Adaptive signal discrimination as applied to coal interface detection

Abstract

A description is given of two coal-rock interface detector (CID) methods associated with vibrations generated by mining machines and how adaptive signal discrimination (ASD) technology is being used to process these signals. In these CID methods, strata (roof, coal seam, floor) or mining machine vibrations are monitored for the complex signals generated, which vary according to the type of mining machine being used. These signals are then analyzed using sophisticated state-of-the-art ASD technology. It is this advanced signal analysis that distinguishes this approach from those of prior research. The ASD system is initially trained using a database of features extracted from known signals measured under conditions of interest. Subsequently, it uses this database to determine if unknown signals belong to a given condition. Assuming that the ASD system classifies these signals correctly, such a system could have the potential for controlling a mining machine so that it always remains in the coal system.<>