Storage device, color detection method, color detection device and color detection equipment for petroleum products

Abstract

The invention discloses a memory and a color detection method and device for a petroleum product. The method comprises the following steps: measuring absorbance of standard colorimetric solutions at three preset wavelengths by using a spectrophotometer so as to obtain tristimulus values of the standard colorimetric solutions; according to the tristimulus value of each standard colorimetric solution, respectively calculating the chromatic aberration value of each standard colorimetric solution; generating a color prediction model for predicting the Seibaud color value of the petroleum product to be detected by taking the Seibaud color value and the color difference value of each standard colorimetric solution as modeling data; the method comprises the following steps: acquiring tristimulus values of a petroleum product to be detected by using a spectrophotometer; calculating a color difference value of the to-be-detected petroleum product according to the tristimulus value of the to-be-detected petroleum product; generating a Siebaud color value of the to-be-detected petroleum product through a color prediction model by taking the color difference value of the to-be-detected petroleum product as input; according to the invention, the manual workload and the manual subjective error can be greatly reduced, so that the color detection efficiency and accuracy of the petroleum product are improved.

Description

Technical Field

[0001] This invention relates to the field of industrial measurement, and particularly to memory, methods, apparatus and equipment for color detection of petroleum products. Background Technology

[0002] During the production process, measuring the color of petroleum products can reflect a variety of important information, such as the degree of refining, the distillation process, and the degree of contamination from mixed oils. Therefore, petroleum products such as diesel, jet fuel, and white oil all use the color of petroleum products as an important control indicator.

[0003] In the existing technology, the main method for color detection of petroleum products is the Cybot color standard GB / T 3555. The Cybot color standard GB / T 3555 determines the color of the sample by comparing it with a standard color chart. This method relies on the subjective judgment of the tester.

[0004] The inventors discovered through research that existing methods for detecting the color of petroleum products have at least the following drawbacks:

[0005] GB / T 3555 standard color charts vary between manufacturers and can change color over time. Furthermore, different individuals have different color sensitivities, making manual judgment of the Seybert color of test samples inefficient, prone to misjudgment, and lacking in repeatability and reproducibility. GB / T 3555 also requires a large volume of samples, making the cleaning and maintenance of sample tubes and optical eyepieces difficult.

[0006] The information disclosed in this background section is intended only to enhance the understanding of the overall background of the invention and should not be construed as an admission or in any way implying that the information constitutes prior art known to those skilled in the art. Summary of the Invention

[0007] The purpose of this invention is to improve the efficiency and accuracy of color detection of petroleum products, and to improve the repeatability and reproducibility of the test.

[0008] This invention provides a color detection method for petroleum products, comprising the following steps:

[0009] S11. Set multiple standard colorimetric solutions and determine the Seybert color value of each standard colorimetric solution respectively;

[0010] S12. Obtain the absorption spectrum of each of the standard colorimetric solutions using a spectrophotometer, and obtain the tristimulus values ​​of each of the standard colorimetric solutions by the absorbance at three preset wavelengths.

[0011] S13. Calculate the color difference value of each of the standard colorimetric solutions based on the tristimulus values ​​of each of the standard colorimetric solutions.

[0012] S14. Establish the correspondence between the Cyborg color values ​​and color difference values ​​of each of the standard colorimetric liquids, and use the Cyborg color values ​​and color difference values ​​as modeling data to generate a color prediction model with color difference values ​​as input to predict the corresponding Cyborg color values.

[0013] S15. When performing color detection on the petroleum product to be tested, a spectrophotometer is used to obtain the absorption spectrum of the petroleum product to be tested, and the tristimulus value of the petroleum product to be tested is obtained by the absorbance of three preset wavelengths.

[0014] S16. Calculate the color difference value of the petroleum product to be tested based on the tristimulus value of the petroleum product to be tested.

[0015] S17. Using the color difference value of the petroleum product to be tested as input, generate the Seybert color value of the petroleum product to be tested through the color prediction model.

[0016] In another aspect of this invention, an apparatus for a color detection method for petroleum products is also provided, comprising:

[0017] A colorimetric liquid color determination unit is used to set multiple standard colorimetric liquids and obtain the Seybert color value of each of the standard colorimetric liquids respectively;

[0018] The tristimulus value calculation unit for colorimetric solutions is used to obtain the absorption spectrum of each of the standard colorimetric solutions using a spectrophotometer, and to obtain the tristimulus value of each of the standard colorimetric solutions by the absorbance of three preset wavelengths.

[0019] The color difference value calculation unit is used to calculate the color difference value of each standard colorimetric solution based on the tristimulus values ​​of each standard colorimetric solution.

[0020] The prediction model building unit is used to establish the correspondence between the Cybaud color values ​​and color difference values ​​of each of the standard colorimetric liquids, and to generate a color prediction model with color difference value as input, using Cybaud color values ​​and color difference values ​​as modeling data, to predict the corresponding Cybaud color values.

[0021] The product tristimulus value acquisition unit is used to obtain the absorption spectrum of the petroleum product to be tested using a spectrophotometer when performing color detection on the petroleum product to be tested, and to obtain the tristimulus value of the petroleum product to be tested by the absorbance of three preset wavelengths.

[0022] The product color difference value calculation unit is used to calculate the color difference value of the petroleum product under test based on the tristimulus value of the petroleum product under test.

[0023] The product color calculation unit is used to generate the Seybert color value of the petroleum product under test by taking the color difference value of the petroleum product under test as input and through the color prediction model.

[0024] In another aspect of the present invention, a memory is also provided, including a software program adapted for a processor to execute the steps of the above-described color detection method for petroleum products.

[0025] Another aspect of this invention provides a color detection device for petroleum products. The color detection device for petroleum products includes a computer program stored in a memory. The computer program includes program instructions. When the program instructions are executed by a computer, the computer performs the methods described in the above aspects and achieves the same technical effects.

[0026] Compared with the prior art, the present invention has the following beneficial effects:

[0027] In this invention, after determining the Cypher color values ​​of multiple standard colorimetric solutions, the absorption spectrum of each standard colorimetric solution is obtained using a spectrophotometer, thereby obtaining the tristimulus values ​​of each standard colorimetric solution; then, the color difference value of each standard colorimetric solution is calculated based on the tristimulus values; in this way, the color difference value of each standard colorimetric solution can be used as modeling data to train and generate a color prediction model that can predict the corresponding Cypher color value.

[0028] In this invention, when measuring the color of a petroleum product, the absorbance of each preset wavelength of the petroleum product is obtained using a spectrophotometer, and then the corresponding tristimulus values ​​are obtained. The color difference value of the petroleum product is then calculated. Then, using the color difference value of the petroleum product as input, the Cypher color value of the petroleum product can be generated through a color prediction model.

[0029] This invention only requires personnel to use a spectrophotometer for color measurement, and subsequent data processing can be handled by computer equipment to obtain the test results. There is no need to manually judge the color of petroleum products by comparing color charts. Therefore, not only is the detection efficiency greatly improved, but also the misjudgment in the manual judgment process is reduced. In addition, this invention can improve the efficiency and accuracy of petroleum product color detection, and improve the repeatability and reproducibility of the test.

[0030] Furthermore, this invention uses a small sample volume, and a test optical path of only 10 mm is sufficient to ensure test accuracy. This invention requires no pretreatment and enables rapid detection, thus achieving online detection of the color of petroleum products.

[0031] The above description is merely an overview of the technical solution of the present invention. In order to better understand the technical means of the present invention and to implement it according to the contents of the specification, and to make the above and other objects, technical features and advantages of the present invention easier to understand, one or more preferred embodiments are listed below and described in detail with reference to the accompanying drawings. Attached Figure Description

[0032] Figure 1 This is a flowchart illustrating the steps of the color detection method for petroleum products according to the present invention;

[0033] Figure 2 This is a schematic diagram of the structure of the color detection device for petroleum products according to the present invention;

[0034] Figure 3 This is a schematic diagram of the structure of the color detection device for petroleum products according to the present invention. Detailed Implementation

[0035] The specific embodiments of the present invention will now be described in detail with reference to the accompanying drawings, but it should be understood that the scope of protection of the present invention is not limited to the specific embodiments.

[0036] Unless otherwise expressly stated, throughout the specification and claims, the term "comprising" or its variations such as "including" or "comprises" shall be understood to include the stated elements or components without excluding other elements or other components.

[0037] In this document, for ease of description, spatial relative terms such as “below,” “under,” “down,” “above,” “above,” “upper,” etc., are used to describe the relationship of one element or feature to another element or feature in the accompanying drawings. It should be understood that spatial relative terms are intended to encompass different orientations of an object in use or operation, in addition to those depicted in the figures. For example, if an object in the figure is flipped, an element described as “below” or “under” another element or feature would be oriented “above” that element or feature. Thus, the exemplary term “below” can encompass both the downward and upward orientations. An object may also have other orientations (rotated 90 degrees or other orientations), and the spatial relative terms used herein should be interpreted accordingly.

[0038] In this document, the terms "first," "second," etc., are used to distinguish two different elements or parts, and are not used to define specific positions or relative relationships. In other words, in some embodiments, the terms "first," "second," etc., can also be used interchangeably.

[0039] Example 1

[0040] In order to improve the efficiency and accuracy of color detection of petroleum products, and to enhance test repeatability and reproducibility, such as Figure 1 As shown, this embodiment of the invention provides a color detection method for petroleum products, including the following steps:

[0041] S11. Set multiple standard colorimetric solutions and determine the Seybert color value of each standard colorimetric solution respectively;

[0042] In this embodiment of the invention, it is first necessary to set up a number of standard colorimetric solutions with different color values. The standard colorimetric solutions are prepared using decolorized kerosene and asphalt. Then, the Seybert color value of each standard colorimetric solution is determined.

[0043] In practical applications, standard colorimetric solutions corresponding to each Seybert color value can be set according to the range of Seybert color values ​​(-16 to +30).

[0044] S12. Obtain the absorption spectrum of each of the standard colorimetric solutions using a spectrophotometer, and obtain the tristimulus values ​​of each of the standard colorimetric solutions by the absorbance at three preset wavelengths.

[0045] In this embodiment of the invention, instead of directly using standard colorimetric solutions to perform manual colorimetric comparison with the sample of the petroleum product to be tested, a spectrophotometer is used to obtain the absorption spectrum of each standard colorimetric solution. The tristimulus values ​​of each standard colorimetric solution are obtained by measuring the absorbance at three preset wavelengths (usually expressed as red primary color stimulus X, green primary color stimulus Y, and blue primary color stimulus Z).

[0046] In this embodiment of the invention, the absorbance ranges of the three preset wavelengths used to obtain the tristimulation values ​​of each standard colorimetric solution are 577nm-600nm, 492nm-577nm, and 380nm-492nm, respectively; preferably, the three preset wavelengths can be 595nm, 555nm, and 445nm, respectively.

[0047] In a specific example, the tristimulus values ​​X, Y, and Z of the CIE 1931 standard colorimetric system, and the color stimulus function, can be expressed as:

[0048] φ(λ)=τ(λ)S(λ)

[0049] In the formula, τ(λ) represents the spectral transmittance of the object; S(λ) represents the relative spectral power distribution of the standard illuminator used.

[0050] The transmittance is given as a percentage, and the formula for calculating the tristimulus value can be approximated as follows:

[0051] X = (0.7833 * T1) + (0.1974 * T3)

[0052] Y = T2

[0053] Z = 1.1822 * T3

[0054] In the formula, T1, T2, and T3 represent the percentage transmittance at three preset wavelengths λ1, λ2, and λ3, respectively.

[0055] It should be noted that the percentage transmittance can be calculated from the absorbance at that wavelength measured by a spectrophotometer.

[0056] S13. Calculate the color difference value of each of the standard colorimetric solutions based on the tristimulus values ​​of each of the standard colorimetric solutions.

[0057] After obtaining the tristimulus values ​​of each standard colorimetric solution, the color difference value of each standard colorimetric solution can be calculated based on the tristimulus values ​​of each standard colorimetric solution.

[0058] In practical applications, color difference calculation formulas such as CIE 1931, CIE1976, DE94, DE2000, or DECMC can be used to obtain the color difference values ​​of each standard colorimetric liquid.

[0059] Based on the tristimulus values ​​of each standard colorimetric liquid, and using standard light source C as a reference white, multiple sets of color difference values ​​can be obtained.

[0060] S14. Establish the correspondence between the Cyborg color values ​​and color difference values ​​of each of the standard colorimetric liquids, and use the Cyborg color values ​​and color difference values ​​as modeling data to generate a color prediction model with color difference values ​​as input to predict the corresponding Cyborg color values.

[0061] After obtaining the color difference values ​​of each standard colorimetric liquid, and combining them with the Cybot color values ​​of each standard colorimetric liquid, the Cybot color values ​​and color difference values ​​of the standard colorimetric liquids are used as modeling data. Through model training, a color prediction model for predicting Cybot color values ​​is constructed.

[0062] In practical applications, the methods used to train color prediction models can include least squares, inverse least squares, multivariate linear regression, principal component regression, partial least squares, robust partial least squares, or artificial neural networks.

[0063] S15. When performing color detection on the petroleum product to be tested, a spectrophotometer is used to obtain the absorption spectrum of the petroleum product to be tested, and the tristimulus value of the petroleum product to be tested is obtained by the absorbance of three preset wavelengths.

[0064] To obtain the color difference value of the petroleum product under test, it is first necessary to use a spectrophotometer to acquire the absorbance of the petroleum product at each preset wavelength and to obtain the tristimulus values ​​of the petroleum product under test. In practical applications, the petroleum product under test can be sampled, and then the absorbance of the petroleum product at each preset wavelength can be quickly acquired using a spectrophotometer.

[0065] S16. Calculate the color difference value of the petroleum product to be tested based on the tristimulus value of the petroleum product to be tested.

[0066] After obtaining the tristimulus values ​​of the petroleum product to be tested, the color difference value of the petroleum product to be tested can be calculated based on the tristimulus values.

[0067] S17. Using the color difference value of the petroleum product to be tested as input, generate the Seybert color value of the petroleum product to be tested through the color prediction model.

[0068] The prediction model in this embodiment of the invention uses the color difference value as input to predict the corresponding Cypher color value, that is, it can obtain the color value of the petroleum product to be tested in real time based on the color difference value of the petroleum product to be tested.

[0069] In summary, in this embodiment of the invention, after determining the Cypher color values ​​of multiple standard colorimetric solutions, the absorption spectrum of each standard colorimetric solution is obtained using a spectrophotometer, thereby obtaining the tristimulus values ​​of each standard colorimetric solution; then, the color difference value of each standard colorimetric solution is calculated based on the tristimulus values; in this way, the color difference value of each standard colorimetric solution can be used as modeling data to train and generate a color prediction model that can predict the corresponding Cypher color value.

[0070] In this embodiment of the invention, when measuring the color of a petroleum product to be tested, after obtaining the absorbance of each preset wavelength of the petroleum product to be tested using a spectrophotometer, the corresponding tristimulus values ​​are further obtained, and then the color difference value of the petroleum product to be tested is calculated; then, using the color difference value of the petroleum product to be tested as input, the Cypher color value of the petroleum product to be tested can be generated through a color prediction model.

[0071] In this embodiment of the invention, color measurement only requires personnel to use a spectrophotometer, and subsequent data processing can be handled by computer equipment to obtain the test results. There is no need to manually judge the color of petroleum products by comparing color charts. Therefore, not only is the detection efficiency greatly improved, but also the misjudgment in the manual judgment process is reduced. In addition, this invention can improve the efficiency and accuracy of petroleum product color detection, and improve the repeatability and reproducibility of the test.

[0072] Furthermore, in this embodiment of the invention, a sample volume and a test optical path of 10 mm are sufficient to ensure test accuracy. In addition, this embodiment of the invention requires no pretreatment and enables rapid detection, thus achieving online detection of the color of petroleum products.

[0073] Example 2

[0074] Corresponding to the method embodiment, another aspect of the present invention also provides a color detection device for petroleum products. Figure 2 This diagram illustrates the structure of a color detection device for petroleum products provided in an embodiment of the present invention. The color detection device for petroleum products is... Figure 1The device corresponding to the color detection method for petroleum products described in the corresponding embodiment is implemented through a virtual device. Figure 1 In the corresponding embodiment of the color detection method for petroleum products, the various virtual modules constituting the color detection device for petroleum products can be executed by electronic devices, such as network devices, terminal devices, or servers. Specifically, the color detection device for petroleum products in the embodiment of the present invention includes:

[0075] The colorimetric liquid color determination unit 01 is used to set multiple standard colorimetric liquids and obtain the Seybert color value of each of the standard colorimetric liquids respectively;

[0076] The tristimulus value calculation unit 02 is used to obtain the absorption spectrum of each of the standard colorimetric solutions using a spectrophotometer, and to obtain the tristimulus value of each of the standard colorimetric solutions by the absorbance of three preset wavelengths.

[0077] The color difference value calculation unit 03 is used to calculate the color difference value of each standard colorimetric solution based on the tristimulus values ​​of each standard colorimetric solution.

[0078] Prediction model building unit 04 is used to establish the correspondence between the Cybaud color values ​​and color difference values ​​of each of the standard colorimetric liquids, and to generate a color prediction model with color difference value as input, using Cybaud color values ​​and color difference values ​​as modeling data, to predict the corresponding Cybaud color values.

[0079] Product tristimulus value acquisition unit 05 is used to acquire the absorption spectrum of the petroleum product to be tested using a spectrophotometer when performing color detection on the petroleum product to be tested, and to obtain the tristimulus value of the petroleum product to be tested by the absorbance of three preset wavelengths.

[0080] Product color difference value calculation unit 06 is used to calculate the color difference value of the petroleum product under test based on the tristimulus value of the petroleum product under test.

[0081] Product color calculation unit 07 is used to generate the Seybert color value of the petroleum product under test by taking the color difference value of the petroleum product under test as input and through the color prediction model.

[0082] Since the working principle and beneficial effects of the color detection device for petroleum products in the embodiments of the present invention have already been demonstrated, Figure 1 The corresponding color detection methods for petroleum products are also described and explained, so they can be referenced together, and will not be repeated here.

[0083] Example 3

[0084] Corresponding to the method embodiments, this embodiment of the invention also provides a drawing device for data analysis, such as a terminal or server. The server can be a standalone physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms. The terminal can be a smartphone, tablet computer, laptop computer, desktop computer, etc., but is not limited to these.

[0085] Example diagrams of the hardware structure block diagrams of the plotting device for data analysis provided in this application are shown below. Figure 3 As shown, it may include:

[0086] Processor 1, communication interface 2, memory 3, and communication bus 4;

[0087] The processor 1, communication interface 2, and memory 3 communicate with each other via communication bus 4.

[0088] Optionally, communication interface 2 can be an interface of a communication module, such as the interface of a GSM module;

[0089] Processor 1 may be a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of this application.

[0090] Memory 3 may include high-speed RAM memory, and may also include non-volatile memory, such as at least one disk storage device.

[0091] Specifically, processor 1 is used to execute the computer program stored in memory 3 to perform the following steps:

[0092] S11. Set multiple standard colorimetric solutions and obtain the Seybert color value of each standard colorimetric solution respectively;

[0093] S12. Obtain the absorption spectrum of each of the standard colorimetric solutions using a spectrophotometer, and obtain the tristimulus values ​​of each of the standard colorimetric solutions by the absorbance at three preset wavelengths.

[0094] S13. Calculate the color difference value of each of the standard colorimetric solutions based on the tristimulus values ​​of each of the standard colorimetric solutions.

[0095] S14. Establish the correspondence between the Cyborg color values ​​and color difference values ​​of each of the standard colorimetric liquids, and use the Cyborg color values ​​and color difference values ​​as modeling data to generate a color prediction model with color difference values ​​as input to predict the corresponding Cyborg color values.

[0096] S15. When performing color detection on the petroleum product to be tested, a spectrophotometer is used to obtain the absorption spectrum of the petroleum product to be tested, and the tristimulus value of the petroleum product to be tested is obtained by the absorbance of three preset wavelengths.

[0097] S16. Calculate the color difference value of the petroleum product to be tested based on the tristimulus value of the petroleum product to be tested.

[0098] S17. Using the color difference value of the petroleum product to be tested as input, generate the Seybert color value of the petroleum product to be tested through the color prediction model.

[0099] The above-described product can execute the methods provided in the embodiments of the present invention, and has the corresponding functional modules and beneficial effects for executing the methods. Technical details not described in detail in this embodiment can be found in the plotting method for data analysis provided in the embodiments of the present invention.

[0100] Example 4

[0101] In this embodiment of the invention, a storage medium is also provided, which can store a program suitable for execution by a processor, the program being used for:

[0102] S11. Set multiple standard colorimetric solutions and obtain the Seybert color value of each standard colorimetric solution respectively;

[0103] S12. Obtain the absorption spectrum of each of the standard colorimetric solutions using a spectrophotometer, and obtain the tristimulus values ​​of each of the standard colorimetric solutions by the absorbance at three preset wavelengths.

[0104] S13. Calculate the color difference value of each of the standard colorimetric solutions based on the tristimulus values ​​of each of the standard colorimetric solutions.

[0105] S14. Establish the correspondence between the Cyborg color values ​​and color difference values ​​of each of the standard colorimetric liquids, and use the Cyborg color values ​​and color difference values ​​as modeling data to generate a color prediction model with color difference values ​​as input to predict the corresponding Cyborg color values.

[0106] S15. When performing color detection on the petroleum product to be tested, a spectrophotometer is used to obtain the absorption spectrum of the petroleum product to be tested, and the tristimulus value of the petroleum product to be tested is obtained by the absorbance of three preset wavelengths.

[0107] S16. Calculate the color difference value of the petroleum product to be tested based on the tristimulus value of the petroleum product to be tested.

[0108] S17. Using the color difference value of the petroleum product to be tested as input, generate the Seybert color value of the petroleum product to be tested through the color prediction model.

[0109] Optionally, the refined and extended functions of the program can be found in the description above.

[0110] The above-described product can execute the methods provided in the embodiments of the present invention, and has the corresponding functional modules and beneficial effects for executing the methods. Technical details not described in detail in this embodiment can be found in the methods provided in other embodiments of the present invention.

[0111] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0112] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. Furthermore, the couplings or direct couplings or communication connections shown or discussed may be indirect couplings or communication connections through interfaces, devices, or units, and may be electrical, mechanical, or other forms.

[0113] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0114] In addition, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0115] It should be understood that in the embodiments of this application, the claims, various embodiments, and features can be combined with each other to solve the aforementioned technical problems.

[0116] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0117] The above description of the disclosed embodiments enables those skilled in the art to make or use this application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for color detection of petroleum products, characterized in that, Including the following steps: S11. Set multiple standard colorimetric solutions and obtain the Seybert color value of each standard colorimetric solution respectively; S12. Obtain the absorption spectrum of each of the standard colorimetric solutions using a spectrophotometer, and obtain the tristimulus values ​​of each of the standard colorimetric solutions by the absorbance at three preset wavelengths. S13. Calculate the color difference value of each of the standard colorimetric solutions based on the tristimulus values ​​of each of the standard colorimetric solutions. S14. Establish the correspondence between the Cyborg color values ​​and color difference values ​​of each of the standard colorimetric liquids, and use the Cyborg color values ​​and color difference values ​​as modeling data to generate a color prediction model with color difference values ​​as input to predict the corresponding Cyborg color values. S15. When performing color detection on the petroleum product to be tested, a spectrophotometer is used to obtain the absorption spectrum of the petroleum product to be tested, and the tristimulus value of the petroleum product to be tested is obtained by the absorbance of three preset wavelengths. S16. Calculate the color difference value of the petroleum product to be tested based on the tristimulus value of the petroleum product to be tested. S17. Using the color difference value of the petroleum product to be tested as input, generate the Seybert color value of the petroleum product to be tested through the color prediction model.

2. The color detection method for petroleum products according to claim 1, characterized in that, The value ranges of each of the preset wavelengths include: First preset wavelength: 577nm-600nm; Second preset wavelength: 492nm-577nm; The third preset wavelength is 380nm-492nm.

3. The color detection method for petroleum products according to claim 2, characterized in that, The values ​​of each of the preset wavelengths include: First preset wavelength: 595nm; Second preset wavelength: 555nm; Third preset wavelength: 445nm.

4. The color detection method for petroleum products according to claim 1, characterized in that, The methods used to train the prediction model include: Least squares, inverse least squares, multivariate linear regression, principal component regression, partial least squares, robust partial least squares, or artificial neural networks.

5. The color detection method for petroleum products according to claim 1, characterized in that, The Saibot color value ranges from -16 to +30.

6. A color detection device for petroleum products, characterized in that, include: A colorimetric liquid color determination unit is used to set multiple standard colorimetric liquids and obtain the Seybert color value of each of the standard colorimetric liquids respectively; The tristimulus value calculation unit for colorimetric solutions is used to obtain the absorption spectrum of each of the standard colorimetric solutions using a spectrophotometer, and to obtain the tristimulus value of each of the standard colorimetric solutions by the absorbance of three preset wavelengths. The color difference value calculation unit is used to calculate the color difference value of each standard colorimetric solution based on the tristimulus values ​​of each standard colorimetric solution. The prediction model building unit is used to establish the correspondence between the Cybaud color values ​​and color difference values ​​of each of the standard colorimetric liquids, and to generate a color prediction model with color difference value as input, using Cybaud color values ​​and color difference values ​​as modeling data, to predict the corresponding Cybaud color values. The product tristimulus value acquisition unit is used to obtain the absorption spectrum of the petroleum product to be tested using a spectrophotometer when performing color detection on the petroleum product to be tested, and to obtain the tristimulus value of the petroleum product to be tested by the absorbance of three preset wavelengths. The product color difference value calculation unit is used to calculate the color difference value of the petroleum product under test based on the tristimulus value of the petroleum product under test. The product color calculation unit is used to generate the Seybert color value of the petroleum product under test by taking the color difference value of the petroleum product under test as input and through the color prediction model.

7. The color detection device for petroleum products according to claim 6, characterized in that, The value ranges of each of the preset wavelengths include: First preset wavelength: 577nm-600nm; Second preset wavelength: 492nm-577nm; The third preset wavelength is 380nm-492nm.

8. The color detection device for petroleum products according to claim 7, characterized in that, The values ​​of each of the preset wavelengths include: First preset wavelength: 595nm; Second preset wavelength: 555nm; Third preset wavelength: 445nm.

9. The color detection device for petroleum products according to claim 6, characterized in that, The methods used to train the color prediction model include: Least squares, inverse least squares, multivariate linear regression, principal component regression, partial least squares, robust partial least squares, or artificial neural networks.

10. The color detection device for petroleum products according to claim 6, characterized in that, The Saibot color value ranges from -16 to +30.

11. A memory, characterized in that, Includes a software program adapted by a processor to perform the steps of the color detection method for petroleum products as described in any one of claims 1 to 5.

12. A method and apparatus for color detection of petroleum products, characterized in that, Includes a bus, a processor, and the memory as described in claim 11; The bus is used to connect the memory and the processor; The processor is used to execute the instruction set in the memory.

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