Abstract: This paper proposes an intelligent management model for distribution network equipment centered on dual ultrasonic transient ground voltage partial discharge monitoring sensors. By aggregating both electrical and non-electrical data through intelligent agents, the system enables continuous 24/7 data acquisition, filtering, computation, and condition assessment of distribution equipment. Sampled data are transmitted to a cloud-based distribution Internet of Things platform, where intelligent filtering and diagnostics are performed to provide auxiliary decision-making suggestions. The proposed model has been successfully implemented in 12 distribution substations within the Beijing Economic-Technological Development Area, significantly enhancing the early warning capability for equipment anomalies and improving the efficiency of routine operation and maintenance.