This project belongs to the field of distribution networks. As the scale of the distribution network continues to expand, traditional operation and maintenance models are no longer able to meet the requirements of power users for power supply reliability. The distribution network with the closest relationship with users is mainly composed of high-voltage circuits, distribution transformers, etc. At present, the distribution network lacks multi-source data fusion analysis and processing models and multi-protocol compatible IoT gateways, and it is difficult to locate fault points in low-voltage circuits. Problems such as low monitoring rate of non-electrical information of distribution transformers and frequent failures, inaccurate non-contact temperature measurement at cable terminal heads, have seriously affected the improvement of the reliability of the distribution network's power supply. In order to solve the above problems, research on key technologies of intelligent sensing diagnosis of power distribution equipment was carried out, and an intelligent diagnosis and analysis system for power distribution equipment was built. This system is designed using the ldquo; cloud pipe side end rdquo; system architecture, which is mainly composed of data collection and analysis terminals located on the equipment site, Internet of Things gateway, cloud platform, and monitoring terminals. Based on operation and maintenance experience, the outgoing status of the low-voltage circuit, the oil temperature and oil level of the distribution transformer, and the temperature of the cable terminal head, which can reflect the operating information of the distribution equipment, were selected as research objects to monitor the operating status of the distribution equipment, and at the same time, on the cloud platform A power distribution equipment intelligent sensing diagnosis module has been developed based on big data technology to intelligently diagnose the defects and faults of the distribution equipment. The key innovation points are: 1. A multi-protocol compatible and multi-data source information extraction method for distribution equipment status analysis is proposed. A typical fault fingerprint coding library based on the characteristics of electrical and non-electrical information of distribution equipment faults is constructed. A decision tree for equipment defect diagnosis based on information entropy is proposed., which realizes intelligent analysis of the status of distribution equipment, rapid diagnosis of defects and advance warning; 2. A comprehensive platform for rapid diagnosis of low-voltage outgoing lines based on the structural characteristics and fault characteristics of low-voltage power grids has been built, and a modular, combined, and live-mountable fault diagnosis device has been developed to achieve rapid diagnosis of low-voltage loop faults; 3. Proposed distribution transformer oil temperature monitoring and magnetron switch oil level monitoring technology based on surface acoustic wave technology, and developed an embedded installed integrated monitoring and protection device for oil temperature, oil level and pressure release, effectively realizing distribution transformer oil temperature. Comprehensive online monitoring of oil level solves the problems of low efficiency, untimely and inaccurate manual inspection; 4. A contact-type, self-energy-extracting and micro-power-consuming cable terminal head temperature measurement technical solution was designed, and a temperature measurement device integrated with the cable terminal head was developed to achieve effective temperature measurement. The project has obtained 3 authorized invention patents, 4 utility model patents, 3 software copyrights, and 8 papers have been published. At the scientific and technological achievements appraisal meeting organized by the China Electric Power Enterprises Federation, the expert group headed by Bai Xiaomin unanimously agreed that ldquo; key technologies and applications for intelligent sensing of distribution equipment rdquo; the overall results of the project have reached the international advanced level, among which the overall application of intelligent analysis of distribution equipment status, rapid diagnosis of defects and prior warning has reached the international leading level. The project results are very important for creating a ubiquitous power Internet of Things with comprehensive status perception, efficient information processing, and convenient and flexible application, improving the operating reliability of distribution equipment, optimizing the business environment, and building a world-class energy Internet company with excellent competitiveness. Promote effect. The project results have been applied in State Grid Shanghai City Electric Power Company, State Grid Zhejiang Jinhua Power Supply Company and other units, and achieved significant economic and social benefits. Among them, the project results played an important role in the power protection work of the first China International Import Expo, effectively ensuring the safe and reliable power supply of various venues and surrounding core areas.