Research on Noise Reduction Method of High-Voltage Transmission Conductor Temperature Detection Signals Based on Adaptive Kalman Filtering

In the power system, high-voltage conductor temperature monitoring is a key link to ensure the safe and stable operation of the power grid, so it is necessary to monitor the temperature of high-voltage transmission conductors. However, the data monitored by traditional high-voltage wire temperature sensors is too single, and there are problems with data uncertainty and errors, which have a great impact on the accuracy of temperature signal detection. Due to the limited accuracy of the traditional Kalman filter mathematical model, accurate prediction results cannot be obtained. Therefore, an adaptive Kalman filtering method for estimating and detecting the temperature signal of high-voltage transmission conductors is proposed to reduce signal noise. This model provides a method for calculating the operating temperature of the conductor, and compares it with the temperature sensor measurement results using adaptive Kalman filtering. For comparison, the results show that the adaptive Kalman filter method has higher prediction accuracy.