Application of ANFIS Neural Network for Wire Network Signal Prediction

In the process of monitoring and repairing, it is difficult to measure wire net signal of power system´s high voltage transmission lines in work-field accurately. In order to solve this problem, the signal measured in remote substation or laboratory is employed to make multipoint prediction and then the predicted data is sent to work-field via wireless network GPRS to gain the needed data. Because ANFIS network has the ability of expressing knowledge, fuzzy reference effectively and quick learning speed on-line, it is used to forecast data. The needed precise data may be computed based on current time and received data, which may provide reliably basis for fault diagnosis of air bracket high voltage power transmission lines. Experiment results show that the designed ANFIS network has strong predicting ability, which offers accurate data for the monitoring and fault diagnosis of power high voltage transmission lines.