Abstract: With the rapid development of the wind power industry, the traditional operation and maintenance (O&M) model for electrical equipment in wind farms can no longer meet the needs of efficient management. Aiming at problems such as high equipment failure rate and lagging diagnosis, this paper constructs an intelligent O&M technical system of "state perception - intelligent diagnosis - decision optimization", realizing real-time collection of key equipment parameters, accurate fault diagnosis, and dynamic adjustment of O&M strategies. Engineering verification shows that this system significantly improves the accuracy of equipment fault identification and early warning lead time, reduces O&M costs, and provides an effective solution for the efficient and reliable operation of wind farms. Meanwhile, cutting-edge technologies such as digital twin and edge intelligence can be applied to the O&M of electrical equipment in wind farms to further enhance the operational reliability of wind farms.