Reid vapor pressure estimation method, device, electronic device and storage medium

Abstract

The present application provides a method, device, electronic device and storage medium for estimating Reid vapor pressure, comprising: determining the saturated vapor pressure of a component; determining the Reid vapor pressure of the component based on the saturated vapor pressure and a Reid vapor pressure estimation model, wherein the Reid vapor pressure estimation model is determined based on sample data, and the sample data includes a sample saturated vapor pressure and a sample Reid vapor pressure.

Description

Technical Field

[0001] The present application relates to the field of petrochemical technology, and in particular to a method, device, electronic equipment and storage medium for estimating Reid vapor pressure. Background Art

[0002] Reid vapor pressure is one of the important properties of gasoline and jet fuel. It is a standard for product blending and a useful parameter for estimating losses during tank filling and drainage. The Reid vapor pressure of petroleum fractions is widely used in petroleum refining engineering calculations, and is therefore indispensable in petroleum-related chemical design, production, and scientific research. The reliability of the Reid vapor pressure of petroleum fractions largely determines the reliability of petroleum refining engineering calculations and process simulation calculations. However, the estimation method of Reid vapor pressure in related technologies is complex, and the results have large errors. Summary of the invention

[0003] In view of the above problems, the present application provides a method, device, equipment and storage medium for estimating Reid vapor pressure.

[0004] The present application provides a method for estimating Reid vapor pressure, including:

[0005] Determine the saturated vapor pressure of the components;

[0006] The Reid vapor pressure of the component is determined based on the saturated vapor pressure and the Reid vapor pressure estimation model, wherein the Reid vapor pressure estimation model is determined based on sample data, and the sample data includes a sample saturated vapor pressure and a sample Reid vapor pressure.

[0007] In some embodiments, determining the saturated vapor pressure of the component comprises:

[0008] obtaining critical parameters of the component;

[0009] Determine the coefficient of the Antoine equation based on the critical parameters to obtain a target Antoine equation;

[0010] Based on the target Antoine equation and the critical temperature in the critical parameter, the saturated vapor pressure of the component is calculated.

[0011] In some embodiments, the method further comprises:

[0012] Acquiring sample data, wherein the sample data includes the sample saturated vapor pressure and the sample Reid vapor pressure;

[0013] The initial estimation model is trained based on the sample data to obtain the Reid vapor pressure estimation model.

[0014] In some embodiments, the training of the initial estimation model based on the sample data to obtain the Reid vapor pressure estimation model includes:

[0015] Optimizing the coefficients to be optimized in the initial estimation model based on the population evolution algorithm and the sample data to obtain intermediate values ​​of the coefficients to be optimized;

[0016] determining an intermediate Reid vapor pressure estimation model based on the intermediate value;

[0017] When it is determined based on the intermediate Reed vapor pressure model that the optimization stop condition is satisfied, the intermediate Reed vapor pressure estimation model is determined as the Reed vapor pressure estimation model.

[0018] In some embodiments, the method further comprises:

[0019] Obtain reference values ​​of Reid vapor pressures of known components;

[0020] determining an estimate of the Reid vapor pressure of the known component based on the intermediate Reid vapor pressure estimation model;

[0021] It is determined whether a stop optimization condition is satisfied based on the reference value and the estimated value.

[0022] In some embodiments, the determining whether a stop optimization condition is met based on the reference value and the estimated value includes:

[0023] determining a degree of error between the reference value and the estimated value;

[0024] Whether the optimization stopping condition is met is determined based on the error degree value, wherein when the error degree value is less than a preset condition threshold, it is determined that the optimization stopping condition is met; when the error degree value is greater than or equal to the preset condition threshold, it is determined that the optimization stopping condition is not met.

[0025] In some embodiments, the Reid vapor pressure estimation model is:

[0026]

[0027] Among them, RVP is Reid vapor pressure and TVP is saturated vapor pressure.

[0028] The present application embodiment provides a device for estimating Reid vapor pressure, comprising:

[0029] A first determination module, for determining the saturated vapor pressure of a component;

[0030] A calculation module is used to determine the Reid vapor pressure of the component based on the saturated vapor pressure and the Reid vapor pressure estimation model, wherein the Reid vapor pressure estimation model is determined based on sample data, and the sample data includes a sample saturated vapor pressure and a sample Reid vapor pressure.

[0031] An embodiment of the present application provides an electronic device, including a memory and a processor, wherein a computer program is stored in the memory, and when the computer program is executed by the processor, any one of the above-mentioned methods for estimating Reid vapor pressure is executed.

[0032] An embodiment of the present application provides a storage medium, and a computer program stored in the storage medium can be executed by one or more processors and can be used to implement any of the above-mentioned methods for estimating Reid vapor pressure.

[0033] The present application provides a Reid vapor pressure estimation method, device, electronic device and storage medium. The Reid vapor pressure model is obtained by pre-training based on sample data. When the saturated vapor pressure of the component is determined, the Reid vapor pressure is determined based on the saturated vapor pressure and the Reid vapor pressure estimation model. The calculation process is simple and the error of the obtained estimation result is small. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] The present application will be described in more detail below based on embodiments and with reference to the accompanying drawings.

[0035] Figure 1 A schematic diagram of a process flow for implementing a method for estimating Reid vapor pressure provided in an embodiment of the present application;

[0036] Figure 2 A schematic diagram of a process flow for implementing another method for estimating Reid vapor pressure provided in an embodiment of the present application;

[0037] Figure 3 A schematic diagram of a flow chart for determining a Reid vapor pressure estimation model provided in an embodiment of the application;

[0038] Figure 4 A schematic diagram of the structure of a device for estimating Reid vapor pressure provided in an embodiment of the present application;

[0039] Figure 5 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application.

[0040] In the drawings, the same reference numerals are used for the same components, and the drawings are not drawn to scale. DETAILED DESCRIPTION

[0041] In order to make the purpose, technical solutions and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings. The described embodiments should not be regarded as limiting the present application. All other embodiments obtained by ordinary technicians in the field without making creative work are within the scope of protection of this application.

[0042] In the following description, reference is made to “some embodiments”, which describe a subset of all possible embodiments, but it will be understood that “some embodiments” may be the same subset or different subsets of all possible embodiments and may be combined with each other without conflict.

[0043] If similar descriptions of "first\second\third" appear in the application documents, the following instructions will be added. In the following description, the terms "first\second\third" involved are merely used to distinguish similar objects and do not represent a specific ordering of the objects. It can be understood that "first\second\third" can be interchanged in a specific order or sequence where permitted, so that the embodiments of the present application described herein can be implemented in an order other than that illustrated or described herein.

[0044] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art to which this application belongs. The terms used herein are only for the purpose of describing the embodiments of this application and are not intended to limit this application.

[0045] Before introducing a method for estimating Reid vapor pressure provided in an embodiment of the present application, the current status and problems in the related technology are briefly introduced first.

[0046] Reid vapor pressure is the absolute pressure of a mixture at 37.8°C and a gas-liquid volume ratio of 4. Fill the liquid chamber of the vapor pressure device with cold samples and connect it to the gas chamber. The gas chamber is heated to 37.8°C in a water bath until the pressure is constant. The pressure is corrected to obtain the Reid vapor pressure. Reid vapor pressure is one of the important properties of gasoline and jet fuel. It is a standard for product blending and a useful parameter for estimating losses during tank filling and drainage. The Reid vapor pressure property of petroleum fractions is widely used in calculations in petroleum refining engineering. Therefore, it is indispensable in petroleum-related chemical design, production, and scientific research. The reliability of the Reid vapor pressure property of petroleum fractions largely determines the reliability of petroleum refining engineering calculations and process simulation calculations.

[0047] The standard measurement apparatus and procedure for Reid vapor pressure is given in ASTM D323. Generally speaking, the true vapor pressure is higher than the Reid vapor pressure because of the presence of light gases dissolved in the liquid fuel. The Reid vapor pressure and boiling range of gasoline control starting, engine warm-up, mileage costs, and vapor resistance. The vapor resistance is directly related to the Reid vapor pressure. At an ambient temperature of 21°C, the maximum acceptable Reid vapor pressure is 75.8 kPa. At an ambient temperature of 32°C, this limit drops to 55.2 kPa. The Reid vapor pressure can also be used to estimate the true vapor pressure of petroleum fractions at different temperatures. The true vapor pressure is important in calculating the loss and evaporation rate of liquid petroleum products. Since the Reid vapor pressure does not represent the true vapor pressure, the current trend is to replace the Reid vapor pressure with more modern and more meaningful techniques. The test method in ASTM D4953 discusses more precise instruments for measuring the true vapor pressure at different temperatures. This method can measure the Reid vapor pressure of oxygenated gasoline, and the measured value is closer to the actual vapor pressure.

[0048] As one of the important physical properties of petroleum fractions, Reid vapor pressure plays an important role in petrochemical simulation and safety engineering research. In the process of oil production, real-time monitoring of oil products is the most direct way to ensure production safety and maintain the stability of oil quality. For petroleum fractions, the composition is complex, and there are many actual crude oil data measured, but compared with the types of oil involved in industry and research, it is still insufficient. With the development of production and scientific research, petroleum fractions whose Reid vapor pressure has not been measured are often encountered, and estimation is required.

[0049] Early data for the estimation of Reid vapor pressure physical properties of petroleum fractions were mainly based on experimental measurements. As the types and quantities of petroleum fractions increased, the experimental measurement conditions became more demanding and the process was also limited. Accurate calculation of vapor pressure requires a gas-liquid phase equilibrium that is strictly calculated using the state equation. The Reid vapor pressure calculation method introduced in the API-TDB book requires a series of tedious flash calculations using the Soave cubic state equation. Simple relationships for estimating Reid vapor pressure have been given by Jenkins and White. These relationships are related to the temperature of the ASTM D86 distillation curve. These relationships related to the temperatures corresponding to the distillation volume fractions of 5%, 10%, 30%, and 50% are as follows:

[0050]

[0051] The difficulty in using this equation is that it requires distillation data from 0% to 50% points, and there are often significant errors in that the Reid vapor pressure of heavier fuels is negative, so it is not often used in practice.

[0052] Bird and Kimball proposed a method for predicting Reid vapor pressure, in which gasoline is cut into several virtual components characterized by average boiling points, and then the harmonic Reid vapor pressure of each virtual component is calculated; Hatzioznnidis et al. gave some gasoline Reid vapor pressure data, which they measured according to the ASTM D5191 method. They also related the measured vapor pressure to the real vapor pressure, so the Reid vapor pressure can also be obtained from the real vapor pressure, but their relationship has not been evaluated with a wide range of petroleum fractions; Riazi used the Reid vapor pressure data of 52 petroleum products (including light and heavy naphtha, gasoline and kerosene) in the oil and gas database to establish a simple relationship for predicting Reid vapor pressure. In the process of estimating the petroleum fraction model, due to the existence of many components in the substance, it is very difficult to estimate its characteristics, and it is usually difficult to obtain a good estimation result. At present, the calculation results of the existing Reid vapor pressure estimation model still have large errors. With the increasing number of oil varieties today, it is difficult to meet the needs of actual estimation.

[0053] Based on the problems existing in the related art, an embodiment of the present application provides a method for estimating Reid vapor pressure, which is applied to an electronic device. The function implemented by the method for estimating Reid vapor pressure provided in the embodiment of the present application can be implemented by calling a program code by a processor of the electronic device, wherein the program code can be stored in a computer storage medium.

[0054] Embodiment 1

[0055] The present application embodiment provides a method for estimating Reid vapor pressure. Figure 1 A schematic diagram of a method for estimating Reid vapor pressure provided in an embodiment of the present application is shown in FIG. Figure 1 As shown, including:

[0056] Step S101, determining the saturated vapor pressure of the component.

[0057] In the embodiment of the present application, the component may be a pure component or a petroleum fraction. The determination of the saturated vapor pressure of the component may be performed by directly measuring the saturated vapor pressure of the component through a measuring device, and the measuring device sends the measured saturated vapor pressure to an electronic device, so that the electronic device determines the saturated vapor pressure of the component.

[0058] In some embodiments, when the saturated vapor pressure cannot be directly measured, the critical parameters of the component can be obtained; the coefficients of the Antoine equation are determined based on the critical parameters to obtain a target Antoine equation; and the saturated vapor pressure of the component is calculated based on the target Antoine equation and the critical temperature in the critical parameters.

[0059] Step S102: determining the Reid vapor pressure of the component based on the saturated vapor pressure and the Reid vapor pressure estimation model.

[0060] In the embodiment of the present application, the Reid vapor pressure estimation model includes a calculation relationship between saturated vapor pressure and Reid vapor pressure. The Reid vapor pressure of a component can be calculated by substituting the saturated vapor pressure into the Reid vapor pressure estimation model.

[0061] In the embodiment of the present application, the Reid vapor pressure estimation model is obtained by training the initial estimation model based on sample data. The sample data includes sample saturated vapor pressure and sample Reid vapor pressure. The sample data can be directly obtained from the Internet or directly input by the user. In the embodiment of the present application, when training is performed, it can be implemented in the following manner: optimizing the coefficients to be optimized in the initial estimation model based on the population evolution algorithm and the sample data to obtain the intermediate values ​​of the coefficients to be optimized; determining the intermediate Reid vapor pressure estimation model based on the intermediate value; and determining that the intermediate Reid vapor pressure estimation model is the Reid vapor pressure estimation model when it is determined based on the intermediate Reid vapor pressure model that the optimization stop condition is met.

[0062] In an embodiment of the present application, a reference value of the Reid vapor pressure of a known component can be obtained; an estimated value of the Reid vapor pressure of the known component is determined based on the intermediate Reid vapor pressure estimation model; and whether a stop optimization condition is met is determined based on the reference value and the estimated value. In an embodiment of the present application, an error degree value between the reference value and the estimated value can be determined; and whether a stop optimization condition is met is determined based on the error degree value, wherein when the error degree value is less than a preset condition threshold, it is determined that the stop optimization condition is met; and when the error degree value is greater than or equal to the preset condition threshold, it is determined that the stop optimization condition is not met.

[0063] The Reid vapor pressure estimation method provided in the embodiment of the present application obtains a Reid vapor pressure model by pre-training based on sample data, and then determines the saturated vapor pressure of the component. The Reid vapor pressure is determined based on the saturated vapor pressure and the Reid vapor pressure estimation model. The calculation process is simple and the error of the obtained estimation result is small.

[0064] Embodiment 2

[0065] Based on the above embodiments, the present application further provides a method for estimating Reid vapor pressure. Figure 2 A schematic diagram of the implementation flow of another method for estimating Reid vapor pressure provided in an embodiment of the present application is shown in FIG. Figure 2 As shown, including:

[0066] Step S201, obtaining critical parameters of the components.

[0067] In the embodiment of the present application, the critical parameters can be directly measured and / or obtained by calculation. In the embodiment of the present application, the critical parameters may include: critical temperature, boiling point, critical pressure, eccentricity factor, etc.

[0068] Step S202, determining the coefficients of the Antioin equation based on the critical parameters to obtain a target Antioin equation.

[0069] In the embodiment of the present application, when the component is a pure component, the coefficient of the Antoine equation can be determined based on the critical parameter;

[0070] The antoin equation is shown in formula (1):

[0071] ln (TVP)=A+BT -1 +CT+DlnT+ET 2 (1);

[0072] Wherein, A, B, C, D, and E are coefficients of the Antoine equation. For example, parameter A is 18.8, parameter B is -999.6, parameter C is -4.58, parameter D is 0, and parameter E is 679. The corresponding values ​​of A, B, C, D, and E are substituted into the Antoine equation to obtain the target Antoine equation.

[0073] When the component is a petroleum fraction, the petroleum fraction can be divided into virtual components, each virtual component is considered to be a pure component, and the coefficients of the Antoine equation are calculated based on the critical parameters, so that the Antoine equation can be determined.

[0074] Step S203, calculating the saturated vapor pressure of the component based on the target Antoine equation and the critical temperature in the critical parameter.

[0075] In the embodiment of the present application, the saturated vapor pressure is obtained by substituting the critical temperature in the critical parameter into formula (1).

[0076] Exemplarily, the saturated vapor pressure is TVP=156.02Pa.

[0077] Step S204: determining the Reid vapor pressure of the component based on the saturated vapor pressure and the Reid vapor pressure estimation model.

[0078] In the embodiment of the present application, the Reid vapor pressure estimation model is shown in formula (2):

[0079]

[0080] Among them, RVP is Reid vapor pressure and TVP is saturated vapor pressure.

[0081] Continuing with the above example, TVP=156.02Pa can be substituted into formula (2) to obtain the Reid vapor pressure, and the calculated Reid vapor pressure is 880.22Pa.

[0082] The method for estimating Reid vapor pressure provided in the embodiment of the present application obtains the critical parameters of the components and then determines the coefficients of the Antoine equation based on the critical parameters, thereby calculating the saturated vapor pressure, and then determining the Reid vapor pressure through the saturated vapor pressure and Reid vapor pressure estimation model. The estimation method is simple and the calculated error is small.

[0083] Embodiment 3

[0084] Based on the above embodiments, the present application further provides a method for estimating Reid vapor pressure, including:

[0085] Step S301, obtaining sample data.

[0086] In the embodiment of the present application, the sample data includes the sample saturated vapor pressure and the sample Reid vapor pressure. The sample saturated vapor pressure and the sample Reid vapor pressure are obtained by analyzing historical data.

[0087] Step S302: training an initial estimation model based on the sample data to obtain the Reid vapor pressure estimation model.

[0088] In the embodiment of the present application, the initial estimation module is a neural network model, and the training of the initial estimation model based on sample data can be regression training based on a swarm evolution algorithm, which can be a standard differential evolution algorithm, a quasi-Newton method, or the like.

[0089] In the embodiment of the present application, Figure 3 A schematic diagram of a flow chart for determining a Reid vapor pressure estimation model is provided in an embodiment of the application, such as Figure 3 As shown, the step S302 of "training the initial estimation model on the sample data to obtain the Reid vapor pressure estimation model" can be implemented by the following steps:

[0090] Step S1, optimizing the coefficients to be optimized in the initial estimation model based on the population evolution algorithm and the sample data to obtain intermediate values ​​of the coefficients to be optimized.

[0091] Step S2, determining an intermediate Reid vapor pressure estimation model based on the intermediate value.

[0092] Step S3, obtaining a reference value of the Reid vapor pressure of a known component.

[0093] In the embodiments of this application, the reference value may be a measured value, a literature value, etc.

[0094] Step S4, determining an estimated value of the Reid vapor pressure of the known component based on the intermediate Reid vapor pressure estimation model;

[0095] Step S5: determining whether a stop optimization condition is met based on the reference value and the estimated value.

[0096] In an embodiment of the present application, the error degree value between the reference value and the estimated value can be determined; based on the error degree value, it is determined whether the optimization stopping condition is met, wherein when the error degree value is less than a preset condition threshold, it is determined that the optimization stopping condition is met; when the error degree value is greater than or equal to the preset condition threshold, it is determined that the optimization stopping condition is not met.

[0097] For example, the error degree value can be obtained to be 3.13%, and when the preset condition threshold is 4%, the optimization stop condition is met. If the preset condition threshold is 2%, the optimization stop condition is not met.

[0098] In the embodiment of the present application, when the optimization stopping condition is not met, step S1 is continued to be executed, and when the optimization stopping condition is met, step S6 is executed.

[0099] Step S6: when it is determined based on the intermediate Reed vapor pressure model that the optimization stop condition is satisfied, determining the intermediate Reed vapor pressure estimation model as the Reed vapor pressure estimation model.

[0100] Step S303, determining the saturated vapor pressure of the component.

[0101] Step S304, determining the Reid vapor pressure of the component based on the saturated vapor pressure and the Reid vapor pressure estimation model, wherein the Reid vapor pressure estimation model is determined based on sample data, and the sample data includes sample saturated vapor pressure and sample Reid vapor pressure.

[0102] The Reid vapor pressure estimation method provided in the embodiment of the present application performs regression training through the sample saturated vapor pressure and the sample Reid vapor pressure, and verifies whether the optimization stop condition is reached during the training process. When the optimization stop condition is reached, a Reid vapor pressure estimation model is determined, and the Reid vapor pressure of the component is determined based on the Reid vapor pressure estimation model, and the calculated error is small.

[0103] In some embodiments, after the Reid vapor pressure is determined, the component can be determined based on the Reid vapor pressure. For example, the component can be determined by looking up the calculated Reid vapor pressure in a comparison table, wherein the comparison table includes a correspondence between the component and the Reid vapor pressure.

[0104] In some embodiments, oil production can be monitored in real time based on Reid vapor pressure.

[0105] Embodiment 4

[0106] Based on the Reid vapor pressure estimation model obtained in the above-mentioned embodiments, the embodiment of the present application verifies the Reid vapor pressure estimation model, and the Reid vapor pressure model is:

[0107]

[0108] Verification of the Reid vapor pressure estimation model for pure component substances:

[0109] Table 1 shows the estimation results and error table of Reid vapor pressure of pure components by the new model. As shown in Table 1, taking ethylene in alkanes as an example, the values ​​of saturated vapor pressure parameters A, B, C, D, and E are known as shown in the table. Substituting them into the Antoine equation, the saturated vapor pressure is obtained:

[0110]

[0111] Then, the saturated vapor pressure is substituted into the regression formula (i.e., the Reid vapor pressure estimation model) to obtain the estimated value of the Reid vapor pressure:

[0112]

[0113] The prediction results and relative errors of the Reid vapor pressure model for pure components are shown in Table 1. It can be found that the estimated value of the Reid vapor pressure estimation model provided in the embodiment of the present application has an average relative error of about 3.13% compared with the literature value. The Reid vapor pressure estimation of pure component substances has a high accuracy.

[0114] Table 1 Estimation results and errors of Reid vapor pressure of pure components by the new model

[0115]

[0116]

[0117]

[0118] Validation of the Reid Vapor Pressure Estimation Model for Oil Substances:

[0119] Taking the oil in the atmospheric and vacuum process as an example, it is known that the reference value of the Reid vapor pressure of the oil is 72954Pa, and the estimated value of the Reid vapor pressure is 72920.25Pa. The estimated calculation is as follows:

[0120] At this time, RVP is obtained as Reid vapor pressure, in degrees Celsius. Compared with the reference value of 72954Pa, the relative error between the calculated value obtained by the Reid vapor pressure estimation model and the actual analysis value (the same as the reference value in the above embodiment) is 0.05%. Similarly, the reference values ​​and estimated values ​​of other 10 real oil products can be verified, and the error analysis results are shown in the following table:

[0121] Table 2 Relative error between the estimated values ​​of the new Reid vapor pressure model and the reference values ​​of oil products

[0122]

[0123]

[0124] It also has high accuracy in estimating the Reid vapor pressure of petroleum fractions.

[0125] In the embodiment of the present application, the saturated vapor pressure is obtained according to the saturated vapor pressure coefficient and the Antoine equation; a pure component Reid vapor pressure estimation formula is established; a petroleum fraction Reid vapor pressure estimation formula is established; experimental data are collected, a regression equation is established, and a solution is obtained to obtain a Reid vapor pressure estimation model; a model goodness test is performed; and an estimation method for the Reid vapor pressure of pure components and petroleum fractions is established. The estimation method provided by the present invention is based on the establishment of a Reid vapor pressure estimation model for pure substances and petroleum fractions, predicts unknown Reid vapor pressure physical properties of petroleum fractions, and the estimation process is simple and the calculation result is unique.

[0126] Embodiment 5

[0127] Based on the foregoing embodiments, the embodiments of the present application provide a device for estimating Reid vapor pressure. The modules included in the device and the units included in the modules can be implemented by a processor in a computer device; of course, they can also be implemented by a specific logic circuit; in the implementation process, the processor can be a central processing unit (CPU, Central Processing Unit), a microprocessor (MPU, Microprocessor Unit), a digital signal processor (DSP, Digital Signal Processing) or a field programmable gate array (FPGA, Field Programmable Gate Array), etc.

[0128] The present application embodiment provides a device for estimating Reid vapor pressure. Figure 4 A schematic diagram of a structure of a device for estimating Reid vapor pressure provided in an embodiment of the present application is shown in FIG. Figure 4 As shown, the Reid vapor pressure estimation device 400 includes:

[0129] A first determination module 401 is used to determine the saturated vapor pressure of a component;

[0130] The calculation module 402 is used to determine the Reid vapor pressure of the component based on the saturated vapor pressure and the Reid vapor pressure estimation model, wherein the Reid vapor pressure estimation model is determined based on sample data, and the sample data includes sample saturated vapor pressure and sample Reid vapor pressure.

[0131] In some embodiments, the first determining module 401 includes:

[0132] An acquisition unit, used for acquiring critical parameters of the component;

[0133] An obtaining unit is used to determine the coefficient of the Antoine equation based on the critical parameter to obtain a target Antoine equation;

[0134] A calculation unit is used to calculate the saturated vapor pressure of the component based on the target Antoine equation and the critical temperature in the critical parameter.

[0135] In some embodiments, the Reid vapor pressure estimation device 400 further includes:

[0136] An acquisition module, used for acquiring sample data, wherein the sample data includes the sample saturated vapor pressure and the sample Reid vapor pressure;

[0137] A training module is used to train the initial estimation model based on the sample data to obtain the Reid vapor pressure estimation model.

[0138] In some embodiments, the training module includes:

[0139] An optimization unit, which optimizes the coefficients to be optimized in the initial estimation model based on a population evolution algorithm and the sample data to obtain intermediate values ​​of the coefficients to be optimized;

[0140] a first determining unit, configured to determine an intermediate Reid vapor pressure estimation model based on the intermediate value;

[0141] The second determining unit is configured to determine, when it is determined based on the intermediate Reed vapor pressure model that a stop optimization condition is satisfied, that the intermediate Reed vapor pressure estimation model is the Reed vapor pressure estimation model.

[0142] In some embodiments, the training module further includes:

[0143] An acquisition unit, used for acquiring a reference value of the Reid vapor pressure of a known component;

[0144] a third determining unit, configured to determine an estimated value of the Reid vapor pressure of the known component based on the intermediate Reid vapor pressure estimation model;

[0145] A fourth determining unit is used to determine whether a stop optimization condition is met based on the reference value and the estimated value.

[0146] In some embodiments, the fourth determining unit further includes:

[0147] A first determining subunit, configured to determine an error degree value between the reference value and the estimated value;

[0148] The second determination subunit is used to determine whether the optimization stopping condition is met based on the error degree value, wherein when the error degree value is less than a preset condition threshold, it is determined that the optimization stopping condition is met; when the error degree value is greater than or equal to the preset condition threshold, it is determined that the optimization stopping condition is not met.

[0149] In some embodiments, the Reid vapor pressure estimation model is:

[0150]

[0151] Among them, RVP is Reid vapor pressure and TVP is saturated vapor pressure.

[0152] The embodiment of the present application provides a Reid vapor pressure estimation device 400: a first determination module 401 is used to determine the saturated vapor pressure of a component; a calculation module 402 is used to determine the Reid vapor pressure of the component based on the saturated vapor pressure and the Reid vapor pressure estimation model, and the calculated error is small.

[0153] It should be noted that in the embodiment of the present application, if the above-mentioned estimation method of Reid vapor pressure is implemented in the form of a software function module and sold or used as an independent product, it can also be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the embodiment of the present application is essentially or the part that contributes to the prior art can be embodied in the form of a software product, which is stored in a storage medium, including several instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the methods described in each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as a U disk, a mobile hard disk, a read-only memory (ROM, Read Only Memory), a disk or an optical disk. In this way, the embodiment of the present application is not limited to any specific combination of hardware and software.

[0154] Accordingly, an embodiment of the present application provides a storage medium having a computer program stored thereon, characterized in that when the computer program is executed by a processor, the steps in the method for estimating Reid vapor pressure provided in the above embodiment are implemented.

[0155] Embodiment 6

[0156] An embodiment of the present application provides an electronic device; Figure 5A schematic diagram of the structure of an electronic device provided in an embodiment of the present application is shown in FIG. Figure 5 As shown, the electronic device 500 includes: a processor 501, at least one communication bus 502, a user interface 503, at least one external communication interface 504, and a memory 505. The communication bus 502 is configured to realize connection and communication between these components. The user interface 503 may include a display screen, and the external communication interface 504 may include a standard wired interface and a wireless interface. The processor 501 is configured to execute the program of the method for estimating Reid vapor pressure stored in the memory to implement the steps in the method for estimating Reid vapor pressure provided in the above embodiment.

[0157] The description of the above display device and storage medium embodiments is similar to the description of the above method embodiments, and has similar beneficial effects as the method embodiments. For technical details not disclosed in the computer device and storage medium embodiments of this application, please refer to the description of the method embodiments of this application for understanding.

[0158] It should be noted here that the description of the above storage medium and device embodiments is similar to the description of the above method embodiments, and has similar beneficial effects as the method embodiments. For technical details not disclosed in the storage medium and device embodiments of this application, please refer to the description of the method embodiments of this application for understanding.

[0159] It should be understood that "one embodiment" or "an embodiment" mentioned throughout the specification means that specific features, structures or characteristics related to the embodiment are included in at least one embodiment of the present application. Therefore, "in one embodiment" or "in an embodiment" appearing throughout the specification does not necessarily refer to the same embodiment. In addition, these specific features, structures or characteristics can be combined in one or more embodiments in any suitable manner. It should be understood that in various embodiments of the present application, the size of the sequence number of the above-mentioned processes does not mean the order of execution, and the execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application. The above-mentioned sequence numbers of the embodiments of the present application are only for description and do not represent the advantages and disadvantages of the embodiments.

[0160] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the existence of other identical elements in the process, method, article or device including the element.

[0161] In the several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as: multiple units or components can be combined, or can be integrated into another system, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the components shown or discussed can be through some interfaces, and the indirect coupling or communication connection of the devices or units can be electrical, mechanical or other forms.

[0162] The units described above as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units; they may be located in one place or distributed on multiple network units; some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0163] In addition, all functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may be separately configured as a unit, or two or more units may be integrated into one unit; the above-mentioned integrated units may be implemented in the form of hardware or in the form of hardware plus software functional units.

[0164] A person of ordinary skill in the art can understand that: all or part of the steps of implementing the above-mentioned method embodiment can be completed by hardware related to program instructions, and the aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it executes the steps of the above-mentioned method embodiment; and the aforementioned storage medium includes: mobile storage devices, read-only memories (ROM, Read Only Memory), disks or optical disks, etc. Various media that can store program codes.

[0165] Alternatively, if the above-mentioned integrated unit of the present application is implemented in the form of a software function module and sold or used as an independent product, it can also be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the embodiment of the present application can essentially or in other words, the part that contributes to the prior art can be embodied in the form of a software product, which is stored in a storage medium and includes a number of instructions for a controller to execute all or part of the methods described in each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as mobile storage devices, ROMs, magnetic disks, or optical disks.

[0166] The above is only an implementation method of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A method for estimating Reid vapor pressure, characterized in that: include: Determine the saturated vapor pressure of the components; Determining the Reid vapor pressure of the component based on the saturated vapor pressure and Reid vapor pressure estimation model, wherein the Reid vapor pressure estimation model is determined based on sample data, and the sample data includes a sample saturated vapor pressure and a sample Reid vapor pressure; Wherein, the determining of the saturated vapor pressure of the component comprises: obtaining critical parameters of the component; Determine the coefficient of the Antoine equation based on the critical parameters to obtain a target Antoine equation; Calculating the saturated vapor pressure of the component based on the target Antoine equation and the critical temperature in the critical parameter; The Reid vapor pressure estimation model is: Among them, RVP is Reid vapor pressure and TVP is saturated vapor pressure.

2. The method according to claim 1, characterized in that The method further comprises: Acquiring sample data, wherein the sample data includes the sample saturated vapor pressure and the sample Reid vapor pressure; The initial estimation model is trained based on the sample data to obtain the Reid vapor pressure estimation model.

3. The method according to claim 2, characterized in that The training of the initial estimation model based on the sample data to obtain the Reid vapor pressure estimation model includes: Optimizing the coefficients to be optimized in the initial estimation model based on the population evolution algorithm and the sample data to obtain intermediate values ​​of the coefficients to be optimized; determining an intermediate Reid vapor pressure estimation model based on the intermediate value; When it is determined based on the intermediate Reed vapor pressure model that the optimization stop condition is satisfied, the intermediate Reed vapor pressure estimation model is determined as the Reed vapor pressure estimation model.

4. The method according to claim 3, characterized in that: The method further comprises: Obtain reference values ​​of Reid vapor pressures of known components; determining an estimate of the Reid vapor pressure of the known component based on the intermediate Reid vapor pressure estimation model; It is determined whether a stop optimization condition is satisfied based on the reference value and the estimated value.

5. The method according to claim 4, characterized in that The determining whether a stop optimization condition is met based on the reference value and the estimated value comprises: determining a degree of error between the reference value and the estimated value; Whether the optimization stopping condition is met is determined based on the error degree value, wherein when the error degree value is less than a preset condition threshold, it is determined that the optimization stopping condition is met; when the error degree value is greater than or equal to the preset condition threshold, it is determined that the optimization stopping condition is not met.

6. A device for estimating Reid vapor pressure for implementing the method for estimating Reid vapor pressure according to any one of claims 1 to 5, characterized in that: include: A first determination module, for determining the saturated vapor pressure of a component; A calculation module is used to determine the Reid vapor pressure of the component based on the saturated vapor pressure and the Reid vapor pressure estimation model, wherein the Reid vapor pressure estimation model is determined based on sample data, and the sample data includes a sample saturated vapor pressure and a sample Reid vapor pressure.

7. An electronic device, characterized in that: The method comprises a memory and a processor, wherein a computer program is stored in the memory, and when the computer program is executed by the processor, the method for estimating the Reid vapor pressure according to any one of claims 1 to 5 is executed.

8. A storage medium, characterized in that: The computer program stored in the storage medium can be executed by one or more processors and can be used to implement the method for estimating Reid vapor pressure as claimed in any one of claims 1 to 5.

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