Research on High-Voltage Transmission Tower State Identification Based on CNN-Transformer

High-voltage transmission towers are susceptible to damage risks under environmental stimuli such as strong winds and landslides, posing serious threats to the safety of the power system. To improve the accuracy of existing tower state identification methods, a high-voltage transmission tower state identification method based on the CNN-Transformer is proposed. The sensor optimization layout scheme for different tower models is formulated, and vibration acceleration data for various damage states of the towers are obtained through ANSYS dynamic simulation. Based on this data, the tower state is identified using the CNN-Transformer model. The results show that the high-voltage transmission tower state identification model based on CNN-Transformer can accurately identify the state of the towers, confirming the effectiveness of the optimized sensor layout scheme for transmission tower state identification.