Abstract: The present disclosure discloses a detection method and system of power equipment based on a multispectral image, and relates to the field of smart grid information technology. The method includes: obtaining an image of power equipment to be detected, where the image is one of an infrared image, an ultraviolet image, and a visible image; inputting the image into a pre-trained pixel-based power equipment detection model for detection, and performing classified prediction on pixels in the image to obtain a predicted result; and outputting a predicted image based on the predicted result, where the predicted image is power equipment image with background information removed, and is marked with a name of each piece of equipment. With the implementation of the present disclosure, efficiency and accuracy of power equipment detection can be improved.

Abstract: The present disclosure discloses an infrared thermal imaging defect detection method and apparatus for a substation insulator. An infrared module is bidirectionally connected to a core computing module, and an infrared module is unidirectionally connected to a high-rate battery. The core computing module is unidirectionally connected to a touch screen. The infrared module is configured to obtain infrared radiation information through a lens, and calculate and generate a temperature distribution video. The method includes infrared video acquisition, thermal region segmentation, device type determination, key temperature information extraction, defect diagnoses, result display and result saving.

Abstract: A method for detecting a topological structure of a grounding grid under extremely cold condition, includes the following steps: in a substation in an extremely cold area, determining a measuring area S on a ground surface of a grounding grid according to the positions of branches and nodes of the grounding grid in a selected area, acquiring dynamic current values of the branches and nodes through a current sensor based on TMR tunnel magnetoresistance, and then indirectly acquiring the magnetic induction intensity of the measuring area S through conversion; calculating moduli of first to third derivatives of magnetic induction intensities; and determining specific positions and laying depths of the branches of the grounding grid according to peak distances between main lobe peaks and side peaks between strong peaks of the moduli. According to the method, the calculation amount is greatly reduced, and the detection method has strong anti-interference.