evaluate roof support effectiveness for ground control in coal mines. The expert system com- pares roof support capacities with the support requirements estimated to be necessary to maintain entry stability. It does this by evaluating the results of tests on various types of roof support and establishing the maximum allowable load according to anchorage capacity and yield strength of the support. After the user enters geological information (rock properties, geometry of the opening, in situ stresses, bolt pattern parameters, etc. ), the expert system compares the predicted required loading to the roof support capacity and gives the operator advice on the adequacy of the design and how improvements could be made. A good source of the real-time data necessary to allow the expert system to make decisions will come from a roof bolting machine being developed by the Bureau of Mines. Researchers have collected data from a Western coal mine on drill bit position, penetration rate thrust, torque, and rotation rate. Using this information, two neural net- works were developed to identify different types of strata and features in a mine roof such as rock type, rock compressive strength and joint characteristics. The result is a system that can assist a mining engineer with design information that can be constantly updated as mining progresses.