An emergency management system for a gas station

Abstract

The present invention discloses an emergency management system for a gas station, which relates to the technical field of gas station management and solves the problem that it is impossible to monitor the pressure change of a gas station pipeline in real time, and when an emergency such as oil and gas leakage or pipeline overpressure occurs, it may be impossible to discover and respond in time. The present invention realizes comprehensive monitoring of the oil pipeline system of the gas station through the collaborative work of different modules, including the design of data collection, processing, time period distinction and alarm modules; the system can monitor the pipeline pressure in real time, and compare it with a preset standard, and accurately identify overpressure or leakage; through data analysis within a preset time period, the system can accurately distinguish between voltage change, frequency change and observation time periods, and formulate corresponding detection and response strategies for different situations; this accuracy and time period response mechanism enable the emergency management system to accurately judge potential risks in the early stage and issue early warnings in time, thereby improving the efficiency and effect of emergency response.

Description

Technical Field

[0001] The present invention relates to the technical field of gas station management, in particular to an emergency management system for a gas station. Background Art

[0002] In the field of gas station management and safety, traditional emergency management systems mainly rely on regular manual inspections and periodic maintenance to ensure the normal operation and safety of gas stations. These methods include physical inspections of key equipment such as oil tanks, pipelines, pumping stations, and monitoring of the gas station environment. The advantage of this manual inspection method is that it is simple and direct and does not require complex technical support. However, they can usually only be carried out periodically, and cannot continuously monitor the operating status of gas stations, especially in terms of monitoring pressure changes. There are obvious deficiencies.

[0003] However, this traditional manual detection method has significant limitations. Due to the inability to monitor pressure changes in real time, emergency situations such as oil and gas leaks or pipeline overpressure may not be discovered and responded to in a timely manner. This delay may cause serious consequences before the problem is detected, such as environmental pollution, increased risk of fire and explosion, and may even endanger personnel safety. In addition, due to the lack of real-time data and analysis, traditional emergency management systems also have difficulty in conducting effective risk assessments and formulating preventive measures. Therefore, there is an urgent need for an emergency management system for gas stations that can monitor and reflect pressure changes in real time and identify potential safety risks in a timely manner, thereby improving the safety management level and emergency response capabilities of gas stations. Summary of the invention

[0004] In view of the deficiencies of the prior art, the present invention provides an emergency management system for a gas station, which solves the problems of the background technology.

[0005] To achieve the above objectives, the present invention is implemented through the following technical solutions: an emergency management system for a gas station, comprising:

[0006] The data acquisition module is used to perform pressure detection on the oil pipelines in the gas station every standard period t, collect the pipeline pressures in different oil pipelines, and then obtain the measured pipeline pressure and the preset standard pipeline pressure, and obtain the evaluation difference by calculating the absolute value between them, and send the evaluation difference to the subsequent data analysis module, where the standard period t is a preset value;

[0007] A data processing module is used to compare the received evaluation difference with a preset critical value. When the evaluation difference is greater than the critical value, it is marked as 1 and recorded as an overpressure value. When the evaluation difference is less than the critical value, it is marked as 0 and recorded as a range value, and sent to a subsequent time period differentiation module;

[0008] A time period distinction module is used to divide each day into a pending time periods on average, receive the overpressure value and range value sent by the data processing module, wherein the received overpressure value and range value include the overpressure value and range value sent by all data processing modules within T time, and then determine each of the a pending time periods as a voltage change period, a frequency change period or an observation period, wherein a and T are both preset times;

[0009] The detection module is used to formulate different detection strategies for the time periods distinguished by the time period distinguishing module, generate different alarm signals according to the detection results, and send the generated alarm signals to the subsequent alarm module;

[0010] The alarm module is used to receive three alarm signals sent by the detection module in real time, including overpressure warning signal, differential current warning signal and alarm signal, make different response processing respectively, and output corresponding safety management measures;

[0011] Display module: used to display the corresponding safety management measures output by the alarm module.

[0012] Preferably, the specific method of determining the pending time period distinction in the time period distinction module is:

[0013] S1: Get the overpressure value within T time. The preset time T means the time period of h days from the current time. The data of the day when the data is obtained is not included. T=﹛1, 2, ..., h﹜; where h is the preset value;

[0014] S2: Then divide a day into a pending time periods on average, select a pending time period at random, obtain the number of overpressure values ​​Ci in the pending time period within T time, then calculate the total number of overpressure values ​​x within T time, and then divide x by h to calculate the average value p of the number of overpressure values ​​in this time period within T time, and then use the formula, where Ci represents the number of overpressure values ​​in this time period on the i-th day, 1≤i≤h, and Sfad is the calculated deviation value;

[0015] S3: Compare the deviation value Sfad with the preset value g. When the deviation value Sfad exceeds the preset value g, sort Ci from large to small, delete the first one in the sorting each time, and calculate the deviation value Sfad for the remaining Ci again until the deviation value Sfad does not exceed the preset value g.

[0016] S4: Obtain the number D1 of deleted Ci, subtract D1 from h to get D2, and then divide the time periods into voltage change period, frequency change period or observation period;

[0017] After step S4, the method further includes:

[0018] S5: Then repeat the process from step S1 to step S4, and divide the a pending time periods into voltage change time periods, frequency change time periods or observation time periods.

[0019] Preferably, the time period is divided into a voltage change period, a frequency change period or an observation period in the following manner:

[0020] If D1 is greater than or equal to D2, this period is marked as a voltage change period. If D1 is less than D2, or when the first calculated deviation value Sfad does not exceed the preset value g and is not 0, this period is marked as a frequency change period. If the first calculated deviation value Sfad is 0, this period is marked as an observation period.

[0021] Preferably, the method of formulating different detection strategies in the detection module is:

[0022] During the voltage transformation period, real-time detection is performed every T1 time, during the frequency transformation period, real-time detection is performed every T2 time, and during the observation period, real-time detection is performed every T3 time, where T1, T2 and T3 are all preset values, and T1 <T2<T3。

[0023] Preferably, the specific detection method of the detection module is:

[0024] P1: Obtain the detected pipeline pressure and determine whether the pipeline pressure is an overpressure value. The determination method is to calculate the pipeline pressure through the data acquisition module and the data processing module;

[0025] P2: Based on the difference between the inlet and outlet flow rates, the formula is:

[0026]

[0027] Will Compared with the preset K value, Expressed as the mass flow rate of leakage, is the volume flow rate into the pipe, is the volume flow rate leaving the pipe, ρ is the density of the fluid, and the preset K value is expressed as the allowable error, which allows a certain error range;

[0028] Preferably, after step P2, the method further includes:

[0029] P3: Determine the results of P1 and P2:

[0030] When the pipeline pressure is judged to be overpressure, and When the K value is not exceeded, an overpressure warning signal is generated;

[0031] When the pipeline pressure is judged to be within the range value, and If the K value is not exceeded, no processing is performed;

[0032] When the pipeline pressure is judged to be within the range value, and When the K value is exceeded, a differential current warning signal is generated;

[0033] When the pipeline pressure is judged to be overpressure, and When the K value is exceeded, an alarm signal is generated;

[0034] Preferably, the specific different response processing modes in the alarm module are:

[0035] AS1: When receiving an overpressure warning signal, it issues an overpressure warning broadcast and outputs corresponding safety management measures;

[0036] AS2: When receiving the differential current warning signal, it issues a differential current warning broadcast and outputs corresponding safety management measures;

[0037] AS3: When an alarm signal is received, an alarm signal is issued, indicating that a leak has occurred in the oil pipeline, and corresponding safety management measures are output.

[0038] Preferably, the output corresponding safety management measures are represented by various effective measures required to be taken by outputting the alarm signal or early warning signal by a preset storage model when an alarm signal or early warning signal appears.

[0039] The present invention provides an emergency management system for a gas station. Compared with the prior art, it has the following beneficial effects:

[0040] (1) In the present invention, the system realizes comprehensive monitoring of the oil pipeline system of a gas station through the collaborative work of different modules, including the design of data collection, processing, time period distinction and alarm modules; the system can monitor the pipeline pressure in real time and compare it with the preset standard to accurately identify overpressure or leakage; through data analysis within a preset time period, the system can accurately distinguish between voltage change, frequency change and observation time periods, and formulate corresponding detection and response strategies for different situations; this accuracy and time-divided response mechanism enable the emergency management system to accurately judge potential risks in the early stage, issue early warnings in time, effectively avoid or reduce the occurrence of accidents, and thus improve the efficiency and effectiveness of emergency response.

[0041] (2) The present invention, through the implementation of highly automated and intelligent monitoring and analysis, can reduce the reliance on manual monitoring, thereby reducing labor costs and potential human errors; the system can not only monitor and warn in real time, but also automatically propose corresponding safety management measures according to different types of warning signals, such as pipeline inspection and maintenance when pressure is abnormal, emergency investigation when leakage warning is issued, etc., which greatly improves the efficiency and effectiveness of emergency management. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] The present invention will be further described below in conjunction with the accompanying drawings.

[0043] Figure 1 This is a system framework diagram of an emergency management system for a gas station according to the present invention;

[0044] Figure 2 This is a time period differentiation flow chart of an emergency management system for a gas station according to the present invention. DETAILED DESCRIPTION

[0045] The following will be combined with the 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 without creative work are within the scope of protection of the present invention.

[0046] Embodiment 1

[0047] See also Figure 1-Figure 2 ,The present invention provides an emergency management system for a gas station, comprising;

[0048] The data acquisition module is used to perform pressure detection on the oil pipelines in the gas station every standard period t, collect the pipeline pressures in different oil pipelines, and then obtain the measured pipeline pressure and the preset standard pipeline pressure, and obtain the evaluation difference by calculating the absolute value between them, and send the evaluation difference to the subsequent data analysis module, where the standard period t is a preset value, and the standard pipeline pressure is set by the relevant staff;

[0049] It should be noted that the pressure measurement of the oil pipeline is usually achieved by using a pressure sensor or a pressure gauge, which can monitor and record the pressure level inside the pipeline; the pressure sensor can be installed at key locations of the pipeline, such as the inlet and outlet of the pipeline, important branch points, and areas known to be prone to leakage, and in this embodiment, t is 1 minute;

[0050] A data processing module is used to compare the received evaluation difference with a preset critical value. When the evaluation difference is greater than the critical value, it is marked as 1 and recorded as an overpressure value. When the evaluation difference is less than the critical value, it is marked as 0 and recorded as a range value, and sent to a subsequent time period differentiation module;

[0051] It should be noted that the preset critical value is a standard value of the up and down change value of the pipeline pressure, and also represents the threshold value of the up and down change value of the pipeline pressure. The specific parameters are set by the staff;

[0052] A time period distinction module is used to divide each day into a pending time periods on average, receive the overpressure value and range value sent by the data processing module, wherein the received overpressure value and range value include the overpressure value and range value sent by all data processing modules within T time, and then determine each of the a pending time periods as a voltage change period, a frequency change period or an observation period, wherein a and T are both preset times;

[0053] The specific method of distinguishing the pending determination period is as follows:

[0054] S1: Obtain the overpressure value within T time, the preset time T, represents the time period of h days from the current time, and the data of the day of acquisition is not included, T=﹛1, 2, ..., h﹜; where h is a preset value, which is specifically set by professional staff, and in this embodiment, h=14;

[0055] S2: Then divide a day into a pending time periods on average, select a pending time period at random, obtain the number of overpressure values ​​Ci in the pending time period within T time, then calculate the total number of overpressure values ​​x within T time, and then divide x by h to calculate the average value p of the number of overpressure values ​​in this time period within T time, and then use the formula, where Ci represents the number of overpressure values ​​in this time period on the i-th day, 1≤i≤h, and Sfad is the calculated deviation value;

[0056] S3: Compare the deviation value Sfad with the preset value g. When the deviation value Sfad exceeds the preset value g, sort Ci from large to small, delete the first one in the sorting each time, and calculate the deviation value Sfad for the remaining Ci again until the deviation value Sfad does not exceed the preset value g.

[0057] S4: Get the number D1 of deleted Ci, and get D2 by subtracting D1 from h. If D1 is greater than or equal to D2, mark this period as a voltage-changing period. If D1 is less than D2, or the first calculated deviation value Sfad does not exceed the preset value g and is not 0, mark this period as a frequency-changing period. If the first calculated deviation value Sfad is 0, mark this period as an observation period.

[0058] S5: then repeat the process from step S1 to step S4, and divide the a pending time periods into voltage change time periods, frequency change time periods or observation time periods;

[0059] The detection module is used to formulate different detection strategies for the time periods distinguished by the time period distinguishing module, generate different alarm signals according to the detection results, and send the generated alarm signals to the subsequent alarm module;

[0060] The specific methods for formulating different detection strategies are as follows:

[0061] During the voltage transformation period, real-time detection is performed every T1 time. During the frequency variation period, real-time detection is performed every T2 time. During the observation period, real-time detection is performed every T3 time;

[0062] Among them, T1, T2, and T3 are all preset values, and T1 < T2 < T3. The specific time parameters are set by relevant staff;

[0063] Embodiment 2

[0064] In the specific implementation process of this embodiment, on the basis of Embodiment 1, the difference from Embodiment 1 is that this embodiment specifically describes the detection method:

[0065] The specific detection method is as follows:

[0066] P1: Obtain the pipeline pressure to be detected, and judge whether the pipeline pressure is an overpressure value. The judgment method is to calculate the pipeline pressure through the data acquisition module and the data processing module internally;

[0067] P2: At the same time, according to the difference between the inlet and outlet flow rates, through the formula:

[0068]

[0069] Compare with the preset K value, where represents the mass flow rate of leakage, is the volume flow rate entering the pipeline, is the volume flow rate leaving the pipeline, ρ is the density of the fluid, here it refers to the density of fuel oil, and the preset K value represents the allowable error within a certain error range;

[0070] P3: Judge the results of P1 and P2:

[0071] When the pipeline pressure is judged to be an overpressure value, and does not exceed the K value, generate an overpressure warning signal;

[0072] When the pipeline pressure is judged to be within the range value, and does not exceed the K value, do nothing;

[0073] When the pipeline pressure is judged to be within the range value, and exceeds the K value, generate a differential flow warning signal;

[0074] When the pipeline pressure is judged to be an overpressure value, and exceeds the K value, generate an alarm signal;

[0075] It should be noted that the gas station pipeline system is regarded as a closed system, in which any mass loss can be considered as leakage. According to the law of conservation of mass, the rate of mass change in the system is equal to the mass flow rate entering the system minus the mass flow rate leaving the system; and The volume flow rate is measured by installing a meter at the inlet and outlet of the pipeline;

[0076] Embodiment 3

[0077] In the specific implementation process, this embodiment is based on the first and second embodiments, and the difference from the first and second embodiments is that:

[0078] The alarm module is used to receive three alarm signals sent by the detection module in real time, including overpressure warning signal, differential current warning signal and alarm signal, make different response processing respectively, and output corresponding safety management measures;

[0079] The specific response processing methods are as follows:

[0080] AS1: When receiving an overpressure warning signal, it issues an overpressure warning broadcast and outputs safety management measures:

[0081] Action 1: Observe whether the pressure quickly returns to normal range. If so, no further action is required, but the event should be recorded for future analysis.

[0082] Cause: Changes in pipe network operation (such as valve operation), pump start and stop, etc. may cause instantaneous pressure fluctuations;

[0083] Measure 2: Verify the accuracy of the flow measurement equipment and the real-time performance of the data transmission system. The flow meter needs to be calibrated.

[0084] Cause: Measurement errors or data transmission delays in flow monitoring equipment may cause flow data to fail to reflect actual conditions in a timely manner;

[0085] Measure 3: Conduct pipeline inspections, use endoscopes or pressure wave analysis techniques to locate blockages, and clean or repair them;

[0086] Cause: Partial blockage occurs inside the pipeline, causing local pressure to rise, but the flow rate may not be significantly affected, or the change in flow rate does not exceed the K value;

[0087] Measure 4: Check the working condition of the pump and valve, and make necessary repairs or replacements;

[0088] Cause: Abnormal operation of the pump or valve failure may cause abnormal system pressure, while the flow rate does not change much or is not captured in time;

[0089] Measure 5: Check and calibrate the pressure sensor and replace the damaged sensor if necessary;

[0090] Cause: The pressure sensor itself is faulty or the reading is incorrect due to inaccurate calibration;

[0091] AS2: When receiving the differential current warning signal, it issues a differential current warning broadcast and outputs safety management measures:

[0092] Measure 1: Check and calibrate the flow meter, and repair or replace it if necessary;

[0093] Cause: Metering errors or failures in the flow meter may result in erroneous flow readings;

[0094] Measure 2: Check the operating status of the pump and valve configuration, and adjust to appropriate working conditions;

[0095] Cause: Over-running of the pump or incorrect valve configuration may cause the flow rate to increase while the pressure remains within the normal range;

[0096] Action 3: Check if there have been any recent changes to pipeline configuration or operations and ensure that all changes have been properly documented and managed;

[0097] Cause: Configuration changes within the piping system (e.g. opening of additional branches) or operational changes (e.g. increasing the oil supply) may result in an increase in flow;

[0098] Measure 4: Carefully check the leak detection system and automatic control system to ensure they are working properly and look for possible leak sources;

[0099] Cause: If the system detects a leak and attempts to compensate for the pressure loss caused by the leak by increasing the amount of oil pumped, an increase in flow may occur without a significant change in pressure.

[0100] Action 5: Use more sensitive detection techniques, such as sonic testing or the use of special dyes to identify small leaks;

[0101] Reason: A small leak may not be enough to cause a significant drop in pressure, but over time, the increased flow in the system to maintain pressure may exceed the flow threshold;

[0102] Measure 6: Check data transmission systems and recording equipment to ensure that all data can be updated accurately in real time;

[0103] Cause: The real-time update of flow data may be delayed while the pressure data is not affected, resulting in an apparent abnormal increase in flow;

[0104] AS3: When receiving an alarm signal, it issues an alarm signal, indicating that a leak has occurred in the oil pipeline, and outputs safety management measures:

[0105] Measures: Comprehensively inspect the oil pipeline and various equipment to find out the leakage location;

[0106] Display module: used to display the corresponding management measures information output by the alarm module, so that the staff can easily conduct one-by-one investigation and prevention.

[0107] Embodiment 4

[0108] The specific implementation process of this embodiment includes all the implementation processes of the above three groups of embodiments.

[0109] Some of the data in the above formulas are dimensionless and numerically calculated. Meanwhile, the contents not described in detail in this specification belong to the prior art known to those skilled in the art.

[0110] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. An emergency management system for a gas station, characterized in that: include: The data acquisition module is used to perform pressure detection on the oil pipelines in the gas station every standard period t, collect the pipeline pressures in different oil pipelines, and then obtain the measured pipeline pressure and the preset standard pipeline pressure, and obtain the evaluation difference by calculating the absolute value between them, and send the evaluation difference to the subsequent data processing module, wherein the standard period t is a preset value; A data processing module is used to compare the received evaluation difference with a preset critical value. When the evaluation difference is greater than the critical value, it is marked as 1 and recorded as an overpressure value. When the evaluation difference is less than the critical value, it is marked as 0 and recorded as a range value, and sent to a subsequent time period differentiation module; A time period distinction module is used to divide each day into a pending time periods on average, receive the overpressure value and range value sent by the data processing module, wherein the received overpressure value and range value include the overpressure value and range value sent by all data processing modules within T time, and then determine each of the a pending time periods as a voltage change period, a frequency change period or an observation period, wherein a and T are both preset times; The detection module is used to formulate different detection strategies for the time periods distinguished by the time period distinguishing module, generate different alarm signals according to the detection results, and send the generated alarm signals to the subsequent alarm module; The alarm module is used to receive three alarm signals sent by the detection module in real time, including overpressure warning signal, differential current warning signal and alarm signal, make different response processing respectively, and output corresponding safety management measures; Display module: used to display the corresponding safety management measures output by the alarm module; The specific method of determining the pending time period distinction in the time period distinction module is as follows: S1: Get the overpressure value within T time. The preset time T means the time period of h days from the current time. The data of the day when the data is obtained is not included. T=﹛1, 2, ..., h﹜; where h is the preset value; S2: Then divide a day into a pending periods on average, select a pending period at random, obtain the number of overpressure values ​​Ci in the pending period within T time, then calculate the total number of overpressure values ​​x within T time, then divide x by h to calculate the average value p of the number of overpressure values ​​in the pending period within T time, and then calculate the deviation value Sfad, where Ci is expressed as the number of overpressure values ​​in the pending period on the i-th day, 1≤i≤h; S3: Compare the deviation value Sfad with the preset value g. When the deviation value Sfad exceeds the preset value g, sort Ci from large to small, delete the first one in the sorting each time, and calculate the deviation value Sfad for the remaining Ci again until the deviation value Sfad does not exceed the preset value g. S4: Obtain the number D1 of deleted Ci, subtract D1 from h to get D2, and then divide the time periods into voltage change period, frequency change period or observation period; After step S4, the method further includes: S5: then repeat the process from step S1 to step S4, and divide the a pending time periods into voltage change time periods, frequency change time periods or observation time periods; The time periods are divided into voltage change period, frequency change period or observation period in the following ways: If D1 is greater than or equal to D2, this period is marked as a voltage-changing period. If D1 is less than D2, or the first calculated deviation value Sfad does not exceed the preset value g and is not 0, this period is marked as a frequency-changing period. If the first calculated deviation value Sfad is 0, this period is marked as an observation period. The specific way to formulate different detection strategies in the detection module is as follows: During the voltage transformation period, real-time detection is performed every T1 time, during the frequency transformation period, real-time detection is performed every T2 time, and during the observation period, real-time detection is performed every T3 time, where T1, T2 and T3 are all preset values, and T1 <T2<T3; The specific detection method of the detection module is: P1: Obtain the detected pipeline pressure and determine whether the pipeline pressure is an overpressure value. The determination method is to calculate the pipeline pressure through the data acquisition module and the data processing module; P2: Based on the difference between the inlet and outlet flow rates, the formula is: Will Compared with the preset K value, Expressed as the mass flow rate of leakage, is the volume flow rate into the pipe, is the volume flow rate leaving the pipe, ρ is the density of the fluid, and the preset K value is expressed as the allowable error; After step P2, the following steps are also included: P3: Determine the results of P1 and P2: When the pipeline pressure is judged to be overpressure, and When the K value is not exceeded, an overpressure warning signal is generated; When the pipeline pressure is judged to be within the range value, and If the K value is not exceeded, no processing is performed; When the pipeline pressure is judged to be within the range value, and When the K value is exceeded, a differential current warning signal is generated; When the pipeline pressure is judged to be overpressure, and When the K value is exceeded, an alarm signal is generated.

2. The emergency management system for a gas station according to claim 1, characterized in that: The specific different response processing methods in the alarm module are: AS1: When receiving an overpressure warning signal, it issues an overpressure warning broadcast and outputs corresponding safety management measures; AS2: When receiving the differential current warning signal, it issues a differential current warning broadcast and outputs corresponding safety management measures; AS3: When an alarm signal is received, an alarm signal is issued, indicating that a leak has occurred in the oil pipeline, and corresponding safety management measures are output.

3. The emergency management system for a gas station according to claim 2, characterized in that: The output corresponding safety management measures represent that when an alarm signal or a warning signal appears, a preset storage model outputs various effective measures required for the alarm signal or the warning signal.

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