CN116430014A - Method and system for acquiring detailed evaluation data of target oil product - Google Patents
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Abstract
The invention provides a method and a system for acquiring detailed evaluation data of a target oil product, wherein the method comprises the following steps: determining the class of the oil product affiliated to the target oil product according to the criticizing data of the target oil product, and searching whether an oil product sample consistent with the target oil product exists in an oil product database of the class of the oil product; if not, searching a plurality of oil samples similar to the target oil in an oil database of the oil types to which the target oil belongs; determining the mixing proportion of a plurality of oil samples, and mixing the plurality of oil samples according to the mixing proportion to form a blended oil; determining the molecular composition data and macroscopic physical property data of the blended oil based on the blending proportion and the molecular composition data and macroscopic physical property data of each of the plurality of oil samples; the molecular composition data and macroscopic physical property data of the blended oil are used as detailed evaluation data of the target oil. The method can rapidly and accurately acquire detailed evaluation data of the target oil product according to the criticizing data of the target oil product, and provides technical support for subsequent production processes.
Description
Technical Field
The invention belongs to the field of oil data processing, and particularly relates to a method and a system for acquiring detailed evaluation data of a target oil.
Background
In the big data age, data plays a very important role in various industries and also plays a very important role in the petroleum processing field. In the precise control process of petroleum processing, relevant simulation is often required according to detailed evaluation data of petroleum products so as to optimize the operation conditions of various produced petroleum products, however, the difficulty faced by the process is that only the brief evaluation data of the petroleum products are generated, and the error result in the simulation process flow is caused by the lack of the data, so that the products cannot meet the requirements.
To solve the above-mentioned difficulties, it is necessary to study how to obtain detailed evaluation data of oil products according to the brief evaluation data of oil products, however, the existing data processing method has few specific studies on the data of oil products, so it is needed to provide a method for obtaining detailed evaluation data of target oil products to overcome the above-mentioned difficulties.
Disclosure of Invention
In view of the above problems, one of the objects of the present invention is to: provides a method for acquiring detailed evaluation data of target oil products.
In order to achieve the above object, the present invention provides the following technical solutions:
a method for acquiring detailed evaluation data of a target oil product comprises the following steps:
determining the class of the oil product affiliated to the target oil product according to the criticizing data of the target oil product, wherein the criticizing data of the target oil product comprises macroscopic physical property data of the target oil product;
searching whether an oil sample consistent with the target oil exists in an oil database of the oil types affiliated by the target oil;
if no oil sample consistent with the target oil is found in the oil database, searching a plurality of oil samples similar to the target oil in the oil database of the oil types affiliated to the target oil;
determining the mixing proportion of the oil samples by using a mixed integer nonlinear programming method, and mixing the oil samples into a blended oil according to the mixing proportion;
determining molecular composition data and macroscopic physical property data of the blended oil based on the molecular composition data and macroscopic physical property data of each of the plurality of oil samples in the blending proportion;
and taking the molecular composition data and the macroscopic physical property data of the blended oil product as detailed evaluation data of the target oil product, wherein the macroscopic physical property data in the detailed evaluation data of the target oil product is more than the macroscopic physical property data in the criticizing data of the target oil product.
Preferably, the method further comprises the steps of:
and if the oil product sample consistent with the target oil product is found in the oil product database, taking the molecular composition data and macroscopic physical property data of the oil product sample as detailed evaluation data of the target oil product.
Preferably, the macro physical property data of the detailed evaluation data is any of boiling point, density, octane number, aromatic hydrocarbon, olefin, benzene, flash point, refractive index, congeal point, cloud point, pour point, aniline point, freeze point, viscosity index, viscosity, API gravity, and wax content.
Preferably, the step of determining the molecular composition data and macroscopic physical property data of the blended oil product based on the blending proportion and the molecular composition data and macroscopic physical property data of the plurality of oil samples specifically includes:
determining molecular composition data of the blended oil based on the blending ratio and the molecular composition data of the plurality of oil samples;
for one linear macroscopic physical property, weighting and summing the data of the linear macroscopic physical properties of the oil samples according to a mixing proportion to obtain the data of the linear macroscopic physical properties of the blended oil;
for a nonlinear macroscopic property, determining the data of the nonlinear macroscopic property of the blended oil based on the molecular composition data of the blended oil and a corresponding property calculation model.
In view of the above problems, a second object of the present invention is to: a system for acquiring detailed evaluation data of a target oil product is provided.
In order to achieve the above object, the present invention provides the following technical solutions:
a system for acquiring detailed evaluation data of a target oil product comprises:
the first analysis module is used for determining the class of the oil product affiliated to the target oil product according to the criticizing data of the target oil product, wherein the criticizing data of the target oil product comprises macroscopic physical property data of the target oil product;
the first searching module is used for searching whether an oil sample consistent with the target oil exists in an oil database of the oil types affiliated to the target oil;
the second searching module is used for searching a plurality of oil samples similar to the target oil in the oil database of the oil types affiliated to the target oil if the oil samples consistent with the target oil are not found in the oil database;
the blending module is used for determining the blending proportion of the plurality of oil samples by utilizing a mixed integer nonlinear programming method and blending the plurality of oil samples into blended oil according to the blending proportion;
the second analysis module is used for determining the molecular composition data and macroscopic physical property data of the blended oil based on the mixing proportion and the molecular composition data and macroscopic physical property data of each of the plurality of oil samples;
and the first output module is used for taking the molecular composition data and the macroscopic physical property data of the blended oil product as detailed evaluation data of the target oil product, wherein the macroscopic physical property data in the detailed evaluation data of the target oil product is more than the macroscopic physical property data in the criticizing data of the target oil product.
Preferably, the system further comprises a second output module, wherein the second output module is used for taking the molecular composition data and macroscopic physical property data of the oil product sample as detailed evaluation data of the target oil product if the oil product sample consistent with the target oil product is found in the oil product database.
Preferably, in the first output module, the macro physical property data of the detailed evaluation data is any of boiling point, density, octane number, aromatic hydrocarbon, olefin, benzene, flash point, refractive index, condensation point, cloud point, pour point, aniline point, freezing point, viscosity index, viscosity, API degree, and wax content.
Preferably, the second analysis module comprises:
the determining unit is used for determining the molecular composition data of the blended oil based on the mixing proportion and the molecular composition data of the oil samples;
the first calculation unit is used for carrying out weighted summation on the data of the linear macroscopic physical properties of the oil samples according to the mixing proportion to obtain the data of the linear macroscopic physical properties of the blended oil;
and the second calculation unit is used for determining the data of the nonlinear macroscopic physical property of the blended oil according to the molecular composition data of the blended oil and the corresponding physical property calculation model.
In view of the above problems, a third object of the present invention is to: an electronic device is provided.
In order to achieve the above object, the present invention provides the following technical solutions:
an electronic device comprises a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory are communicated with each other through the communication bus;
a memory for storing a computer program;
and the processor is used for realizing the method for acquiring the detailed evaluation data of the target oil product when executing the program stored in the memory.
Preferably, the memory is a disk memory, and the processor is one of a central processing unit, a network processor, a digital signal processor, and a field programmable gate array.
In view of the above problems, the fourth object of the present invention is to: a computer-readable storage medium is provided.
In order to achieve the above object, the present invention provides the following technical solutions:
a computer readable storage medium storing one or more programs executable by one or more processors to implement the method for obtaining target oil detailed evaluation data described above.
The invention has the beneficial effects that:
1. the method can rapidly and accurately acquire detailed evaluation data of the target oil product according to the criticizing data of the target oil product, and provides technical support for subsequent production processes.
2. When the molecular composition data and macroscopic physical property data of the blended oil are determined, the linear macroscopic physical property and the nonlinear macroscopic physical property are processed by two different processing methods, so that the method can accurately determine the molecular composition data and macroscopic physical property data of the blended oil, and the economic loss caused by wrong molecular composition in the subsequent process flow is avoided.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention may be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions of the prior art, the following description will briefly explain the drawings used in the embodiments or the description of the prior art, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings can be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 shows a workflow diagram of a method for acquiring detailed evaluation data of a target oil product according to an embodiment of the invention;
FIG. 2 is a flowchart showing a method for acquiring detailed evaluation data of a target oil product according to a second embodiment of the present invention;
FIG. 3 is a schematic diagram of a system for acquiring detailed evaluation data of a target oil product according to a third embodiment of the present invention;
FIG. 4 shows a schematic diagram of a second analysis module according to a third embodiment of the invention;
fig. 5 shows a schematic diagram of an electronic device according to a fourth embodiment of the present invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments of the present invention. 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.
The method, system, apparatus and storage medium for acquiring detailed evaluation data of a target oil product according to the present invention will be explained in detail with reference to specific examples.
Example 1
As shown in FIG. 1, the invention aims to provide a method for acquiring detailed evaluation data of a target oil product, which mainly comprises the following steps:
s10, determining the class of the oil product affiliated to the target oil product according to the criticizing data of the target oil product, wherein the criticizing data of the target oil product comprises macroscopic physical property data of the target oil product;
s20, searching whether an oil sample consistent with the target oil exists in an oil database of the oil types affiliated by the target oil;
s30, if no oil sample consistent with the target oil is found in the oil database, searching a plurality of oil samples similar to the target oil in the oil database of the oil types affiliated by the target oil;
s40, determining the mixing proportion of the oil samples by using a mixed integer nonlinear programming method, and mixing the oil samples into a blended oil according to the mixing proportion;
s50, determining the molecular composition data and macroscopic physical property data of the blended oil based on the mixing proportion and the molecular composition data and macroscopic physical property data of each of the plurality of oil samples;
and S60, taking the molecular composition data and the macroscopic physical property data of the blended oil product as detailed evaluation data of the target oil product, wherein the macroscopic physical property data in the detailed evaluation data of the target oil product is more than the macroscopic physical property data in the criticizing data of the target oil product.
Example two
Fig. 2 is a flowchart of a method for obtaining detailed evaluation data of a target oil product according to a second embodiment of the present invention. As shown in fig. 2, the method for obtaining detailed evaluation data of a target oil product in this embodiment mainly includes the following steps:
s10, determining the class of the oil product affiliated to the target oil product according to the criticizing data of the target oil product, wherein the criticizing data of the target oil product comprises part of macroscopic physical property data of the target oil product.
In this embodiment, the criticizing data of the target oil product may be obtained by measuring with an instrument or by calculating with a model; the criticizing data of the target oil may include macroscopic physical property data such as density, distillation range, sulfur content, octane number, cetane number, and the like. In the present invention, the criticizing data is relative to the detailed evaluation data. In general, macroscopic physical property data in the criticizing data is smaller than macroscopic physical property data in the detailed evaluation data.
And then, utilizing the criticizing data of the target oil products, such as data of density, distillation range and the like, to perform target oil product gathering screening in a pre-established crude oil database, a gasoline database, a diesel oil database and a wax oil database, and judging which oil product category the target oil products belong to and the corresponding oil product database.
For example, the density, initial and final distillation points, 5% distillation temperature and 95% distillation temperature are used to determine which of the above oil databases a target oil belongs to.
Firstly, determining a density interval formed by the minimum value and the maximum value of the density of each database, a first distillation range interval formed by the minimum value and the maximum value of the 5% distillation temperature, and a second distillation range interval formed by the minimum value and the maximum value of the 95% distillation temperature, then matching the density of a target oil product with the density interval of each database, selecting the database if the density is single, and matching the 5% distillation temperature of the target oil product with the first distillation range interval of each database if the density is single, and determining whether the density is overlapped; or matching the distillation temperature of 95% of the target oil product with the second distillation range interval of each database to determine whether the target oil product is overlapped; if the data base is single, the data base is selected, if the data base is overlapped, the judgment is continued until the affiliated oil product data base is determined.
After determining the class of the oil product to which the target oil product belongs, the following steps are executed:
s100, searching an oil sample consistent with the target oil in an oil database of the class of the oil affiliated by the target oil:
if an oil sample consistent with a target oil (target crude oil) is found in an oil database, taking the molecular composition data of the oil sample as the molecular composition data of the target oil;
if no oil sample consistent with the target oil is found in the oil database, step S200 is performed.
S200, searching a plurality of oil samples similar to the target oil in an oil database of the oil types to which the target oil belongs.
In this embodiment, the step S200 mainly includes analyzing the physical similarity between each oil sample in the oil database and the target oil according to the criticizing data of the target oil, sorting the oil samples in the oil database according to the physical similarity, and selecting a plurality of oil samples closest to the physical properties of the target oil according to the sorting result.
In this regard, the step S200 may include the following steps, when applied specifically:
s210, calculating the physical similarity between each oil sample in an oil database and a target oil, wherein the physical similarity is equal to the vector between each corresponding macroscopic physical data of the oil sample and the target oil; wherein, the weight can be determined in advance according to the importance of each macroscopic physical property;
s220, sorting the oil samples in the oil database according to the physical similarity between each oil sample in the oil database and the target oil;
s230, selecting a plurality of oil samples closest to the physical properties of the target oil according to the sorting result.
For example, the oil samples in the oil database are ordered in the order of high-to-low similarity of physical properties, and then a plurality of top-ranked oil samples are selected as the oil samples closest to the physical properties of the target oil. Here, the number of oil samples to be selected is not limited, and is generally set according to a trade-off between accuracy of the calculation result and time. The penalty function associated with the number of oil samples will cause the selected number of oils to be selected in a decreasing direction.
S300, determining the mixing proportion of the oil samples by using a mixed integer nonlinear programming method.
In this embodiment, the blending ratio of the plurality of oil samples is determined by using a mixed integer nonlinear programming method, and is mainly determined based on a mixed integer nonlinear programming and a penalty function. Wherein the penalty function comprises:
a penalty function for the number of oil species to define the number of oil species selected from the ordered oil samples for modeling;
and a penalty function for defining a minimum blending proportion value of the finally obtained blending proportions.
S400, mixing the oil samples according to the mixing proportion to form a blended oil.
S500, determining the molecular composition data and macroscopic physical property data of the blended oil based on the mixing proportion and the molecular composition data and macroscopic physical property data of each of the oil samples.
In this embodiment, this step S500 may be subdivided into the following steps:
s510, determining molecular composition data of the blended oil based on the mixing proportion and the molecular composition data of the oil samples;
s520, for one linear macroscopic physical property, carrying out weighted summation on the data of the linear macroscopic physical properties of the oil samples according to the mixing proportion to obtain the data of the linear macroscopic physical properties of the blended oil;
s530, for a nonlinear macroscopic physical property, determining the data of the nonlinear macroscopic physical property of the blended oil according to the molecular composition data of the blended oil and a corresponding physical property calculation model.
For linear physical properties, linear weighted summation calculation can be carried out by utilizing linear macroscopic physical property data of a plurality of oil samples which participate in mixing and mixing proportion examples, so as to obtain linear macroscopic physical property data of the blended oil;
for nonlinear physical properties, nonlinear macroscopic physical property data of the blended oil can be calculated according to molecular composition data and a physical property calculation formula of the blended oil.
It should be noted that the execution order of steps S520 and S530 is not limited to this in practical application.
S600, analyzing the difference between the macroscopic physical property data of the blended oil product and the macroscopic physical property data of the target oil product.
And S700, if the difference does not meet the preset threshold condition, adjusting the mixing proportion, returning to the step S400, and re-mixing the plurality of oil samples into a blended oil according to the adjusted mixing proportion so as to re-analyze the difference between the macroscopic physical property data of the blended oil and the macroscopic physical property data of the target oil.
In this embodiment, the difference meeting the preset threshold condition means that the difference between the macroscopic physical property data of the blended oil and the macroscopic physical property data of the target oil can be minimized.
For this purpose, the difference between the macroscopic physical property data of the blend oil and the macroscopic physical property data of the target oil can preferably be measured by means of a quality assessment parameter. In particular, the quality assessment parameter is equal to the weighted distance between vectors of corresponding macroscopic physical property data of the blended oil product and the target oil product.
In this example, when the value of the quality evaluation parameter reaches the minimum value, it is judged that the difference between the macroscopic property data of the blended oil and the macroscopic property data of the target oil is minimized.
S800, if the difference meets the preset threshold condition, taking the molecular composition data and macroscopic physical property data of the blended oil product as detailed evaluation data of the target oil product, wherein the macroscopic physical property data in the detailed evaluation data of the target oil product is more than the macroscopic physical property data in the criticizing data of the target oil product. Macroscopic physical property data of the detailed evaluation data are any of boiling point, density, octane number, aromatic hydrocarbon, olefin, benzene, flash point, refractive index, condensation point, cloud point, pour point, aniline point, freezing point, viscosity index, viscosity, API degree and wax content.
The method of the embodiment can rapidly and accurately determine the molecular composition of the oil product and corresponding more comprehensive macroscopic physical property data (detailed evaluation data) through limited macroscopic physical property data, can be used as a soft measuring tool for the molecular composition and macroscopic physical property, improves the detection speed, reduces the detection cost and even provides beneficial guidance for the subsequent process flow operation compared with the traditional analysis mode.
Example III
As shown in fig. 3, an embodiment of the present invention provides a system for acquiring detailed evaluation data of a target oil product, including:
the first analysis module 1 is used for determining the class of the oil product affiliated to the target oil product according to the criticizing data of the target oil product, wherein the criticizing data of the target oil product comprises macroscopic physical property data of the target oil product;
the first searching module 2 is used for searching whether an oil sample consistent with the target oil exists in an oil database of the oil types affiliated to the target oil;
the second searching module 3 is configured to search, if no oil sample consistent with the target oil is found in the oil database, a plurality of oil samples similar to the target oil in the oil database of the oil types to which the target oil belongs;
the blending module 4 is used for determining the blending proportion of the plurality of oil samples by utilizing a mixed integer nonlinear programming method and blending the plurality of oil samples into blended oil according to the blending proportion;
the second analysis module 5 is used for determining the molecular composition data and macroscopic physical property data of the blended oil based on the mixing proportion and the molecular composition data and macroscopic physical property data of each of the plurality of oil samples;
and the first output module 6 is used for taking the molecular composition data and macroscopic physical property data of the blended oil product as detailed evaluation data of the target oil product, wherein the macroscopic physical property data in the detailed evaluation data of the target oil product is more than the macroscopic physical property data in the criticizing data of the target oil product. In the first output module, the macro physical property data of the detailed evaluation data are any of boiling point, density, octane number, aromatic hydrocarbon, olefin, benzene, flash point, refractive index, condensation point, cloud point, pour point, aniline point, freezing point, viscosity index, viscosity, API degree and wax content.
In one possible embodiment, the system further comprises a second output module,
and the second output module is used for taking the molecular composition data and macroscopic physical property data of the oil product sample as detailed evaluation data of the target oil product if the oil product sample consistent with the target oil product is found in the oil product database.
In a possible embodiment, as shown in fig. 4, the second analysis module 5 includes:
a determining unit 501, configured to determine molecular composition data of the blended oil product based on a blending ratio and molecular composition data of the plurality of oil product samples;
a first calculating unit 502, configured to weight and sum data of the linear macroscopic physical properties of the plurality of oil samples according to a blending ratio, to obtain data of the linear macroscopic physical properties of the blended oil;
a second calculation unit 503 is configured to determine, for a nonlinear macroscopic property, data of the nonlinear macroscopic property of the blended oil based on molecular composition data of the blended oil and a corresponding property calculation model.
In a possible implementation, the second search module 3 includes:
the sequencing unit is used for determining the physical similarity between each oil sample in the oil database and the target oil according to the criticizing data of the target oil, and sequencing the oil samples in the oil database according to the physical similarity;
and the selection unit is used for selecting a plurality of oil samples closest to the physical properties of the target oil based on the sorting result.
Example IV
Based on the same inventive concept, as shown in fig. 5, an embodiment of the present invention provides an electronic device, including a processor 1110, a communication interface 1120, a memory 1130, and a communication bus 1140, where the processor 1110, the communication interface 1120, and the memory 1130 complete communication with each other through the communication bus 1140;
a memory 1130 for storing a computer program;
the processor 1110 is configured to implement a method for acquiring detailed evaluation data of a target oil product as shown below when executing a program stored in the memory 1130, and includes the following steps:
determining the class of the oil product affiliated to the target oil product according to the criticizing data of the target oil product, wherein the criticizing data of the target oil product comprises macroscopic physical property data of the target oil product;
searching whether an oil sample consistent with the target oil exists in an oil database of the oil types affiliated by the target oil;
if no oil sample consistent with the target oil is found in the oil database, searching a plurality of oil samples similar to the target oil in the oil database of the oil types affiliated to the target oil;
determining the mixing proportion of the oil samples by using a mixed integer nonlinear programming method, and mixing the oil samples into a blended oil according to the mixing proportion;
determining molecular composition data and macroscopic physical property data of the blended oil based on the molecular composition data and macroscopic physical property data of each of the plurality of oil samples in the blending proportion;
and taking the molecular composition data and the macroscopic physical property data of the blended oil product as detailed evaluation data of the target oil product, wherein the macroscopic physical property data in the detailed evaluation data of the target oil product is more than the macroscopic physical property data in the criticizing data of the target oil product.
The communication bus 1140 may be a peripheral component interconnect standard (Peripheral Component Interconnect, PCI) bus or an extended industry standard architecture (Extended Industry StandardArchitecture, EISA) bus, among others. The communication bus 1140 may be divided into an address bus, a data bus, a control bus, and the like. For ease of illustration, the figures are shown with only one bold line, but not with only one bus or one type of bus.
The communication interface 1120 is used for communication between the electronic device and other devices described above.
The memory 1130 may include random access memory (RandomAccess Memory, simply RAM) or may include non-volatile memory (non-volatile memory), such as at least one magnetic disk memory. Optionally, the memory 1130 may also be at least one storage device located remotely from the processor 1110.
The processor 1110 may be a general-purpose processor, including a central processing unit (Central Processing Unit, CPU for short), a network processor (Network Processor, NP for short), etc.; but also digital signal processors (Digital Signal Processing, DSP for short), application specific integrated circuits (Application Specific Integrated Circuit, ASIC for short), field-programmable gate arrays (Field-Programmable GateArray, FPGA for short) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components.
Example five
Based on the same inventive concept, the embodiments of the present invention provide a computer readable storage medium storing one or more programs executable by one or more processors to implement the steps of the method for acquiring target oil detailed evaluation data in any of the possible implementations described above.
Alternatively, the storage medium may be a non-transitory computer readable storage medium, which may be, for example, ROM, random Access Memory (RAM), CD-ROM, magnetic tape, floppy disk, optical data storage device, and the like.
In the above embodiments, it may be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented in software, may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the processes or functions in accordance with embodiments of the present invention are produced in whole or in part. The computer may be a general purpose computer, a special purpose computer, a computer network, or other programmable apparatus. The computer instructions may be stored in or transmitted from one computer-readable storage medium to another, for example, by wired (e.g., coaxial cable, fiber optic, digital Subscriber Line (DSL)), or wireless (e.g., infrared, wireless, microwave, etc.) means from one website, computer, server, or data center. Computer readable storage media can be any available media that can be accessed by a computer or data storage devices, such as servers, data centers, etc., that contain an integration of one or more available media. Usable media may be magnetic media, (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., DVDs), or semiconductor media (e.g., solid State Disks (SSDs)), among others.
Although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims (11)
1. The method for acquiring the detailed evaluation data of the target oil product is characterized by comprising the following steps of:
determining the class of the oil product affiliated to the target oil product according to the criticizing data of the target oil product, wherein the criticizing data of the target oil product comprises macroscopic physical property data of the target oil product;
searching whether an oil sample consistent with the target oil exists in an oil database of the oil types affiliated by the target oil;
if no oil sample consistent with the target oil is found in the oil database, searching a plurality of oil samples similar to the target oil in the oil database of the oil types affiliated to the target oil;
determining the mixing proportion of the oil samples by using a mixed integer nonlinear programming method, and mixing the oil samples into a blended oil according to the mixing proportion;
determining molecular composition data and macroscopic physical property data of the blended oil based on the molecular composition data and macroscopic physical property data of each of the plurality of oil samples in the blending proportion;
and taking the molecular composition data and the macroscopic physical property data of the blended oil product as detailed evaluation data of the target oil product, wherein the macroscopic physical property data in the detailed evaluation data of the target oil product is more than the macroscopic physical property data in the criticizing data of the target oil product.
2. The method for obtaining detailed evaluation data of a target oil product according to claim 1, further comprising the steps of:
and if the oil product sample consistent with the target oil product is found in the oil product database, taking the molecular composition data and macroscopic physical property data of the oil product sample as detailed evaluation data of the target oil product.
3. The method of claim 1, wherein the macro physical property data of the target oil product detailed evaluation data is any of boiling point, density, octane number, aromatic hydrocarbon, olefin, benzene, flash point, refractive index, congeal point, cloud point, pour point, aniline point, freeze point, viscosity index, viscosity, API gravity, and wax content.
4. The method for obtaining detailed evaluation data of a target oil product according to claim 1, wherein the step of determining the molecular composition data and macroscopic physical property data of the blended oil product based on the blending ratio and the molecular composition data and macroscopic physical property data of each of the plurality of oil product samples specifically comprises:
determining molecular composition data of the blended oil based on the blending ratio and the molecular composition data of the plurality of oil samples;
for one linear macroscopic physical property, weighting and summing the data of the linear macroscopic physical properties of the oil samples according to a mixing proportion to obtain the data of the linear macroscopic physical properties of the blended oil;
for a nonlinear macroscopic property, determining the data of the nonlinear macroscopic property of the blended oil based on the molecular composition data of the blended oil and a corresponding property calculation model.
5. The system for acquiring the target oil product detailed evaluation data is characterized by comprising the following components:
the first analysis module is used for determining the class of the oil product affiliated to the target oil product according to the criticizing data of the target oil product, wherein the criticizing data of the target oil product comprises macroscopic physical property data of the target oil product;
the first searching module is used for searching whether an oil sample consistent with the target oil exists in an oil database of the oil types affiliated to the target oil;
the second searching module is used for searching a plurality of oil samples similar to the target oil in the oil database of the oil types affiliated to the target oil if the oil samples consistent with the target oil are not found in the oil database;
the blending module is used for determining the blending proportion of the plurality of oil samples by utilizing a mixed integer nonlinear programming method and blending the plurality of oil samples into blended oil according to the blending proportion;
the second analysis module is used for determining the molecular composition data and macroscopic physical property data of the blended oil based on the mixing proportion and the molecular composition data and macroscopic physical property data of each of the plurality of oil samples;
and the first output module is used for taking the molecular composition data and the macroscopic physical property data of the blended oil product as detailed evaluation data of the target oil product, wherein the macroscopic physical property data in the detailed evaluation data of the target oil product is more than the macroscopic physical property data in the criticizing data of the target oil product.
6. The system of claim 5, further comprising a second output module, wherein the second output module is configured to take molecular composition data and macroscopic physical property data of an oil sample as detailed evaluation data of a target oil if the oil sample is found in an oil database to be consistent with the target oil.
7. The system of claim 5, wherein the macro physical property data of the target oil product detailed evaluation data in the first output module is any of boiling point, density, octane number, aromatic hydrocarbon, olefin, benzene, flash point, refractive index, congeal point, cloud point, pour point, aniline point, freeze point, viscosity index, viscosity, API gravity, and wax content.
8. The system for obtaining target oil product detailed evaluation data according to claim 5, wherein the second analysis module comprises:
the determining unit is used for determining the molecular composition data of the blended oil based on the mixing proportion and the molecular composition data of the oil samples;
the first calculation unit is used for carrying out weighted summation on the data of the linear macroscopic physical properties of the oil samples according to the mixing proportion to obtain the data of the linear macroscopic physical properties of the blended oil;
and the second calculation unit is used for determining the data of the nonlinear macroscopic physical property of the blended oil according to the molecular composition data of the blended oil and the corresponding physical property calculation model.
9. The electronic equipment is characterized by comprising a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory are communicated with each other through the communication bus;
a memory for storing a computer program;
the processor is configured to implement the method for acquiring target oil detailed evaluation data according to any one of claims 1 to 4 when executing the program stored in the memory.
10. The electronic device of claim 9, wherein the memory is a disk memory and the processor is one of a central processing unit, a network processor, a digital signal processor, and a field programmable gate array.
11. A computer-readable storage medium storing one or more programs executable by one or more processors to implement the method of obtaining target oil detailed evaluation data of any one of claims 1 to 4.
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