Substation equipment fault feature recognition method based on multispectral analysis

Abstract

The application belongs to the technical field of data processing and intelligent analysis, and particularly relates to a substation equipment fault feature identification method based on multispectral analysis, which comprises the following steps: acquiring infrared temperature distribution data and ultraviolet photon distribution data and aligning to obtain an infrared temperature distribution map and an ultraviolet photon distribution map; calculating infrared normalized rank values and ultraviolet normalized rank values based on the cumulative distribution characteristics of coordinate point intensity information, and calculating statistical correlation strength according to local joint distribution; obtaining fault saliency according to the spatial direction consistency of gradient vectors and the tail high value distribution characteristics of the infrared normalized rank values and the ultraviolet normalized rank values, and combining the statistical correlation strength; obtaining a fault region through adaptive threshold segmentation and spatial connectivity analysis, and outputting a position and a fault saliency mean value. The application reduces the risk of weak fault features being submerged by background noise in a complex environment, and improves the accuracy of fault identification.

Images