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The large number of auxiliary devices increases the O&M burden of substations, posing significant challenges for O&M personnel.
The information from auxiliary devices is fragmented and lacks an integrated platform, which affects the timeliness and accuracy of decision-making.
The existing auxiliary equipment systems are isolated, lacking coordination mechanisms, which impacts the overall O&M efficiency.
There is a lack of an integrated intelligent O&M solution, and modern technologies have not been fully utilized to enhance the level of intelligent management.
The system is designed to efficiently integrate the scattered auxiliary equipment subsystems in substations, addressing the issues of diverse equipment types, dispersed information, and isolated systems. The system includes a service gateway machine, a comprehensive application host, and front-end intelligent sensors. It features multiple functions such as online monitoring, safety protection, and dynamic environment monitoring, supporting a three-tier system architecture for substations, O&M teams, and centralized control stations. The system's application provides strong support for the digital transformation of power grid enterprises and the construction of new power systems.
Full perception
The system's advantage lies in comprehensive equipment awareness, intelligent monitoring of key equipment, and intelligent identification of multiple types of defects, making the equipment status clear at a glance.
Auxiliary remote control
The system supports remote control, centralized O&M, and intelligent monitoring, with a mobile application module, enabling efficient and comprehensive management.
Digitally and intelligently empowering
By combining digital twins and AI, the system enhances cloud-edge collaboration capabilities, enabling defect prediction and diagnosis of equipment and improving decision-making accuracy and reliability.
Safe and efficient
The system's safety relies on standardized design and autonomous controllable equipment. Efficiency stems from convenient operation and centralized management, ensuring reliability and ease of use.
The auxiliary equipment monitoring system, based on technologies such as IoT, big data, intelligent sensing, artificial intelligence, and 3D modeling, integrates and standardizes the resources of various isolated and scattered auxiliary control subsystems. This achieves optimized system resource allocation, information sharing, and seamless business integration between systems, addressing the complexities of substation auxiliary equipment, scattered operational information, and lack of coordination. It enhances the intelligent O&M of substations and supports the construction of new power systems.
The intelligent auxiliary monitoring system focuses on precise management of auxiliary equipment, and uses IoT, AI, and big data analysis to achieve real-time monitoring of equipment data and in-depth diagnostic analysis. The system provides deep insight into the status of auxiliary equipment, including fire monitoring, safety protection, power environment, and online monitoring subsystems. By remotely controlling and managing equipment, it enhances fault prediction and preventive decision-making capabilities, achieving intelligent O&M and reducing personnel pressure while improving efficiency and safety.
The system integrates ubiquitous power IoT technology, with the intelligent safety helmet as the core device. It connects upward via 5G/WIFI/WAPI to cloud service software, supporting business data interaction, constructing BeiDou differential base stations, and providing centimeter-level precise positioning for personnel, enabling real-time monitoring, remote work permissions, and supervision; it connects downward via Bluetooth/Lora to intelligent wristbands, intelligent safety belts, intelligent glasses, and other wearable devices to transmit data, status, and instructions.
By collecting the voltage and internal resistance of each battery cell and its changing trends, combined with advanced failure judgment models, the system can accurately assess battery performance and provide warnings, achieving online balanced maintenance of batteries and significantly extending battery life.
The online temperature monitoring system for power equipment integrates cutting-edge technologies such as CT power induction, IoT, and edge computing to record the temperature of power equipment and its heat-prone components in real-time, enabling comprehensive temperature monitoring and analysis.
The digital twin platform integrates new technologies such as 3D, AI, and big data, utilizing laser point clouds for precise real-scene modeling. It maps physical entities to digital models, creating a one-to-one replica of on-site conditions across industries. By matching multi-data sources with real-scene models, it constructs a virtual and real "unified map," enabling 3D presentation of primary and auxiliary equipment monitoring, remote intelligent inspections, stereoscopic anti-misoperation, and intelligent campuses, providing enterprises with a unified, efficient, and intelligent digital twin solution to drive digital transformation across industries.
refined remote supervision can be achieved, enabling remote maintenance and enhancing substation O&M management levels.
The intelligent warehouse management solution focuses on controlling tools and equipment , access control, video surveillance, and environmental factors within the safety tools and equipment warehouse.
Wind turbines often face issues such as tower shaking and uneven foundation settlement during operation. To improve maintenance efficiency and ensure stable operation of the turbine, the solution adopts the method of installing tilt sensors at the top of the tower and base, and deploying static level meters to monitor the radial shaking and tilting of the tower in real time. The system provides early warnings and tower health assessments by analyzing collected data, and detects and addresses potential safety issues in a timely manner by using the real-time 3D simulation and an early warning system.
The system can monitor the wear status of the equipment in real-time by tracking key indicators such as moisture content, viscosity, and dielectric constant of lubricating oil. In addition, an intelligent fine filtration module is connected in parallel in the oil circuit circulation unit. When abnormal oil indicators are detected, the module automatically starts to filter the lubricating oil of the gearbox, removing impurities from the oil and preventing equipment failures, achieving perfect linkage between monitoring and diagnosis, greatly avoiding unplanned downtime and extending the equipment's lifespan.
Based on real-time monitoring data, 3D visualization, and intelligent features supported by AI and IoT technologies, the system comprehensively senses and intelligently controls multi-dimensional information such as equipment, environment, and personnel in distribution substations and transformer areas. It identifies potential faults and abnormal situations, combining human, physical, and technical defenses. It enhances the safety and reliability of distribution substations and transformer areas, reduces manual inspection and maintenance costs, improves response speed, and provides foundational support for the intelligent management of distribution networks.