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Grinding grading operation is a key link in mineral processing production, and particle size of grinding circuit directly affect the grade of concentrate and the recovery rate of tailings in the process of flotation. In the actual production, the measurement of particle size, one side we can use online particle size analyzer, but it’s too high cost and high maintenance rate; in other side we can measure it in off-line laboratory tests, but it’s too large time delay. Through the analysis of the actual grinding grading operation process, put forward a soft sensor model of grind size with RBF neural network and training this network by using orthogonal least squares learning algorithm. The simulation results show that the network under less training data is still very strong nonlinear processing ability and approaching ability, learning time is short, model conforms to the basic requirements. Through the OPC technology can contact the Matlab and PKS control system, which can realize real-time soft sensor particle size of grinding circuit.