Petroleum refining safety monitoring system
By combining the appearance data of storage equipment and environmental information, the risk coefficient is calculated and real-time analysis is carried out, the problem of inaccurate leakage risk assessment in traditional oil refining safety monitoring systems is solved, and accurate assessment and early warning of the leakage risk of storage equipment is achieved, thereby avoiding potential accidents.
Patent Information
- Application Number
- CN202510413344.3
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-04-03
- Publication Date
- 2025-07-11
- Estimated Expiration
- Not applicable · inactive patent
AI Technical Summary
When evaluating the risk of leakage of storage equipment, traditional oil refining safety monitoring systems have problems of insufficient accuracy, resulting in potential leakage accidents.
Combined with the video surveillance module, data acquisition unit, equipment evaluation module, risk assessment module, data analysis module and early warning module, the risk coefficient is calculated by collecting the appearance data and environmental information of the storage device, and real-time analysis and early warning are carried out to improve the accuracy of leakage risk assessment.
Through diversified data support, the accuracy of storage equipment leakage risk assessment is improved, and potential leakage risks can be identified in a timely manner and warning can be avoided to avoid accidents.
Smart Images
Figure CN120295239A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the technical field of petroleum processing, and specifically to a safety monitoring system for petroleum refining. Background Art
[0002] The safety monitoring system for petroleum refining is an essential part of the petroleum industry. It utilizes advanced sensor technology, automation control technology, and information technology to monitor and control various key parameters during petroleum refining in real time to ensure the safe, stable, and efficient operation of the production process.
[0003] After the start of petroleum refining, since petroleum contains corrosive impurities such as sulfides, chlorides, and nitrides before refining, when storage equipment is in long-term contact with corrosive media, it is prone to corrosion and fatigue damage, resulting in leakage accidents. To avoid this situation, traditional safety monitoring systems for petroleum refining monitor the overall structure and integrity of storage equipment to identify possible physical damage and corrosion marks during long-term use or improper operation of storage equipment, and evaluate the storage risks during the refining process based on this data, thus avoiding the occurrence of petroleum leakage caused by damage to storage equipment.
[0004] Traditional safety monitoring systems for petroleum refining evaluate by combining the physical damage and corrosion marks of storage equipment. This data can reflect the integrity of the current storage equipment. However, the corrosion and fatigue damage of storage equipment are affected by environmental factors. Therefore, evaluating the leakage risk of storage equipment only based on the physical damage and corrosion marks of storage equipment may result in errors in the evaluation results, reducing the accuracy of the evaluation results of the leakage risk of storage equipment, and thus leading to the occurrence of petroleum leakage accidents. Summary of the Invention
[0005] The purpose of the present invention is to provide a safety monitoring system for petroleum refining to solve the following technical problems: How to improve the accuracy of the evaluation results of the leakage risk of storage equipment.
[0006] The purpose of the present invention can be achieved by the following technical solutions: A safety monitoring system for petroleum refining, the system includes: A video monitoring module, including a video monitoring processing device and a data acquisition unit, the video monitoring processing device is used to collect the appearance data of different storage equipment before the start of petroleum refining operations; A data acquisition unit, used to collect environmental information data at different time points after the start of petroleum refining; An equipment evaluation module, used to evaluate the appearance damage of different storage equipment on the same day by combining the appearance data of different storage equipment before the start of petroleum refining operations; A risk assessment module, which is used to combine the environmental information data collected by the data acquisition unit with the evaluation results of the equipment evaluation module, calculate the risk coefficients of different storage devices at different time points, and evaluate the leakage risks of different storage devices at different time points based on this data; A data analysis module, which is used to analyze the risk change situations of different storage devices at different time points by combining the real-time risk coefficients calculated by the risk assessment module; A risk prediction module, which is used to predict the future leakage risks of different storage devices by combining the analysis results of the data analysis module; An early warning module, which is used to decide whether to give an early warning by combining the analysis results of the equipment evaluation module, the risk assessment module and the risk prediction module respectively.
[0007] Further, the video monitoring and processing device includes a camera and an identification module. The camera is used to capture the appearance images of different storage devices, and the identification module identifies and records the required features in the appearance images captured by the camera, including the number of damage points, the corrosion area, the oil stain area and the deformation area on the surface of the storage device.
[0008] Further, the environmental information data collected by the data acquisition unit includes the environmental temperature and the environmental pressure value.
[0009] Further, the evaluation process of the equipment evaluation module includes: Through the formula Calculate the appearance damage coefficient of the a-th storage device before the start of the oil refining operation ; Where is the corrosion area on the surface of the a-th storage device before the start of the oil refining operation, is the oil stain area on the surface of the a-th storage device before the start of the oil refining operation, is the deformation area on the surface of the a-th storage device before the start of the oil refining operation, is the preset damage area, is the number of damage points on the surface of the a-th storage device, is the preset number of damage points, , and are weight coefficients, is the total number of maintenance times of the a-th storage device, is the standard value of is the maintenance frequency of the a-th storage device, is the preset maintenance frequency, is the service life impact coefficient of the a-th storage device.
[0010] Further, the evaluation process of the device evaluation module further includes: By comparing the appearance damage coefficient of the a-th storage device before the start of the oil refining operation with the preset appearance damage coefficient threshold for comparison; If , the system determines that the a-th storage device has a problem of insufficient structural strength, which will increase the risk of leakage during subsequent oil refining operations and issue a warning; If , the system determines that the structural strength of the a-th storage device is high and will not increase the risk of leakage during subsequent oil refining operations, and further analyzes in combination with the environmental information data.
[0011] Further, the evaluation process of the risk assessment module includes: By using the formula to calculate the risk coefficient of the a-th storage device at the i-th time point after the start of the oil refining operation ; where i is any data collection time point after the start of the oil refining operation, is the total number of data collections at the i-th time point after the start of the oil refining operation, is the environmental temperature at the i-th time point after the start of the oil refining operation, is the preset environmental temperature, is all average value, is the environmental pressure value at the i-th time point after the start of the oil refining operation, is the preset environmental pressure value, is standard value, is a defined function. If , then let , otherwise, let .
[0012] Further, the evaluation process of the risk assessment module includes: By comparing the risk coefficient of the a-th storage device at the i-th time point after the start of the oil refining operation with the preset risk coefficient threshold range for comparison; If , the system determines that the risk coefficient of the a-th storage device at this time point is small, indicating that the a-th storage device has high safety and a low probability of oil leakage, and estimates the future leakage risk of the a-th storage device; If , the system determines that the risk coefficient of the a-th storage device at this time point is high, indicating that the a-th storage device has low safety and a high probability of oil leakage, and issues a warning in a timely manner through the warning module.
[0013] Further, the estimation process of the risk estimation module includes: Based on the risk coefficients of the a-th storage device at different time points obtained by the risk assessment module, establish a risk coefficient change curve of the a-th storage device over time ; And through the formula Calculate the change amount of the risk coefficient of the a-th storage device at the i-th time point after the start of the oil refining operation ; Among them, is the first evaluation time point after the start of the oil refining operation, the i-th evaluation time point after the start of the oil refining operation, is all the average value of.
[0014] Further, the estimation process of the risk estimation module also includes: By assigning a value to the change amount of the risk coefficient of the a-th storage device at the i-th time point after the start of the oil refining operation to generate a change amount influence value of the a-th storage device that is between 1 and 2 and increases as the change amount of the risk coefficient increases; Among them, the change amount of the risk coefficient of the a-th storage device at the i-th time point after the start of the oil refining operation the corresponding change amount influence value of the a-th storage device is set as .
[0015] Further, the estimation process of the risk estimation module also includes: Through the formula Calculate the predicted future risk index of the a-th storage device at the i-th time point after the start of the oil refining operation .
[0016] Further, the estimation process of the risk estimation module also includes: By comparing the predicted future risk index of the a-th storage device at the i-th time point after the start of the oil refining operation with the preset future risk index threshold Perform comparison; If , the system determines that the future leakage risk of the a-th storage device is high and issues a warning through the warning module; If , the system determines that the future leakage risk of the a-th storage device is low and does not issue a warning.
[0017] Furthermore, the warning process of the warning module includes: When it is determined that a warning needs to be issued, first label the risk device and the risk type, and push the labeling information and the warning information to the background management system.
[0018] Advantages of the present invention: (1) By combining the appearance data of different storage devices before the start of oil refining operations and the environmental information data at different time points after the start of oil refining, the present invention can evaluate the appearance damage of different storage devices and the leakage risk at different time points. This data can reflect the leakage risk of the storage device in two states before and after the start of oil refining operations, thereby improving the accuracy of the evaluation results of the leakage risk of the storage device. Finally, through the risk prediction module, the future leakage risk of different storage devices can be predicted, and potential leakage risks that may occur in the future can be identified in advance to prevent potential leakage incidents.
[0019] (2) By comparing the appearance damage coefficient of the a-th storage device before the start of oil refining operations with the preset appearance damage coefficient threshold , through this comparison method, an accurate judgment can be made on whether the a-th storage device has a problem of insufficient structural strength, and further judge whether it will increase the leakage risk during subsequent oil refining operations, thereby making a preliminary evaluation of the leakage risk of the storage device, ensuring that the storage devices for subsequent oil refining operations do not have problems of insufficient structural strength, and avoiding oil leakage accidents.
[0020] (3) By comparing the risk coefficient of the a-th storage device at the i-th time point after the start of oil refining operations with the preset risk coefficient threshold range , since this data is calculated based on the environmental information data combined with the appearance damage coefficient data of the a-th storage device before the start of oil refining operations, the diversified data support can ensure the reliability and accuracy of this data. Therefore, through this comparison method, an accurate judgment can be made on the safety level of the a-th storage device according to the size of the risk coefficient of the a-th storage device at this time point, thereby improving the accuracy of the evaluation results of the leakage risk of the storage device.
[0021] (4) After the start of the oil refining operation, the future risk index predicted by the a-th storage device at the i-th time point in the present invention is compared with the preset future risk index threshold Through such a comparison method, an accurate judgment can be made on the future leakage risk level of the a-th storage device. By setting like this, potential leakage events can be identified and measures can be taken in advance, and through real-time monitoring of this data, potential leakage risks can be detected and warned in time, further avoiding the occurrence of leakage accidents. BRIEF DESCRIPTION OF THE DRAWINGS
[0022] The present invention will be further described below with reference to the accompanying drawings.
[0023] Figure 1 is a schematic block diagram of an oil refining safety monitoring system in the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS
[0024] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without making creative efforts shall fall within the protection scope of the present invention.
[0025] Please refer to Figure 1 As shown, in one embodiment, the present application provides an oil refining safety monitoring system, and the system includes: A video monitoring module, including a video monitoring processing device and a data acquisition unit, where the video monitoring processing device is used to collect the appearance data of different storage devices before the start of the oil refining operation; A data acquisition unit, which is used to collect environmental information data at different time points after the start of the oil refining; An equipment evaluation module, which is used to evaluate the appearance damage condition of different storage devices on the same day by combining the appearance data of different storage devices before the start of the oil refining operation; A risk evaluation module, which is used to calculate the risk coefficients of different storage devices at different time points by combining the environmental information data collected by the data acquisition unit and the evaluation results of the equipment evaluation module, and evaluate the leakage risks of different storage devices at different time points according to this data; A data analysis module, which is used to analyze the risk change conditions of different storage devices at different time points by combining the real-time risk coefficients calculated by the risk evaluation module; A risk prediction module, which is used to predict the future leakage risks of different storage devices by combining the analysis results of the data analysis module; An early warning module, which is used to decide whether to give an early warning by combining the analysis results of the equipment evaluation module, the risk assessment module and the risk prediction module respectively; Through the above technical solution, this embodiment provides a video monitoring module. The appearance data of different storage devices before the start of the oil refining operation and the environmental information data at different time points after the start of the oil refining can be collected respectively by the video monitoring processing device and the data collection unit. Before the start of the oil refining operation, first, the equipment prediction module combines the appearance data of different storage devices before the start of the oil refining operation to evaluate the appearance damage conditions of different storage devices on the same day, and gives an early warning through the early warning module when it is judged that the appearance damage condition is poor, so as to ensure that all storage devices carry out the oil refining operation when there are no defects in the appearance. After that, after the start of the refining operation, the risk assessment module combines the environmental information data collected by the data collection unit and the evaluation results of the equipment evaluation module to calculate the risk coefficients of different storage devices at different time points, and evaluates the leakage risks of different storage devices at different time points according to this data, and gives an early warning through the early warning module in time when it is judged that the leakage risk is large, and timely repairs the storage devices. Finally, the data analysis module combines the real-time risk coefficients calculated by the risk assessment module to analyze the risk change conditions of different storage devices at different time points, and then the risk prediction module can predict the future leakage risks of different storage devices by combining the analysis results of the data analysis module; By combining the appearance data of different storage devices before the start of the oil refining operation and the environmental information data at different time points after the start of the oil refining, this system can evaluate the appearance damage conditions of different storage devices and the leakage risks at different time points. This data can reflect the leakage risks of the storage devices in two states before and after the start of the oil refining operation, thereby improving the accuracy of the evaluation results of the storage device leakage risks. Finally, the risk prediction module predicts the future leakage risks of different storage devices, which can identify potential leakage risks in advance to prevent potential leakage events from occurring.
[0026] The video monitoring processing device includes a camera and an identification module. The camera is used to capture the appearance images of different storage devices, and the identification module identifies and records the required features in the appearance images captured by the camera, including the number of damage points, the corrosion area, the oil stain area and the deformation area on the surface of the storage device; Through the above technical solution, this example provides a video surveillance processing device, including a camera and an identification module. By combining the camera and the identification module, the required features in the appearances of different storage devices can be identified and recorded, including the number of damage points, corrosion area, oil stain area, and deformation area on the surface of the storage device. By combining the appearance data of different storage devices, the appearance damage condition of the storage device can be evaluated, thereby preliminarily evaluating the leakage risk of the storage device, and this data can be used as basic data for further evaluating the leakage risk of the storage device during the oil refining process in combination with environmental data in the subsequent stage. Diversified data support can improve the accuracy of the subsequent evaluation result of the leakage risk of the storage device, thereby avoiding the occurrence of leakage accidents.
[0027] The environmental information data collected by the data collection unit includes environmental temperature and environmental pressure values; Through the above technical solution, this example provides the environmental information data collected by the data collection unit, including environmental temperature and environmental pressure values. During the oil refining process, the temperature and pressure values in the plant will gradually rise. During this process, the temperature and pressure values in the environment will affect the temperature of the oil in the storage device and the pressure in the storage device. As the environmental temperature rises, the temperature of the oil in the storage device will gradually rise. During this process, the oil medium expands due to heat, increasing in volume, thereby generating a greater pressure in the closed device. And the increase in temperature will also reduce the viscosity of the oil, enhancing its fluidity, thereby affecting the pressure distribution inside the storage device and further increasing the leakage risk of the storage device. And as the environmental pressure rises, it will also increase the temperature inside the storage device. Therefore, by combining the environmental information data with the appearance data of different storage devices, diversified data can improve the sensitivity of the evaluation result, thereby further improving the accuracy of the evaluation result of the leakage risk of the storage device.
[0028] The evaluation process of the device evaluation module includes: Through the formula Calculate the appearance damage coefficient of the a-th storage device before the start of the oil refining operation ; Among them, is the corrosion area on the surface of the a-th storage device before the start of the oil refining operation, is the oil stain area on the surface of the a-th storage device before the start of the oil refining operation, is the deformation area on the surface of the a-th storage device before the start of the oil refining operation, is the preset damage area, is the number of damage points on the surface of the a-th storage device, is the preset number of damage points, 、 and is the weight coefficient, which is set by empirical fitting. is the total number of maintenance times of the a-th storage device. is the standard value of, and the above standard value can be selected and set according to the allowable error in the empirical data. is the maintenance frequency of the a-th storage device. is the preset maintenance frequency. is the service life impact coefficient of the a-th storage device; Through the above technical solution, this example provides the appearance damage coefficient of the a-th storage device before the start of oil refining operations , which can be obtained by calculation. Obviously, when the oil stain area, corrosion area and deformation area on the surface of the a-th storage device before the start of oil refining operations are larger, the number of damage points and the total number of maintenance times are more and the maintenance frequency is higher, then the appearance damage coefficient of the a-th storage device before the start of oil refining operations is higher, indicating that there are relatively serious damages to the appearance of the a-th storage device, and there will be a risk of leakage after long-term use. On the contrary, when the oil stain area, corrosion area and deformation area on the surface of the a-th storage device before the start of oil refining operations are smaller, the number of damage points and the total number of maintenance times are less and the maintenance frequency is lower, then the appearance damage coefficient of the a-th storage device before the start of oil refining operations is lower, indicating that the appearance integrity of the a-th storage device is relatively high, and there will be no risk of leakage even after long-term use. Through this calculation method, accurate data can be provided for subsequent judgment of the appearance damage of the storage device, thereby improving the accuracy of the judgment result and making a preliminary judgment on the leakage risk of the storage device.
[0029] The evaluation process of the device evaluation module also includes: By comparing the appearance damage coefficient of the a-th storage device before the start of oil refining operations with the preset appearance damage coefficient threshold ; If , the system judges that the a-th storage device has a problem of insufficient structural strength, which will increase the risk of leakage during subsequent oil refining operations and give an early warning; If , the system judges that the structural strength of the a-th storage device is high and will not increase the risk of leakage during subsequent oil refining operations, and further analyzes in combination with the environmental information data; Through the above technical solution, this implementation passes the appearance damage coefficient Compare with the preset appearance damage coefficient threshold Through this comparison method, it is possible to accurately judge whether there is a problem of insufficient structural strength in the a-th storage device, and further judge whether it will increase the risk of leakage during subsequent oil refining operations, so as to make a preliminary assessment of the leakage risk of the storage device, ensuring that all storage devices for subsequent oil refining operations do not have problems with insufficient structural strength and avoiding oil leakage accidents.
[0030] The evaluation process of the risk assessment module includes: Calculate the risk coefficient of the a-th storage device at the i-th time point after the start of oil refining operations through the formula ; where i is any data collection time point after the start of oil refining operations, is the total number of data collections at the i-th time point after the start of oil refining operations, is the ambient temperature at the i-th time point after the start of oil refining operations, is the preset ambient temperature, is all of the average value, is the ambient pressure value at the i-th time point after the start of oil refining operations, is the preset ambient pressure value, is of the standard value, is a defined function, if , then let , otherwise, let ; Through the above technical solution, this example provides the risk coefficient of the a-th storage device at the i-th time point after the start of oil refining operations, which can be calculated through the formula . Obviously, when the ambient temperature and ambient pressure value of the a-th storage device at the i-th time point after the start of oil refining operations are higher, and the volatility of the environment is greater, then the risk coefficient of the a-th storage device at the i-th time point after the start of oil refining operations is greater, indicating that in the current working environment, the storage device has a greater leakage risk. On the contrary, when the ambient temperature and ambient pressure value of the a-th storage device at the i-th time point after the start of oil refining operations are lower, and the volatility of the environment is smaller, then the risk coefficient The smaller it is, it indicates that in the current working environment, the leakage risk of the storage device is very small. Through this calculation method, the calculation result is based on the environmental information data combined with the appearance damage coefficient of the a-th storage device before the start of the oil refining operation The data is obtained. Diversified data can improve the accuracy of the calculation result, thereby providing accurate data for the subsequent assessment of the leakage risk of the storage device to improve the accuracy of the assessment result of the leakage risk of the storage device
[0031] The evaluation process of the risk assessment module includes: By comparing the risk coefficient of the a-th storage device at the i-th time point after the start of the oil refining operation with the preset risk coefficient threshold range for comparison; If , the system determines that the risk coefficient of the a-th storage device at this time point is small, indicating that the a-th storage device has high safety and a low probability of oil leakage, and estimates the future leakage risk of the a-th storage device If , the system determines that the risk coefficient of the a-th storage device at this time point is high, indicating that the a-th storage device has low safety and a high probability of oil leakage, and issues a warning in a timely manner through the warning module Through the above technical solution, in this embodiment, by comparing the risk coefficient of the a-th storage device at the i-th time point after the start of the oil refining operation with the preset risk coefficient threshold range for comparison. Since this data is calculated based on the environmental information data combined with the appearance damage coefficient of the a-th storage device before the start of the oil refining operation data, the diversified data support can ensure the reliability and accuracy of this data. Therefore, through this comparison method, the safety level of the a-th storage device can be accurately judged according to the size of the risk coefficient of the a-th storage device at this time point, thereby improving the accuracy of the assessment result of the leakage risk of the storage device
[0032] The estimation process of the risk estimation module includes: By using the risk coefficients of the a-th storage device at different time points calculated by the risk assessment module, establish a risk coefficient change curve of the a-th storage device changing with time ; And through the formula calculate the risk coefficient change amount of the a-th storage device at the i-th time point after the start of the oil refining operation ; wherein, is the first evaluation time point after the start of the oil refining operation, At the i-th evaluation time point after the start of the oil refining operation, for all average value; Through the above technical solution, this example provides the change amount of the risk coefficient of the a-th storage device at the i-th time point after the start of the oil refining operation which can be calculated by the formula Through this calculation method, the change situation of the risk coefficient of the a-th storage device after the start of the oil refining operation can be reflected, that is, it represents the change situation of the leakage risk of the a-th storage device after the start of the oil refining operation. This data can provide data support for the subsequent evaluation of the future leakage risk of the a-th storage device, so as to identify potential leakage risks in advance and prevent potential leakage incidents from occurring.
[0033] The estimation process of the risk estimation module further includes: By assigning a value to the change amount of the risk coefficient of the a-th storage device at the i-th time point after the start of the oil refining operation to generate a change amount influence value of the a-th storage device that is between 1 and 2 and increases as the change amount of the risk coefficient increases; Among them, the change amount of the risk coefficient of the a-th storage device at the i-th time point after the start of the oil refining operation The corresponding change amount influence value of the a-th storage device is set as ; Through the above technical solution, this embodiment provides a process for assigning a value to the change amount of the risk coefficient of the a-th storage device at the i-th time point after the start of the oil refining operation ; As an example, The value-taking standard of
[0034] It should be noted that the larger the change amount of the risk coefficient of the a-th storage device at the i-th time point after the start of the oil refining operation the corresponding change amount influence value of the a-th storage device The larger it is, because the data reflects the change in the leakage risk of the a-th storage device after the start of the oil refining operation. When the data is larger, it means that after the start of the oil refining operation, the probability of leakage risk of the a-th storage device is gradually increasing, and the increase is relatively large. Then the probability of future leakage risk will be greater. On the contrary, when the data is smaller, it means that after the start of the oil refining operation, although the probability of leakage risk of the a-th storage device is gradually increasing, the increase is relatively small. Then the probability of future leakage risk will be relatively small. By setting like this, it can provide accurate and reliable data for subsequent evaluation of the future leakage risk of different storage devices, thereby improving the accuracy of the evaluation results.
[0035] The estimation process of the risk estimation module further includes: Through the formula Calculate the predicted future risk index of the a-th storage device at the i-th time point after the start of the oil refining operation ; Through the above technical solution, this example provides the predicted future risk index of the a-th storage device at the i-th time point after the start of the oil refining operation which can be calculated through the formula By this calculation method, by combining the change amount influence value of the a-th storage device, the risk coefficient of the a-th storage device at the i-th time point after the start of the oil refining operation is corrected, and then the predicted future risk index of the a-th storage device at the i-th time point can be obtained. This data can provide accurate data for subsequent judgment of the future leakage risk level of the a-th storage device, and by real-time monitoring the predicted future risk index of the a-th storage device at the i-th time point after the start of the oil refining operation, potential leakage risks can be discovered and warned in time, thereby avoiding the occurrence of leakage accidents and reducing economic losses.
[0036] The estimation process of the risk estimation module further includes: By comparing the predicted future risk index of the a-th storage device at the i-th time point after the start of the oil refining operation with the preset future risk index threshold ; If the system determines that the future leakage risk of the a-th storage device is high and issues a warning through the warning module; If the system determines that the future leakage risk of the a-th storage device is low and does not issue a warning; Through the above technical solution, in this example, the future risk index predicted by the a-th storage device at the i-th time point after the start of the oil refining operation is compared with the preset future risk index threshold Through this comparison method, an accurate judgment can be made on the future leakage risk level of the a-th storage device. By setting it like this, potential leakage events can be identified and measures can be taken in advance. And through the real-time monitoring of this data, potential leakage risks can be detected and warned in time, further avoiding the occurrence of leakage accidents.
[0037] The warning process of the warning module includes: When it is judged that a warning needs to be issued, first label the risk device and the risk type, and push the labeling information and the warning information to the background management system; Through the above technical solution, this example provides that the warning process of the warning module includes that when it is judged that a warning needs to be issued, first label the risk device and the risk type, and push the labeling information and the warning information to the background management system. By setting it like this, the location of the risk device can be quickly located for the operation and maintenance personnel during the warning, and by labeling the risk type, the background management system can be helped to allocate the most suitable operation and maintenance personnel to improve the maintenance efficiency.
[0038] The above has described an embodiment of the present invention in detail, but the content described is only a preferred embodiment of the present invention and cannot be considered as limiting the scope of implementation of the present invention. All equivalent changes and improvements made according to the scope of the present invention application should still fall within the scope covered by the patent of the present invention.
Claims
1. An oil refining safety monitoring system, characterized in that The system includes: A video surveillance module, including a video surveillance processing device and a data acquisition unit. The video surveillance processing device is used to collect the appearance data of different storage devices before the start of oil refining operations. The data acquisition unit is used to collect environmental information data at different time points after the start of oil refining. The equipment evaluation module is used to evaluate the appearance damage conditions of different storage devices on the same day by combining the appearance data of different storage devices before the start of oil refining operations. The risk assessment module is used to calculate the risk coefficients of different storage devices at different time points by combining the environmental information data collected by the data acquisition unit and the evaluation results of the equipment evaluation module, and to evaluate the leakage risks of different storage devices at different time points based on this data. The data analysis module is used to analyze the risk change conditions of different storage devices at different time points by combining the real-time risk coefficients calculated by the risk assessment module. The risk prediction module is used to predict the future leakage risks of different storage devices by combining the analysis results of the data analysis module. The early warning module is used to decide whether to issue an early warning by combining the analysis results of the equipment evaluation module, the risk assessment module and the risk prediction module respectively.
2. The petroleum refining safety monitoring system according to claim 1, wherein The video surveillance processing device includes a camera and an identification module. The camera is used to capture the appearance images of different storage devices, and the identification module identifies and records the required features in the appearance images captured by the camera, including the number of damage points, corrosion area, oil stain area and deformation area on the surface of the storage device.
3. The safety monitoring system for oil refining according to claim 1, characterized in that, The environmental information data collected by the data acquisition unit includes environmental temperature and environmental pressure values.
4. A petroleum refining safety monitoring system according to claim 1, characterized in that, The evaluation process of the equipment evaluation module includes: Obtained by the formula Calculate the appearance damage coefficient of the a-th storage device before the start of the oil refining operation ; Wherein, is the corrosion area on the outer surface of the a-th storage device before the start of the oil refining operation, is the oil stain area on the outer surface of the a-th storage device before the start of the oil refining operation, is the deformation area on the outer surface of the a-th storage device before the start of the oil refining operation, is the preset damage area, is the number of damage points on the outer surface of the a-th storage device, is the preset number of damage points, , and are weight coefficients, is the total number of overhauls of the a-th storage device, is 's standard value, is the overhaul frequency of the a-th storage device, is the preset overhaul frequency, is the service life influence coefficient of the a-th storage device.
5. The safety monitoring system for oil refining according to claim 4, wherein, The evaluation process of the equipment evaluation module also includes: By comparing the appearance damage coefficient of the a-th storage device before the start of the oil refining operation with the preset appearance damage coefficient threshold for comparison; If , the system determines that the a-th storage device has a problem of insufficient structural strength, which will increase the risk of leakage during subsequent oil refining operations and issue a warning; If , the system determines that the structural strength of the a-th storage device is high and will not increase the risk of leakage during subsequent oil refining operations, and further analyzes in combination with environmental information data.
6. The petroleum refining safety monitoring system according to claim 5, characterized in that, The evaluation process of the risk assessment module includes: Obtained through the formula Calculate the risk coefficient of the i-th time point of the a-th storage device after the start of the oil refining operation ; where \(i\) is any data acquisition time point after the start of the oil refining operation, is the total number of data acquisitions at the \(i\)-th time point after the start of the oil refining operation, is the ambient temperature at the \(i\)-th time point after the start of the oil refining operation, is the preset ambient temperature, for all is the average value, is the ambient pressure value at the \(i\)-th time point after the start of the oil refining operation, is the preset ambient pressure value, is the standard value of, is a defined function. If , then let , otherwise, let .
7. An oil refining safety monitoring system according to claim 6, characterized in that, The evaluation process of the risk assessment module includes: By comparing the risk coefficient of the $i$-th time point of the $a$-th storage device after the start of the oil refining operation with the preset risk coefficient threshold range for comparison; If , the system determines that the risk coefficient of the a-th storage device at this time point is small, indicating that the a-th storage device has high safety and a low probability of oil leakage, and estimates the future leakage risk of the a-th storage device; If , the system determines that the risk coefficient of the a-th storage device at this time point is high, indicating that the security of the a-th storage device is low, the probability of oil leakage is high, and an early warning is made in a timely manner through the early warning module.
8. The safety monitoring system for oil refining according to claim 7, wherein, The prediction process of the risk prediction module includes: The risk coefficients of the a-th storage device at different time points obtained by calculation through the risk assessment module are used to establish a risk coefficient change curve of the a-th storage device over time ; and obtain the change in the risk coefficient of the a-th storage device at the i-th time point after the start of the oil refining operation through the formula ; wherein, is the 1st evaluation time point after the start of the oil refining operation, is the i-th evaluation time point after the start of the oil refining operation, is the average value of all of 9. The oil refining safety monitoring system according to claim 8, characterized in that, The prediction process of the risk prediction module also includes: By assigning a value to the change amount of the risk coefficient of the a-th storage device at the i-th time point after the start of the oil refining operation to generate the change amount influence value of the a-th storage device that is between 1 and 2 and increases as the change amount of the risk coefficient increases; Among them, the change amount of the risk coefficient of the a-th storage device at the i-th time point after the start of the oil refining operation The influence value of the change amount of the corresponding a-th storage device is set as .
10. The oil refining safety monitoring system according to claim 9, characterized in that, The prediction process of the risk prediction module also includes: Obtained through the formula Calculate the predicted future risk index of the a-th storage device at the i-th time point after the start of the oil refining operation .
11. An oil refining safety monitoring system according to claim 10, wherein, The prediction process of the risk prediction module also includes: By comparing the predicted future risk index of the a-th storage device at the i-th time point after the start of the oil refining operation with the preset future risk index threshold for comparison; If , the system determines that the future leakage risk of the a-th storage device is high and issues a warning through the warning module; If , the system determines that the future leakage risk of the a-th storage device is low and does not issue a warning.
12. The safety monitoring system for petroleum refining according to claim 1, wherein The early warning process of the early warning module includes: When it is judged that an early warning needs to be issued, first mark the risk equipment and risk types, and push the marked information and early warning information to the background management system.