Identification of GIS equipment isolation switch on/off status based on ILPSO-LSSVM

In order to monitor the opening and closing status of electric GIS equipment isolation switches, this paper proposes a GIS equipment isolation switch opening and closing status recognition method based on ILPSO-LSSVM. This method performs denoising and image correction on the extracted GIS equipment isolation switch images. The pixel integral projection method is used to extract features of the opening and closing status of the switch blade. The ILPSO algorithm is combined with the LSSVM algorithm to optimize the parameters of the LSSVM model and construct an isolation switch contact state recognition model to improve the recognition accuracy and generalization ability of the model, achieving accurate recognition of the opening and closing status of GIS equipment isolation switches. The experiment shows that the processed image feature extraction has strong accuracy and a high recognition rate of over 97% for the opening and closing status of GIS equipment isolation switches. This method can accurately identify the opening and closing status of GIS equipment isolation switches, providing an effective technical means for status monitoring and fault diagnosis of GIS equipment.