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Pulverizing System is an important part of the power plants and it is crucial to keep the system working safely and stably. According to the operation characteristics and fault analysis knowledge of the system, a fault diagnosis method based on neural network with polarization factor for the pulverizing system of the power plant is proposed. The method builds the diagnosis model by treating a neural network. The neural network uses the process variables that are related to the fault symptoms as the inputs and the fault types as the outputs. Moreover, a polarization factor is used to adjust the convergence speed of neural network automatically. Thus, the method can accomplish the treatment of the neural network and avoid the local minimums. The experiments are performed with three typical faults and their nine corresponding fault symptoms parameters derived from the pulverizing system of a real power plant. The experimental results verify the good convergence of the proposed method. The proposed method can achieve the requirement of on-site fault diagnosis of the pulverizing system of the power plants.