A GIS(Gas Insulated Switchgear)performance detection method based on the fusion of target recognition algorithm and multi-source perception technology is designed to address the issue of insufficient accuracy in detecting data in traditional multi-source perception detection methods in GIS operations.Introducing a target recognition algorithm based on the BP neural network algorithm as the core in traditional performance detection techniques,the BP multi-layer neural network achieves effi-cient data target extraction and greatly improves the accuracy of data detection.To solve the problem of a single sensor not being able to fully capture complex environmental information,based on multi-source perception technology,multiple sensors are used to comprehensively perceive multiple data sources,ex-panding the environmental perspective and information dimension,achieving comprehensive monitoring of the surrounding environment,and enabling the detection system to achieve more ideal data detection ca-pabilities.Field testing was conducted in an actual GIS operating environment,and the proposed im-proved multi-source perception method was experimentally compared with traditional multi-source per-ception methods.The results showed that the proposed method can improve the accuracy of GIS perform-ance detection to over 98%.
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