Method, device and equipment for online detection of properties of mixed oil conveyed by product oil pipeline

Abstract

The invention relates to an online detection method, device and equipment for the property of mixed oil conveyed by a product oil pipeline. The method comprises the following steps: obtaining to-be-detected product oil conveyed by the pipeline; detecting the mixed oil concentration of the to-be-detected product oil on line in real time by using a non-modeling method by adopting a near infrared spectroscopy method; and detecting the final boiling point and the flash point of the to-be-detected product oil on line in real time by adopting a pre-established calibration model. According to the method, the mixed oil concentration of the to-be-detected product oil can be detected online in real time based on the near infrared spectroscopy, the property values of the to-be-detected product oil can be detected online in real time based on the pre-established calibration model, and the property values at least comprise the final boiling point and the flash point. Therefore, more accurate data support can be provided for mixed oil cutting based on the mixed oil concentration, the final boiling point and the flash point of the to-be-detected product oil.

Description

Technical Field

[0001] The present invention relates to the field of transportation and storage technology, and in particular to an online detection method, device and equipment for mixed oil properties in finished oil pipeline transportation. Background Art

[0002] At present, domestic and foreign refined oil pipelines transport gasoline and diesel in sequence, mainly relying on online density meters, optical interface detectors (OID) and ultrasonic flow meters to distinguish the gasoline and diesel interfaces. The above three detection methods cannot reflect the quality evaluation indicators such as flash point and final distillation point of oil products. Dispatchers lack perceptual knowledge when cutting oil products at the terminal. They often need to combine experience to determine the timing of cutting mixed oil, and cannot accurately grasp whether the cut oil products meet the standards.

[0003] Near infrared spectroscopy is an ideal signal for qualitative and quantitative analysis of oil products. Combined with spectral analysis calibration methods, it constitutes a rapid analysis technology for oil quality. It is widely used in oil refining enterprises and gasoline blending processes. It has the potential to achieve precise monitoring of the interface of sequentially transported finished oil pipelines and real-time analysis of oil physical properties. At present, the mainstream calibration technology of this technology, partial least squares (PLS) method, has the problem of large workload in calibration sample collection, modeling and maintenance, which is the main difficulty in current applications.

[0004] In addition, analytical instruments may be affected by various interference factors such as changes in ambient temperature, changes in the temperature and pressure of the material itself, so high requirements are placed on sample pretreatment and instrument placement environment. In refineries, the composition changes of materials monitored online are generally relatively small, and the modeling and maintenance workload is relatively small. The pressure of the measured material is not high. Usually, the material is transported from the device to the analysis room, and its spectrum is collected online after decompression, filtration, degassing and constant temperature treatment. However, unlike refinery materials, pipeline-transported refined oil has the following characteristics: high pressure of refined oil, high moving line speed (high Reynolds index), large temperature changes throughout the year, and the same grade of refined oil produced by different manufacturers has large changes in composition, resulting in a large modeling workload. Therefore, in terms of modeling of multiple types of oil products, spectrum collection of high-pressure refined oil, and elimination of the impact of temperature changes on model performance, all pose serious technical challenges to the online detection of the spectrum of pipeline-transported refined oil and mixed oil properties.

[0005] At present, the method usually adopted for measuring oil mixing in pipeline transportation based on near infrared spectroscopy is to only identify oil mixing or predict oil mixing ratio to determine the oil mixing interface, but it is impossible to determine whether the oil mixing properties meet the requirements. Therefore, cutting the oil mixing interface based on the existing technology may cause great economic losses. In addition, the existing prediction of oil mixing ratio based on near infrared spectroscopy requires the use of PLS ​​and other methods to establish a model. Summary of the invention

[0006] The technical problem to be solved by the present invention is to provide a method, device and equipment for online detection of mixed oil properties in finished oil pipeline transportation, aiming to solve at least one of the above technical problems.

[0007] In the first aspect, the technical solution of the present invention to solve the above technical problem is as follows: an online detection method for mixed oil properties in finished oil pipeline transportation, the method comprising:

[0008] Obtaining the finished oil to be tested that is transported by a pipeline, wherein the finished oil to be tested is composed of two pure oil products;

[0009] Adopting near infrared spectroscopy and non-modeling method to detect the mixed oil concentration of the finished oil to be detected in real time online;

[0010] The pre-established calibration model is used to detect the property values ​​of the finished oil to be detected online in real time, and the property values ​​at least include the final distillation point and the flash point.

[0011] The beneficial effects of the present invention are as follows: based on near-infrared spectroscopy, the mixed oil concentration of the finished oil to be detected can be detected online in real time using a non-modeling method; based on a pre-established calibration model, the final distillation point and flash point of the finished oil to be detected can be detected online in real time, so that based on the mixed oil concentration, final distillation point and flash point of the finished oil to be detected, more accurate data support can be provided for mixed oil cutting.

[0012] Based on the above technical solution, the present invention can also be improved as follows.

[0013] Furthermore, the above-mentioned use of a pre-established calibration model to detect the property value of the to-be-tested refined oil in real time online includes:

[0014] Determining the delivery pressure of the finished oil to be tested;

[0015] Based on the delivery pressure of the refined oil to be tested, determining a target calibration model corresponding to the delivery pressure;

[0016] Based on the target calibration model, the property value of the finished oil to be tested is determined.

[0017] The beneficial effect of adopting the above further scheme is that, based on the target calibration model that matches the delivery pressure of the finished oil to be tested, the property value of the finished oil to be tested under the delivery pressure can be accurately detected.

[0018] Furthermore, the above-mentioned near infrared spectroscopy method is used to detect the mixed oil concentration of the finished oil to be detected in real time online using a non-modeling method, including:

[0019] Adopting near infrared spectroscopy and non-modeling method to obtain the spectral components of different oil components in the finished oil to be detected in real time online;

[0020] Based on each of the spectral components, the mixed oil concentration of the finished oil to be tested is determined.

[0021] The beneficial effect of adopting the above further scheme is that, since the spectral components of different oil components in the mixed oil are different, the mixed oil concentration of the finished oil to be tested can be accurately determined based on the spectral components of different oil components in the finished oil to be tested.

[0022] Furthermore, the above method also includes:

[0023] Obtaining the absorbance of the pure oil spectral component in the finished oil to be detected;

[0024] Determine the mixed oil concentration correction value corresponding to the finished oil to be tested based on a pre-established first corresponding relationship and the absorbance, wherein the first corresponding relationship is a corresponding relationship between the absorbance of each pure oil spectral component in the mixed oil and the each pure oil concentration correction value in the mixed oil;

[0025] The mixed oil concentration of the finished oil to be tested is corrected according to the mixed oil concentration correction value.

[0026] The beneficial effect of adopting the above further scheme is that by obtaining the corresponding pure oil spectral components in the finished oil, there is no need to collect or configure a large number of mixed samples to establish a PLS and other concentration ratio prediction model.

[0027] Furthermore, the above calibration model is established based on the following method:

[0028] Obtaining mixed oil samples under different delivery pressures, each of the mixed oil samples being obtained by configuring different pure oil products;

[0029] Determine the near infrared spectra of mixed oil samples at different delivery pressures;

[0030] Based on the near infrared spectra of the mixed oil samples under different delivery pressures and the property values ​​corresponding to each mixed oil sample, a calibration model corresponding to the different delivery pressures is established.

[0031] The beneficial effect of adopting the above further scheme is that different calibration models are trained based on different delivery pressures, which can adapt to the detection of the final distillation point and flash point of the finished oil under different delivery pressures.

[0032] Furthermore, before adopting near infrared spectroscopy to detect the mixed oil concentration of the finished oil to be detected online in real time, the method further includes:

[0033] The near infrared spectrum of the finished oil to be tested is pre-processed by normalization, first derivative, second derivative, baseline correction or angle vector method. The angle vector spectrum data processing method is used for the finished oil without constant temperature treatment, and the absorbance (mode vector) affected by multiplicative effects such as density and temperature is converted into an angle vector not affected by multiplicative effects, thereby effectively eliminating the influence of density and temperature on model performance and improving the prediction accuracy of the model.

[0034] The beneficial effect of adopting the above further scheme is that the near-infrared spectrum of the refined oil to be tested is subjected to spectral preprocessing, thereby improving the accuracy of the spectral data.

[0035] Furthermore, the above-mentioned collection of refined oil at different delivery pressures includes:

[0036] Any mixed oil sample is injected into the circulation pool through the injection device, and there are no bubbles in the mixed oil sample during the injection process. The pressure corresponding to the mixed oil sample in the circulation pool is adjusted, and the near-infrared spectra of the mixed oil sample in the circulation pool under different delivery pressures are collected by a near-infrared spectrometer; after the collection, the any mixed oil sample is discharged, cleaned with petroleum ether, blown dry with nitrogen, and the next mixed oil sample of the any mixed oil sample is collected.

[0037] The beneficial effect of adopting the above further solution is that the accuracy of the mixed oil samples can be improved by collecting the mixed oil samples under different delivery pressures in the above manner.

[0038] In a second aspect, in order to solve the above technical problems, the present invention also provides an online detection device for mixed oil properties in finished oil pipeline transportation, the device comprising:

[0039] An acquisition module is used to acquire the finished oil to be tested that is transported by a pipeline, wherein the finished oil to be tested is composed of two pure oil products;

[0040] A mixed oil concentration detection module, used to detect the mixed oil concentration of the finished oil to be detected online in real time by using near infrared spectroscopy and non-modeling method;

[0041] The terminal distillation point and flash point determination module is used to use a pre-established calibration model to detect the property values ​​of the finished oil to be detected online in real time, and the property values ​​at least include the terminal distillation point and the flash point.

[0042] In the third aspect, in order to solve the above-mentioned technical problem, the present invention also provides an electronic device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the online detection method for mixed oil properties in refined oil pipeline transportation of the present application is implemented.

[0043] In a fourth aspect, in order to solve the above-mentioned technical problem, the present invention also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the online detection method for mixed oil properties in refined oil pipeline transportation of the present application is implemented.

[0044] Additional aspects and advantages of the present application will be partially given in the following description, which will become apparent from the following description, or will be understood through the practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required for describing the embodiments of the present invention are briefly introduced below.

[0046] Figure 1 A schematic flow chart of an online detection method for mixed oil properties in refined oil pipeline transportation provided by an embodiment of the present invention;

[0047] Figure 2 A near infrared spectrum of 0# diesel provided by one embodiment of the present invention;

[0048] Figure 3 A near infrared spectrum of 92# gasoline provided by one embodiment of the present invention;

[0049] Figure 4 A near infrared spectrum diagram of a mixed oil spectrum library provided by an embodiment of the present invention;

[0050] Figure 5 A comparison chart of the predicted final distillation point and the reference value of a finished oil product to be tested provided by one embodiment of the present invention;

[0051] Figure 6 A comparison chart of the predicted flash point and reference value of a finished oil to be tested provided by one embodiment of the present invention;

[0052] Figure 7 A schematic structural diagram of an online detection device for mixed oil properties in finished oil pipeline transportation provided by an embodiment of the present invention;

[0053] Figure 8 A schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0054] The principles and features of the present invention are described below. The examples given are only used to explain the present invention and are not used to limit the scope of the present invention.

[0055] The technical solution of the present invention and how the technical solution of the present invention solves the above-mentioned technical problems are described in detail below with specific embodiments. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The embodiments of the present invention will be described below in conjunction with the accompanying drawings.

[0056] The solution provided by the embodiment of the present invention can be applied to any application scenario where the mixed oil concentration, final distillation point and flash point of the finished oil need to be detected. The solution provided by the embodiment of the present invention can be executed by any electronic device, including at least one of the following: a smart phone, a tablet computer, a laptop computer, a desktop computer, a smart speaker, a smart watch, a smart TV, and a smart car device.

[0057] The embodiment of the present invention provides a possible implementation method, such as Figure 1 As shown, a flowchart of an online detection method for mixed oil properties in finished oil pipeline transportation is provided. The solution can be executed by any electronic device, for example, a terminal device, or a terminal device and a server. For the convenience of description, the method provided by the embodiment of the present invention will be described below by taking the terminal device as the execution subject as an example. Figure 1 The method may include the following steps:

[0058] Step S10, obtaining the finished oil to be tested that is transported by a pipeline, wherein the finished oil to be tested is composed of two pure oil products;

[0059] Step S20, using near infrared spectroscopy and a non-modeling method to detect the mixed oil concentration of the finished oil to be detected in real time online;

[0060] Step S30, using a pre-established calibration model, online and real-time detection of the property values ​​of the to-be-detected refined oil, wherein the property values ​​at least include the final distillation point and the flash point.

[0061] Through the method of the present invention, based on near-infrared spectroscopy, the mixed oil concentration of the finished oil to be tested can be detected online in real time using a non-modeling method, and based on a pre-established calibration model, the final distillation point and flash point of the finished oil to be tested can be detected online in real time, so that based on the mixed oil concentration, final distillation point and flash point of the finished oil to be tested, more accurate data support can be provided for mixed oil cutting.

[0062] The scheme of the present invention is further described below in conjunction with the following specific embodiments. In this embodiment, a method for online detection of mixed oil properties in pipeline transportation of refined oil products may include the following steps:

[0063] Step S10, obtaining the finished oil to be tested that is transported by a pipeline, wherein the finished oil to be tested is composed of two pure oil products;

[0064] The finished oil to be tested refers to finished oil including two different types of pure oil products, for example, finished oil formed by mixing pure diesel and pure gasoline. This solution does not limit the two pure oil products that make up the finished oil. Pure gasoline and pure diesel refer to oil products outside the mixed oil section of pipeline transportation, which can come from different refineries and different batches.

[0065] Step S20, using near infrared spectroscopy and a non-modeling method to detect the mixed oil concentration of the finished oil to be detected in real time online;

[0066] The mixed oil concentration refers to the ratio of different types of oil in the finished oil to be tested.

[0067] Optionally, an implementation of the above S20 is:

[0068] S201, using near infrared spectroscopy and a non-modeling method to obtain spectral components of different oil components in the finished oil to be tested online and in real time;

[0069] S201, determining the mixed oil concentration of the finished oil to be tested based on each of the spectral components.

[0070] There are many types of refined oil products transported by pipelines (different manufacturers produce the same brand but different compositions). One implementation of the above S201 is: based on the correspondence between each of the spectral components and the concentration, determine the mixed oil concentration of the refined oil to be tested, wherein the correspondence is established based on the intensity (absorbance) and concentration data of the spectral components of different oil components of the sample oil.

[0071] The existing technology requires a large number of samples to calibrate the concentration of mixed oil, with a wide range of property changes, a long sample collection cycle, and a large workload. This solution uses spectral quantitative theory (Lambert-Beer law) and a spectral extraction method, without the need for modeling. It has the characteristics of a small number of calibration samples, no limit on the range of property changes, a short modeling cycle, and easy maintenance.

[0072] Optionally, another implementation of the above optional S20 is:

[0073] Online real-time detection of the near infrared spectrum M of the finished oil to be detected c ;

[0074] Determination of near infrared spectroscopy from mixed oil spectral library c The spectrum with the smallest difference M ihl ;

[0075] The spectra M in the pre-built mixed oil spectral library are ihl and the near infrared spectrum M of the finished oil to be tested c Perform normalization, first-order differential or second-order differential preprocessing;

[0076] Based on the pre-established second correspondence and the spectrum M ihl , and obtain the spectrum M ihl Corresponding concentration ratio (mixed oil concentration) C a As the mixed oil concentration of the oil product of unknown concentration (finished oil to be tested), the second corresponding relationship is the corresponding relationship between different near-infrared spectra and different mixed oil concentrations.

[0077] Optionally, the specific steps of establishing the second corresponding relationship are:

[0078] Step 1: Construction of mixed oil spectral library: Using near-infrared spectroscopy, the spectral components of pure oil corresponding to different mixed oil concentrations are added to construct a mixed spectral library (mixed oil spectral library);

[0079] Establish the spectral matrix corresponding to the two pure oil products that form the mixed oil, where the spectral matrix of one pure oil product is A, and the spectral matrix of the other pure oil product is B = [B1, B2, ..., B h , …, B q ];

[0080] The spectral components of two pure oil products are added to construct a mixed oil product spectral library corresponding to the two pure oil products. The pure oil concentration ratio of one pure oil product contained in the mixed oil product spectral library is C a =[c a1 , c a2 , …, c ai , …, c az ], the pure oil concentration of another pure oil product is C b =[c b1 , c b2 , …, c bi , …, c bz ];

[0081] The calculation formula of the spectrum of mixed oil is M ihl =c al *A i +c bl *B h , where M ihl is the spectrum of a pure oil and a mixed oil spectrum of another pure oil, c al +c bl =1, c al *A i A is the near infrared spectrum i The pure oil accounts for c in the spectrum of the mixed oil. al The spectral components, c bj *B h The spectrum is B hThe pure oil accounts for c in the spectrum of the mixed oil. bj spectral components of

[0082] Step 2: Establish the second corresponding relationship between the spectrum of the mixed oil (different near-infrared spectra) and the oil concentration (mixed oil concentration):

[0083] A relationship curve between the mixed spectrum (different near-infrared spectra) and its corresponding concentration ratio (mixed oil concentration) is established, which is the second corresponding relationship.

[0084] The relationship between each spectrum and spectral components in the mixed oil spectral library can also be recorded. The spectral components include the self-composition and concentration ratio (pure oil concentration ratio) of the spectrum of pure oil products, so that the corresponding spectrum can be determined based on different spectral components.

[0085] As an example, the following method is used to construct a mixed oil spectral library:

[0086] 78 0# pure diesel samples and 38 92# pure gasoline samples from different batches of different manufacturers were collected. The near-infrared spectra corresponding to each pure oil product were collected under 4, 8 and 12 MPa pressure conditions. The near-infrared spectrum collection range is 4000-10000 cm -1 , resolution 8cm -1 , scanning times 16 times. For the same pure oil product, the near infrared spectra under different delivery pressures are averaged as the near infrared spectrum of the pure oil product. The near infrared spectra are shown in Figure 2 and Figure 3 ;

[0087] Based on the near-infrared spectra corresponding to the two pure oil products collected above, a mixed oil product spectral library corresponding to the two pure oil products is constructed:

[0088] The diesel concentration in the mixed oil was constructed to be in the range of 0.5%-5.5% and 94.5%-99.5%, respectively, with a concentration increment of 0.5%. The specific concentrations are shown in Table 1. The 78 diesel samples and 38 gasoline samples were mapped one by one according to the concentration ratios, and a mixed oil spectral library containing 65,208 near-infrared spectra was constructed. The near-infrared spectra of the mixed oil spectral library are shown in Figure 4 .

[0089] Table 1 Proportion and concentration of spectral components in constructing mixed spectral library

[0090]

[0091]

[0092] Different oil products have different densities. When the mixing ratio is different, the density is different. The number of oil molecules that light penetrates under the same optical path is different, resulting in changes in spectral intensity. At the same time, the temperature of finished oil transported by pipeline varies greatly throughout the year, which makes the sample density vary greatly, thus causing a large change in spectral intensity. Therefore, the spectral intensity collected at different mixing ratios and different temperatures seriously deviates from the spectral quantitative theory, resulting in inaccurate prediction results. Due to the high linear speed of finished oil transported by pipeline, it is not conducive to the constant temperature of finished oil (temperature exchange takes time). The site of the pipeline for transporting finished oil does not have the conditions for steam heating provided by the refinery; if electric heating is used, the cost and explosion risk will increase. Therefore, it is not feasible to perform on-site temperature control on oil transported by pipeline. Relying on the currently commonly used spectral preprocessing methods, it is still not possible to effectively eliminate the influence of spectral intensity with obvious temperature changes.

[0093] Therefore, in the present application, the spectral data processing method is used for the finished oil to be tested without constant temperature treatment, by converting the absorbance (modulus vector) affected by multiplicative effects such as density and temperature into an angular vector not affected by multiplicative effects, thereby effectively eliminating the influence of density and temperature on model performance and improving the model prediction accuracy. The prediction error range of the mixed oil ratio is reduced from 3.5% to below 1.0%.

[0094] That is, before adopting near infrared spectroscopy and non-modeling method to detect the mixed oil concentration of the finished oil to be detected in real time online, the method further includes:

[0095] The near-infrared spectrum of the finished oil to be tested is preprocessed by normalization, first-order derivative, second-order derivative, baseline correction or angle vector method.

[0096] The specific implementation process of using the angle vector method to perform spectral preprocessing on the near infrared spectrum of the finished oil to be detected is as follows:

[0097] Segmenting the near-infrared spectrum of the finished oil to be tested according to the set segmentation points to obtain multiple sub-spectra corresponding to the near-infrared spectrum of the finished oil to be tested;

[0098] Divide the preset reference vector according to the set segmentation points to obtain multiple sub-vectors;

[0099] The angle between each sub-spectrum and each sub-vector is calculated, and the angle vector formed by each obtained angle is used as the result of spectral preprocessing of the near-infrared spectrum of the finished oil to be tested, that is, the near-infrared spectrum is represented by an angle vector.

[0100] Optionally, in the present application, the reference vector may be determined based on the following method:

[0101] Obtain near-infrared spectra corresponding to m pure oil products and n mixed oil samples of the same type;

[0102] The near-infrared spectra corresponding to m pure oil products of the same type are combined into a spectrum matrix A = [A1, A2, ..., A i , …, A m ], where A i =[a i1 , a i2 , …, a in ] T ;

[0103] The near-infrared spectra corresponding to n mixed oil samples are combined into a spectral matrix A mix =[A 1mix , A 2mix , …, A imix , …, A nmix ];

[0104] Perform principal component analysis on the column vectors of matrix A and obtain the first principal component load vector X = [x1, x2, ..., x n ] T , take the first principal component load vector X as the reference vector.

[0105] After the reference vector is determined, the vector A of each near-infrared spectrum obtained can be divided into the same segmentation point corresponding to the first principal component load vector. i and the first principal component load vector X is divided into z segments, A i Split into A i1 , A i2 , …, A ik , …, A iz , X is divided into X1, X2, …, X k , …, X z ; Calculate the space vector A ik With X k The angle θ ik , we get the angle vector [θ i1 ,θ i2 ,…,θ iz The calculation process of the above angle vector is the same as the calculation process of the angle vector corresponding to the finished oil to be tested, and will not be repeated here.

[0106] It should be noted that the method for determining the above reference vector may also be a unit vector method, in which a unit vector is used as a reference vector, or an average spectral vector obtained by averaging the spectral vectors corresponding to the spectral matrix A is used as the reference vector.

[0107] Furthermore, in the present application, the method further comprises:

[0108] Obtaining the absorbance of the pure oil spectral component in the finished oil to be detected; the absorbance is affected by temperature;

[0109] In the present application, the absorbance of the finished oil to be tested is first obtained, and then the absorbance of the spectral component of the pure oil therein is obtained.

[0110] Determine the mixed oil concentration correction value corresponding to the finished oil to be tested based on a pre-established first corresponding relationship and the absorbance, wherein the first corresponding relationship is a corresponding relationship between the absorbance of each pure oil spectral component in the mixed oil and the each pure oil concentration correction value in the mixed oil;

[0111] The mixed oil concentration of the finished oil to be tested is corrected according to the mixed oil concentration correction value.

[0112] Step S30, using a pre-established calibration model, online and real-time detection of the property values ​​of the to-be-detected refined oil, wherein the property values ​​at least include the final distillation point and the flash point.

[0113] Among them, one possible implementation method of the above S30 is:

[0114] S301, determining the delivery pressure of the finished oil to be tested;

[0115] The delivery pressure refers to the pressure applied to the finished oil to be tested when it is transported in a pipeline.

[0116] S302, based on the delivery pressure of the refined oil to be tested, determining a target calibration model corresponding to the delivery pressure;

[0117] S303, determining the property values ​​of the to-be-tested refined oil based on the target calibration model, wherein the property values ​​at least include a final distillation point and a flash point.

[0118] In the above case, a calibration model corresponding to different delivery pressures is pre-established. In the present application, the pre-constructed calibration model can be a model established based on all delivery pressures. The specific model establishment process is to collect the corresponding near-infrared spectra under different delivery pressures for the same mixed oil sample, and then average the near-infrared spectra under different delivery pressure conditions. Then, the averaged spectrum and the property values ​​corresponding to the spectrum are used as training samples to establish a calibration model. When predicting, the delivery pressure corresponding to the finished oil to be tested is not determined, and the calibration model is directly used to predict the property values ​​of the finished oil to be tested.

[0119] Alternatively, if a calibration model corresponding to different delivery pressures is pre-established, the calibration model is established based on the following method:

[0120] Collect mixed oil samples at different delivery pressures, each mixed oil sample refers to a finished oil composed of different pure oil products;

[0121] Determine the near infrared spectra of mixed oil samples at different delivery pressures;

[0122] Based on the near infrared spectra of the mixed oil samples under different delivery pressures and the property values ​​corresponding to each mixed oil sample, a calibration model corresponding to the different delivery pressures is established.

[0123] Among them, the property values ​​corresponding to each mixed oil sample can be determined using national standards or industry standards.

[0124] Unlike refineries, the pressure of finished oil in pipelines is high (up to 13.3MPa). When using existing near-infrared spectroscopy acquisition technology, the oil to be tested must be decompressed, which will produce a large number of bubbles. The oil-gas interface has a strong scattering effect on light, which will seriously interfere with spectral measurement; therefore, this scheme uses high-pressure spectroscopy acquisition technology to acquire spectra of finished oil at different delivery pressures, and establish a calibration model for the final distillation point and flash point properties of oil products that adapt to different pressures.

[0125] Optionally, the above-mentioned collection of finished oil at different delivery pressures includes:

[0126] Any mixed oil sample is injected into the circulation pool through the injection device, and there are no bubbles in the mixed oil sample during the injection process. The pressure corresponding to the mixed oil sample in the circulation pool is adjusted, and the near-infrared spectra of the mixed oil sample in the circulation pool under different delivery pressures are collected by a near-infrared spectrometer; after the collection, the any mixed oil sample is discharged, cleaned with petroleum ether, blown dry with nitrogen, and the next mixed oil sample of the any mixed oil sample is collected.

[0127] In the scheme of the present application, the spectrum of the mixed oil sample used for modeling is collected or measured in an offline mode. When collecting the spectrum offline, the delivery pipeline needs to be cut off. The mixed oil sample is injected into the circulation pool by a sample injection device, and the oil is pressurized to different pressures by a pressurizing device. This pressure is adjusted according to the maximum design pressure of the pipeline, for example, between normal pressure and 14MPa, such as 0, 4, 8 or 12MPa, etc., which will cover the delivery pressure range, and different delivery pressures are simulated by adjusting the pressure.

[0128] Different delivery pipelines correspond to different maximum delivery pressures. In this application, the delivery pressure corresponding to the mixed oil sample can be adjusted in the circulation pool according to the set delivery pressure, ranging from 0 to 14 MPa. Among them, the spectrum acquisition parameters are: near infrared spectrum range 4000 ~ 10000 cm -1 , resolution 2~16cm -1 , the number of scans is 8 to 64 times.

[0129] As an example, the mixed oil concentration of an unknown mixed oil sample (mixed oil sample) is predicted:

[0130] 70 mixed oil samples to be tested were configured with a certain proportion of pure diesel and pure gasoline, and the concentration of the mixed oil samples was distributed within the oil concentration range. Near-infrared spectra were collected for these mixed oil samples, and the acquisition parameters were set the same as those of pure oil. The spectra in the mixed oil spectral library and the near-infrared spectra of each mixed oil sample to be tested were normalized and preprocessed by second-order differential. The similarity of the near-infrared spectrum of each mixed oil sample to be tested and the spectrum in the mixed oil spectral library were calculated one by one, and the concentrations of the two spectral components corresponding to the spectrum with the greatest similarity in the mixed oil spectral library were taken as the proportions of the spectral components corresponding to the mixed oil sample, that is, the concentration of pure oil in the mixed oil, that is, the mixed oil concentration (predicted concentration) of the corresponding mixed oil sample.

[0131] Table 2 shows the deviation results of the predicted concentration (mixed oil concentration) of the configured mixed oil sample to be tested and the configured actual concentration. It can be seen that the absolute value of the deviation between the actual value and the predicted value does not exceed 1%.

[0132] Table 2 Results and comparison of predicted concentration and actual concentration of mixed oil samples

[0133]

[0134]

[0135]

[0136] As another example, two groups of mixed oil samples consisting of 0# diesel and 92# gasoline were prepared, with gasoline and diesel concentrations ranging from 0 to 5%, and the spectrum acquisition range of 4000-10000 cm -1 , resolution 4cm -1 , 16 scans, and the acquisition pressure is atmospheric pressure. The final distillation point of the mixed oil sample is measured using GB / T6536 "Method for determination of atmospheric distillation characteristics of petroleum products" as the reference value of the calibration model, and the flash point of the mixed oil sample is measured using GB / T261 "Determination of flash point by Pensky-Martin closed cup method" as the reference value of the calibration model.

[0137] The comparison results between the predicted end-point of the mixed oil sample and the reference value can be seen in Table 3 and Figure 5 .in, Figure 5 The solid dots in the figure represent the predicted final distillation point of the corrected mixed oil sample. In the present application, the calibration model can also be verified by using a verification sample. Figure 5 The hollow circles represent the predicted end distillation points corresponding to the validation samples.

[0138] Table 3 Results and comparison of predicted end distillation point (near infrared predicted value) of mixed oil samples with reference values

[0139]

[0140]

[0141] The comparison results between the predicted flash points of the mixed oil samples and the reference values ​​can be seen in Tables 4 and Figure 6 .in, Figure 6 The solid dots in the figure represent the predicted flash point of the corrected mixed oil sample. In the present application, the calibration model can also be verified by using a verification sample. Figure 6 The hollow circles represent the predicted flash points corresponding to the validation samples.

[0142] Table 4 Results and comparison of predicted flash point (near infrared predicted value) of mixed oil samples with reference values

[0143]

[0144]

[0145] As another example, two groups of 0# diesel and 92# gasoline are mixed, the gasoline concentration is 0-100%, and the spectrum acquisition range is 4000-10000cm -1 , resolution 4cm -1 , 16 scans, the acquisition pressure is normal pressure, and the acquisition temperature is 20°C and 13°C. The results of the spectrum acquired at 13°C predicted by the near-infrared correction method for the mixed oil ratio established at 20°C (the method corresponding to the correction of the mixed oil concentration of the finished oil to be tested according to the mixed oil concentration correction value recorded in the previous text) without the angle vector preprocessing and the actual value of the sample ratio, as well as the comparison results can be seen in Table 5.

[0146] Table 5 Comparison of near infrared predicted values ​​and actual values ​​of mixed oil samples

[0147]

[0148]

[0149] The results of the 13℃ collected spectrum predicted by the near-infrared correction method for the mixed oil ratio established at 20℃ after angle vector processing and the actual value of the sample ratio, as well as the comparison results can be seen in Table 6.

[0150] Table 6 Comparison of near infrared predicted values ​​and actual values ​​of mixed oil samples after angle vector processing

[0151] Actual value (v / %, 20℃) Predicted value (v / %) Deviation(v%) 0.2 -0.1 0.3 0.4 0.3 0.1 0.6 0.6 0.0 0.8 0.4 0.4 1.0 0.4 0.6 3.0 2.9 0.1 5.0 4.9 0.1 10.0 9.4 0.6 20.0 20.0 0.0 30.0 30.5 -0.5 40.0 40.0 0.0 50.0 50.8 -0.8 60.0 60.7 -0.7 70.0 70.9 -0.9 80.0 80.0 0.0 90.0 90.4 -0.4 95.0 94.8 0.2 97.0 96.4 0.6 99.0 98.5 0.5 99.2 98.6 0.6 99.4 99.0 0.4 99.6 98.9 0.7 99.8 99.0 0.8

[0152] The solution of the present invention is applicable to the field of pipeline transportation of refined oil products, and is used for real-time online detection of the properties of refined oil products and mixed oils, providing a new basis and technical support for the precise interface definition of mixed oils. The solution can be applied to the online spectral monitoring system of the composition and physical properties of refined oil pipelines, and has important theoretical and application value for the intelligent regulation of refined oil pipelines. If the demonstration project of this project has good application effect, stable and reliable operation, and convenient operation and maintenance, it can be extended to other sequentially transported refined oil pipelines, and even crude oil pipelines, and has a potential good application prospect.

[0153] This scheme can be used to conduct research around the mixed oil samples provided by a certain laboratory. In the fields of pipeline intelligent transportation technology and refined oil product quality technology, there have always been problems such as long time consumption and large number of personnel in offline sampling and testing of physical property indicators of oil products, as well as low precision in cutting gasoline and diesel mixed oil by relying solely on a density meter. This scheme proposes a solution for online detection of refined oil quality indicators using spectroscopy to achieve the purpose of online monitoring of gasoline terminal distillation point, diesel flash point, and gasoline and diesel mixed oil concentration. It is intended to establish a prediction model for physical property indicators of multiple types of oil products to eliminate the influence of pressure and temperature changes on physical properties, and to achieve precise online detection of pipeline mixed oil ratio, terminal distillation point, flash point and other properties at the same time, providing more accurate data support for mixed oil cutting.

[0154] Based on Figure 1 Based on the same principle as the method shown in , the embodiment of the present invention also provides an online detection device 20 for mixed oil properties in pipeline transportation of refined oil products, such as Figure 7 As shown in , the online detection device 20 for mixed oil properties in pipeline transportation of refined oil may include an acquisition module 210, a mixed oil concentration detection module 220 and a terminal distillation point and flash point determination module 230, wherein:

[0155] An acquisition module 210 is used to acquire the finished oil to be tested that is transported by a pipeline, wherein the finished oil to be tested is composed of two pure oil products;

[0156] The mixed oil concentration detection module 220 is used to detect the mixed oil concentration of the finished oil to be detected online in real time by using near infrared spectroscopy and non-modeling method;

[0157] The terminal distillation point and flash point determination module 230 is used to detect the property values ​​of the to-be-detected refined oil in real time online using a pre-established calibration model, wherein the property values ​​at least include the terminal distillation point and the flash point.

[0158] Optionally, when the terminal distillation point and flash point determination module 230 adopts a pre-established calibration model to detect the property value of the to-be-detected refined oil in real time online, it is specifically used for:

[0159] Determining the delivery pressure of the finished oil to be tested;

[0160] Based on the delivery pressure of the refined oil to be tested, determining a target calibration model corresponding to the delivery pressure;

[0161] Based on the target calibration model, the property value of the finished oil to be tested is determined.

[0162] Optionally, when the mixed oil concentration detection module 220 adopts near infrared spectroscopy and non-modeling method to detect the mixed oil concentration of the finished oil to be detected online in real time, it is specifically used for:

[0163] Adopting near infrared spectroscopy to detect the spectral components of different oil components in the finished oil to be detected online and in real time;

[0164] Based on each of the spectral components, the mixed oil concentration of the finished oil to be tested is determined.

[0165] Optionally, the device further comprises:

[0166] A correction module is used to obtain the absorbance of the pure oil spectral component in the finished oil to be detected; determine the mixed oil concentration correction value corresponding to the finished oil to be detected based on a pre-established first corresponding relationship and the absorbance, wherein the first corresponding relationship is the corresponding relationship between the absorbance of each pure oil spectral component in the mixed oil and the each pure oil concentration correction value in the mixed oil; and correct the mixed oil concentration of the finished oil to be detected according to the mixed oil concentration correction value.

[0167] Optionally, the calibration model is established based on the following model training module, which is used to:

[0168] Obtain mixed oil samples at different delivery pressures;

[0169] Determine the near infrared spectra of mixed oil samples at different delivery pressures;

[0170] Based on the near infrared spectra of the mixed oil samples under different delivery pressures and the property values ​​corresponding to each mixed oil sample, a calibration model corresponding to the different delivery pressures is established.

[0171] Optionally, before the mixed oil concentration of the finished oil to be tested is detected online and in real time by near infrared spectroscopy, the device further comprises:

[0172] The preprocessing module is used to perform spectral preprocessing on the near-infrared spectrum of the finished oil to be detected by using normalization, first-order derivative, second-order derivative, baseline correction or angle vector method.

[0173] Optionally, when collecting refined oil under different delivery pressures, the model training module is specifically used to:

[0174] For the mixed oil sample under each delivery pressure, the mixed oil sample is injected into the circulation pool through the sample injection device. During the injection process, there are no bubbles in the mixed oil sample. The near-infrared spectrometer is used to collect the near-infrared spectrum of the mixed oil sample in the circulation pool. After the collection, the mixed oil sample is discharged, cleaned with petroleum ether, blown dry with nitrogen, and the next mixed oil sample of the delivery pressure is collected.

[0175] The online detection device for mixed oil properties in finished oil pipeline transportation of the embodiment of the present invention can execute the online detection method for mixed oil properties in finished oil pipeline transportation provided by the embodiment of the present invention, and its implementation principle is similar. The actions performed by each module and unit in the online detection device for mixed oil properties in finished oil pipeline transportation of the embodiments of the present invention correspond to the steps in the online detection method for mixed oil properties in finished oil pipeline transportation of the embodiments of the present invention. For the detailed functional description of each module of the online detection device for mixed oil properties in finished oil pipeline transportation, please refer to the description of the corresponding online detection method for mixed oil properties in finished oil pipeline transportation shown in the previous text, which will not be repeated here.

[0176] Among them, the above-mentioned online detection device for mixed oil properties in finished oil pipeline transportation can be a computer program (including program code) running in a computer device, for example, the online detection device for mixed oil properties in finished oil pipeline transportation is an application software; the device can be used to execute the corresponding steps in the method provided in the embodiment of the present invention.

[0177] In some embodiments, the online detection device for mixed oil properties in finished oil pipeline transportation provided by the embodiments of the present invention can be implemented in a combination of software and hardware. As an example, the online detection device for mixed oil properties in finished oil pipeline transportation provided by the embodiments of the present invention can be a processor in the form of a hardware decoding processor, which is programmed to execute the online detection method for mixed oil properties in finished oil pipeline transportation provided by the embodiments of the present invention. For example, the processor in the form of a hardware decoding processor can adopt one or more application specific integrated circuits (ASIC, Application Specific Integrated Circuit), DSP, programmable logic device (PLD, Programmable Logic Device), complex programmable logic device (CPLD, Complex Programmable Logic Device), field programmable gate array (FPGA, Field-Programmable Gate Array) or other electronic components.

[0178] In other embodiments, the online detection device for mixed oil properties in pipeline transportation of refined oil provided by the embodiments of the present invention can be implemented in a software manner. Figure 7An online detection device for mixed oil properties in finished oil pipeline transportation stored in a memory is shown, which can be software in the form of programs and plug-ins, and includes a series of modules, including an acquisition module 210, a mixed oil concentration detection module 220 and a terminal distillation point and flash point determination module 230, which are used to implement the online detection method for mixed oil properties in finished oil pipeline transportation provided by an embodiment of the present invention.

[0179] The modules involved in the embodiments of the present invention may be implemented by software or hardware, wherein the name of a module does not limit the module itself in some cases.

[0180] Based on the same principle as the method shown in the embodiments of the present invention, an electronic device is also provided in the embodiments of the present invention, which may include but is not limited to: a processor and a memory; the memory is used to store a computer program; the processor is used to execute the method shown in any embodiment of the present invention by calling the computer program.

[0181] In an alternative embodiment, an electronic device is provided, such as Figure 8 As shown, Figure 8 The electronic device 4000 shown includes: a processor 4001 and a memory 4003. The processor 4001 and the memory 4003 are connected, such as through a bus 4002. Optionally, the electronic device 4000 may also include a transceiver 4004, which may be used for data interaction between the electronic device and other electronic devices, such as data transmission and / or data reception. It should be noted that in actual applications, the transceiver 4004 is not limited to one, and the structure of the electronic device 4000 does not constitute a limitation on the embodiments of the present invention.

[0182] Processor 4001 may be a CPU (Central Processing Unit), a general-purpose processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array) or other programmable logic devices, transistor logic devices, hardware components or any combination thereof. It may implement or execute various exemplary logic blocks, modules and circuits described in conjunction with the disclosure of the present invention. Processor 4001 may also be a combination that implements computing functions, such as a combination of one or more microprocessors, a combination of a DSP and a microprocessor, etc.

[0183] The bus 4002 may include a path to transmit information between the above components. The bus 4002 may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus. The bus 4002 may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 8 Only one thick line is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0184] The memory 4003 can be a ROM (Read Only Memory) or other types of static storage devices that can store static information and instructions, a RAM (Random Access Memory) or other types of dynamic storage devices that can store information and instructions, or an EEPROM (Electrically Erasable Programmable Read Only Memory), a CD-ROM (Compact Disc Read Only Memory) or other optical disk storage, optical disk storage (including compressed optical disk, laser disk, optical disk, digital versatile disk, Blu-ray disk, etc.), a magnetic disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store the desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited to this.

[0185] The memory 4003 is used to store the application code (computer program) for executing the solution of the present invention, and the execution is controlled by the processor 4001. The processor 4001 is used to execute the application code stored in the memory 4003 to implement the content shown in the above method embodiment.

[0186] The electronic device may also be a terminal device. Figure 8 The electronic device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention.

[0187] An embodiment of the present invention provides a computer-readable storage medium, on which a computer program is stored. When the computer-readable storage medium is run on a computer, the computer can execute the corresponding contents of the aforementioned method embodiment.

[0188] According to another aspect of the present invention, a computer program product or a computer program is also provided, the computer program product or the computer program comprising computer instructions, the computer instructions being stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device executes the methods provided in the implementation modes of the above-mentioned various embodiments.

[0189] Computer program code for performing the operations of the present invention may be written in one or more programming languages, or a combination thereof, including object-oriented programming languages, such as Java, Smalltalk, C++, and conventional procedural programming languages, such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., through the Internet using an Internet service provider).

[0190] It should be understood that the flow charts and block diagrams in the accompanying drawings illustrate the possible implementation architecture, functions and operations of the method and computer program product according to various embodiments of the present invention. In this regard, each box in the flow chart or block diagram can represent a module, a program segment, or a part of a code, and the module, the program segment, or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a sequence different from that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flow chart, and the combination of the boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0191] The computer-readable storage medium provided by the embodiment of the present invention may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to, an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present invention, a computer-readable storage medium may be any tangible medium containing or storing a program that may be used by or in conjunction with an instruction execution system, device, or device.

[0192] The computer-readable storage medium carries one or more programs. When the one or more programs are executed by the electronic device, the electronic device executes the method shown in the above embodiment.

[0193] The above description is only a preferred embodiment of the present invention and an explanation of the technical principles used. Those skilled in the art should understand that the disclosure scope involved in the present invention is not limited to the technical solution formed by a specific combination of the above technical features, but should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the above disclosed concept. For example, the above features are replaced with the technical features with similar functions disclosed in the present invention (but not limited to) by each other.

Claims

1. An online detection method for mixed oil properties in finished oil pipeline transportation, characterized in that: The following steps are involved: Obtaining the finished oil to be tested that is transported by a pipeline, wherein the finished oil to be tested is composed of two pure oil products; Adopting near infrared spectroscopy and non-modeling method to detect the mixed oil concentration of the finished oil to be detected in real time online; The pre-established calibration model is used to detect the property values ​​of the finished oil to be detected online in real time, and the property values ​​at least include the final distillation point and the flash point.

2. The method according to claim 1, characterized in that The method of using a pre-established calibration model to detect the property value of the finished oil to be detected in real time online includes: Determining the delivery pressure of the finished oil to be tested; Based on the delivery pressure of the refined oil to be tested, determining a target calibration model corresponding to the delivery pressure; Based on the target calibration model, the property value of the finished oil to be tested is determined.

3. The method according to claim 1, characterized in that The method of using near infrared spectroscopy and non-modeling method to detect the mixed oil concentration of the finished oil to be detected in real time online includes: Adopting near infrared spectroscopy and non-modeling method to obtain the spectral components of different oil components in the finished oil to be detected in real time online; Based on each of the spectral components, the mixed oil concentration of the finished oil to be tested is determined.

4. The method according to any one of claims 1 to 3, characterized in that The method further comprises: Obtaining the absorbance of the pure oil spectral component in the finished oil to be detected; Determine the mixed oil concentration correction value corresponding to the finished oil to be tested based on a pre-established first corresponding relationship and the absorbance, wherein the first corresponding relationship is a corresponding relationship between the absorbance of each pure oil spectral component in the mixed oil and the each pure oil concentration correction value in the mixed oil; The mixed oil concentration of the finished oil to be tested is corrected according to the mixed oil concentration correction value.

5. The method according to any one of claims 1 to 3, characterized in that The calibration model is established based on the following method: Obtaining mixed oil samples under different delivery pressures, each of the mixed oil samples being obtained by configuring different pure oil products; Determine the near infrared spectra of mixed oil samples at different delivery pressures; Based on the near infrared spectra of the mixed oil samples under different delivery pressures and the property values ​​corresponding to each mixed oil sample, a calibration model corresponding to the different delivery pressures is established.

6. The method according to any one of claims 1 to 3, characterized in that Before the near infrared spectroscopy is used to detect the mixed oil concentration of the finished oil to be detected online in real time, the method further comprises: The near-infrared spectrum of the finished oil to be tested is preprocessed by normalization, first-order derivative, second-order derivative, baseline correction or angle vector method.

7. The method according to claim 5, characterized in that The step of obtaining mixed oil samples under different delivery pressures includes: Any mixed oil sample is injected into the circulation pool through the injection device, and there are no bubbles in the mixed oil sample during the injection process. The pressure corresponding to the mixed oil sample in the circulation pool is adjusted, and the near-infrared transmission spectrum of the mixed oil sample in the circulation pool under different delivery pressures is collected by a near-infrared spectrometer; after the collection, the any mixed oil sample is discharged, cleaned with petroleum ether, blown dry with nitrogen, and the next mixed oil sample of the any mixed oil sample is collected.

8. An online detection device for mixed oil properties in finished oil pipeline transportation, characterized in that: include: An acquisition module is used to acquire the finished oil to be tested that is transported by a pipeline, wherein the finished oil to be tested is composed of two pure oil products; A mixed oil concentration detection module, used to detect the mixed oil concentration of the finished oil to be detected online in real time by using near infrared spectroscopy and non-modeling method; The terminal distillation point and flash point determination module is used to use a pre-established calibration model to detect the property values ​​of the finished oil to be detected online in real time, and the property values ​​at least include the terminal distillation point and the flash point.

9. An electronic device, characterized in that: The method comprises a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the method according to any one of claims 1 to 7 when executing the computer program.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

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