CN118463029A - Environment risk source early warning method and system - Google Patents
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Abstract
The invention discloses an environment risk source early warning method and system, in particular relates to the technical field of environment monitoring and early warning, and aims to solve the problem that leakage risks of liquefied petroleum gas stored in a spherical storage tank cannot be found in time in the prior art; determining whether to start early warning of the liquefied petroleum gas by combining the messy degree of the wind direction and the leakage potential safety hazard degree of the storage tank; when the early warning is started, evaluating the uniformity and the density variation degree of the gas components in the spherical storage tank; the leakage risk of the liquefied petroleum gas in the port area can be comprehensively estimated by comprehensively analyzing the leakage potential safety hazard degree of the spherical storage tank, the component uniformity of the gas in the spherical storage tank and the density variation degree of the gas in the spherical storage tank; the comprehensive risk assessment can effectively reduce the probability of accidents, and reduce possible environmental pollution and economic loss.
Description
Technical Field
The invention relates to the technical field of environmental monitoring and early warning, in particular to an environmental risk source early warning method and system.
Background
In the petroleum storage of ports, the spherical storage tank is used for storing Liquefied Petroleum Gas (LPG), and the spherical storage tank is particularly important in large-scale industrial applications such as ports, and not only can store a large amount of the liquefied petroleum gas, but also can ensure the safety and economic efficiency in the transportation process. Liquefied petroleum gas is used as an environmental risk source, and leakage of the liquefied petroleum gas can cause fire or explosion, and can cause serious pollution to surrounding environments (including land and sea), influence air quality and even endanger human health.
If the leakage risk of the liquefied petroleum gas stored in the spherical storage tank cannot be found in time, the leaked liquefied petroleum gas can be evaporated to form high-concentration gas, and the gas can immediately cause large-scale explosion and fire when encountering an ignition source, so as to cause destructive damage to surrounding facilities. In addition, gas diffusion can severely contaminate the air quality and marine environment, posing a threat to human and biological health.
In order to solve the above problems, a technical solution is now provided.
Disclosure of Invention
In order to overcome the above-mentioned drawbacks of the prior art, embodiments of the present invention provide an environmental risk source early warning method and system to solve the problems set forth in the above-mentioned background art.
In order to achieve the above purpose, the present invention provides the following technical solutions:
An environmental risk source early warning method comprises the following steps:
s1: by analyzing the real-time wind direction of the port area, the clutter degree of the wind direction of the port area is estimated;
s2: the potential leakage safety hazard degree of the spherical storage tank is estimated through analysis of the pressure recovery capacity of the spherical storage tank;
s3: judging whether to start early warning of liquefied petroleum gas based on the messy degree of the wind direction of the port area and the leakage potential safety hazard degree of the spherical storage tank;
S4: when the early warning of the liquefied petroleum gas is started: evaluating the uniformity of the composition of the gas in the spherical storage tank by analyzing the variation of the composition of the gas in the spherical storage tank; evaluating the density change degree of the gas in the spherical storage tank;
S5: and comprehensively analyzing the leakage potential safety hazard degree of the spherical storage tank, the component uniformity of the gas in the spherical storage tank and the density change degree of the gas in the spherical storage tank, and pre-warning the potential safety hazard of the leakage of the liquefied petroleum gas in the port area.
In a preferred embodiment, in S1, specifically:
collecting real-time wind direction data of a port area, and recording a wind direction angle;
converting the continuous wind direction angle into a unit vector; for each wind direction angle, its unit vector is calculated: ; wherein, Is the firstThe unit vector of the secondary wind direction angle,Is the firstThe wind direction angle of the secondary measurement,Numbering the wind direction angle;
Calculating an average vector of the unit vectors: ; wherein, Is the average vector of the unit vectors,Is the total number of measurements of wind direction angle;
the wind direction clutter index is obtained through the calculation of the circulation variance, and the expression is as follows: ; wherein, In the form of a wind-direction disorder index,Respectively the average vector of the unit vectorsComponents andA component.
In a preferred embodiment, in S2, specifically:
Setting a pressure recovery monitoring interval;
Acquiring a pressure abnormal event in a pressure recovery monitoring interval; determining the number of pressure anomaly events occurring within the pressure recovery monitoring interval; acquiring the recovery length of the pressure abnormal event; obtaining the maximum offset in the pressure abnormal event;
Calculating an abnormal recovery index of the storage tank, wherein the expression is as follows: ; wherein, Is an index of the abnormal recovery of the tank itself,For the number of pressure anomaly events occurring within the pressure recovery monitoring interval,For the corresponding length of time of the pressure recovery monitoring interval,Monitoring interval for pressure recoveryThe recovery length of the pressure abnormal event corresponding to the secondary pressure abnormal event,Monitoring interval for pressure recoveryThe maximum offset in the secondary pressure anomaly event,Is the number of the pressure abnormal event in the pressure recovery monitoring interval,AndAll of which represent the weight of the object,AndAre all greater than 0.
In a preferred embodiment, in S3, specifically:
setting a wind direction disorder threshold; comparing the wind direction hash index to a wind direction hash threshold:
when the wind direction disorder index is larger than the wind direction disorder threshold value, judging that a wind direction disorder degree large signal is generated;
When the wind direction disorder index is smaller than or equal to the wind direction disorder threshold value, judging that a normal signal of the wind direction disorder degree is generated;
Setting an abnormal recovery threshold value of the storage tank; comparing the tank self-anomaly recovery index with a tank self-anomaly recovery threshold value:
When the abnormal recovery index of the storage tank is larger than the abnormal recovery threshold value of the storage tank, judging that an abnormal risk signal of the storage tank is generated;
When the abnormal recovery index of the storage tank is smaller than or equal to the abnormal recovery threshold of the storage tank, judging that a normal signal of the storage tank is generated;
When a signal with large wind direction disorder degree is generated or an abnormal risk signal of the storage tank is generated, the early warning of the liquefied petroleum gas is started.
In a preferred embodiment, in S4, specifically:
the ratio of each component is calculated, and the formula is: ; wherein, Is the firstThe proportions of the individual components are such that,Is the firstThe concentration of the individual components is determined,Is the sum of all ingredient concentrations;
calculating a gas component uniformity value through an information entropy formula, wherein the expression is as follows: ; wherein, For the gas composition to be of uniform value,In order to determine the amount of the ingredients,Is the number of the component;
Setting a gas uniform monitoring interval; uniformly setting a plurality of monitoring points in a gas uniform monitoring interval, acquiring a gas component uniform value corresponding to each monitoring point, analyzing the change condition of the gas component uniform value in the gas uniform monitoring interval, and calculating a gas component uniformity index, wherein the expression is as follows: ; wherein, Is an index of the uniformity of the gas composition,For the number of monitoring points in the gas uniform monitoring interval,The number of the monitoring points in the gas uniform monitoring interval is given,Respectively the first gas uniform monitoring intervalGas component uniformity value corresponding to each monitoring point and first in gas uniformity monitoring intervalAnd the gas components corresponding to the monitoring points are uniform.
In a preferred embodiment, the degree of density variation of the gas inside the spherical tank is evaluated, in particular:
applying a numerical partial derivative method to the spatial data at each time point to calculate a density gradient;
calculating the square of the density gradient;
Calculating a density change abnormality index, the expression of which is: ; wherein, In order to change the abnormality index of the density,Expressed in timeAnd positionIs used for the gas density gradient of (a),Is the volume within the spherical storage tank,Representing the start and end times of the analysis, respectively.
In a preferred embodiment, in S5, specifically:
Normalizing the abnormal recovery index of the storage tank, the gas component uniformity index and the density change abnormal index, respectively endowing the normalized abnormal recovery index of the storage tank, the normalized gas component uniformity index and the normalized density change abnormal index with preset proportionality coefficients, and calculating to obtain risk source leakage early warning coefficients;
setting a risk source leakage early warning threshold value, and carrying out early warning on potential safety hazards of liquefied petroleum gas leakage in a port area through comparison of a risk source leakage early warning coefficient and the risk source leakage early warning threshold value:
when the risk source leakage early warning coefficient is larger than the risk source leakage early warning threshold value, judging that a leakage risk early warning signal is generated;
And when the risk source leakage early warning coefficient is smaller than or equal to the risk source leakage early warning threshold value, judging that a leakage risk normal signal is generated.
On the other hand, the invention provides an environment risk source early warning system, which comprises a wind direction clutter evaluation module, a pressure recovery evaluation module, an early warning starting judgment module, an early warning information acquisition module and a risk hidden danger early warning module;
the wind direction clutter evaluation module evaluates the clutter degree of the wind direction of the port area through analyzing the real-time wind direction of the port area;
The pressure recovery evaluation module evaluates the leakage potential safety hazard degree of the spherical storage tank by analyzing the pressure recovery capacity of the spherical storage tank;
The early warning starting judging module judges whether to start early warning of the liquefied petroleum gas based on the messy degree of the wind direction of the port area and the leakage potential safety hazard degree of the spherical storage tank;
When the early warning of the liquefied petroleum gas is started: the early warning information acquisition module evaluates the component uniformity of the gas in the spherical storage tank by analyzing the change of the gas component in the spherical storage tank; evaluating the density change degree of the gas in the spherical storage tank;
The risk potential hazard early warning module comprehensively analyzes the leakage potential safety hazard degree of the spherical storage tank, the component uniformity of the gas in the spherical storage tank and the density variation degree of the gas in the spherical storage tank, and early warns the potential safety hazard of the leakage of the liquefied petroleum gas in the port area.
The environmental risk source early warning method and the system have the technical effects and advantages that:
1. The real-time wind direction of the port area is analyzed, so that the disorder degree of the wind direction can be effectively estimated, and the risk factors caused by the wind direction can be timely predicted and early-warned. And determining whether to start early warning of the liquefied petroleum gas by combining the messy degree of the wind direction and the leakage potential safety hazard degree of the storage tank. The early warning mechanism based on multi-factor comprehensive judgment not only improves the early warning accuracy, but also optimizes the use efficiency of resources.
2. When the early warning is started, the uniformity and the density change degree of the gas components in the spherical storage tank are further finely estimated by monitoring the change and the density change of the gas components in the storage tank. This step helps to monitor the internal state of the tank, ensure the stability and safety of the gas storage, and discover and deal with potential leaks or other related risks in time.
3. The leakage risk of the liquefied petroleum gas in the port area can be comprehensively estimated by comprehensively analyzing the leakage potential safety hazard degree of the spherical storage tank, the component uniformity of the gas in the spherical storage tank and the density variation degree of the gas in the spherical storage tank. The comprehensive risk assessment mechanism enables risk management to be more scientific and systematic, can effectively reduce the probability of accidents, and reduces possible environmental pollution and economic loss.
Drawings
FIG. 1 is a schematic diagram of an environmental risk source early warning method according to the present invention;
Fig. 2 is a schematic structural diagram of an environmental risk source early warning system according to the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Example 1
FIG. 1 shows an environmental risk source early warning method of the invention, which comprises the following steps:
s1: by analyzing the real-time wind direction of the port area, the clutter degree of the wind direction of the port area is estimated.
S2: and the potential leakage safety hazard degree of the spherical storage tank is estimated through analysis of the pressure recovery capability of the spherical storage tank.
S3: judging whether to start early warning of liquefied petroleum gas based on the messy degree of the wind direction of the port area and the leakage potential safety hazard degree of the spherical storage tank.
S4: when the early warning of the liquefied petroleum gas is started: evaluating the uniformity of the composition of the gas in the spherical storage tank by analyzing the variation of the composition of the gas in the spherical storage tank; the degree of density change of the gas inside the spherical tank was evaluated.
S5: and comprehensively analyzing the leakage potential safety hazard degree of the spherical storage tank, the component uniformity of the gas in the spherical storage tank and the density change degree of the gas in the spherical storage tank, and pre-warning the potential safety hazard of the leakage of the liquefied petroleum gas in the port area.
In S1, the clutter degree of the wind direction of the port area is estimated by analyzing the real-time wind direction of the port area, specifically:
the wind direction of the port area is continuously monitored by using a high-precision anemoscope, and recording data once every minute.
And acquiring real-time wind direction data of a port area, and recording the angle of wind direction, wherein the angle range of wind direction is from 0 degree to 360 degrees.
Successive wind direction angles are converted into unit vectors. For each wind direction angle, its unit vector is calculated: ; wherein, Is the firstThe unit vector of the secondary wind direction angle,Is the firstThe wind direction angle of the secondary measurement,Numbering the wind direction angle.
The cyclic variance is used to evaluate the stability of the wind direction.
Calculating an average vector of the unit vectors: ; wherein, Is the average vector of the unit vectors,Is the total number of measurements of the wind direction angle.
Analysis of wind direction data by cyclic statistics (cyclic variance) is one of the standard methods of processing ring data, applicable to such periodic data as wind direction.
The wind direction clutter index is obtained through the calculation of the circulation variance, and the expression is as follows: ; wherein, For the wind direction clutter index (for evaluating the degree of change and stability of wind direction),Respectively the average vector of the unit vectorsComponents andA component.
The components are as follows: based on the angle of the wind directionAnd represents the component of the vector in the horizontal direction (east-west direction).The components are as follows: based on the angle of the wind directionRepresenting the component of the vector in the vertical direction (north-south direction).
The greater the wind direction clutter index, the higher the wind direction clutter degree, if the liquefied petroleum gas of the spherical storage tank leaks at this time, the wind direction clutter can lead to the gas that leaks to spread more widely, has increased the pollution scope, this makes the emergent response more complicated and difficult. Unstable wind directions increase the difficulty of predicting a leakage gas diffusion path. Traditional diffusion models assume that the wind direction is relatively stable, and that the cluttered wind direction can lead to inaccurate model predictions. Wind direction instability can carry gas to unpredictable areas such as residential and marine protected areas, etc., adding potential health and safety risks.
By converting wind direction into vectors and calculating average vectors, continuity and pattern of change of wind direction can be captured more accurately. The cyclic variance can effectively process the limit problem between 360 degrees and 0 degrees, and the discontinuity error in the traditional variance calculation is avoided. Through real-time monitoring and quick response, the risk early warning is more timely and accurate. In addition, the method can effectively integrate a large amount of real-time data and provide a simple and visual index to evaluate the stability of the wind direction.
In S2, through the analysis of the pressure recovery capacity of the spherical storage tank, the leakage potential safety hazard degree of the spherical storage tank is estimated, and specifically:
Setting a pressure recovery monitoring interval, wherein the pressure recovery monitoring interval is a real-time monitoring interval, namely, the end point of the pressure recovery monitoring interval is always a real-time point, and the corresponding time length of the pressure recovery monitoring interval is determined according to the actual monitoring requirement for the pressure recovery capability of the spherical storage tank, for example, the time is set to be 10 hours.
And acquiring a pressure abnormal event in the pressure recovery monitoring interval, wherein the pressure abnormal event is the condition that the pressure in the spherical storage tank is not in a safe pressure range.
The number of pressure anomaly events occurring within the pressure recovery monitoring interval is determined.
And acquiring a pressure abnormal event recovery length, wherein the pressure abnormal event recovery length is a time range from when the pressure in the spherical storage tank starts to deviate from the safe pressure range to when the pressure is recovered to the safe pressure range.
The maximum offset in the pressure anomaly event is obtained, and the maximum offset in the pressure anomaly event refers to the maximum value of the pressure in the spherical storage tank in the pressure anomaly event, which deviates from the safe pressure range.
Calculating an abnormal recovery index of the storage tank, wherein the expression is as follows: ; wherein, Is an index of the abnormal recovery of the tank itself,For the number of pressure anomaly events occurring within the pressure recovery monitoring interval,For the corresponding length of time of the pressure recovery monitoring interval,Monitoring interval for pressure recoveryThe recovery length of the pressure abnormal event corresponding to the secondary pressure abnormal event,Monitoring interval for pressure recoveryThe maximum offset in the secondary pressure anomaly event,Is the number of the pressure abnormal event in the pressure recovery monitoring interval,AndAll represent weights, wherein,Is thatIs used for the weight of the (c),Is thatIs used for the weight of the (c),AndAre all greater than 0.
The expression of the abnormal recovery index of the storage tank indicates that the greater the abnormal recovery index of the storage tank is, the greater the potential safety hazard degree of the leakage of the spherical storage tank is, which indicates that the spherical storage tank has weak capability of recovering to the normal pressure state when the spherical storage tank encounters pressure change, and this means that the spherical storage tank is likely to have hidden danger or damage, such as micro cracks or poor sealing, which may not cause obvious leakage.
In S3, judging whether to start early warning of liquefied petroleum gas based on the messy degree of the wind direction of the port area and the leakage potential safety hazard degree of the spherical storage tank, specifically:
The wind direction disorder threshold is set by a person skilled in the art according to the magnitude of the wind direction disorder index and other practical situations such as safety requirement standards for adverse effects on liquefied petroleum gas of the spherical storage tank after leakage of the liquefied petroleum gas in the port area due to the disorder degree of the wind direction, and the like, and will not be repeated here.
When the wind direction disorder index is larger than the wind direction disorder threshold value, judging that a wind direction disorder degree large signal is generated; at this time, the harbour area wind direction is described to be greatly disordered.
When the wind direction disorder index is smaller than or equal to the wind direction disorder threshold value, judging that a normal signal of the wind direction disorder degree is generated; at this time, the port area is described the disorder degree of the wind direction is normal.
The abnormal recovery threshold value of the storage tank is set by a person skilled in the art according to the magnitude of the abnormal recovery index of the storage tank and other actual conditions such as safety requirement standards of the leakage potential safety hazard degree of the spherical storage tank in practice, and is not repeated here.
When the abnormal recovery index of the storage tank is larger than the abnormal recovery threshold of the storage tank, the generation of the abnormal risk signal of the storage tank is judged, and the leakage potential safety hazard degree of the spherical storage tank is larger.
When the abnormal recovery index of the storage tank is smaller than or equal to the abnormal recovery threshold of the storage tank, the generation of the normal signal of the storage tank is judged, and the condition that the leakage potential safety hazard degree of the spherical storage tank is smaller or does not exist is indicated.
When a signal with large wind direction disorder degree is generated or an abnormal risk signal of the storage tank is generated, starting early warning of liquefied petroleum gas; otherwise, the early warning of the liquefied petroleum gas is not started. The reason is as follows:
when the wind direction disorder index exceeds a set threshold value, the wind direction is unstable, and the leaked gas can be rapidly and unpredictably diffused, so that the difficulty and the potential hazard range for controlling the leakage are increased. Initiation of the early warning may be responsive more quickly, deploying necessary safety and control measures, such as enhancing monitoring, limiting portions of the operating area, or preparing the emergency response resource.
When the tank's own abnormal recovery index exceeds a threshold, it is indicated that the spherical tank has problems in pressure management, possibly due to leaks or other structural damage. In this case, the problem can be found in time by early warning, and necessary inspection and maintenance can be performed, thereby preventing the situation from deteriorating.
In S4, the component uniformity of the gas in the spherical tank is evaluated by analyzing the variation of the gas component in the spherical tank; the method comprises the following steps:
In the chemical and petroleum industries, it is critical to ensure uniformity of the stored gas or liquid in the spherical storage tanks. Non-uniformity of the composition may lead to safety risks, such as minor variations in the proportions of the composition during certain chemical processes, which may cause serious safety problems. Information entropy is a mathematical tool for measuring randomness of a system, is originally used in the field of information theory and is used for describing uncertainty or content of information. It was used to quantify the compositional uniformity of the gas in the spherical tank.
A plurality of sampling points are installed at different positions of the spherical tank. Multi-point sampling may help to obtain more comprehensive data because of stratification or aggregation of gas that may occur due to flow and temperature differences within the spherical tank.
And setting reasonable sampling frequency according to the stability of the operation condition and the dynamic change of the process. For a process with fast dynamic changes, it is recommended to sample once per hour; for more stable storage conditions, sampling once a day may be sufficient.
Normalization processing is carried out on the collected concentration data of each component, so that the sum is ensured to be 1, namely the proportion of each component meets the following conditions: ; wherein, Is the firstThe proportions of the individual components are such that,Is the firstThe concentration of the individual components is determined,Is the sum of all ingredient concentrations.
Normalization is necessary because it removes the influence of the measurement scale, making the data comparable at different time points and under different conditions.
Calculating a gas component uniformity value through an information entropy formula, wherein the expression is as follows: ; wherein, For the gas composition to be of uniform value,In order to determine the amount of the ingredients,Is the number of the component.
Wherein the method comprises the steps ofNatural logarithms are typically taken, but 2-base logarithms may also be taken, depending on the application context.
The gas composition uniformity value at each time point provides a snapshot of the instantaneous gas composition distribution at that time point when analyzing the gas composition uniformity within the spherical tank. Theoretically, if the operating conditions are stable and there is no disturbance (e.g., changes in the input materials, changes in the operation of the equipment, etc.), these gas composition uniformity values should be relatively fixed, exhibiting some stability.
In order to more fully monitor and evaluate the composition uniformity of the gas in the spherical tank, the calculation of such gas composition uniformity values can be extended to a series of time points, forming a time series analysis. Thus, not only can the condition of a single time point be observed, but also the dynamic change of the uniformity of the components along with the time can be analyzed.
Setting a gas uniform monitoring interval, wherein the gas uniform monitoring interval is a real-time monitoring interval, namely, the end point of the gas uniform monitoring interval is always a real-time point, and the time length corresponding to the gas uniform monitoring interval is determined according to the monitoring requirement of the gas uniformity in the spherical storage tank, for example, the time length is set to be 5 minutes.
Uniformly setting a plurality of monitoring points in a gas uniform monitoring interval, acquiring a gas component uniform value corresponding to each monitoring point, analyzing the change condition of the gas component uniform value in the gas uniform monitoring interval, and calculating a gas component uniformity index, wherein the expression is as follows: ; wherein, Is an index of the uniformity of the gas composition,For the number of monitoring points in the gas uniform monitoring interval,The number of the monitoring points in the gas uniform monitoring interval is given,Respectively the first gas uniform monitoring intervalGas component uniformity value corresponding to each monitoring point and first in gas uniformity monitoring intervalAnd the gas components corresponding to the monitoring points are uniform.
The greater the gas composition uniformity index, the poorer the composition uniformity of the gas in the spherical tank within the gas uniformity monitoring interval. Uneven composition distribution may lead to local pressure or chemical imbalance inside the spherical tank. For example, in the storage of liquid fuels or chemicals, certain areas may be more corrosive or reactive due to too high a concentration, which may accelerate wear of the spherical tank interior structure, thereby increasing the risk of leakage. If leakage occurs, compositional non-uniformities may result in unpredictable behavior of the leaked material. For example, certain components may be more volatile or reactive than others, which may behave very differently in the environment, thereby increasing the complexity and cost of handling leaks.
The density change degree of the gas in the spherical storage tank is evaluated, specifically:
Monitoring the gas density variation within a spherical tank is critical. The change in gas density may reflect a number of important physical and chemical processes such as temperature changes, pressure changes, chemical reactions, or leakage of substances. Thus, accurate assessment of the extent of these variations is necessary to ensure safe operation and process control.
Density sensors are mounted at strategic locations on the spherical tank, such as near the inlet and outlet, and in any known areas of flow dynamics complexity.
Ensuring that all sensors are accurately calibrated to provide reliable density data.
Gas density data for each monitoring point is continuously recorded.
A numerical partial derivative method is applied to the spatial data at each time point to calculate a density gradient.
The square of the density gradient is calculated to quantify the intensity of the density change for each point.
Calculating a density change abnormality index, the expression of which is: ; wherein, Is an abnormality index of density change; Expressed in time And positionIs a vector whose component is the partial derivative of the gas density in each direction; Is the volume within the spherical tank, used to define the spatial integration range of the model; Refers to the time frame considered and represents the start and end times of the analysis, respectively.
Wherein:
: density data for a particular location and time is acquired using a density sensor. Numerical partial derivatives methods (finite differences) are then applied to approximate these derivatives.
: Representing an infinitely small volume element in a spatial dimension; in the integration calculation, this is typically automatically handled by numerical integration methods, such as meshing.
: Representing an infinite small time interval in the time dimension; in implementing integration, the time step is typically determined by the sampling frequency.
: The integration process is from the start timeBy the end timeIs a time interval of (a). The start and end times of the monitoring are selected and the integration range is determined by the experiment or monitoring period.
: This is a spatial integration of the volume within the entire spherical tank.
The greater the density variation abnormality index, the more significant the density variation of the gas in the spherical storage tank, and the greater the degree of density variation of the gas in the spherical storage tank, the significant variation may be caused by factors such as leakage of liquefied petroleum gas in the spherical storage tank, temperature or pressure fluctuation, and the greater the risk of leakage of liquefied petroleum gas in the spherical storage tank.
The gas density over the whole volume and time range is analyzed in a continuous manner, providing comprehensive monitoring. By detecting unusual patterns of density variations, potential equipment failure or leakage events can be indicated as an early warning.
In S5, comprehensively analyzing the leakage potential safety hazard degree of the spherical storage tank, the component uniformity of the gas in the spherical storage tank and the density variation degree of the gas in the spherical storage tank, and early warning the potential safety hazard of the leakage of the liquefied petroleum gas in the port area, wherein the method specifically comprises the following steps:
And carrying out normalization treatment on the abnormal recovery index of the storage tank, the gas component uniformity index and the density change abnormal index, respectively endowing the normalized abnormal recovery index of the storage tank, the gas component uniformity index and the density change abnormal index with preset proportionality coefficients, and calculating to obtain a risk source leakage early warning coefficient.
The specific implementation manner of calculating the risk source leakage early-warning coefficient is not particularly limited herein, and the risk source leakage early-warning coefficient can be calculated after the normalized storage tank self abnormality recovery index, the gas composition uniformity index and the density variation abnormality index are respectively endowed with the preset proportion coefficient. The expression of the risk source leakage early warning coefficient is as follows: ; wherein, As the early warning coefficient of the leakage of the risk source,Respectively a preset proportion coefficient of an abnormal recovery index of the storage tank, a gas composition uniformity index and a density change abnormal index, andAre all greater than 0.
Wherein, the setting of the preset proportionality coefficient should consider the actual influence degree of each index on the safety of the spherical storage tank, and the sensitivity and reliability of each index. The following are several aspects that need to be considered in order to set the preset scaling factor:
Referencing industry standards and previous incident survey reports may help determine which factors historically have a greater impact on safety, and the index of these factors should be given a higher preset scaling factor.
Quantitative data on the impact of different parameter variations on the safety of the spherical tank can be obtained through experiments and simulations. These data can be used to adjust the preset scaling parameters based on the extent of influence of each index.
Sensitivity analysis was performed on the model to see how small changes in different indices affect the overall risk assessment results. The scaling factor may be adjusted according to its sensitivity to ensure stability and predictive accuracy of the model.
Ensuring that the preset scaling factor is set reflects a comprehensive risk assessment perspective, taking environmental, operational and technical risks into account.
The greater the abnormal recovery index of the storage tank is, the greater the potential safety hazard degree of leakage of the spherical storage tank is; the larger the gas composition uniformity index is, the worse the composition uniformity of the gas in the spherical storage tank is in the gas uniformity monitoring interval; the larger the density change abnormality index, the more remarkable the gas density change is; therefore, the expression of the risk source leakage early warning coefficient shows that the greater the risk source leakage early warning coefficient is, the greater the potential safety hazard of liquefied petroleum gas leakage is.
Setting a risk source leakage early warning threshold value, and carrying out early warning on potential safety hazards of liquefied petroleum gas leakage in a port area through comparison of a risk source leakage early warning coefficient and the risk source leakage early warning threshold value:
When the risk source leakage early warning coefficient is larger than the risk source leakage early warning threshold value, judging that a leakage risk early warning signal is generated, and indicating that the liquefied petroleum gas in the spherical storage tank has larger leakage risk at the moment, wherein the following problems possibly exist:
Indicating that the spherical tank itself may have structural defects or improper maintenance, making it difficult to quickly restore normal pressure after leakage has occurred.
It is shown that the gas is unevenly distributed within the spherical tank, possibly due to malfunction or improper operation of the internal stirring system.
Indicating a significant change in gas density, which may be due to excessive temperature fluctuations or gas leakage.
Measures to be taken after the leakage risk early warning signal is generated are as follows:
immediately a detailed check is made: the spherical tank is thoroughly physically inspected for possible structural problems or leaks.
Enhancement monitoring: monitoring of spherical tanks is enhanced, particularly with respect to real-time data on density and pressure, to facilitate timely discovery of signs of leakage.
Preparing emergency measures: ensuring that emergency response plans are updated and are ready for execution, including evacuation plans, leak control, and safety isolation measures.
Notifying the relevant departments: ensuring that all relevant personnel and departments are notified so that a quick response can be achieved.
When the risk source leakage early warning coefficient is smaller than or equal to the risk source leakage early warning threshold value, judging that a leakage risk normal signal is generated, and at the moment, indicating that the liquefied petroleum gas in the spherical storage tank has smaller or no leakage risk and no measures are needed.
The risk source leakage early warning threshold is set by a person skilled in the art according to the magnitude of the risk source leakage early warning coefficient and other actual conditions such as safety requirement standards of liquefied petroleum gas leakage hidden danger in the spherical storage tank in practice, and will not be described herein.
Example 2
The difference between embodiment 2 and embodiment 1 of the present invention is that this embodiment describes an environmental risk source early warning system.
Fig. 2 shows a schematic structural diagram of an environmental risk source early warning system according to the present invention, which includes a wind direction clutter evaluation module, a pressure recovery evaluation module, an early warning start judgment module, an early warning information acquisition module, and a risk hidden danger early warning module.
The wind direction clutter evaluation module evaluates the clutter degree of the wind direction of the port area through analyzing the real-time wind direction of the port area.
The pressure recovery evaluation module evaluates the leakage potential safety hazard degree of the spherical storage tank by analyzing the pressure recovery capability of the spherical storage tank.
The early warning start judging module judges whether to start early warning of liquefied petroleum gas based on the messy degree of the wind direction of the port area and the leakage potential safety hazard degree of the spherical storage tank.
When the early warning of the liquefied petroleum gas is started: the early warning information acquisition module evaluates the component uniformity of the gas in the spherical storage tank by analyzing the change of the gas component in the spherical storage tank; the degree of density change of the gas inside the spherical tank was evaluated.
The risk potential hazard early warning module comprehensively analyzes the leakage potential safety hazard degree of the spherical storage tank, the component uniformity of the gas in the spherical storage tank and the density variation degree of the gas in the spherical storage tank, and early warns the potential safety hazard of the leakage of the liquefied petroleum gas in the port area.
The above formulas are all formulas with dimensionality removed and numerical calculation, the formulas are formulas with the latest real situation obtained by software simulation through collecting a large amount of data, and preset parameters and threshold selection in the formulas are set by those skilled in the art according to the actual situation.
The above embodiments may be implemented in whole or in part by software, hardware, firmware, or any other combination. When implemented in software, the above-described embodiments may be implemented in whole or in part in the form of a computer program product. The computer program product comprises one or more computer instructions or computer programs. When the computer instructions or computer program are loaded or executed on a computer, the processes or functions described in accordance with embodiments of the present application are produced in whole or in part. The computer may be a general purpose computer, a special purpose computer, a network of computers, or other programmable devices. The computer instructions may be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another computer-readable storage medium, for example, the computer instructions may be transmitted from one website site, computer, server, or data center to another website site, computer, server, or data center by wired (e.g., infrared, wireless, microwave, etc.). The computer readable storage medium may be any available medium that can be accessed by a computer or a data storage device such as a server, data center, etc. that contains one or more sets of available media. The usable medium may be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium. The semiconductor medium may be a solid state disk.
Those of ordinary skill in the art will appreciate that the various illustrative modules and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
It will be clearly understood by those skilled in the art that, for convenience and brevity of description, specific working procedures of the above-described system, apparatus and module may refer to corresponding procedures in the foregoing method embodiments, which are not repeated herein.
In the several embodiments provided in the present application, it should be understood that the disclosed system, apparatus and method may be implemented in other manners. For example, the apparatus embodiments described above are merely illustrative, and for example, the division of the modules is merely a logical function division, and there may be additional divisions when actually implemented, for example, multiple modules or components may be combined or integrated into another system, or some features may be omitted or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be an indirect coupling or communication connection via some interfaces, devices or modules, which may be in electrical, mechanical, or other forms.
The modules described as separate components may or may not be physically separate, and components shown as modules may or may not be physical modules, may be located in one place, or may be distributed over multiple network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional module in each embodiment of the present application may be integrated into one processing module, or each module may exist alone physically, or two or more modules may be integrated into one module.
The functions, if implemented in the form of software functional modules and sold or used as a stand-alone product, may be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution, in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server, a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a read-only memory (ROM), a random access memory (random access memory, RAM), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
The foregoing is merely illustrative of the present application, and the present application is not limited thereto, and any person skilled in the art will readily recognize that variations or substitutions are within the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Finally: the foregoing description of the preferred embodiments of the invention is not intended to limit the invention to the precise form disclosed, and any such modifications, equivalents, and alternatives falling within the spirit and principles of the invention are intended to be included within the scope of the invention.
Claims (8)
1. The environment risk source early warning method is characterized by comprising the following steps:
s1: by analyzing the real-time wind direction of the port area, the clutter degree of the wind direction of the port area is estimated;
s2: the potential leakage safety hazard degree of the spherical storage tank is estimated through analysis of the pressure recovery capacity of the spherical storage tank;
s3: judging whether to start early warning of liquefied petroleum gas based on the messy degree of the wind direction of the port area and the leakage potential safety hazard degree of the spherical storage tank;
S4: when the early warning of the liquefied petroleum gas is started: evaluating the uniformity of the composition of the gas in the spherical storage tank by analyzing the variation of the composition of the gas in the spherical storage tank; evaluating the density change degree of the gas in the spherical storage tank;
S5: and comprehensively analyzing the leakage potential safety hazard degree of the spherical storage tank, the component uniformity of the gas in the spherical storage tank and the density change degree of the gas in the spherical storage tank, and pre-warning the potential safety hazard of the leakage of the liquefied petroleum gas in the port area.
2. The environmental risk source early warning method according to claim 1, wherein in S1, specifically:
collecting real-time wind direction data of a port area, and recording a wind direction angle;
converting the continuous wind direction angle into a unit vector; for each wind direction angle, its unit vector is calculated: ; wherein, Is the firstThe unit vector of the secondary wind direction angle,Is the firstThe wind direction angle of the secondary measurement,Numbering the wind direction angle;
Calculating an average vector of the unit vectors: ; wherein, Is the average vector of the unit vectors,Is the total number of measurements of wind direction angle;
the wind direction clutter index is obtained through the calculation of the circulation variance, and the expression is as follows: ; wherein, In the form of a wind-direction disorder index,Respectively the average vector of the unit vectorsComponents andA component.
3. The environmental risk source early warning method according to claim 2, wherein in S2, specifically:
Setting a pressure recovery monitoring interval;
Acquiring a pressure abnormal event in a pressure recovery monitoring interval; determining the number of pressure anomaly events occurring within the pressure recovery monitoring interval; acquiring the recovery length of the pressure abnormal event; obtaining the maximum offset in the pressure abnormal event;
Calculating an abnormal recovery index of the storage tank, wherein the expression is as follows: ; wherein, Is an index of the abnormal recovery of the tank itself,For the number of pressure anomaly events occurring within the pressure recovery monitoring interval,For the corresponding length of time of the pressure recovery monitoring interval,Monitoring interval for pressure recoveryThe recovery length of the pressure abnormal event corresponding to the secondary pressure abnormal event,Monitoring interval for pressure recoveryThe maximum offset in the secondary pressure anomaly event,Is the number of the pressure abnormal event in the pressure recovery monitoring interval,AndAll of which represent the weight of the object,AndAre all greater than 0.
4. The environmental risk source warning method according to claim 3, wherein in S3, specifically:
setting a wind direction disorder threshold; comparing the wind direction hash index to a wind direction hash threshold:
when the wind direction disorder index is larger than the wind direction disorder threshold value, judging that a wind direction disorder degree large signal is generated;
When the wind direction disorder index is smaller than or equal to the wind direction disorder threshold value, judging that a normal signal of the wind direction disorder degree is generated;
Setting an abnormal recovery threshold value of the storage tank; comparing the tank self-anomaly recovery index with a tank self-anomaly recovery threshold value:
When the abnormal recovery index of the storage tank is larger than the abnormal recovery threshold value of the storage tank, judging that an abnormal risk signal of the storage tank is generated;
When the abnormal recovery index of the storage tank is smaller than or equal to the abnormal recovery threshold of the storage tank, judging that a normal signal of the storage tank is generated;
When a signal with large wind direction disorder degree is generated or an abnormal risk signal of the storage tank is generated, the early warning of the liquefied petroleum gas is started.
5. The environmental risk source warning method according to claim 4, wherein in S4, specifically:
the ratio of each component is calculated, and the formula is: ; wherein, Is the firstThe proportions of the individual components are such that,Is the firstThe concentration of the individual components is determined,Is the sum of all ingredient concentrations;
calculating a gas component uniformity value through an information entropy formula, wherein the expression is as follows: ; wherein, For the gas composition to be of uniform value,In order to determine the amount of the ingredients,Is the number of the component;
Setting a gas uniform monitoring interval; uniformly setting a plurality of monitoring points in a gas uniform monitoring interval, acquiring a gas component uniform value corresponding to each monitoring point, analyzing the change condition of the gas component uniform value in the gas uniform monitoring interval, and calculating a gas component uniformity index, wherein the expression is as follows: ; wherein, Is an index of the uniformity of the gas composition,For the number of monitoring points in the gas uniform monitoring interval,The number of the monitoring points in the gas uniform monitoring interval is given,Respectively the first gas uniform monitoring intervalGas component uniformity value corresponding to each monitoring point and first in gas uniformity monitoring intervalAnd the gas components corresponding to the monitoring points are uniform.
6. The environmental risk source warning method according to claim 5, wherein the assessment of the degree of density change of the gas in the spherical storage tank is specifically:
applying a numerical partial derivative method to the spatial data at each time point to calculate a density gradient;
calculating the square of the density gradient;
Calculating a density change abnormality index, the expression of which is: ; wherein, In order to change the abnormality index of the density,Expressed in timeAnd positionIs used for the gas density gradient of (a),Is the volume within the spherical storage tank,Representing the start and end times of the analysis, respectively.
7. The environmental risk source warning method according to claim 6, wherein in S5, specifically:
Normalizing the abnormal recovery index of the storage tank, the gas component uniformity index and the density change abnormal index, respectively endowing the normalized abnormal recovery index of the storage tank, the normalized gas component uniformity index and the normalized density change abnormal index with preset proportionality coefficients, and calculating to obtain risk source leakage early warning coefficients;
setting a risk source leakage early warning threshold value, and carrying out early warning on potential safety hazards of liquefied petroleum gas leakage in a port area through comparison of a risk source leakage early warning coefficient and the risk source leakage early warning threshold value:
when the risk source leakage early warning coefficient is larger than the risk source leakage early warning threshold value, judging that a leakage risk early warning signal is generated;
And when the risk source leakage early warning coefficient is smaller than or equal to the risk source leakage early warning threshold value, judging that a leakage risk normal signal is generated.
8. An environmental risk source early warning system for implementing the environmental risk source early warning method according to any one of claims 1 to 7, which is characterized by comprising a wind direction clutter evaluation module, a pressure recovery evaluation module, an early warning start judgment module, an early warning information acquisition module and a risk hidden danger early warning module;
the wind direction clutter evaluation module evaluates the clutter degree of the wind direction of the port area through analyzing the real-time wind direction of the port area;
The pressure recovery evaluation module evaluates the leakage potential safety hazard degree of the spherical storage tank by analyzing the pressure recovery capacity of the spherical storage tank;
The early warning starting judging module judges whether to start early warning of the liquefied petroleum gas based on the messy degree of the wind direction of the port area and the leakage potential safety hazard degree of the spherical storage tank;
When the early warning of the liquefied petroleum gas is started: the early warning information acquisition module evaluates the component uniformity of the gas in the spherical storage tank by analyzing the change of the gas component in the spherical storage tank; evaluating the density change degree of the gas in the spherical storage tank;
The risk potential hazard early warning module comprehensively analyzes the leakage potential safety hazard degree of the spherical storage tank, the component uniformity of the gas in the spherical storage tank and the density variation degree of the gas in the spherical storage tank, and early warns the potential safety hazard of the leakage of the liquefied petroleum gas in the port area.
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