The tilting of transmission towers may seriously threaten the normal operation of power grids. In this study, an online monitoring system for transmission towers based on the Internet of Things platform is designed, which aims to ensure the safe operation of the power grid by real-time monitoring of the tilting status of the towers and the surrounding meteorological environment. The system adopts a variety of sensors and ZigBee wireless communication technology, and transmits the data to the monitoring center through the on-site monitoring base station, which is able to realize remote real-time monitoring. Aiming at the problem of low-cost inertial measurement unit (IMU) accuracy in the existing monitoring system, this paper proposes an improved adaptive hybrid filtering algorithm (Sage-Husa), which is experimentally verified to effectively improve the stability and accuracy of the system. In the static experiments, the standard deviation of the Sage-Husa algorithm in the X-axis, Y-axis and Zaxis is 0.018, 0.0073 and 0.018, respectively, which shows a better noise reduction effect. In the dynamic experiments, evaluated using the root mean square error (RMSE), the RMSE of the Sage-Husa algorithm is 0.00154°/s (gyroscope) and 0.00305 m/s² (accelerometer), which shows better performance compared to other algorithms. The system designed in this paper can effectively improve the accuracy and reliability of tilt state monitoring of transmission towers, and has a wide range of application prospects.
