Method, apparatus, and processor for determining separation efficiency of a cyclonic gas-liquid separator

Abstract

Embodiments of the present application provide a method, device and processor for determining separation efficiency of a cyclone gas-liquid separator. The method comprises: obtaining gas phase flow rate and liquid phase flow rate of an inlet by a flow meter; obtaining pipeline parameters of a pipeline connected with the inlet; determining gas phase flow velocity and liquid phase flow velocity of the inlet according to the pipeline parameters, the gas phase flow rate and the liquid phase flow rate; inputting the gas phase flow velocity and the liquid phase flow velocity into a discriminant model to determine the separation efficiency of the cyclone gas-liquid separator by the discriminant model. Through the technical solution, the separation efficiency of the cyclone gas-liquid separator can be quickly and accurately determined, and relevant data of the cyclone gas-liquid separator can be quickly obtained.

Description

Technical Field

[0001] This application relates to the field of computer technology, and specifically to a method, apparatus, processor, and storage medium for determining the separation efficiency of a cyclone gas-liquid separator. Background Technology

[0002] Hydrocyclone gas-liquid separators (GLCCs) are crucial separation equipment in the petroleum and chemical industries. Their working principle involves a gas-liquid mixture entering the separator through a tangential inlet. The two phases separate due to the difference in centrifugal force and are then discharged in different directions. As a component connected to pipelines in oil and gas gathering and transportation modules, predicting its separation efficiency is of great significance to users. Separation efficiency is one of the key parameters for evaluating separators, and its identification and detection are essential for their operation.

[0003] Existing technologies for predicting separator efficiency mainly rely on indirect measurement methods, which result in large errors in the predictions and cause considerable inconvenience to users. Summary of the Invention

[0004] The purpose of this application is to provide a method, apparatus, processor, and storage medium for determining the separation efficiency of a cyclone gas-liquid separator.

[0005] To achieve the above objectives, a first aspect of this application provides a method for determining the separation efficiency of a cyclone gas-liquid separator, wherein a flow meter is installed at the inlet of the cyclone gas-liquid separator, comprising:

[0006] The gas phase flow rate and liquid phase flow rate at the inlet are obtained through a flow meter;

[0007] Obtain the pipe parameters of the pipe connected to the inlet;

[0008] The inlet gas velocity and liquid velocity are determined based on the pipeline parameters, gas flow rate, and liquid flow rate.

[0009] The gas phase velocity and liquid phase velocity are input into the discriminant model to determine the separation efficiency of the cyclone gas-liquid separator.

[0010] In this embodiment of the application, a first pressure sensor is installed at the overflow port of the cyclone gas-liquid separator, and a second pressure sensor is installed at the inlet of the cyclone gas-liquid separator. The method further includes: acquiring a first pressure and a second pressure at the overflow port and the inlet respectively through the first pressure sensor and the second pressure sensor; determining the pressure difference between the overflow port and the inlet based on the first pressure and the second pressure; inputting the pressure difference into a discrimination model to output a predicted index value corresponding to the pressure difference through the discrimination model; and determining the inlet flow pattern based on the numerical range corresponding to the predicted index value.

[0011] In this embodiment, the pipe parameters include the inner diameter and cross-sectional area of ​​the pipe. Determining the inlet gas velocity and liquid velocity based on the pipe parameters, gas flow rate, and liquid flow rate includes calculating the gas velocity and liquid velocity according to formulas (1) and (2), respectively:

[0012]

[0013] Among them, v g Q is the inlet gas flow rate. g Where A is the inlet gas flow rate, d is the cross-sectional area of ​​the pipe, and d is the inner diameter of the pipe.

[0014]

[0015] Among them, v l Q is the inlet liquid flow rate. l This represents the liquid flow rate at the inlet.

[0016] In this embodiment, the predicted index values ​​include the single-period fluctuation time ratio, the number of large fluctuations within a single period, the minimum outlier within a single period, and the maximum outlier within a single period. The single-period fluctuation time ratio is the ratio of the duration of the pressure drop fluctuation signal to the period within a single period. The number of large fluctuations within a single period is the number of peaks in the pressure drop fluctuation signal within a single period that exceed a preset value. The minimum and maximum outliers within a single period are the minimum and maximum values ​​of the abnormal data in the pressure drop fluctuation signal within a single period, respectively. The pressure drop fluctuation signal is determined based on the pressure difference. The abnormal data in the pressure drop fluctuation signal is determined based on discrete data, which refers to the data after discretization of the pressure drop fluctuation signal.

[0017] In this embodiment of the application, the single fluctuation time ratio is calculated according to formula (3):

[0018]

[0019] Among them, t st The duration of one effective pressure drop fluctuation, T is the period of the fluctuation, and r is the effective pressure drop fluctuation. st This represents the duration of a single fluctuation.

[0020] In this embodiment of the application, the number of large fluctuations occurring within a single period is calculated according to formula (4):

[0021] n bw =N i (i∈N*) (4)

[0022] Where, n bw N represents the number of large fluctuations occurring within a single period. i Let represent the number of large fluctuations occurring in the i-th period.

[0023] In this embodiment of the application, the minimum outlier and the maximum outlier within a single period are calculated according to formulas (5) and (6), respectively:

[0024] U min =min(U bi (5)

[0025] Among them, U min U is the smallest outlier within a single period. bi This refers to a smaller outlier within the i-th period;

[0026] U max =max(U ai (6)

[0027] Among them, U max U is the largest outlier within a single period. ai This refers to a larger outlier within the i-th period.

[0028] A second aspect of this application provides an apparatus for determining the separation efficiency of a cyclone gas-liquid separator, comprising:

[0029] The data acquisition module is used to obtain the gas phase flow rate and liquid phase flow rate at the inlet via a flow meter;

[0030] The data acquisition module is used to acquire the pipe parameters of the pipe connected to the inlet;

[0031] The data processing module is used to determine the inlet gas phase velocity and liquid phase velocity based on pipeline parameters, gas phase flow rate, and liquid phase flow rate.

[0032] The discrimination module is used to input the gas phase velocity and liquid phase velocity into the discrimination model in order to determine the separation efficiency of the cyclone gas-liquid separator.

[0033] A third aspect of this application provides a processor configured to perform the above-described method for determining the separation efficiency of a cyclone gas-liquid separator.

[0034] A fourth aspect of this application provides a machine-readable storage medium storing instructions that, when executed by a processor, configure the processor to perform the aforementioned method for determining the separation efficiency of a cyclone gas-liquid separator.

[0035] The above technical solution involves installing a flow meter at the inlet of the cyclone gas-liquid separator. The flow meter acquires the gas and liquid flow rates at the inlet, along with the pipe parameters of the pipeline connected to the inlet. Based on these parameters, the gas and liquid flow rates, the inlet gas and liquid velocities are determined. These velocities are then input into a discriminant model to determine the separation efficiency of the cyclone gas-liquid separator. This technical solution enables rapid and accurate determination of the separation efficiency of the cyclone gas-liquid separator and allows for the quick acquisition of relevant data.

[0036] Other features and advantages of the embodiments of this application will be described in detail in the following detailed description section. Attached Figure Description

[0037] The accompanying drawings are provided to further illustrate the embodiments of this application and form part of the specification. They are used together with the following detailed description to explain the embodiments of this application, but do not constitute a limitation on the embodiments of this application. In the drawings:

[0038] Figure 1 A schematic flowchart of a method for determining the separation efficiency of a cyclone gas-liquid separator according to an embodiment of this application is shown.

[0039] Figure 2 This schematic diagram illustrates a structural block diagram of an apparatus for determining the separation efficiency of a cyclone gas-liquid separator according to an embodiment of this application;

[0040] Figure 3 The diagram illustrates the internal structure of a computer device according to an embodiment of this application. Detailed Implementation

[0041] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are only for illustration and explanation of the embodiments of this application and are not intended to limit the embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.

[0042] Figure 1 A schematic flowchart illustrating a method for determining the separation efficiency of a cyclone gas-liquid separator according to an embodiment of this application is shown. Figure 1 As shown in one embodiment of this application, a method for determining the separation efficiency of a cyclone gas-liquid separator is provided, comprising the following steps:

[0043] Step 101: Obtain the gas phase flow rate and liquid phase flow rate at the inlet using a flow meter.

[0044] Step 102: Obtain the pipe parameters of the pipe connected to the inlet.

[0045] Step 103: Determine the inlet gas velocity and liquid velocity based on the pipeline parameters, gas flow rate, and liquid flow rate.

[0046] Step 104: Input the gas phase velocity and liquid phase velocity into the discrimination model to determine the separation efficiency of the cyclone gas-liquid separator through the discrimination model.

[0047] A flow meter is an instrument that indicates the measured flow rate and / or the total volume of fluid within a selected time interval. Specifically, it is used to measure the flow rate of fluid in a pipe or open channel. Installing a flow meter at the inlet of a cyclone gas-liquid separator allows the acquisition of both the inlet gas and liquid flow rates. The processor can then determine the gas and liquid velocities based on the obtained gas and liquid flow rates and pipe parameters. These pipe parameters refer to the parameters of the pipe connected to the inlet of the cyclone gas-liquid separator. The gas and liquid velocities are then input into a discriminant model to determine the separation efficiency of the cyclone gas-liquid separator.

[0048] In one embodiment, pipe parameters may include the pipe's inner diameter and cross-sectional area. The gas phase velocity can be the ratio of the gas phase flow rate to the pipe's cross-sectional area, which can be calculated based on the pipe's inner diameter. The processor can calculate the inlet gas phase velocity according to formula (1):

[0049]

[0050] Among them, v g Q is the inlet gas flow rate. g Let A be the inlet gas flow rate, A be the cross-sectional area of ​​the pipe, and d be the inner diameter of the pipe.

[0051] The liquid phase velocity can be the ratio of the liquid phase flow rate to the cross-sectional area of ​​the pipe, which can be calculated based on the pipe's inner diameter. The processor can calculate the inlet liquid phase velocity using formula (2):

[0052]

[0053] Among them, v l Q is the inlet liquid flow rate. l Let A be the inlet liquid flow rate, A be the cross-sectional area of ​​the pipe, and d be the inner diameter of the pipe.

[0054] In one embodiment, a first pressure sensor can be installed at the overflow port of the cyclone gas-liquid separator, and a second pressure sensor can be installed at the inlet of the cyclone gas-liquid separator. The first pressure sensor can acquire a first pressure value at the overflow port, and the second pressure sensor can acquire a second pressure value at the inlet. The processor can determine the pressure difference between the overflow port and the inlet based on the first and second pressure values. The pressure difference is input into a discriminant model to output a predicted index value corresponding to the pressure difference; the inlet flow pattern is determined based on the numerical range corresponding to the predicted index value. For example, the first pressure sensor acquires a first pressure value P1 at the overflow port, and the second pressure sensor acquires a second pressure value P2 at the inlet. The processor determines the pressure difference between the overflow port and the inlet as ΔP = P1 - P2 based on the first pressure value P1 and the second pressure value P2. The pressure difference ΔP is input into the discriminant model to output a predicted index value corresponding to the pressure difference; the inlet flow pattern is determined based on the numerical range corresponding to the predicted index value.

[0055] In one embodiment, the predicted index values ​​may include the single-period fluctuation time ratio, the number of large fluctuations within a single period, the minimum outlier within a single period, and the maximum outlier within a single period. The single-period fluctuation time ratio is the ratio of the duration of the pressure drop fluctuation signal to the period within a single period; the number of large fluctuations within a single period is the number of peaks in the pressure drop fluctuation signal exceeding a preset value within a single period; the minimum and maximum outliers within a single period are the minimum and maximum values ​​of the abnormal data in the pressure drop fluctuation signal within a single period, respectively. The pressure drop fluctuation signal is determined based on the pressure difference. The abnormal data in the pressure drop fluctuation signal is determined based on discrete data, which refers to the data after discretization of the pressure drop fluctuation signal.

[0056] Specifically, after the processor inputs the pressure difference value into the discrimination model, the model processes the pressure difference value to obtain the corresponding pressure drop fluctuation signal. Simultaneously, the discrimination model can also process the pressure drop fluctuation signal to obtain the corresponding predicted index value. This predicted index value can include the single fluctuation time ratio, the number of large fluctuations within a single period, the minimum outlier within a single period, and the maximum outlier within a single period.

[0057] In one embodiment, the single-wave fluctuation time ratio can be determined by the ratio of the time from the start to the end of a single voltage drop fluctuation signal within a single cycle to the cycle itself. That is, the single-wave fluctuation time ratio can be determined by the duration and cycle of the voltage drop fluctuation signal. The single-wave fluctuation time ratio can be used to evaluate the duration characteristics of a single fluctuation in the voltage drop fluctuation signal, and can be calculated according to formula (3):

[0058]

[0059] Among them, tst The duration of one effective pressure drop fluctuation, T is the period of the fluctuation, and r is the effective pressure drop fluctuation. st This represents the duration of a single fluctuation.

[0060] In one embodiment, the number of large fluctuations occurring within a single cycle can be determined by the number of peaks in the voltage drop fluctuation signal that exceed a preset value. The preset value can be obtained through actual experiments. For example, if the preset value is found to be 50% of the maximum peak value of the voltage drop fluctuation signal within a single cycle, then peaks exceeding 50% of the maximum peak value can be identified as large fluctuations. The frequency and severity of the voltage drop fluctuation signal can be evaluated by the number of large fluctuations occurring within a single cycle. The number of large fluctuations occurring within a single cycle can be calculated using formula (4):

[0061] n bw =N i (i∈N*) (4)

[0062] Where, n bw N represents the number of large fluctuations occurring within a single period. i Let represent the number of large fluctuations occurring in the i-th period.

[0063] In one embodiment, the processor can discretize the voltage drop fluctuation signal and determine the minimum and maximum outliers within a single period based on the obtained discrete data. This can be achieved through box plot analysis, a method that uses five statistical measures—minimum, first quartile, median, third quartile, and maximum—to describe the data. Specifically, the interquartile range (I) is determined based on the upper quartile (Q3) and lower quartile (Q1) of the discrete data. QR =Q3-Q1. Add 1.5I to Q3. QR and Q1-1.5I QR These two outlier cutoff points are used to determine the normal range of discrete data. Discrete data outside the normal range are identified as outlier data. The minimum and maximum outlier values ​​within a single period are the minimum and maximum values ​​among the outlier data, respectively. The minimum and maximum outlier values ​​within a single period can be calculated using formulas (5) and (6), respectively.

[0064] U min =min(U bi (5)

[0065] Among them, U min U is the smallest outlier within a single period. bi This refers to a smaller outlier within the i-th period;

[0066] Umax =max(U ai (6)

[0067] Among them, U max U is the largest outlier within a single period. ai This refers to a larger outlier within the i-th period.

[0068] In one embodiment, a flow meter is installed at the inlet of the cyclone gas-liquid separator to obtain the inlet gas phase flow rate Q. g and liquid phase flow rate Q l The processor can determine the gas flow rate Q based on the obtained gas phase flow rate. g Determine the gas phase velocity v based on pipeline parameters g According to the liquid phase flow rate Q l Determine the liquid phase flow velocity v based on pipeline parameters l The pipe parameters include the cross-sectional area A and the inner diameter d of the pipe. The inlet gas velocity v can be calculated using formula (1). g :

[0069]

[0070] The inlet liquid flow velocity v can be calculated using formula (2). l :

[0071]

[0072] gas flow rate v g and liquid phase flow rate v l The pressure is input into the discriminant model to determine the separation efficiency μ of the cyclone gas-liquid separator. A first pressure sensor is installed at the overflow port of the cyclone gas-liquid separator, acquiring a first pressure value P1 of 40 kPa. A second pressure sensor is installed at the inlet of the cyclone gas-liquid separator, acquiring a second pressure value P2 of 30 kPa. The processor can determine the pressure difference between the overflow port and the inlet as ΔP = P1 - P2 = 40 kPa - 30 kPa = 10 kPa based on the first pressure value P1 (40 kPa) and the second pressure value P2 (30 kPa). The pressure difference ΔP (10 kPa) is input into the discriminant model to output the predicted index value I1 corresponding to the pressure difference. The predicted index value I1 includes the single fluctuation time ratio r. st The number of times large fluctuations occur within a single period (n) bw Minimum outlier U within a single period min and the maximum outlier U within a single period max The single fluctuation time ratio can be calculated according to formula (3):

[0073]

[0074] Among them, t st The duration of one effective pressure drop fluctuation, T is the period of the fluctuation, and r is the effective pressure drop fluctuation. st This represents the duration of a single fluctuation.

[0075] The number of large fluctuations within a single period can be calculated using formula (4):

[0076] n bw =N i (i∈N*) (4)

[0077] Where, n bw N represents the number of large fluctuations occurring within a single period. i Let represent the number of large fluctuations occurring in the i-th period.

[0078] The minimum outlier and the maximum outlier within a single period can be calculated using formulas (5) and (6), respectively:

[0079] U min =min(U bi (5)

[0080] Among them, U min U is the smallest outlier within a single period. bi This refers to a smaller outlier within the i-th period;

[0081] U max =max(U ai (6)

[0082] Among them, U max U is the largest outlier within a single period. ai This refers to a larger outlier within the i-th period.

[0083] The inlet flow pattern of the cyclone gas-liquid separator corresponding to a preset index value in the range of 0 to 2 is R1; the inlet flow pattern corresponding to a preset index value in the range of 2 to 4 is R2; the inlet flow pattern corresponding to a preset index value in the range of 4 to 6 is R3; the inlet flow pattern corresponding to a preset index value in the range of 6 to 8 is R4; and the inlet flow pattern corresponding to a preset index value in the range of 8 to 10 is R5. The predicted index value I1 output by the discrimination mode is 4.8, corresponding to a value range of 4 to 6, and the determined inlet flow pattern of the cyclone gas-liquid separator is R3.

[0084] The above technical solution involves installing a flow meter at the inlet of the cyclone gas-liquid separator. The flow meter acquires the gas and liquid flow rates at the inlet, along with the pipe parameters of the pipeline connected to the inlet. Based on these parameters, the gas and liquid flow rates, the inlet gas and liquid velocities are determined. These velocities are then input into a discriminant model to determine the separation efficiency of the cyclone gas-liquid separator. This technical solution enables rapid and accurate determination of the separation efficiency of the cyclone gas-liquid separator and allows for the quick acquisition of relevant data.

[0085] Figure 1 This is a schematic flowchart of a method for determining the separation efficiency of a cyclone gas-liquid separator in one embodiment. It should be understood that, although... Figure 1 The steps in the flowchart are shown sequentially as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order in which these steps are executed, and they can be performed in other orders. Figure 1 At least some of the steps in the process may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily executed at the same time, but may be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but may be executed in turn or alternately with other steps or at least some of the sub-steps or stages of other steps.

[0086] In one embodiment, such as Figure 2 As shown, a device 200 for determining the separation efficiency of a cyclone gas-liquid separator is provided, including a data acquisition module 201, a data acquisition module 202, a data processing module 203, and a discrimination module 204, wherein:

[0087] The data acquisition module 201 is used to acquire the gas phase flow rate and liquid phase flow rate at the inlet through the flow meter.

[0088] The data acquisition module 202 is used to acquire the pipe parameters of the pipe connected to the inlet.

[0089] The data processing module 203 is used to determine the inlet gas phase velocity and liquid phase velocity based on the pipeline parameters, gas phase flow rate and liquid phase flow rate.

[0090] The discrimination module 204 is used to input the gas phase velocity and liquid phase velocity into the discrimination model so as to determine the separation efficiency of the cyclone gas-liquid separator through the discrimination model.

[0091] This application provides a processor for running a program, wherein the program executes the above-described method for determining the separation efficiency of a cyclone gas-liquid separator.

[0092] This application provides a storage medium storing a program that, when executed by a processor, implements the method described above for determining the separation efficiency of a cyclone gas-liquid separator.

[0093] In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 3 As shown. The computer device includes a processor A01, a network interface A02, a memory (not shown), and a database (not shown) connected via a system bus. The processor A01 provides computing and control capabilities. The memory includes internal memory A03 and a non-volatile storage medium A04. The non-volatile storage medium A04 stores an operating system B01, a computer program B02, and a database (not shown). The internal memory A03 provides an environment for the operation of the operating system B01 and the computer program B02 stored in the non-volatile storage medium A04. The database stores data on flow rate, velocity, and separation efficiency. The network interface A02 communicates with external terminals via a network connection. When executed by the processor A01, the computer program B02 implements a method for determining the separation efficiency of a cyclone gas-liquid separator.

[0094] Those skilled in the art will understand that Figure 3 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0095] This application provides an embodiment of a device, which includes a processor, a memory, and a program stored in the memory and executable on the processor. When the processor executes the program, it performs the following steps: acquiring the gas phase flow rate and liquid phase flow rate at the inlet through a flow meter; acquiring the pipe parameters of the pipe connected to the inlet; determining the gas phase velocity and liquid phase velocity at the inlet based on the pipe parameters, the gas phase flow rate, and the liquid phase flow rate; and inputting the gas phase velocity and liquid phase velocity into a discrimination model to determine the separation efficiency of the cyclone gas-liquid separator through the discrimination model.

[0096] In one embodiment, a first pressure sensor and a second pressure sensor are used to acquire the first pressure and the second pressure of the overflow port and the inlet, respectively; the pressure difference between the overflow port and the inlet is determined based on the first pressure and the second pressure; the pressure difference is input into a discrimination model to output a predicted index value corresponding to the pressure difference; and the inlet flow pattern is determined based on the numerical range corresponding to the predicted index value.

[0097] In one embodiment, the pipe parameters include the pipe's inner diameter and cross-sectional area. Determining the inlet gas and liquid velocities based on the pipe parameters, gas flow rate, and liquid flow rate includes calculating the gas and liquid velocities according to formulas (1) and (2), respectively:

[0098]

[0099] Among them, v g Q is the inlet gas flow rate. g Where A is the inlet gas flow rate, d is the cross-sectional area of ​​the pipe, and d is the inner diameter of the pipe.

[0100]

[0101] Among them, v l Q is the inlet liquid flow rate. l This represents the liquid flow rate at the inlet.

[0102] In one embodiment, the predicted index values ​​include the single-period fluctuation time ratio, the number of large fluctuations within a single period, the minimum outlier within a single period, and the maximum outlier within a single period. The single-period fluctuation time ratio is the ratio of the duration of the pressure drop fluctuation signal to the period within a single period. The number of large fluctuations within a single period is the number of peaks in the pressure drop fluctuation signal within a single period that exceed a preset value. The minimum and maximum outliers within a single period are the minimum and maximum values ​​of the abnormal data in the pressure drop fluctuation signal within a single period, respectively. The pressure drop fluctuation signal is determined based on the pressure difference. The abnormal data in the pressure drop fluctuation signal is determined based on discrete data, which refers to the data after discretization of the pressure drop fluctuation signal.

[0103] In one embodiment, the single fluctuation time ratio is calculated according to formula (3):

[0104]

[0105] Among them, t st The duration of one effective pressure drop fluctuation, T is the period of the fluctuation, and r is the effective pressure drop fluctuation. st This represents the duration of a single fluctuation.

[0106] In one embodiment, the number of large fluctuations occurring within a single period is calculated according to formula (4):

[0107] n bw =N i (i∈N*) (4)

[0108] Where, n bw N represents the number of large fluctuations occurring within a single period. i Let represent the number of large fluctuations occurring in the i-th period.

[0109] In one embodiment, the minimum outlier and the maximum outlier within a single period are calculated according to formulas (5) and (6), respectively:

[0110] U min =min(U bi (5)

[0111] Among them, U min U is the smallest outlier within a single period. bi This refers to a smaller outlier within the i-th period;

[0112] U max =max(U ai (6)

[0113] Among them, U max U is the largest outlier within a single period. ai This refers to a larger outlier within the i-th period.

[0114] This application also provides a computer program product, which, when executed on a data processing device, is suitable for executing an initialization program having the following method steps: obtaining the gas phase flow rate and liquid phase flow rate at the inlet through a flow meter; obtaining the pipe parameters of the pipe connected to the inlet; determining the gas phase velocity and liquid phase velocity at the inlet based on the pipe parameters, the gas phase flow rate, and the liquid phase flow rate; and inputting the gas phase velocity and liquid phase velocity into a discrimination model to determine the separation efficiency of the cyclone gas-liquid separator through the discrimination model.

[0115] In one embodiment, a first pressure sensor and a second pressure sensor are used to acquire the first pressure and the second pressure of the overflow port and the inlet, respectively; the pressure difference between the overflow port and the inlet is determined based on the first pressure and the second pressure; the pressure difference is input into a discrimination model to output a predicted index value corresponding to the pressure difference; and the inlet flow pattern is determined based on the numerical range corresponding to the predicted index value.

[0116] In one embodiment, the pipe parameters include the pipe's inner diameter and cross-sectional area. Determining the inlet gas and liquid velocities based on the pipe parameters, gas flow rate, and liquid flow rate includes calculating the gas and liquid velocities according to formulas (1) and (2), respectively:

[0117]

[0118] Among them, v g Q is the inlet gas flow rate. g Where A is the inlet gas flow rate, d is the cross-sectional area of ​​the pipe, and d is the inner diameter of the pipe.

[0119]

[0120] Among them, v lQ is the inlet liquid flow rate. l This represents the liquid flow rate at the inlet.

[0121] In one embodiment, the predicted index values ​​include the single-period fluctuation time ratio, the number of large fluctuations within a single period, the minimum outlier within a single period, and the maximum outlier within a single period. The single-period fluctuation time ratio is the ratio of the duration of the pressure drop fluctuation signal to the period within a single period. The number of large fluctuations within a single period is the number of peaks in the pressure drop fluctuation signal within a single period that exceed a preset value. The minimum and maximum outliers within a single period are the minimum and maximum values ​​of the abnormal data in the pressure drop fluctuation signal within a single period, respectively. The pressure drop fluctuation signal is determined based on the pressure difference. The abnormal data in the pressure drop fluctuation signal is determined based on discrete data, which refers to the data after discretization of the pressure drop fluctuation signal.

[0122] In one embodiment, the single fluctuation time ratio is calculated according to formula (3):

[0123]

[0124] Among them, t st The duration of one effective pressure drop fluctuation, T is the period of the fluctuation, and r is the effective pressure drop fluctuation. st This represents the duration of a single fluctuation.

[0125] In one embodiment, the number of large fluctuations occurring within a single period is calculated according to formula (4):

[0126] n bw =N i (i∈N*) (4)

[0127] Where, n bw N represents the number of large fluctuations occurring within a single period. i Let represent the number of large fluctuations occurring in the i-th period.

[0128] In one embodiment, the minimum outlier and the maximum outlier within a single period are calculated according to formulas (5) and (6), respectively:

[0129] U min =min(U bi (5)

[0130] Among them, U min U is the smallest outlier within a single period. bi This refers to a smaller outlier within the i-th period;

[0131] U max =max(U ai (6)

[0132] Among them, U maxU is the largest outlier within a single period. ai This refers to a larger outlier within the i-th period.

[0133] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0134] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0135] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0136] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0137] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0138] Memory may include non-persistent memory in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0139] Computer-readable media includes both permanent and non-permanent, removable and non-removable media that can store information using any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic magnetic disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transient computer-readable media, such as modulated data signals and carrier waves.

[0140] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0141] The above are merely embodiments of this application and are not intended to limit the scope of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of the claims of this application.

Claims

1. A method for determining the separation efficiency of a cyclonic gas-liquid separator, characterized by, A flow meter and a second pressure sensor are installed at the inlet of the cyclone gas-liquid separator, and a first pressure sensor is installed at the overflow port of the cyclone gas-liquid separator. The method includes: The gas phase flow rate and liquid phase flow rate at the inlet are obtained through the flow meter; Obtain the pipe parameters of the pipe connected to the inlet; The gas phase velocity and liquid phase velocity at the inlet are determined based on the pipeline parameters, the gas phase flow rate, and the liquid phase flow rate. The gas phase velocity and the liquid phase velocity are input into the discrimination model to determine the separation efficiency of the cyclone gas-liquid separator. The first pressure and the second pressure of the overflow port and the inlet are respectively obtained by the first pressure sensor and the second pressure sensor; The pressure difference between the overflow port and the inlet is determined based on the first pressure and the second pressure. The pressure difference is input into the discrimination model to output a predicted index value corresponding to the pressure difference. The predicted index value includes the single fluctuation time ratio, the number of large fluctuations in a single period, the minimum outlier in a single period, and the maximum outlier in a single period. The single fluctuation time ratio is the ratio of the duration of the pressure drop fluctuation signal to the period in a single period. The number of large fluctuations in a single period is the number of peaks in the pressure drop fluctuation signal that exceed a preset value in a single period. The minimum outlier and the maximum outlier in a single period are the minimum and maximum values ​​of the abnormal data of the pressure drop fluctuation signal in a single period, respectively. The pressure drop fluctuation signal is determined based on the pressure difference, and the abnormal data of the pressure drop fluctuation signal is determined based on discrete data. The discrete data refers to the data after discretization of the pressure drop fluctuation signal. The inlet flow pattern is determined based on the numerical range corresponding to the predicted index value.

2. The method of claim 1, wherein, The pipe parameters include the inner diameter and cross-sectional area of ​​the pipe. Determining the gas phase velocity and liquid phase velocity at the inlet based on the pipe parameters, the gas phase flow rate, and the liquid phase flow rate includes calculating the gas phase velocity and the liquid phase velocity according to formulas (1) and (2), respectively. （1） in, The gas phase flow rate at the inlet is [value missing]. The gas phase flow rate at the inlet. Let be the cross-sectional area of ​​the pipe. The inner diameter of the pipe; （2） wherein, is the liquid phase flow rate of the inlet, is the liquid phase flow rate of the inlet.

3. The method of claim 1, wherein, The single fluctuation time ratio is calculated according to formula (3): （3） in, t st The duration of one effective pressure drop fluctuation. T The period in which the fluctuation occurs. r st This refers to the ratio of the duration of a single fluctuation.

4. The method of claim 1, wherein, The number of large fluctuations occurring within a single period is calculated using formula (4): （4） in, The number of large fluctuations occurring within the single period. N i For the first i The number of times a major fluctuation occurs in a cycle.

5. The method of claim 1, wherein, The minimum outlier and the maximum outlier within a single period are calculated according to formulas (5) and (6), respectively: （5） wherein, U min is the smallest abnormal value in the single cycle, U bi is the smaller abnormal value in the first i cycle. （6） in, The maximum outlier within the single period. U ai For the first i Large outliers within a period.

6. An apparatus for determining the separation efficiency of a cyclone gas-liquid separator, characterized in that, include: The data acquisition module is used to obtain the gas phase flow rate and liquid phase flow rate at the inlet via a flow meter; The data acquisition module is used to acquire the pipe parameters of the pipe connected to the inlet; The data processing module is used to determine the gas phase velocity and liquid phase velocity at the inlet based on the pipeline parameters, the gas phase flow rate, and the liquid phase flow rate. The discrimination module is used to input the gas phase flow rate and the liquid phase flow rate into the discrimination model, so as to determine the separation efficiency of the cyclone gas-liquid separator through the discrimination model.

7. A processor, comprising: It is configured to perform the method for determining the separation efficiency of a cyclone gas-liquid separator as described in any one of claims 1 to 5.

8. A machine-readable storage medium having stored thereon instructions, the instructions being executable by a machine to cause the machine to: The instructions, when executed by a processor, cause the processor to be configured to perform the method for determining separation efficiency of a cyclonic gas-liquid separator according to any one of claims 1 to 5.

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