H2S leakage diffusion range prediction method and system

Abstract

The invention belongs to the technical field of gas diffusion safety engineering, and relates to a H2S leakage diffusion range prediction method and system, and the method comprises the steps: arranging a plurality of different sensors in a predicted leakage region; calculating predicted concentration values of different sensors according to weather information and H2S mass fraction of a predicted leakage region; a target function is set according to the predicted concentration values of different sensors, and the leakage point position and the gas mass release speed are obtained; and according to the unsteady instantaneous point source puff superposition model, simulating the leakage point position and the gas mass release velocity diffusion to obtain the H2S leakage diffusion range. The system comprises a setting module, a calculation module, an acquisition module and a diffusion simulation module. According to the method and the system, the problems of small monitoring range, high possibility of missing report, insufficient H2S early warning capability and the like of the existing point type sensor are effectively solved; and the leakage source information is inversed by using the linear sensor information, so that the prediction precision can be further improved.

Description

Technical Field

[0001] The invention belongs to the technical field of gas diffusion safety engineering, and in particular relates to a method and system for predicting the H2S leakage diffusion range. Background Art

[0002] H2S gas leakage is one of the major disasters in the production and development of the petroleum and petrochemical industries. It is highly concealed, sudden and harmful. Once the leaked hydrogen sulfide spreads over a large area, it may cause acute and serious casualties, seriously threaten on-site workers, and may even cause public harm. H2S gas leakage is often sudden, resulting in uncertainty in the time, location and environment of the leak.

[0003] Therefore, in the event of an emergency, it is very necessary to identify the unknown leakage source in the shortest time possible, so as to further determine the emergency evacuation area and safe distance, and provide a basis for emergency decision-making. Traditional prediction and early warning of H2S gas leakage are mostly based on point sensors, which have a small monitoring range and are prone to underreporting; linear sensors are rarely considered for prediction and early warning of H2S gas leakage, but linear sensors have a large measurement range and can obtain H2S gas leakage information more quickly. Therefore, it is very necessary and meaningful to carry out prediction of H2S leakage diffusion range based on linear sensors. Summary of the invention

[0004] In view of the above problems, the technical solution adopted by the present invention is as follows: a method for predicting the spread range of H2S leakage, the method comprising the following steps: setting a plurality of different sensors in the predicted leakage area; calculating the predicted concentration values ​​of different sensors according to the meteorological information of the predicted leakage area and the H2S mass fraction; setting the objective function according to the predicted concentration values ​​of different sensors to obtain the leakage point position and the gas mass release rate; and simulating the diffusion of the leakage point position and the gas mass release rate according to the non-steady-state instantaneous point source smoke puff superposition model to obtain the H2S leakage spread range.

[0005] Further, the setting of a plurality of different sensors in the predicted leakage area includes: arranging a plurality of point and line H2S sensors in the predicted leakage area, and numbering the plurality of point and line H2S sensors, wherein the point sensors are numbered D i , the coordinates are (x Di ,y Di , z Di ); the serial number of the linear sensor is S i , the coordinates are (x1 Si , y1 Si , z1 Si ) and (x2 Si , y2 Si , z2 Si), i represents the number of different sensors, i = 1, 2...n; obtain the measured concentration value C of each point sensor Di And the measured concentration value C of the linear sensor Si .

[0006] Furthermore, the meteorological information of the leakage area includes atmospheric stability, wind speed, and wind direction.

[0007] Furthermore, according to the meteorological information and H2S mass fraction of the predicted leakage area, the predicted concentration values ​​of different sensors are calculated, including: inputting the atmospheric stability, wind speed, wind direction and H2S mass fraction of the predicted leakage area into the calculation model, and calculating the predicted concentration value of the point sensor for:

[0008]

[0009] Among them, Y H2S Q is the mass fraction of H2S in the leaked gas; m is the gas mass release rate; H r is the height of the leakage source; u is the ambient wind speed; σ x* , σ y* , σ z* are the diffusion coefficients in the downwind, crosswind and vertical directions of the wind field, respectively, and are related to the atmospheric stability; x*, y*, z* are the new relative coordinates after rotation and translation considering that the wind direction and the leakage source are not at the origin (x0, y0, z0);

[0010] x*=(x-x0)cosθ+(y-y0)sinθ;

[0011] y*=(y-y0)cosθ-(x-x0)sinθ;

[0012] z*=z0.

[0013] Furthermore, according to the meteorological information and H2S mass fraction of the predicted leakage area, the predicted concentration values ​​of different sensors are calculated, including: inputting the atmospheric stability, wind speed, wind direction and H2S mass fraction of the predicted leakage area into the calculation model, and calculating the predicted concentration value of the linear sensor for: C L1 , C L2 , ...C Ln It represents the predicted concentration value of the 1st, 2nd and nth linear sensors;

[0014] The predicted concentration value C of the jth linear sensor Lj (x j ,y j ,z j )for:

[0015]

[0016] The linear sensor is cut into n segments, and the coordinates of the center point of the jth segment (x j * ,y j * , z j * )for:

[0017]

[0018]

[0019]

[0020] in, Q is the mass fraction of H2S in the leaked gas; m is the gas mass release rate; H r is the height of the leakage source; u is the ambient wind speed; σ xj* , σ yj* , σ zj* are the diffusion coefficients in the downwind, crosswind and vertical directions of the wind field respectively; (x0, y0, z0) are the coordinates of the leakage point in the coordinate system assuming that the leakage source is located at the origin.

[0021] Furthermore, the objective function is set according to the predicted concentration values ​​of different sensors to obtain the leakage point location and the gas mass release rate, including: when the leakage point location and the gas mass release rate Q m When determining, the exhaustive method is used to set the objective function W as: Among them, C Di and C Si They are the measured concentration values ​​of the point sensor and the line sensor respectively. and are the predicted concentration values ​​of the point sensor and the line sensor, n is the number of point sensors, and m is the number of line sensors; when the objective function W is the smallest, the corresponding leakage point position and gas mass release rate Q m The exhaustive method is used to obtain the leakage point location and gas mass release rate results.

[0022] Furthermore, the objective function is set according to the predicted concentration values ​​of different sensors to obtain the leakage point location and the gas mass release rate, including: when the leakage point location and the gas mass release rate Q m When uncertain, the particle swarm method is used to set the objective function, including: initializing the leakage point position and gas mass release rate Q of each particle m ; According to the leakage point location and gas mass release speed Qm , calculate the objective function W of each particle; calculate the individual optimal solution of each particle; calculate the global optimal solution of the particle community; according to the individual optimal solution and the global optimal solution, the leakage point position and gas mass release rate Q in the objective function are calculated. m Update; determine the updated leak point location and gas mass release rate Q m Whether the set conditions are met. If the set conditions are met, the updated leakage point position and gas mass release speed Q are output m ; If the set conditions are not met, return to the leak point location and gas mass release speed Q m , calculate the objective function W of each particle.

[0023] Furthermore, assuming that in a 4-dimensional target search space, a community is composed of N particles; then the initial leakage point position of the i-th particle is Then the gas mass release rate after initialization is Q m It is expressed as: i=1,2,3……N;

[0024] The flying speed v of the i-th particle i :v i =(v i1 ,v i2 ,v i3 ,v i4 );

[0025] The optimal position searched by the i-th particle so far is the individual optimal solution p best :

[0026] p best =(p i1 ,p i2 ,p i3 ,p i4 );

[0027] The optimal position searched by the entire particle swarm so far is the global optimal solution g best :

[0028] g best =(p g1 ,p g2 ,p g3 ,p g4 );

[0029] Each particle follows the current optimal particle in the solution space and updates its own speed and position according to the speed transformation formula and position transformation formula. The speed transformation formula is:

[0030] v id (t+1)=wv id(t)+c1r1(p id -A id (t))+c2r2(p gd -A id (t));

[0031] The position transformation formula is:

[0032] A id (t+1)=A id (t)+v id (t+1);

[0033] Among them, w is the inertia weight; c1 and c2 are learning factors, which respectively reflect the particle's self-learning ability and the ability to learn from the optimal particle in the group; r1 and r2 are uniform random numbers in [0,1]; v i The value range is [-v max ,v max ],v max To set a constant, it means limiting the speed of the particle.

[0034] Furthermore, according to the non-steady-state instantaneous point source puff superposition model, the leakage point position and the gas mass release rate diffusion simulation are carried out, and the H2S leakage diffusion range is obtained, including: According to the non-steady-state instantaneous point source puff superposition model, the leakage point position and the gas mass release rate diffusion simulation are carried out. The non-steady-state instantaneous point source puff superposition model treats continuous leakage as continuous instantaneous leakage. The H2S concentration at a certain point in space at a certain moment is equal to the sum of the H2S concentrations of all puffs released at that moment at that point in space; that is:

[0035]

[0036] in, Q is the mass fraction of H2S in the leaked gas; m is the gas mass release rate; H r is the height of the leakage source; u is the ambient wind speed; σ x* , σ y* , σ z* are the diffusion coefficients of the downwind, crosswind and vertical directions of the wind field respectively; x*, y*, z* represent the positions after coordinate transformation; t represents a certain moment; C' D (x, y, z) represents the H2S concentration at the spatial coordinate point (x, y, z) at a certain moment.

[0037] In addition, the present invention also provides an H2S leakage diffusion range prediction system, which includes a setting module, a calculation module, an acquisition module and a diffusion simulation module; the setting module is used to set a plurality of different sensors in the predicted leakage area; the calculation module is used to calculate the predicted concentration values ​​of different sensors according to the meteorological information of the predicted leakage area and the H2S mass fraction; the acquisition module is used to set the objective function according to the predicted concentration values ​​of different sensors, and obtain the leakage point position and the gas mass release rate; the diffusion simulation module is used to simulate the diffusion of the leakage point position and the gas mass release rate according to the non-steady-state instantaneous point source smoke puff superposition model, and obtain the H2S leakage diffusion range.

[0038] The present invention proposes a method and system for predicting the spread range of H2S leakage, which can effectively solve the problems of small monitoring range, easy underreporting, and insufficient H2S early warning capability of existing point sensors; the method is based on the design of linear sensors, which have a large monitoring range, and uses linear sensor information to invert leakage source information, which can further improve the prediction accuracy. At the same time, the method and system for predicting the spread range of H2S leakage can be applied in the field of gas diffusion technology in safety engineering, which can promote the development of H2S monitoring and early warning technology, help H2S leakage risk early warning and emergency disposal decision-making, and reduce casualties caused by H2S leakage.

[0039] Other features and advantages of the present invention will be described in the following description, and part of them will become obvious from the description, or be understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained through the description and the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0041] Figure 1 It is a flow chart of a method for predicting the diffusion range of H2S leakage;

[0042] Figure 2 This is a schematic diagram of the location of the sensor and H2S leakage area;

[0043] Figure 3 A flow chart of setting the objective function using the particle swarm method;

[0044] Figure 4 A schematic diagram of a H2S leakage diffusion range prediction system;

[0045] Figure numerals: 1. Predicted leakage area; 2. H2S leakage source location; 3. Point sensor; 4. Line sensor. DETAILED DESCRIPTION

[0046] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below. Obviously, the described embodiments are 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.

[0047] A method for predicting the spread of H2S leakage, such as Figure 1 As shown, the method includes the following steps: S1, setting a plurality of different sensors in the predicted leakage area; S2, calculating the predicted concentration values ​​of different sensors according to the meteorological information of the predicted leakage area and the H2S mass fraction; S3, setting the objective function according to the predicted concentration values ​​of different sensors to obtain the leakage point position and the gas mass release rate; S4, simulating the diffusion of the leakage point position and the gas mass release rate according to the non-steady-state instantaneous point source smoke puff superposition model, and obtaining the H2S leakage diffusion range.

[0048] Specifically, step S1 includes: Figure 2 As shown, a plurality of point sensors 3 and a plurality of line sensors 4 are arranged in the predicted leakage area 1 (the H2S leakage source position 2 is in the predicted leakage area 1), and the plurality of point sensors 3 and the plurality of line sensors 4 are numbered. The number of the point H2S sensor 3 is D i , the coordinates are (x Di ,y Di , z Di ); Linear sensor 4 is numbered S i , the coordinates are (x1 Si , y1 Si , z1 Si ) and (x2 Si , y2 Si , z2 Si ), i represents the number of different sensors, i = 1, 2...n; obtain the measured concentration value C of each point sensor 3 Di and the measured concentration value C of the line sensor 4 Si .

[0049] Specifically, in step S2, the meteorological information of the leakage area is predicted to include atmospheric stability, wind speed, wind direction, etc. It should be noted that the meteorological information does not include the location of the leakage source and the leakage amount of the leakage source; step S2 includes: according to the meteorological information of the leakage area predicted to occur and the H2S mass fraction, respectively calculating the predicted concentration values ​​of the point sensor 3 and the line sensor 4, wherein the predicted concentration value calculation process of the point sensor 3 is: inputting the atmospheric stability, wind speed, wind direction and H2S mass fraction of the leakage area predicted to occur into the calculation model (Pasquill-Gifford diffusion model), and calculating the predicted concentration value of the point sensor for:

[0050]

[0051] Q is the mass fraction of H2S in the leaked gas; m is the gas mass release rate; H r is the height of the leakage source; u is the ambient wind speed; σ x* , σ y* , σ z* are the diffusion coefficients in the downwind, crosswind and vertical directions of the wind field, respectively, and are related to the atmospheric stability; x*, y*, z* are the new relative coordinates after rotation and translation after considering the wind direction and the leakage source is not at the origin (x0, y0, z0),

[0052] x*=(x-x0)cosθ+(y-y0)sinθ;

[0053] y*=(y-y0)cosθ-(x-x0)sinθ;

[0054] z*=z0;

[0055] The calculation process of the predicted concentration value of the linear sensor 4 is as follows: the atmospheric stability, wind speed, wind direction and H2S mass fraction of the predicted leakage area are input into the calculation model to calculate the predicted concentration value of the linear sensor 4. for: C L1 , C L2 , ...C Ln represents the predicted concentration values ​​of the 1st, 2nd, and nth linear sensors; the predicted concentration value C of the jth linear sensor Lj (x j ,y j ,z j )for:

[0056]

[0057] The linear sensor is cut into n segments, and the coordinates of the center point of the jth segment (x j* ,y j * , z j * )for:

[0058]

[0059]

[0060]

[0061] After considering the influence of wind direction, the coordinate calculation method after rotation is the same as that of the point sensor.

[0062] Specifically, step S3 includes: when the leakage point position and gas mass release speed Q m When it is relatively certain, the exhaustive method is used. Each possible leakage point information is recorded as (x 0k ,y 0k , z 0k , Q mk ), calculate the predicted concentration values ​​of the point sensor 3 and the line sensor 4 through step S2, and use the exhaustive method to select the sum of squares of concentration deviations as the objective function W: Among them, C Di and C Si are the measured concentration values ​​of point sensor 3 and line sensor 4 respectively, and are the predicted concentration values ​​of point sensor 4 and line sensor 4 respectively, n is the number of point sensors, and m is the number of line sensors. When the objective function W is the smallest, the corresponding leakage point position and gas mass release rate Q m The exhaustive method is used to obtain the leakage point location and gas mass release rate results.

[0063] Step S3 includes: when the leakage point position and gas mass release speed Q m When uncertain, the particle swarm method is used to set the objective function, such as Figure 3 As shown in Figure 2, the objective function is set by the particle swarm method, which includes the following steps: initializing the leakage point position and gas mass release rate Q of each particle m ; According to the leakage point location and gas mass release speed Q m , calculate the objective function W of each particle; calculate the individual optimal solution of each particle; calculate the global optimal solution of the particle community; according to the individual optimal solution and the global optimal solution, the leakage point position and gas mass release rate Q in the objective function are calculated. m Update; determine the updated leak point location and gas mass release rate Q mWhether the set conditions are met. If the set conditions are met, the updated leakage point position and gas mass release speed Q are output m ; If the set conditions are not met, return to the leak point location and gas mass release speed Q m , calculate the objective function W of each particle. The setting condition may be the set number of iterations, a typical value such as 100 or 200 times; or the relative change value of the objective function is less than 3%.

[0064] In the embodiment of the present invention, it is assumed that in a 4-dimensional target search space, a colony is formed by N particles; then the leakage point position of the i-th particle is initialized and gas mass release rate Q m , gas mass release rate Q after initialization m for: i=1,2,3……N;flying speed v of the ith particle i For: v i =(v i1 ,v i2 ,v i3 ,v i4 ); The optimal position searched by the i-th particle so far is the individual optimal solution p best For: p best =(p i1 ,p i2 ,p i3 ,p i4 ); The optimal position searched by the entire particle swarm so far is the global optimal solution g best is: g best =(p g1 ,p g2 ,p g3 ,p g4 ); Each particle follows the current optimal particle in the solution space and updates its own speed and position according to the speed transformation formula and position transformation formula. The speed transformation formula is: id (t+1)=wv id (t)+c1r1(p id -A id (t))+c2r2(p gd -A id (t)); the position transformation formula is: A id (t+1)=A id (t)+v id (t+1); where w is the inertia weight; c1 and c2 are learning factors, which respectively reflect the particle's self-learning ability and its ability to learn from the optimal particle in the group; r1 and r2 are uniform random numbers in [0,1]; the flight speed v i The value range is [-vmax ,v max ],v max To set a constant to limit the speed of particles.

[0065] Specifically, step S4 includes: at the initial moment of continuous leakage, the concentration distribution of the leaked material in the environment is not only a function of space, but also a function of time. Therefore, for unsteady states, the Pasquill-Gifford puff superposition model (unsteady-state instantaneous point source puff superposition model) is used for diffusion simulation. The Pasquill-Gifford puff superposition model regards continuous leakage as continuous instantaneous leakage, that is, the continuous smoke plume is regarded as composed of continuous puffs. In this way, the concentration at a certain point in space at a certain moment is equal to the sum of the concentrations of all puffs released at that moment at that point in space. According to the Pasquill-Gifford puff superposition model simulation, the H2S concentration at a certain point in space at a certain moment is obtained, and the H2S concentration is the leakage diffusion range to be finally obtained. The mathematical expression of the Pasquill-Gifford puff superposition model is as follows:

[0066]

[0067]

[0068] in, Q is the mass fraction of H2S in the leaked gas; m is the gas mass release rate; H r is the height of the leakage source; u is the ambient wind speed; σ x* , σ y* , σ z* are the diffusion coefficients of the downwind, crosswind and vertical directions of the wind field respectively; x*, y*, z* represent the positions after coordinate transformation; t represents a certain moment; C' D (x, y, z) represents the H2S concentration at the spatial coordinate point (x, y, z) at a certain moment.

[0069] In addition, the present invention also relates to a H2S leakage diffusion range prediction system, such as Figure 4 As shown, the system includes a setting module 11, a calculation module 12, an acquisition module 13 and a diffusion simulation module 14; the setting module 11 is used to set a plurality of different sensors in the predicted leakage area; the calculation module 12 is used to calculate the predicted concentration values ​​of different sensors according to the meteorological information of the predicted leakage area and the H2S mass fraction; the acquisition module 13 is used to set the objective function according to the predicted concentration values ​​of different sensors, and obtain the leakage point position and the gas mass release rate; the diffusion simulation module 14 is used to simulate the diffusion of the leakage point position and the gas mass release rate according to the non-steady-state instantaneous point source smoke puff superposition model, and obtain the H2S leakage diffusion range.

[0070] Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent substitutions for some of the technical features therein; and these modifications or substitutions do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for predicting the spread range of H2S leakage, characterized in that: The method comprises the following steps: Setting up a number of different sensors in the area where the leak is predicted to occur; Calculate the predicted concentration values ​​of different sensors based on the meteorological information and H2S mass fraction of the predicted leakage area; The objective function is set according to the predicted concentration values ​​of different sensors to obtain the leakage point location and gas mass release rate; According to the non-steady-state instantaneous point source puff superposition model, the leakage point location and gas mass release rate diffusion simulation are carried out to obtain the H2S leakage diffusion range.

2. The method according to claim 1, characterized in that The method of setting a plurality of different sensors in the predicted leakage area includes: Arrange multiple point and line H2S sensors in the predicted leakage area and number them. The point sensor is numbered D. i , the coordinates are (x Di ,y Di , z Di ); the serial number of the linear sensor is S i , the coordinates are (x1 Si ,y1 Si , z1 Si ) and (x2 Si , y2 Si , z2 Si ), i represents the number of different sensors, i = 1, 2, ..., n; obtain the measured concentration value C of each point sensor Di And the measured concentration value C of the linear sensor Si .

3. The method according to claim 2, characterized in that The meteorological information of the leakage area includes atmospheric stability, wind speed and wind direction.

4. The method according to claim 3, characterized in that The calculation of predicted concentration values ​​of different sensors according to the predicted meteorological information of the leakage area and the H2S mass fraction includes: The atmospheric stability, wind speed, wind direction and H2S mass fraction in the predicted leakage area are input into the calculation model to calculate the predicted concentration value of the point sensor. for: in, Q is the mass fraction of H2S in the leaked gas; m is the gas mass release rate; H r is the height of the leakage source; u is the ambient wind speed; σ x* , σ y* , σ z* are the diffusion coefficients in the downwind, crosswind and vertical directions of the wind field, respectively, and are related to the atmospheric stability; x*, y*, z* are the new relative coordinates after rotation and translation considering that the wind direction and the leakage source are not at the origin (x0, y0, z0); x*=(x-x0)cosθ+(y-y0)sinθ; y*=(y-y0)cosθ-(x-x0)sinθ; z*=z0.

5. The method according to claim 3, characterized in that: The calculation of predicted concentration values ​​of different sensors according to the predicted meteorological information of the leakage area and the H2S mass fraction includes: The atmospheric stability, wind speed, wind direction and H2S mass fraction in the predicted leakage area are input into the calculation model to calculate the predicted concentration value of the line sensor. for: C L1 , C L2 , ...C Ln It represents the predicted concentration value of the 1st, 2nd and nth linear sensors; The predicted concentration value C of the jth linear sensor Lj (x j ,y j ,z j )for: The linear sensor is cut into n segments, and the coordinates of the center point of the jth segment (x j * ,y j * , z j * )for: in, Q is the mass fraction of H2S in the leaked gas; m is the gas mass release rate; H r is the height of the leakage source; u is the ambient wind speed; σ xj* , σ yj* , σ zj* are the diffusion coefficients in the downwind, crosswind and vertical directions of the wind field respectively; (x0, y0, z0) are the coordinates of the leakage point in the coordinate system assuming that the leakage source is located at the origin.

6. The method according to claim 4 or 5, characterized in that: The objective function is set according to the predicted concentration values ​​of different sensors to obtain the leakage point location and the gas mass release rate, including: When the leakage point location and gas mass release rate Q m When determining, the exhaustive method is used to set the objective function W as: Among them, C Di and C Si They are the measured concentration values ​​of the point sensor and the line sensor respectively. and are the predicted concentration values ​​of the point sensor and the line sensor, respectively, n is the number of point sensors, and m is the number of line sensors; When the objective function W is the smallest, the corresponding leakage point position and gas mass release rate Q m The exhaustive method is used to obtain the leakage point location and gas mass release rate results.

7. The method according to claim 4 or 5, characterized in that: The objective function is set according to the predicted concentration values ​​of different sensors to obtain the leakage point location and the gas mass release rate, including: When the leakage point location and gas mass release rate Q m When uncertain, the particle swarm method is used to set the objective function, including: Initialize the leakage point position and gas mass release rate Q of each particle m ; According to the leakage point location and gas mass release speed Q m , calculate the objective function W of each particle; Calculate the individual optimal solution for each particle; Calculate the global optimal solution for each particle group; According to the individual optimal solution and the global optimal solution, the leakage point position and the gas mass release rate Q in the objective function are calculated. m Make updates; Determine the updated leak point location and gas mass release rate Q m Whether the set conditions are met. If the set conditions are met, the updated leakage point position and gas mass release speed Q are output m ; If the set conditions are not met, it will return to the original state according to the leak point location and gas mass release speed Q. m , calculate the objective function W of each particle.

8. The method according to claim 6, characterized in that Assume that in a four-dimensional target search space, a community is composed of N particles; then the initial leakage point position of the i-th particle is Then the gas mass release rate after initialization is Q m It is expressed as: The flying speed v of the i-th particle i :v i =(v i1 ,v i2 ,v i3 ,v i4 ); The optimal position searched by the i-th particle so far is the individual optimal solution p best : p best =(p i1 ,p i2 ,p i3 ,p i4 ); The optimal position searched by the entire particle swarm so far is the global optimal solution g best : g best =(p g1 ,p g2 ,p g3 ,p g4 ); Each particle follows the current optimal particle in the solution space and updates its own speed and position according to the speed transformation formula and position transformation formula. The speed transformation formula is: v id (t+1)=wv id (t)+c1r1(p id -A id (t))+c2r2(p gd -A id (t)); The position transformation formula is: A id (t+1)=A id (t)+v id (t+1); Among them, w is the inertia weight; c1 and c2 are learning factors, which respectively reflect the particle's self-learning ability and the ability to learn from the optimal particle in the group; r1 and r2 are uniform random numbers in [0,1]; v i The value range is [-v max ,v max ],v max To set a constant, it means limiting the speed of the particle.

9. The method according to claim 1, characterized in that: According to the non-steady instantaneous point source puff superposition model, the leakage point location and gas mass release rate diffusion simulation are carried out, and the H2S leakage diffusion range is obtained to include: According to the non-steady instantaneous point source puff superposition model, the leakage point location and gas mass release rate diffusion simulation are carried out. The non-steady instantaneous point source puff superposition model treats continuous leakage as continuous instantaneous leakage. The H2S concentration at a certain point in space at a certain moment is equal to the sum of the H2S concentrations of all puffs released at that moment at that point in space; that is: in, Q is the mass fraction of H2S in the leaked gas; m is the gas mass release rate; H r is the height of the leakage source; u is the ambient wind speed; σ x* , σ y* , σ z* are the diffusion coefficients of the downwind, crosswind and vertical directions of the wind field respectively; x*, y*, z* represent the positions after coordinate transformation; t represents a certain moment; C' D (x, y, z) represents the H2S concentration at the spatial coordinate point (x, y, z) at a certain moment.

10. A H2S leakage diffusion range prediction system, characterized in that: The system includes a setting module, a calculation module, an acquisition module and a diffusion simulation module; The setting module is used to set a plurality of different sensors in the area where leakage is predicted to occur; The calculation module is used to calculate the predicted concentration values ​​of different sensors based on the meteorological information of the predicted leakage area and the H2S mass fraction; The acquisition module is used to set the objective function according to the predicted concentration values ​​of different sensors to obtain the leakage point location and gas mass release rate; The diffusion simulation module is used to simulate the diffusion of the leakage point location and gas mass release rate based on the non-steady-state instantaneous point source smoke puff superposition model to obtain the H2S leakage diffusion range.

Images