A Wavelet Transform and ResNet Based Method for Sensing the Operational Status of Secondary Equipment in the Distribution Room

With the improvement of the level of grid intelligence, the distribution network, as the terminal of the power system, ensures the safety of the distribution room and has an important significance to the smooth operation of the grid. To be able to understand the operation condition of the secondary equipment in the distribution room in real-time and ensure the safe and stable operation of the distribution room, a method for sensing the secondary operation status of the distribution room is proposed. Firstly, the noise processing method based on the wavelet transform is proposed based on the environmental data and the operation data of the secondary equipment such as voltage and current in the distribution room, and then the time-frequency analysis method of the data characteristics of the secondary equipment is designed for the denoised data and transformed into the form of time-frequency diagram to extract the data features. Finally, a ResNet-based secondary equipment operation situational awareness model is proposed to determine the current operation status of the power distribution room by means of time-frequency graph classification. The analysis of the algorithm shows that the method can effectively sense the current secondary equipment operation status of the power distribution room and ensure that the power distribution room is in a smooth operation state.