Currently, inspection at domestic oil and gas stations is generally in a transition stage where "manual work is dominant and equipment plays a supporting role". As safety management requirements for oil and gas exploitation, refining and chemical production, and storage & transportation continue to escalate, the shortcomings of traditional inspection modes have become a core obstacle to intelligent transformation.
Combined with the actual operation conditions of oil and gas stations in Jinan, Shandong Province and surrounding areas, there are five core pain points that directly affect station safety and operational efficiency:
Oil and gas stations cover multiple scenarios such as oil storage tank areas, pipe galleries, booster stations, and valve groups. Some areas have extreme working conditions including -30℃ severe cold, 60℃ high temperature, strong corrosion, and high dust. Ordinary inspection equipment cannot operate stably for a long time. For some old stations, the steel structure pipe galleries and narrow operation rooms cannot meet the passage requirements of conventional inspection robots.
Under the traditional inspection mode, data collected by robots such as instrument readings, gas concentration, temperature and pressure are scattered in different systems, resulting in serious data island problems. These data cannot be directly connected to the existing DCS and MES safety management platforms of the stations, and a large amount of data requires manual secondary entry, which is not only time-consuming but also prone to human errors.
Most traditional inspection equipment can only complete basic data collection. All AI identification and anomaly judgment tasks need to be uploaded to the cloud for processing. In some remote stations with signal occlusion, the data transmission latency exceeds 3 seconds, making it impossible to realize real-time warning of anomalies such as instrument leakage and equipment overheating.
Traditional solutions require the simultaneous procurement of multiple independent devices such as ARM industrial PCs, gateways, and PLC controllers. The supporting hardware cost for a single inspection robot exceeds 80,000 yuan, the protocol joint debugging cycle between different devices lasts up to 2 weeks, and the annual subsequent equipment maintenance cost exceeds 120,000 yuan.
Under the traditional manual inspection mode, the inspection frequency in high-risk areas can only reach 2 times per day, and 7×24-hour uninterrupted monitoring cannot be realized. Historical data shows that nearly 30% of safety hazards in oil and gas stations occur during the gap periods of manual inspection, which easily leads to safety accidents.
This solution takes the EG628 intelligent edge control core as the carrier, replaces the traditional multi-device combination mode, and builds a new oil and gas inspection architecture of "local real-time processing + cloud collaborative management", which fully covers all core requirements of station inspection in the whole process:
Each oil and gas inspection robot is equipped with one EG628 as the core control unit. Using its built-in RK3562J industrial-grade 4-core processor and 1TOPS AI computing power, it directly connects to the motion control module of the robot body, and simultaneously accesses 12 types of inspection peripherals such as infrared thermal imagers, combustible gas detectors, sound sensors, and high-definition cameras. No additional independent gateways or ARM industrial PCs are required, and a single device can complete all data collection and local processing tasks. Relying on the modular IO expansion design of EG628, it can flexibly adapt to different types of sensor interfaces such as digital, analog, and serial ports. The pre-installed library of more than 100 industrial protocols can directly connect to PLC equipment of existing brands such as Siemens and Mitsubishi in the station, no additional protocol converter development is required.
In the WukongEdge edge intelligent platform built into EG628, a lightweight exclusive AI model for oil and gas inspection is deployed to realize three core functions:
① Local real-time identification: It can automatically identify instrument readings, judge valve status, and detect leakage defects without uploading data to the cloud, and the identification response latency is controlled within 500 milliseconds.
② Autonomous anomaly warning: When it detects that the concentration of combustible gas exceeds the standard or the equipment temperature rises abnormally, it directly triggers an acousto-optic alarm locally, and simultaneously pushes warning information to the station management platform. The warning response speed is 80% higher than that of the traditional cloud mode.
③ Data preprocessing: It filters redundant data locally, and only uploads valid feature data to the cloud, reducing the overall cloud transmission traffic of the station by 70%.
Relying on the multi-network convergence capability of EG628, dual-link redundant communication with 5G/4G and Ethernet is configured. When the main link signal is interrupted, the device automatically switches to the backup link to ensure that inspection data is not interrupted or lost.
At the same time, through the built-in cloud-edge collaboration capability of EG628, all inspection data is synchronized to the existing safety management platform of the station, realizing unified visual display of inspection data, equipment operation data, and environmental monitoring data. Managers can view the inspection status of the entire station in real time through mobile phones and computers, without the need to build a separate inspection data management system.
Using the wide-temperature operation characteristics of EG628 itself, after being modified with an explosion-proof shell, it can be directly deployed in high-risk explosion-proof areas such as Zone 0 and Zone 1. The device's built-in three-level surge protection, three-level electrostatic protection and system watchdog mechanism can operate stably under complex working conditions in oil and gas stations with strong electromagnetic interference and frequent power-off restarts, and the annual fault-free operation duration exceeds 8700 hours.
After 6 months of pilot operation at an oil and gas booster station in Shandong, all indicators of this solution have reached the industry-leading level, realizing triple improvements in safety, efficiency and cost:
At the safety management level, the inspection coverage rate of high-risk areas in the station has increased from 65% to 100%, realizing 7×24-hour uninterrupted inspection. The abnormal warning response speed has been shortened from the original 3 minutes to 1 second. During the pilot period, the system warned of bearing overheating hazards of 3 booster pumps 15 days in advance, avoiding unplanned shutdowns and reducing direct economic losses by more than 1.8 million yuan.
At the efficiency improvement level, the manual inspection frequency has been reduced from 2 times a day to 1 time a week, the manual input for single-station inspection has been reduced by 75%, and the accuracy rate of inspection data has increased from 90% to 99.5%, completely eliminating human errors in manual readings. The overall work efficiency of station inspection has increased by 3 times.
At the cost control level, the supporting hardware procurement cost of a single inspection robot has been reduced from 82,000 yuan to 21,000 yuan, the overall deployment cycle has been shortened from the original 2 weeks to 4 hours, the annual inspection equipment operation and maintenance cost of the station has been reduced from 120,000 yuan to 48,000 yuan, the annual operation and maintenance cost has decreased by 60%, and it is expected to recover all project investment within 2 years.
Through the highly integrated features of EG628, this solution breaks the bottlenecks of computing power, communication and data collaboration in the traditional oil and gas inspection mode, and provides a cost-effective and highly reliable implementation path for the intelligent inspection transformation of oil and gas stations.
