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At present, most of the power capacitor condition monitoring systems are lack of real-time and data frequency density. It is difficult to achieve accurate online fault prediction, which is easy to lead to bad consequences such as delay in fault processing or false alarm. Based on the actual demand of operation and maintenance of power capacitor, this paper constructs a complete on-line fault monitoring system of power capacitor, and presents a fault diagnosis model and method using neural network to fuse the current, capacitance, resistance and voltage information of capacitor, which is applied in practice. In practical application, the system can timely and accurately capture the abnormal state and fault characteristics of capacitors, avoid the lag of fault judgment, improve the accuracy of data acquisition, improve the operation and maintenance efficiency of power grid equipment, and improve the reliability of power grid operation.