Products
Solutions
Traditional manual inspection methods require a large workforce to regularly inspect equipment on-site at substations, leading to high labor costs and low efficiency.
With numerous substations spread over wide areas, it is difficult to monitor the operational status and equipment information of all sites in real-time under traditional management models.
Manual inspections are influenced by personal skill levels, fatigue, responsibility, and weather conditions, potentially leading to missed inspections or misjudgments.
In the event of emergencies involving operating equipment or on-site personnel, manual inspections often cannot quickly locate and rectify the fault.
By deploying various intelligent devices such as sensors, high-definition cameras, infrared thermography, robots, and drones, the system collects critical parameters like the temperature, vibration, sound signature, meter readings, and environment of electrical equipment in real-time. Through big data analysis and AI algorithms, it conducts in-depth analysis of the monitoring data, achieving fault warnings, status assessments, and lifespan predictions. It generates visual reports, enhancing substation O&M efficiency and management levels, and strengthens the safety and stability of power grid operations.
Ensuring inspection quality
Machines replace humans to achieve all-round, no-blind-spot inspections from ground, air, and space, accurately collecting equipment operating parameters to ensure high-quality inspection results.
Improving inspection efficiency
This increases inspection efficiency, reduces the time required for each inspection, saves travel time for O&M personnel, and enhances overall work effectiveness.
Enhancing response speed
It supports on-site equipment status analysis and intelligent linkage functions, allowing real-time remote monitoring of equipment operating conditions and improving emergency response speed.
Strengthening monitoring intensity
The system provides 24/7 comprehensive remote monitoring, enabling real-time analysis of equipment status. It actively sends alarms in the event of abnormalities, ensuring the equipment remains controllable and under supervision at all times.
With intelligent analysis and 3D visualization, the system provides innovative technical support for the safe and stable operation of infrastructure in sectors like power grids and petrochemicals, driving substation, distribution station, and transmission line operations toward intelligence and unmanned management. Through intelligent analysis and 3D visualization, the system provides innovative technical support for the safe and stable operation of critical infrastructure in industries such as power grids and petrochemicals. It drives key areas, including substations, distribution stations, and transmission lines, toward intelligent and unmanned operations.
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.
Utilizing image recognition algorithms combined with feature extraction, data augmentation, and model fusion technologies, the system automatically and intelligently detects the open/close status of the disconnector, precisely identifying four states: open in place, close in place, abnormal opening, and abnormal closing. These states, combined with traditional auxiliary contacts, form a "multi-source confirmation" criterion to prevent incomplete disconnector operations, ensuring safe disconnector status transitions during one-click sequence control operations.
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.
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.
By deploying various intelligent devices such as sensors, HD cameras, infrared thermal imagers, robots, and drones, the system collects real-time key parameters of electrical equipment, including temperature, vibration, sound patterns, meter readings, and environmental data. Through big data analysis and AI algorithms, the monitoring data is deeply mined and intelligently analyzed to enable functions like fault prediction, condition assessment, and life expectancy forecasting. The system generates visual reports, improving the efficiency and management of petrochemical electrical O&M while enhancing the safety and stability of petrochemical equipment operations.