A Measuring Water Content Method Based on K-RBF Neural Network in the Coal on Transportation Belt

摘要

In coal mines fire consists of one of the main disasters, which usually take place for the reason that the water content of coal is over low. Over low water content of the coal transported with belt more likely brings about flying coal dust, which, when accumulated to some degree, will triggers explosion. Given that in China now coal is mainly transported with belt in coal mines, the author in this paper proposes a way to measure water content of coal transported with belt by use of microwave attenuation method and improve the measure accuracy through RBF neural network algorithm. This method is proved to be scientifically reasonable through laboratory simulation and experimentation. The theoretical basis and technical support are provided to increase the accuracy measuring water content of coal transported with belt by this method.