Intelligent oil discharge supervision method and system based on oil discharge eight-step method

Abstract

The invention discloses an intelligent oil unloading supervision method and system based on an oil unloading eight-step method, and the method comprises the following steps: a superior platform inquires an oil unloading plan, and sends an oil receiving and unloading instruction to a comprehensive service management device if the oil unloading plan exists; the comprehensive service management equipment receives the oil receiving and unloading instruction and sends the oil receiving and unloading instruction to the AI video analysis equipment; and the AI video analysis equipment calls the video data of the high-definition camera for intelligent analysis. Related technologies such as video intelligent analysis and Internet of Things sensing are adopted, automatic supervision of oil receiving and unloading is achieved, the safety process management and control level is improved through man-machine intelligent interaction, key risk management and control measures are innovated, efficient lean management and whole-process field operation guidance are enabled, the oil receiving and unloading efficiency is improved, the operation process is optimized and simplified, and the oil receiving and unloading efficiency is improved. Load reduction in oil receiving and discharging links is achieved. According to the invention, through intelligent supervision of oil receiving and unloading, the efficiency of oil receiving and unloading safety production supervision can be greatly improved, and powerful support is provided for intelligent supervision and safety production of a gas station.

Description

Technical Field

[0001] The present invention relates to the field of video artificial intelligence technology, and in particular to an intelligent oil unloading supervision method and system based on an eight-step oil unloading method. Background Art

[0002] Nearly 90% of the "three violations" in the daily operation of gas stations occur in the oil loading and unloading process. The current "double confirmation" management mechanism is essentially a "one-to-one, person-to-person" on-site monitoring. At the same time, managers at all levels need to register and supervise various paper ledgers and conduct 24-hour video monitoring of the oil unloading site, which generates huge management costs, but various irregular operations still occur from time to time. The risks of petrochemical system gas stations are distributed all over the country, and the entire oil retail industry faces the same management pain points, mainly as follows: 1. The risks of oil loading and unloading are high and the frequency is high, and the responsibility for safe production is heavy; 2. The oil unloading process is complex and labor intensive, and prone to errors; 3. One-to-one supervision at all levels has low efficiency and insufficient coverage.

[0003] To solve the above problems, how to effectively supervise the identification of non-compliant operations in the oil unloading process, verify whether they are implemented in place, control non-compliant operations, correct them on-site through human-computer interaction, and simplify the employee oil unloading process based on the traditional eight-step oil unloading method, and realize intelligent monitoring of the "three violations" at gas stations has become a technical problem that people urgently need to solve. Summary of the invention

[0004] In view of the above technical problems in the related art, the present invention proposes an intelligent oil unloading supervision method and system based on the eight-step oil unloading method, which can overcome the above shortcomings of the prior art.

[0005] To achieve the above technical objectives, the technical solution of the present invention is implemented as follows: An intelligent oil unloading supervision method based on the eight-step oil unloading method comprises the following steps: S1 The upper platform inquires about the oil unloading plan. If there is an oil unloading plan, it sends the oil unloading instruction to the integrated service management equipment; S2 The integrated service management device receives the oil loading and unloading instruction and sends the oil loading and unloading instruction to the AI ​​video analysis device; The S3 AI video analysis device retrieves high-definition camera video data for intelligent analysis; The specific parsing steps are as follows: S31 analyzes intelligent scenarios: if an oil unloading truck is found parked during parking, the vehicle will enter the next analysis scenario, otherwise it will continue to detect parking. S32 detects enclosure layout, fire equipment placement and on-site monitoring. If the detection is normal, it will send the correct instructions to the upper-level platform for judgment; if an abnormality is detected, it will send an alarm instruction to the upper-level platform; The S33 integrated service management equipment detects the static grounding status through the IO terminal, monitors the oil stabilization process before and after unloading through sensor data, and sends correct instructions to the superior platform for analysis; The S34 superior platform makes judgments based on the received data and provides feedback on whether the oil unloading is safe.

[0006] Furthermore, the on-site maintenance work in step S23 includes the presence of staff and no intrusion of outsiders.

[0007] An intelligent oil unloading supervision system based on the eight-step oil unloading method, including a high-definition network camera, an integrated service management server and an AI video analysis server; The high-definition network camera is used to collect high-definition video data; The integrated service management server is used to obtain IoT data, obtain intelligent analysis data from the AI ​​video analysis server, and send the data to the upper-level platform; The AI ​​video analysis server is used to retrieve high-definition videos collected by high-definition network cameras, and perform intelligent analysis of parking, enclosure layout, fire-fighting equipment placement, and on-site monitoring based on the videos.

[0008] Furthermore, the high-definition network camera is a gun camera with a video resolution not less than 1080P and supports an IO input port.

[0009] Furthermore, the comprehensive service management server is a single server.

[0010] Furthermore, the AI ​​video analysis server is an embedded integrated edge-side intelligent analysis computing device with a computing power of not less than 32T.

[0011] Beneficial effects of the invention: The invention adopts video intelligent analysis and Internet of Things sensing and other related technologies to realize automatic supervision of oil loading and unloading, improve the level of safety process control through human-machine intelligent interaction, innovate key risk control measures, enable efficient lean management, provide full-process on-site operation guidance, improve oil loading and unloading efficiency, optimize and simplify the operation process, and reduce the burden of oil loading and unloading. The invention can greatly improve the efficiency of safety production supervision of oil loading and unloading by connecting to intelligent supervision of oil unloading, and provide strong support for realizing intelligent supervision and safe production of gas stations. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0013] Figure 1 It is a workflow diagram of the intelligent oil unloading supervision method based on the eight-step oil unloading method according to an embodiment of the present invention; Figure 2 It is a structural block diagram of an intelligent oil unloading monitoring system based on the eight-step oil unloading method according to an embodiment of the present invention. DETAILED DESCRIPTION

[0014] The following will be combined with the accompanying drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field belong to the scope of protection of the present invention.

[0015] like Figure 1 As shown, an intelligent oil unloading supervision method based on the eight-step oil unloading method according to an embodiment of the present invention includes the following steps: S1 The upper platform inquires about the oil unloading plan. If there is an oil unloading plan, it sends the oil unloading instruction to the integrated service management equipment; S2 The integrated service management device receives the oil loading and unloading instruction and sends the oil loading and unloading instruction to the AI ​​video analysis device; The S3 AI video analysis device retrieves high-definition camera video data for intelligent analysis; The specific parsing steps are as follows: S31 analyzes intelligent scenarios: if an oil unloading truck is found parked during parking, the vehicle will enter the next analysis scenario, otherwise it will continue to detect parking. S32 detects enclosure layout, fire equipment placement and on-site monitoring. If the detection is normal, it will send the correct instructions to the upper-level platform for judgment; if an abnormality is detected, it will send an alarm instruction to the upper-level platform; The S33 integrated service management equipment detects the static grounding status through the IO terminal, monitors the oil stabilization process before and after unloading through sensor data, and sends correct instructions to the superior platform for analysis; The S34 superior platform makes judgments based on the received data and provides feedback on whether the oil unloading is safe.

[0016] In the embodiment, the on-site maintenance work in step S23 includes that staff are present and no outsiders are found to break in.

[0017] like Figure 2 As shown, an intelligent oil unloading supervision system based on the eight-step oil unloading method includes a high-definition network camera, an integrated service management server and an AI video analysis server; The high-definition network camera is used to collect high-definition video data; The integrated service management server is used to obtain IoT data, obtain intelligent analysis data from the AI ​​video analysis server, and send the data to the upper-level platform; The AI ​​video analysis server is used to retrieve high-definition videos collected by high-definition network cameras, and perform intelligent analysis of parking, enclosure layout, fire-fighting equipment placement, and on-site monitoring based on the videos.

[0018] In the embodiment, the high-definition network camera is a gun camera with a video resolution not less than 1080P and supports an IO input port.

[0019] In the embodiment, the comprehensive service management server is a single server.

[0020] In the embodiment, the AI ​​video analysis server is an embedded integrated edge-side intelligent analysis computing device with a computing power of not less than 32T.

[0021] In order to facilitate understanding of the above technical solutions of the present invention, the above technical solutions of the present invention are described in detail below through specific usage methods.

[0022] In specific use, according to the intelligent oil unloading supervision method and system based on the eight-step oil unloading method described in the present invention, automatic supervision of oil unloading is realized based on mobile explosion-proof POS, video AI analysis and Internet of Things technology. It covers the following two types of supervision methods: 1. Through intelligent video analysis, supervision of vehicle introduction, enclosure layout, firefighting equipment placement, and on-site monitoring work; 2. Using Internet of Things monitoring to realize static grounding, oil stabilization before unloading, oil stabilization after unloading, etc.

[0023] To achieve the above purpose, Figure 2 As shown, the intelligent oil loading and unloading system provided by the present invention includes components such as high-definition cameras, AI video analysis equipment, and comprehensive service management equipment.

[0024] HD network camera: realizes HD video data collection, requires a gun camera, and fixed scene adjustment. The HD camera is characterized by a video resolution of not less than 1080P, a wide dynamic function, and supports IO input ports.

[0025] Integrated service management server: The management core of the system, which obtains IoT data, obtains AI video analysis server intelligent analysis data, and sends the data to the superior management platform. The integrated service management server is a single server with a network interface AI video analysis server: The computing center of the system performs intelligent analysis of videos on parking, enclosure layout, fire equipment placement, and on-site monitoring. The AI ​​video analysis server is an embedded integrated edge-side intelligent analysis computing device with a computing power of no less than 32T.

[0026] System initialization: After the system is powered on, each component first completes the power-on initialization work. After the integrated service management server is started, the system is automatically loaded to execute the IoT data reception and detection process. The AI ​​video analysis server automatically loads the intelligent algorithm and starts the algorithm analysis plan. The overall initialization time is 4 to 5 minutes.

[0027] System operation: After initialization, the AI ​​video analysis server starts parking, enclosure layout, fire equipment placement, and on-site monitoring scene analysis according to the oil loading and unloading plan, and sends the analysis results to the comprehensive service management server. At the same time, the comprehensive service management server detects static grounding, oil stabilization before unloading, and oil stabilization after unloading through the Internet of Things. The detected data is sent to the upper platform.

[0028] like Figure 1 As shown, the specific implementation steps are as follows: 1) The upper platform sends the oil loading and unloading instructions to the integrated service management equipment; 2) The integrated service management device sends instructions to the AI ​​video analysis device; 3) AI video analysis equipment retrieves high-definition camera video data for intelligent analysis; 4) First, analyze the intelligent scene: parking. If an oil unloading truck is found parked, enter the next analysis scene, otherwise continue to detect parking; 5) Continue to inspect enclosure layout, firefighting equipment placement, and on-site monitoring (staff and outsiders); 6) If the above intelligent detection is carried out in accordance with the regulations (the enclosure is set correctly, the fire-fighting equipment is placed correctly, the staff is present, and no outsiders are found to break in), send the correct command to the superior platform for judgment; if it is found that it is not carried out in accordance with the regulations (the enclosure is not set correctly or the fire-fighting equipment is not placed correctly or the staff is not present or outsiders are found to break in), send an alarm command to the superior platform; 7) During intelligent detection, the comprehensive service management equipment detects the static grounding status through the IO terminal and monitors the oil stabilization process before and after unloading through sensor data; 8) If the above monitoring is carried out in accordance with the regulations (the oil unloading process is in an electrostatic grounding state, and the oil stabilization before and after unloading is normal), send the correct instructions to the superior platform for analysis; 9) The superior platform will make judgments based on the received data and provide feedback on whether the oil unloading is safe.

[0029] In the present invention, the front-end camera is required to be a high-definition camera supporting functions such as wide dynamic range.

[0030] In summary, with the help of the above technical solution of the present invention, video intelligent analysis and related technologies such as Internet of Things sensors are adopted to realize automatic supervision of oil loading and unloading, improve the level of safety process control through human-machine intelligent interaction, innovate key risk control measures, enable efficient lean management, provide full-process on-site operation guidance, improve oil loading and unloading efficiency, optimize and simplify the operation process, and realize the reduction of the burden of oil loading and unloading. The present invention can greatly improve the efficiency of safety production supervision of oil loading and unloading through intelligent supervision of oil unloading, and provide strong support for realizing intelligent supervision and safe production of gas stations.

[0031] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. An intelligent oil unloading supervision method based on the eight-step oil unloading method, characterized in that: The steps include: S1 The upper platform inquires about the oil unloading plan. If there is an oil unloading plan, it sends the oil unloading instruction to the integrated service management equipment; S2 The integrated service management device receives the oil loading and unloading instruction and sends the oil loading and unloading instruction to the AI ​​video analysis device; The S3 AI video analysis device retrieves high-definition camera video data for intelligent analysis; The specific parsing steps are as follows: S31 analyzes intelligent scenarios: if an oil unloading truck is found parked during parking, the vehicle will enter the next analysis scenario, otherwise it will continue to detect parking. S32 detects enclosure layout, fire equipment placement and on-site monitoring. If the detection is normal, it will send the correct instructions to the upper-level platform for judgment; if an abnormality is detected, it will send an alarm instruction to the upper-level platform; The S33 integrated service management equipment detects the static grounding status through the IO terminal, monitors the oil stabilization process before and after unloading through sensor data, and sends correct instructions to the superior platform for analysis; The S34 superior platform makes judgments based on the received data and provides feedback on whether the oil unloading is safe.

2. The intelligent oil unloading supervision method based on the eight-step oil unloading method according to claim 1 is characterized in that: The on-site maintenance work in step S23 includes the presence of staff and no intrusion of outsiders.

3. An intelligent oil unloading supervision system based on the eight-step oil unloading method, characterized in that: Includes high-definition network cameras, integrated service management servers, and AI video analysis servers; The high-definition network camera is used to collect high-definition video data; The integrated service management server is used to obtain IoT data, obtain intelligent analysis data from the AI ​​video analysis server, and send the data to the upper-level platform; The AI ​​video analysis server is used to retrieve high-definition videos collected by high-definition network cameras, and perform intelligent analysis of parking, enclosure layout, fire-fighting equipment placement, and on-site monitoring based on the videos.

4. The intelligent oil unloading supervision system based on the eight-step oil unloading method according to claim 1 is characterized in that: The high-definition network camera is a gun camera with a video resolution of not less than 1080P and supports an IO input port.

5. The intelligent oil unloading supervision system based on the eight-step oil unloading method according to claim 1 is characterized in that: The comprehensive service management server is a single server.

6. The intelligent oil unloading supervision system based on the eight-step oil unloading method according to claim 1 is characterized in that: The AI ​​video analysis server is an embedded integrated edge-side intelligent analysis computing device with a computing power of no less than 32T.

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