Implement an Advanced Soft Measurement Method of Mine Dust Concentration Based on K-RBF Neural Network

In view of the coal dust concentration measurement elements, the measurement pollution environment will reduce the measurement accuracy. The paper proposes a soft measurement method of mine dust concentration based on the K-RBF neural network theory. It takes the electrostatic signal as the measurement signal and extracts the short-term energy, RMS and rectification value of the electrostatic signal as the characteristic quantities of signal. And then a measurement method model has been created due to the dust concentration network study. The method shows the high speediness, little measurement error and high precision characteristic after it compared with the simulation modeling and performance evaluation of BP soft measurement method as well as the traditional optical measurement method. The method can be used to coal mine to realize real-time rapid detection of dust concentration. Keyword — Mine dust concentration, The electrostatic signal, K-RBF neural network, Soft measurement