Abstract: With the continuous expansion of power grid scale, transmission line inspection faces challenges such as low efficiency, high risks, and insufficient coverage. This paper studies an intelligent inspection and fault diagnosis technology based on collaborative drones. A multi-drone task allocation and path planning algorithm is constructed to establish a collaborative inspection system, while deep learning models are utilized to achieve intelligent defect recognition and fault classification in transmission lines. Experimental results demonstrate that the system significantly improves inspection efficiency and fault diagnosis accuracy, reduces manual inspection costs and safety risks, and provides effective technical support for the safe and stable operation of power grids. The research findings hold significant practical value for advancing the intelligentization of transmission line inspection.