The high timeliness of distribution network emergency repair requires accurate fault positioning and efficient resource scheduling. UAV inspection combined with AI optimized scheduling can improve the efficiency of emergency repair. This paper analyzes the methods of patrol mission planning

flight path optimization

multi-sensor data collection and fault identification

and proposes an improved target detection and timing prediction algorithm. The study discusses the collaborative optimization strategy of UAV inspection and equipment scheduling

and improves the intelligent level of emergency repair decision-making. The research results can reduce the response time of distribution network emergency repair

and provide theoretical support and technical reference for the construction of an intelligent and efficient distribution emergency repair system.