Drainage test data processing method, device, equipment and medium

Abstract

The invention relates to the technical field of data processing, and discloses a drainage test data processing method and device, equipment and a medium, and the method comprises the steps: obtaining target drainage test data of preset drainage fluid; wherein the target drainage test data comprises to-be-processed drainage data and a plurality of drainage condition data corresponding to the to-be-processed drainage data; under the condition that the to-be-processed drainage data meets a preset data error condition, the drainage capacity of preset drainage fluid is predicted based on the to-be-processed drainage data, and drainage capacity data of the preset drainage fluid is obtained; and according to the drainage capacity data and the multiple drainage condition data, constructing a drainage capacity model of the preset drainage fluid. The method has the beneficial effects that the corresponding drainage capacity model is established for the preset drainage fluid, so that quantitative drainage control can be performed on the water storage tank by utilizing the preset drainage fluid based on the drainage capacity model, the accuracy of ship attitude adjustment is improved, and the safety and maneuverability of the ship are improved.

Description

Technical Field

[0001] The present application relates to the technical field of data processing, and particularly to a method, device, equipment and medium for processing drainage test data. Background Art

[0002] The ship attitude has a direct impact on the safety and maneuverability of the ship. When the ship has longitudinal or transverse inclination or rocking, if the ship attitude cannot be stabilized in time, it may cause the ship to lose balance and have a great impact on the navigation process, and even lead to safety accidents. The ship attitude is related to the buoyancy received by the ship at different positions. Therefore, in order to adjust the ship attitude, water storage tanks are usually arranged at multiple positions inside the ship, and the water injection and drainage of the corresponding water storage tanks are controlled to adjust the gravity of the ship at different positions, so as to effectively adjust the ship attitude. In the related art, when adjusting the ship attitude, the accuracy of quantitatively draining water from the water storage tank by using pneumatic drive still needs to be improved. Summary of the Invention

[0003] The present application provides a method, device, equipment and medium for processing drainage test data. According to the target drainage test data of the preset drainage fluid, a corresponding drainage capacity model is established for the preset drainage fluid, so that based on the drainage capacity model, the preset drainage fluid can be used to control the quantitative drainage of the water storage tank, improving the accuracy of ship attitude adjustment and enhancing the safety and maneuverability of the ship.

[0004] To achieve the above object, the main technical solutions adopted by the present application include: In a first aspect, an embodiment of the present application provides a method for processing drainage test data, the method comprising: Obtaining target drainage test data of a preset drainage fluid; wherein, the target drainage test data includes drainage data to be processed and a plurality of drainage condition data corresponding to the drainage data to be processed; When the drainage data to be processed meets the preset data error condition, predicting the drainage capacity of the preset drainage fluid based on the drainage data to be processed to obtain drainage capacity data of the preset drainage fluid; Constructing a drainage capacity model of the preset drainage fluid according to the drainage capacity data and the plurality of drainage condition data; wherein, the drainage capacity model is used to describe the drainage capacity data of the preset drainage fluid under target drainage conditions, and the target drainage conditions correspond to any one of the drainage condition data in the plurality of drainage condition data.

[0005] The drainage test data processing method proposed in the embodiments of this application obtains the target drainage test data of a preset drainage fluid, and predicts the drainage capacity of the preset drainage fluid based on the target drainage test data to obtain the drainage capacity data of the preset drainage fluid; according to the drainage capacity data and the drainage condition data, a drainage capacity model of the preset drainage fluid is constructed, so that the drainage capacity of the preset drainage fluid under any drainage conditions can be determined using the drainage capacity model. Compared with the related art, in this application, the preset drainage fluid is tested in advance, and a drainage capacity model of the preset drainage fluid is constructed based on the test results. Therefore, in the actual scenario, the drainage capacity model can be used to determine the actual drainage capacity of the preset drainage fluid according to the actual drainage condition data, realizing quantitative drainage control of the water storage tank, improving the accuracy of ship attitude adjustment, and enhancing the safety and maneuverability of the ship. In addition, this application can effectively cope with complex actual drainage conditions, reduce the interference of the actual environment on drainage control, and improve the reliability of drainage control.

[0006] Optionally, the constructing the drainage capacity model of the preset drainage fluid according to the drainage capacity data and the multiple drainage condition data includes: Perform a correlation analysis on the multiple drainage condition data, and determine the corresponding data fitting model according to the correlation between the multiple drainage condition data; Perform an optimal fitting times analysis on the data fitting model according to the target drainage test data to obtain the target fitting times; fit the drainage capacity data and the multiple drainage condition data according to the target fitting times and the data fitting model to obtain the drainage capacity model.

[0007] Optionally, the performing an optimal fitting times analysis on the data fitting model according to the target drainage test data to obtain the target fitting times includes: According to the initial fitting times and the data fitting model, perform training fitting on the target drainage test data used as training data to obtain an initial fitting model; Perform error analysis on the initial fitting model using the target drainage test data used as test data, and update the initial fitting times according to the error analysis result; Repeat the above steps of performing training fitting on the target drainage test data and updating the initial fitting times until the error analysis result meets the preset model error condition, and use the initial fitting times at this time as the target fitting times.

[0008] Optionally, the drainage data to be processed includes multiple simulated drainage data; the following method is used to determine whether the drainage data to be processed meets the preset data error condition: Perform error analysis on any two simulated drainage data to obtain drainage data error; In the case where all the drainage data errors exceed the data error threshold, it is determined that the drainage data to be processed does not meet the preset data error condition; In the case where any drainage data error does not exceed the data error threshold, it is determined that the drainage data to be processed meets the preset data error condition.

[0009] Optionally, the predicting the drainage capacity of the preset drainage fluid based on the drainage data to be processed includes: Determining valid test data according to the numerical relationship between the drainage data error and the data error threshold; wherein, the valid test data is the simulated drainage data corresponding to the drainage data error that does not exceed the data error threshold; Performing an average analysis of the total drainage volume based on the valid test data to obtain the drainage capacity data.

[0010] Optionally, the obtaining the target drainage test data of the preset drainage fluid includes: Obtaining the initial drainage test data of the preset drainage fluid under the target drainage condition; Performing data synchronization preprocessing on the initial drainage test data to obtain the target drainage test data.

[0011] Optionally, the initial drainage test data corresponds to a trigger timestamp indicating the data generation time and a reception timestamp indicating the data reception time, and the obtaining process of the initial drainage test data corresponds to a response delay and a communication delay; the performing data synchronization preprocessing on the initial drainage test data to obtain the target drainage test data includes: Adding the response delay and the communication delay to obtain the total delay; Performing delay compensation on the reception timestamp of the initial drainage test data according to the total delay so that the reception timestamp is consistent with the trigger timestamp to obtain the target drainage test data.

[0012] In a second aspect, an embodiment of the present application provides a drainage test data processing device, and the device includes: A drainage data test module, configured to obtain target drainage test data of a preset drainage fluid; wherein, the target drainage test data includes drainage data to be processed and a plurality of drainage condition data corresponding to the drainage data to be processed; A drainage capacity prediction module, configured to predict the drainage capacity of the preset drainage fluid based on the drainage data to be processed when the drainage data to be processed meets the preset data error condition, to obtain the drainage capacity data of the preset drainage fluid; A drainage capacity model fitting module, configured to construct a drainage capacity model of the preset drainage fluid according to the drainage capacity data and the multiple drainage condition data; wherein, the drainage capacity model is used to describe the drainage capacity data of the preset drainage fluid under the target drainage condition; the target drainage condition corresponds to any one of the multiple drainage condition data.

[0013] In a third aspect, an embodiment of the present application provides a computer device, including: a memory and a processor, the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the computer instructions to execute the method according to any one of the above embodiments.

[0014] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, on which computer instructions are stored, and the computer instructions are used to cause a computer to execute the method according to any one of the above embodiments.

[0015] In a fifth aspect, an embodiment of the present application provides a computer program product, including computer instructions, and the computer instructions are used to cause a computer to execute the method according to any one of the above embodiments. Description of the Drawings

[0016] In order to more clearly illustrate the specific embodiments of the present application or the technical solutions in the prior art, the following will briefly introduce the drawings required to be used in the description of the specific embodiments or the prior art. Obviously, the drawings in the following description are some embodiments of the present application. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained according to these drawings.

[0017] Figure 1 It is a step diagram of the drainage test data processing method provided by the embodiment of the present application; Figure 2 It is a structural diagram of the drainage capacity test system in the embodiment of the present application; Figure 3 It is a step diagram of constructing a drainage capacity model in the embodiment of the present application; Figure 4 It is a step diagram of obtaining the target fitting times in the embodiment of the present application; Figure 5 It is a step diagram of determining whether the drainage data to be processed meets the preset data error condition in the embodiment of the present application; Figure 6 It is a step diagram of obtaining the drainage capacity data in the embodiment of the present application; Figure 7 It is a step diagram of obtaining the target drainage test data in the embodiment of the present application; Figure 8It is a step diagram for data synchronization preprocessing of initial drainage test data in an embodiment of this application; Figure 9 It is a module diagram of a drainage test data processing device provided in an embodiment of this application; Figure 10 It is a schematic structural diagram of a computer device provided in an embodiment of this application.

[0018] Among them, the reference numerals of the specification drawings are as follows: 110. Fluid storage unit, 120. Drainage test unit, 130. Drainage receiving unit, 140. Drainage flow measurement unit. Detailed implementation manners

[0019] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions in the embodiments of this application will be clearly and completely described below with reference to the drawings in the embodiments of this application. Apparently, the described embodiments are some, rather than all, of the embodiments of this application. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of this application without creative efforts shall fall within the protection scope of this application.

[0020] The ship attitude has a direct impact on the safety and maneuverability of the ship. When the ship has situations such as longitudinal and transverse inclination or rocking, if the ship attitude cannot be stabilized in time, it may cause the ship to lose balance and have a great impact on the navigation process, and even lead to safety accidents. The ship attitude is related to the buoyancy received by the ship at different positions. Therefore, in order to adjust the ship attitude, water storage tanks are usually arranged at multiple positions inside the ship, and the corresponding water storage tanks are controlled to fill and drain water, so as to adjust the gravity magnitudes received by the ship at different positions and effectively adjust the ship attitude.

[0021] In related technologies, the methods for controlling the filling and draining of water storage tanks include pump-driven drainage and gas-driven drainage, etc. Among them, pump-driven drainage refers to the method of using pump equipment to pump out the water in the water storage tank and discharge it to the external environment. It has the advantages of precise control and high drainage efficiency, but pump equipment usually has high energy consumption and high maintenance requirements, and pump equipment will also occupy a large space inside the ship, increasing the complexity inside the ship. Gas-driven drainage refers to the method of inputting a compressible fluid into the water storage tank to use the expansion effect of the compressible fluid to discharge the water in the water storage tank to the external environment. It has the advantages of not requiring an additional power source and having a simple and reliable structure compared with pump-driven drainage. The compressible fluids used in gas-driven drainage can include fluids such as air, nitrogen, and carbon dioxide.

[0022] However, in gas-driven drainage, the volume of the compressible fluid after expansion is affected by various drainage conditions, and it is difficult to accurately control the drainage volume when controlling the drainage of the water storage tank, resulting in a decline in the effect of adjusting the ship's attitude and affecting the safety and maneuverability of the ship. In addition, the expansion process of the compressible fluid takes a certain amount of time. During the expansion process, it is necessary to continuously control and adjust the flow rate and pressure of the compressible fluid, and the drainage condition data corresponding to the compressible fluid during the expansion process may also change in real time, further increasing the difficulty of quantitatively controlling the drainage of the water storage tank.

[0023] Based on the above problems, the present application provides a drainage test data processing method, device, equipment and medium. The method includes: obtaining target drainage test data of a preset drainage fluid; wherein the target drainage test data includes to-be-processed drainage data and a plurality of drainage condition data corresponding to the to-be-processed drainage data; when the to-be-processed drainage data meets the preset data error condition, predicting the drainage capacity of the preset drainage fluid based on the to-be-processed drainage data to obtain drainage capacity data of the preset drainage fluid; and constructing a drainage capacity model of the preset drainage fluid according to the drainage capacity data and the plurality of drainage condition data.

[0024] The drainage test data processing method provided by the present application obtains the target drainage test data of the preset drainage fluid, predicts the drainage capacity of the preset drainage fluid according to the target drainage test data to obtain the drainage capacity data of the preset drainage fluid, and constructs a drainage capacity model of the preset drainage fluid according to the drainage capacity data and the drainage condition data, so that the drainage capacity of the preset drainage fluid under any drainage condition can be determined by using the drainage capacity model.

[0025] Compared with the related technology, the present application conducts tests on the preset drainage fluid in advance and constructs a drainage capacity model of the preset drainage fluid based on the test results, so that in the actual scenario, the drainage capacity model can be used to determine the actual drainage capacity of the preset drainage fluid according to the actual drainage condition data, realize the quantitative drainage control of the water storage tank, improve the accuracy of ship attitude adjustment, and enhance the safety and maneuverability of the ship. In addition, the present application can also effectively cope with complex actual drainage conditions, reduce the interference of the actual environment on drainage control, and improve the reliability of drainage control.

[0026] The drainage test data processing method provided in this specification can be applied to compressible fluids capable of gas-driven drainage to construct a corresponding drainage capacity model and determine the drainage capacity data of the preset drainage fluid under different drainage conditions. Compressible fluids capable of gas-driven drainage can include fluids such as air, nitrogen, and carbon dioxide. It can be understood that after adaptive modification, the drainage test data processing method provided in this specification can also be applied to other compressible fluids other than the above fluids, including but not limited to oils or other chemical liquids.

[0027] According to an embodiment of the present application, an embodiment of a drainage test data processing method is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although the logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in a different order than here.

[0028] In this embodiment, a drainage test data processing method is provided, which can be used for the compressible fluid capable of pneumatically driven drainage described above. Refer to Figure 1 As shown, the method includes: S100. Obtain the target drainage test data of the preset drainage fluid; wherein, the target drainage test data includes the drainage data to be processed and a plurality of drainage condition data corresponding to the drainage data to be processed.

[0029] S200. When the drainage data to be processed meets the preset data error condition, predict the drainage capacity of the preset drainage fluid based on the drainage data to be processed to obtain the drainage capacity data of the preset drainage fluid.

[0030] S300. Construct a drainage capacity model of the preset drainage fluid according to the drainage capacity data and a plurality of drainage condition data; wherein, the drainage capacity model is used to describe the drainage capacity data of the preset drainage fluid under the target drainage conditions, and the target drainage conditions correspond to any one of the drainage condition data in the plurality of drainage condition data.

[0031] Refer to Figure 2 , the drainage test data processing method provided by the present application can be applicable to Figure 2 the drainage capacity test system shown. Obtain the target drainage test data of the preset drainage fluid according to the drainage capacity test system. The drainage capacity test system includes a fluid storage unit 110, a drainage test unit 120, and a drainage receiving unit 130. Among them, the fluid storage unit 110 and the drainage test unit 120 are connected by a first conveying pipeline, and a first conveying valve is provided on the first conveying pipeline to control the opening and closing of the first conveying pipeline; the drainage test unit 120 and the drainage receiving unit 130 are connected by a second conveying pipeline, and a second conveying valve and a drainage flow measurement unit 140 are provided on the second conveying pipeline, and the second conveying valve is used to control the opening and closing of the second conveying pipeline.

[0032] The fluid storage unit 110 stores a preset drainage fluid in a compressed state. The preset drainage fluid is a compressible fluid that can be used for gas-driven drainage, including air, nitrogen, carbon dioxide, etc. The preset drainage fluid can be introduced into the drainage test unit 120 through the first delivery pipeline. The drainage test unit 120 stores water and is used to receive the preset drainage fluid through the first delivery pipeline and drain the water with the preset drainage fluid to simulate the process of the preset drainage fluid controlling the water storage tank of a ship to drain water in an actual scenario. The water discharged from the drainage test unit 120 is transported through the second delivery pipeline and stored in the drainage receiving unit 130, and the water flow rate flowing through the second delivery pipeline can be measured by the drainage flow rate measuring unit 140. In some embodiments, the drainage receiving unit 130 is also connected to a pressure regulating unit for regulating the pressure in the drainage receiving unit 130 to modify the drainage condition data in the drainage receiving unit 130.

[0033] A liquid level gauge is provided in the drainage test unit 120 for measuring the liquid level height in the drainage test unit 120, so as to obtain the total drainage volume caused by the preset drainage fluid to the drainage test unit 120 during the test process. Similarly, a liquid level gauge is also provided in the drainage receiving unit 130 for measuring the liquid level height in the drainage receiving unit 130, so as to obtain the total amount of water discharged from the drainage test unit 120 during the test process. It can be understood that various types of sensors can be respectively provided in the fluid storage unit 110, the drainage test unit 120, and the drainage receiving unit 130 for obtaining the drainage condition data corresponding to each unit. Exemplarily, the types of sensors can include temperature sensors and pressure sensors, etc.

[0034] Based on the above drainage capacity test system, the drainage data to be processed can include the direct drainage total amount, the drainage receiving total amount, and the drainage transportation total amount. Among them, the direct drainage total amount can be the total drainage volume caused by the preset drainage fluid to the drainage test unit 120 during the test process, which can be determined according to the change in the liquid level height in the drainage test unit 120. The drainage receiving total amount can be the total amount of water discharged from the drainage test unit 120 during the test process, which can be determined according to the change in the liquid level height in the drainage receiving unit 130. The drainage transportation total amount can be the total water flow volume flowing through the second delivery pipeline during the test process, which can be obtained according to the water flow rate measured by the drainage flow rate measuring unit 140 and the duration of the test process.

[0035] The drainage condition data can be the unit condition data of the drainage test unit 120 and the drainage receiving unit 130 respectively, including but not limited to the unit pressure data representing the pressure magnitude in each unit, and the unit temperature data representing the temperature level in each unit, etc. It can be understood that the drainage data to be processed and the drainage condition data are corresponding to each other, and the drainage condition data represents the drainage conditions in the drainage capacity test system when the drainage data to be processed is generated.

[0036] Specifically, a target drainage test data of a preset drainage fluid is obtained by using a drainage capacity test system. During the test, the first delivery valve and the second delivery valve are opened, so that the preset drainage fluid stored in the fluid storage unit 110 enters the drainage test unit 120 through the first delivery pipe. The preset drainage fluid expands in the drainage test unit 120, and the expansion of the preset drainage fluid is used to apply pressure to the water in the drainage test unit 120, so that the water in the drainage test unit 120 enters the drainage receiving unit 130 through the second delivery pipe, causing changes in the liquid levels of the drainage test unit 120 and the drainage receiving unit 130. After the test, the drainage data to be processed is obtained according to multiple measurement results in the drainage capacity test system, including the total direct drainage volume, the total drainage receiving volume, and the total drainage delivery volume. Among them, the total direct drainage volume is obtained from the change in the liquid level height of the drainage test unit 120, the total drainage receiving volume is obtained from the change in the liquid level height of the drainage receiving unit 130, and the total drainage delivery volume is obtained from the measurement result of the drainage flow measurement unit 140. It can be understood that the test process can be carried out under various drainage conditions, so as to obtain the drainage data to be processed under different drainage conditions. Different drainage conditions are represented by different drainage condition data, and the target drainage test data can be obtained according to the drainage data to be processed and the corresponding drainage condition data.

[0037] Furthermore, it is judged whether the drainage data to be processed meets the preset data error condition to judge whether the drainage data to be processed is valid. When the drainage data to be processed meets the preset data error condition, the drainage volume caused by the preset drainage fluid during the test is predicted according to the total direct drainage volume, the total drainage receiving volume, and the total drainage delivery volume, and the drainage capacity data of the preset drainage fluid is obtained. It can be understood that by obtaining the drainage data to be processed at multiple positions in the drainage capacity test system, error analysis is carried out according to the drainage data to be processed at different positions to ensure the validity and accuracy of the drainage data to be processed, and further improve the accuracy of the drainage capacity data.

[0038] Furthermore, data fitting is performed according to the drainage capacity data of the preset drainage fluid and its corresponding drainage condition data, and a drainage capacity model is constructed for the preset drainage fluid to describe the drainage capacity data of the preset drainage fluid under the target drainage conditions, where the target drainage conditions can be any drainage conditions, which correspond to any drainage condition data among the multiple drainage condition data. According to the drainage capacity model, the drainage capacity data of the preset drainage fluid under any drainage conditions can be determined, so as to improve the control accuracy when using the preset drainage fluid for drainage in the actual scenario and realize quantitative drainage control.

[0039] It should be noted that in the related art, the drainage capacity data of the preset drainage fluid is usually determined only by experimental data, and the experimental data is discrete, so it is impossible to determine the accurate drainage capacity data of the preset drainage fluid under any drainage condition. In addition, there are also some related technologies that use the state equation corresponding to the preset drainage fluid to directly calculate the drainage capacity data of the preset drainage fluid. Compared with the above-mentioned related technologies, the drainage capacity model in this application can represent the continuous change trend of the drainage capacity data of the preset drainage fluid with the drainage condition, improving the comprehensiveness and accuracy of the data. At the same time, in the actual scenario, according to the drainage condition in the actual scenario, the drainage capacity model can be used to determine the drainage capacity data of the preset drainage fluid under the current condition, so as to accurately control the quantitative drainage of the water storage tank of the ship, improving the safety and maneuverability of the ship.

[0040] The drainage test data processing method provided in this embodiment obtains the target drainage test data of the preset drainage fluid, predicts the drainage capacity of the preset drainage fluid according to the target drainage test data, and obtains the drainage capacity data of the preset drainage fluid; according to the drainage capacity data and the drainage condition data, a drainage capacity model of the preset drainage fluid is constructed, so that the drainage capacity of the preset drainage fluid under any drainage condition can be determined by using the drainage capacity model.

[0041] Compared with the related art, in this application, the preset drainage fluid is tested in advance, and a drainage capacity model of the preset drainage fluid is constructed based on the test results. Thus, in the actual scenario, the drainage capacity model can be used to determine the actual drainage capacity of the preset drainage fluid according to the actual drainage condition data, realizing the quantitative drainage control of the water storage tank, improving the accuracy of ship attitude adjustment, and enhancing the safety and maneuverability of the ship. In addition, this application can also effectively cope with complex actual drainage conditions, reduce the interference of the actual environment on drainage control, and improve the reliability of drainage control.

[0042] Refer to Figure 3 As shown in the figure, as an embodiment of this application, constructing a drainage capacity model of the preset drainage fluid according to the drainage capacity data and multiple drainage condition data includes: S310. Perform a correlation analysis on multiple drainage condition data, and determine the corresponding data fitting model according to the correlation between the multiple drainage condition data.

[0043] S320. Perform an optimal fitting times analysis on the data fitting model according to the target drainage test data to obtain the target fitting times.

[0044] S330. Fit the drainage capacity data and multiple drainage condition data according to the target fitting times and the data fitting model to obtain the drainage capacity model.

[0045] Specifically, perform a correlation analysis on multiple drainage condition data to determine the correlation between the multiple drainage condition data. The drainage condition data may include unit pressure data and test time data. Among them, the unit pressure data can represent the pressure magnitude in the drainage receiving unit 130, and the test time data can represent the length of the test time, that is, the time length from opening the first conveying valve and conveying the preset drainage medium to the end of drainage. Perform a correlation analysis on the unit pressure data and the test time data to obtain the correlation between the unit pressure data and the test time data.

[0046] Exemplarily, the method of correlation analysis can be image analysis or correlation coefficient calculation. Among them, the process of image analysis can include: drawing a scatter plot or a three-dimensional surface plot according to the trend of the drainage capacity data changing with multiple drainage condition data, and determining the correlation between the drainage condition data according to the distribution and change trend of each data point in the image. Correlation coefficient calculation can be to calculate the correlation coefficient using the drainage condition data and determine the correlation between the drainage condition data according to the value of the correlation coefficient. The correlation coefficient in the correlation coefficient calculation can be the Pearson correlation coefficient, and its form is as follows: where r is the correlation coefficient; x i and y i are respectively any drainage condition data; and are respectively the sample means of the corresponding drainage condition data. If r is close to 1 or -1, it indicates that there is an approximate linear relationship between the drainage condition data; if r is close to 0, it indicates that there is a non-linear relationship between the drainage condition data.

[0047] Further, according to the correlation between the multiple drainage condition data, determine a data fitting model corresponding to the correlation between the drainage condition data for fitting the drainage capacity data and the multiple drainage condition data. Exemplarily, the data fitting model can be a linear regression model or a polynomial regression model. Among them, the linear regression model corresponds to the drainage condition data with an approximate linear relationship, and its form is as follows: Q = β0 + β1p + β2t where Q is the drainage capacity data; p and t are the drainage condition data. Here, taking the unit pressure data and the test time data as examples, where p is the unit pressure data and t is the test time data; β0, β1, and β2 are the regression coefficients of the data fitting model. The polynomial regression model corresponds to the drainage condition data with a non-linear relationship, and its form is as follows: Q = β0 + β1p + β2t + β3pt + β4p 2 + β5t 2 Among them, β3, β4, and β5 are the regression coefficients of the data fitting model.

[0048] Furthermore, before using the data fitting model to fit the drainage capacity data and the drainage condition data, it is also necessary to determine the target fitting times corresponding to the drainage capacity data and the drainage condition data to reduce the probability of overfitting or underfitting during the fitting process. Based on the target drainage test data, an optimal fitting times analysis is performed on the selected data fitting model to obtain the target fitting times. According to the target fitting times and the data fitting model, the drainage capacity data and multiple drainage condition data are fitted to obtain the drainage capacity model.

[0049] Referring to Figure 4 As shown, as an embodiment of the present application, performing an optimal fitting times analysis on the data fitting model according to the target drainage test data to obtain the target fitting times includes: S322. According to the initial fitting times and the data fitting model, perform training fitting on the target drainage test data used as training data to obtain an initial fitting model.

[0050] S324. Use the target drainage test data used as test data to perform error analysis on the initial fitting model, and update the initial fitting times according to the error analysis result.

[0051] S326. Repeat the above steps of performing training fitting on the target drainage test data and updating the initial fitting times until the error analysis result meets the preset model error condition, and use the initial fitting times at this time as the target fitting times.

[0052] Specifically, based on the preset initial fitting times, all possible feature combinations are generated according to multiple drainage condition data. The feature combination is a combination of drainage condition data, and the number of each feature combination does not exceed the initial fitting times. Exemplarily, when the initial fitting times is 2 and the drainage condition data includes unit pressure data and test time data, the form of the feature combination is as follows: x = {1, p, t, p 2 , pt, t 2} Among them, x is the feature combination.

[0053] Furthermore, the target drainage test data is divided into training data and test data according to a ratio. Exemplarily, this ratio can be 7:3. Using the feature combination as the input and the drainage capacity data as the output, use the corresponding regression model to fit the target drainage test data used as training data to obtain an initial fitting model.

[0054] Further, error analysis is performed on the initial fitting model using the target drainage test data as the test data, and the error index of the initial fitting model on the target drainage test data as the test data is calculated as the error analysis result, where the error index can be an index such as the mean square error or the coefficient of determination. If the error analysis result meets the preset model error condition, the initial fitting times at this time are used as the target fitting times; if the error analysis result does not meet the preset model error condition, the initial fitting times are updated and adjusted according to the error analysis result, so as to obtain the updated initial fitting times.

[0055] Further, based on the updated initial fitting times, the above steps of training and fitting the target drainage test data and updating the initial fitting times are repeated until the error analysis result meets the preset model error condition, and the initial fitting times at this time are used as the target fitting times.

[0056] Refer to Figure 5 As shown, as an embodiment of the present application, the drainage data to be processed includes multiple simulated drainage data; the following method is used to determine whether the drainage data to be processed meets the preset data error condition: S202. Perform error analysis on any two simulated drainage data to obtain the drainage data error.

[0057] S204. In the case where all drainage data errors exceed the data error threshold, it is determined that the drainage data to be processed does not meet the preset data error condition.

[0058] S206. In the case where any drainage data error does not exceed the data error threshold, it is determined that the drainage data to be processed meets the preset data error condition.

[0059] Specifically, the simulated drainage data can be any one of the direct drainage total amount, the drainage receiving total amount, and the drainage conveying total amount. It can be understood that in the case of no error, the numerical values of the direct drainage total amount, the drainage receiving total amount, and the drainage conveying total amount are the same. If the error between any two simulated drainage data exceeds the data error threshold, it indicates that there is an error in the sensor corresponding to one of the any two simulated drainage data. The process of error analysis includes: taking the difference between any two simulated drainage data and calculating the relative error between the above two simulated drainage data according to the difference as the drainage data error.

[0060] Further, if all drainage data errors exceed the data error threshold, it indicates that there are significant errors among the total direct drainage volume, the total drainage reception volume, and the total drainage transportation volume. The source of this error can be the error or drift of the sensors in each unit of the drainage capacity test system. At this time, a warning can be given to the test personnel to remind them to recalibrate the sensors in the drainage capacity test system accurately to reduce the drainage data error. Correspondingly, if any of the drainage data errors does not exceed the data error threshold among the drainage data errors, it indicates that the error between the corresponding simulated drainage data of this any drainage data error is small and can be used as valid simulated drainage data. At this time, it is determined that the drainage data to be processed meets the preset data error condition, and the corresponding simulated drainage data is used as valid test data.

[0061] It can be understood that error analysis can also be performed on the drainage condition data to determine whether there is an error or drift in the sensor used to obtain the drainage condition data, and a warning is given to the test personnel according to the error analysis result to remind the test personnel to recalibrate the sensors in the drainage capacity test system accurately and improve the accuracy of the drainage condition data. Exemplarily, in the drainage capacity test system, the pressure in the drainage test unit 120 is similar to the pressure in the drainage reception unit 130. If there is a large error between the two, it indicates that there is an error or drift in the pressure sensor in the drainage test unit 120 or the drainage reception unit 130, and the test personnel need to recalibrate it accurately.

[0062] Similarly, in the drainage capacity test system, the temperature data in the drainage reception unit 130 can also be obtained. The temperature data in the drainage reception unit 130 is time-series data that changes with time, indicating the temperature change inside the drainage reception unit 130 during the test. If the temperature change in the drainage reception unit 130 exceeds the preset temperature change range, it indicates that the test process is abnormal, and the simulated drainage data obtained at this time cannot be used as valid test data.

[0063] Refer to Figure 6 As shown, as an embodiment of the present application, predicting the drainage capacity of a preset drainage fluid based on the drainage data to be processed includes: S210. Determine valid test data according to the numerical relationship between the drainage data error and the data error threshold; wherein, the valid test data is the simulated drainage data corresponding to the drainage data error that does not exceed the data error threshold.

[0064] S220. Perform an average analysis of the total drainage volume based on the valid test data to obtain the drainage capacity data.

[0065] Specifically, when any of the drainage data errors does not exceed the data error threshold among the drainage data errors, the simulated drainage data corresponding to the any drainage data error is taken as valid test data. In some embodiments, if there are multiple drainage data errors that do not exceed the data error threshold, it indicates that the errors between the simulated drainage data corresponding to the multiple drainage data errors all meet the requirements. At this time, the simulated drainage data corresponding to the multiple drainage data errors can all be taken as valid test data.

[0066] Further, perform an average analysis of the total drainage volume based on the valid test data to obtain drainage capacity data, and its form is as follows: Wherein, q1 and q2 are respectively valid test data, and q1 and q2 can each be any one of the direct total drainage volume, the total drainage reception volume, and the total drainage transportation volume. In some embodiments, if there are multiple valid test data, the above formula can also be adaptively modified to perform an average analysis of the total drainage volume based on the multiple valid test data together to obtain drainage capacity data.

[0067] Referring to Figure 7 As shown, as an embodiment of the present application, obtaining target drainage test data of a preset drainage fluid includes: S110. Obtain initial drainage test data of the preset drainage fluid under target drainage conditions.

[0068] S120. Perform data synchronization preprocessing on the initial drainage test data to obtain target drainage test data.

[0069] Specifically, under the set target drainage conditions, use a drainage capacity test system to test the drainage capacity of the preset drainage fluid, and obtain initial drainage test data according to the measurement results of the sensors in the drainage capacity test system, including the direct total drainage volume, the total drainage reception volume, and the total drainage transportation volume that have not undergone data synchronization preprocessing.

[0070] Further, since each sensor in the drainage capacity test system has its own response time and communication delay, there may be a problem of time asynchronization between the initial drainage test data, which affects the accuracy of the drainage capacity data and the drainage capacity model. Therefore, it is necessary to perform data synchronization preprocessing on the initial drainage test data to align the data times of the initial drainage test data fed back by different sensors, reduce the deviation of the drainage capacity data and the drainage capacity model, and ensure the accuracy of both.

[0071] Furthermore, various data preprocessings can also be performed on the target drainage test data to further improve the accuracy and effectiveness of the target drainage test data. The data preprocessing can include denoising filtering, outlier removal, and data interpolation, etc. Among them, denoising filtering can include using a filter to filter the sensors in the drainage capacity test system to reduce the noise in the measurement results of the sensors. Exemplarily, the filter can be a Kalman filter.

[0072] Outlier removal can include identifying and removing the abnormal data points in the target drainage test data to reduce the interference of sensor failures or environmental factors, etc. on the test process. Exemplarily, the method of identifying abnormal data points can be a statistical method, including based on the 3σ principle, etc.

[0073] Data interpolation can include identifying the missing data points in the target drainage test data and complementing the missing data points. Exemplarily, the method of complementing the missing data points can be methods such as linear interpolation or spline interpolation.

[0074] Referring to Figure 8 As shown, as an embodiment of the present application, the initial drainage test data corresponds to a trigger timestamp representing the data generation moment and a reception timestamp representing the data reception moment, and the acquisition process of the initial drainage test data corresponds to a response delay and a communication delay; performing data synchronization preprocessing on the initial drainage test data to obtain the target drainage test data, including: S122. Summing the response delay and the communication delay to obtain the total delay.

[0075] S124. Performing delay compensation on the reception timestamp of the initial drainage test data according to the total delay to make the reception timestamp consistent with the trigger timestamp, thereby obtaining the target drainage test data.

[0076] Specifically, the response delay can be the response time of the sensors in the drainage capacity test system, representing the time length between the generation moment of the initial drainage test data and the moment when the sensors measure the initial drainage test data. The communication delay can be the time length between the moment when the sensors measure the initial drainage test data and the moment when the initial drainage test data is transmitted to the data processing unit. Summing the response delay and the communication delay to obtain the total delay, and the total delay represents the delay error between the reception timestamp and the trigger timestamp of the initial drainage test data. Performing delay compensation on the reception timestamp of the initial drainage test data according to the total delay to make the reception timestamp consistent with the trigger timestamp, thereby obtaining the target drainage test data. The form of the delay compensation is as follows: t corrected =t rts -τ total where, t correctedis the received timestamp after delay compensation; t rts is the received timestamp before delay compensation; τ total is the total delay, and its form is as follows: τ total = τ sensor + τ communication where τ sensor is the response delay; τ communication is the communication delay.

[0077] Correspondingly, please refer to Figure 9 , an embodiment of the present application provides a drainage test data processing device, and the device includes: a drainage data test module 910, configured to obtain target drainage test data of a preset drainage fluid; wherein, the target drainage test data includes drainage data to be processed and a plurality of drainage condition data corresponding to the drainage data to be processed.

[0078] A drainage capacity prediction module 920, configured to predict the drainage capacity of the preset drainage fluid based on the drainage data to be processed to obtain drainage capacity data of the preset drainage fluid when the drainage data to be processed meets a preset data error condition.

[0079] A capacity model fitting module 930, configured to construct a drainage capacity model of the preset drainage fluid according to the drainage capacity data and the plurality of drainage condition data; wherein, the drainage capacity model is used to describe the drainage capacity data of the preset drainage fluid under target drainage conditions; the target drainage conditions correspond to any one of the plurality of drainage condition data.

[0080] In some alternative embodiments, the capacity model fitting module 930 includes: A correlation analysis unit, configured to perform a correlation analysis on the plurality of drainage condition data, and determine a corresponding data fitting model according to the correlation between the plurality of drainage condition data.

[0081] A fitting times analysis unit, configured to perform an optimal fitting times analysis on the data fitting model according to the target drainage test data to obtain a target fitting times.

[0082] A model fitting unit, configured to fit the drainage capacity data and the plurality of drainage condition data according to the target fitting times and the data fitting model to obtain a drainage capacity model.

[0083] In some alternative embodiments, the fitting times analysis unit includes: A training fitting subunit, configured to perform training fitting on the target drainage test data as training data according to an initial fitting times and the data fitting model to obtain an initial fitting model.

[0084] An error analysis subunit, configured to perform error analysis on an initial fitting model by using target drainage test data as test data, and update the initial fitting times according to the error analysis result.

[0085] A repeated update subunit, configured to repeat the above steps of training and fitting the target drainage test data and updating the initial fitting times until the error analysis result meets a preset model error condition, and use the initial fitting times at this time as the target fitting times.

[0086] In some alternative embodiments, the drainage data to be processed includes a plurality of simulated drainage data; the drainage capacity prediction module 920 includes: A drainage data error analysis unit, configured to perform error analysis on any two simulated drainage data to obtain a drainage data error.

[0087] A first condition analysis unit, configured to determine that the drainage data to be processed does not meet the preset data error condition when all drainage data errors exceed a data error threshold.

[0088] A second condition analysis unit, configured to determine that the drainage data to be processed meets the preset data error condition when any one drainage data error does not exceed the data error threshold.

[0089] In some alternative embodiments, the drainage capacity prediction module 920 further includes: A valid data determination unit, configured to determine valid test data according to the numerical relationship between the drainage data error and the data error threshold; wherein, the valid test data is the simulated drainage data corresponding to the drainage data error that does not exceed the data error threshold.

[0090] A total drainage analysis unit, configured to perform an average analysis of the total drainage amount based on the valid test data to obtain drainage capacity data.

[0091] In some alternative embodiments, the drainage data test module 910 includes: An initial data acquisition unit, configured to acquire initial drainage test data of a preset drainage fluid under target drainage conditions.

[0092] A data synchronization preprocessing unit, configured to perform data synchronization preprocessing on the initial drainage test data to obtain target drainage test data.

[0093] In some alternative embodiments, the initial drainage test data corresponds to a trigger timestamp indicating the data generation time and a reception timestamp indicating the data reception time, and the acquisition process of the initial drainage test data corresponds to a response delay and a communication delay; the data synchronization preprocessing unit includes: A delay calculation subunit, configured to sum the response delay and the communication delay to obtain a total delay.

[0094] A delay compensation subunit, configured to perform delay compensation on the reception timestamp of the initial drainage test data according to the total delay, so that the reception timestamp is consistent with the trigger timestamp, and obtain target drainage test data.

[0095] The further functional descriptions of the above-mentioned various modules and units are the same as those in the corresponding embodiments above, and will not be elaborated here.

[0096] The drainage test data processing device in this embodiment is presented in the form of functional units. Here, the unit refers to an ASIC (Application Specific Integrated Circuit) circuit, a processor and a memory that execute one or more software or fixed programs, and / or other devices that can provide the above functions.

[0097] Please refer to Figure 10 , Figure 10 , which is a schematic structural diagram of a computer device provided by an embodiment of the present application. As shown in the figure, the computer device includes: one or more processors 10, a memory 20, and interfaces for connecting various components, including a high-speed interface and a low-speed interface. Each component communicates with each other using different buses and can be installed on a common motherboard or installed in other ways as needed. The processor can process instructions executed within the computer device, including instructions stored in the memory or on the memory to display graphical information of the GUI on an external input / output device (such as a display device coupled to the interface). In some alternative embodiments, if necessary, multiple processors and / or multiple buses can be used together with multiple memories and multiple memories. Similarly, multiple computer devices can be connected, and each device provides some necessary operations (such as a server array, a set of blade servers, or a multi-processor system). Figure 10 In

[0098]

[0099] The memory 20 stores instructions executable by at least one processor 10, so that the at least one processor 10 executes the method shown in the above embodiment.

[0100] ​The memory 20 may include a program storage area and a data storage area, wherein the program storage area may store an operating system and application programs required for at least one function; the data storage area may store data created based on the use of the computer device, etc. In addition, the memory 20 may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some optional embodiments, the memory 20 may optionally include a memory remotely located relative to the processor 10, and these remote memories may be connected to the computer device via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0101] The memory 20 may include a volatile memory, such as a random access memory; the memory may also include a non-volatile memory, such as a flash memory, a hard disk or a solid-state drive; the memory 20 may also include a combination of the above types of memory.

[0102] The computer device further includes a communication interface 30 for the computer device to communicate with other devices or a communication network.

[0103] The embodiments of the present application also provide a computer-readable storage medium. The above-mentioned method according to the embodiment of the present application can be implemented in hardware, firmware, or implemented as a computer code that can be recorded in a storage medium, or implemented as a computer code that is originally stored in a remote storage medium or a non-temporary machine-readable storage medium and downloaded through a network and will be stored in a local storage medium, so that the method described herein can be stored in such software processing on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. Among them, the storage medium can be a magnetic disk, an optical disk, a read-only storage memory, a random access memory, a flash memory, a hard disk or a solid-state drive, etc.; further, the storage medium can also include a combination of the above-mentioned types of memory. It can be understood that a computer, a processor, a microprocessor controller or programmable hardware includes a storage component that can store or receive software or computer code. When the software or computer code is accessed and executed by a computer, a processor or hardware, the method shown in the above embodiment is implemented.

[0104] An embodiment of the present application provides a computer program product, which includes computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform a method according to any embodiment of the present application.

[0105] Although the embodiments of the present application are described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the present application, and such modifications and variations fall within the scope defined by the appended claims.

[0106] The systems, devices, modules or units illustrated in the above embodiments can be specifically implemented by computer chips or entities, or by products with certain functions. A typical implementation device is a computer. Specifically, the computer can be, for example, a personal computer, a laptop computer, a cellular phone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.

[0107] For the convenience of description, when describing the above devices, various units are described separately according to their functions. Of course, when implementing the present application, the functions of each unit can be implemented in the same or multiple software and / or hardware.

[0108] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented 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.

[0109] The present application is described with reference to the flowcharts and / or block diagrams of methods, apparatuses (systems), and computer program products according to the embodiments of the present application. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, and the combination of flows and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to the processors of general-purpose computers, special-purpose computers, embedded processors, or other programmable data processing devices to generate a machine, so that the instructions executed by the processors of the computer or other programmable data processing devices generate a device for implementing the functions specified in Figure 1 one or more of the flows Figure 1 or multiple flows and / or blocks

[0110] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory generate a manufactured article including an instruction device that implements the functions specified in Figure 1 one or more of the flows Figure 1The functions specified in one or more boxes.

[0111] These computer program instructions can also be loaded onto a computer or other programmable data processing device, so that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process. Thus, the instructions executed on the computer or other programmable device provide for implementing steps for the functions specified in one Figure 1 One process or more processes and / or boxes Figure 1 The steps of the functions specified in one or more boxes.

[0112] It should also be noted that the term "comprising", "including" or any other variant thereof is intended to cover non-exclusive inclusion, such that a process, method, commodity or device comprising a series of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, commodity or device. Without further limitation, an element defined by the statement "comprising one..." does not exclude the presence of additional identical elements in the process, method, commodity or device comprising the said element.

[0113] Each embodiment in this specification is described in a progressive manner. For the same or similar parts among the embodiments, reference can be made to each other. Each embodiment focuses on the differences from other embodiments. In particular, for the system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can refer to the partial description of the method embodiment.

[0114] The above are only the embodiments of the present application and are not used to limit the present application. For those skilled in the art, various changes and modifications can be made to the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included within the scope of the claims of the present application.

[0115] Although the embodiments of the present application are described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the present application, and such modifications and variations fall within the scope defined by the appended claims.

Claims

1. A method for processing drainage test data, characterized in that, The method includes: Obtaining target drainage test data of a preset drainage fluid; wherein, the target drainage test data includes drainage data to be processed and a plurality of drainage condition data corresponding to the drainage data to be processed; When the drainage data to be processed meets the preset data error condition, predicting the drainage capacity of the preset drainage fluid based on the drainage data to be processed to obtain the drainage capacity data of the preset drainage fluid; Constructing a drainage capacity model of the preset drainage fluid according to the drainage capacity data and the plurality of drainage condition data; wherein, the drainage capacity model is used to describe the drainage capacity data of the preset drainage fluid under target drainage conditions, and the target drainage conditions correspond to any one of the plurality of drainage condition data.

2. The method according to claim 1, wherein The constructing a drainage capacity model of the preset drainage fluid according to the drainage capacity data and the plurality of drainage condition data includes: Performing a correlation analysis on the plurality of drainage condition data, and determining a corresponding data fitting model according to the correlation between the plurality of drainage condition data; Performing an optimal fitting times analysis on the data fitting model according to the target drainage test data to obtain a target fitting times; fitting the drainage capacity data and the plurality of drainage condition data according to the target fitting times and the data fitting model to obtain the drainage capacity model.

3. The method according to claim 2, wherein The performing an optimal fitting times analysis on the data fitting model according to the target drainage test data to obtain a target fitting times includes: Performing a training fit on the target drainage test data as training data according to an initial fitting times and the data fitting model to obtain an initial fitting model; Performing an error analysis on the initial fitting model by using the target drainage test data as test data, and updating the initial fitting times according to the error analysis result; Repeating the above steps of performing a training fit on the target drainage test data and updating the initial fitting times until the error analysis result meets the preset model error condition, and taking the initial fitting times at this time as the target fitting times.

4. The method according to claim 1, wherein The drainage data to be processed includes a plurality of simulated drainage data; the following method is used to determine whether the drainage data to be processed meets the preset data error condition: Performing an error analysis on any two simulated drainage data to obtain a drainage data error; When all the drainage data errors exceed the data error threshold, determining that the drainage data to be processed does not meet the preset data error condition; When any one of the drainage data errors does not exceed the data error threshold, determining that the drainage data to be processed meets the preset data error condition.

5. The method according to claim 4, characterized in that, The predicting the drainage capacity of the preset drainage fluid based on the drainage data to be processed includes: Determining valid test data according to the numerical relationship between the drainage data error and the data error threshold; wherein, the valid test data is the simulated drainage data corresponding to the drainage data error that does not exceed the data error threshold; Performing a drainage total amount mean analysis according to the valid test data to obtain the drainage capacity data.

6. The method according to any one of claims 1 to 5, characterized in that, Obtaining the target drainage test data of the preset drainage fluid includes: Obtaining the initial drainage test data of the preset drainage fluid under the target drainage conditions; Performing data synchronization preprocessing on the initial drainage test data to obtain the target drainage test data.

7. The method according to claim 6, wherein The initial drainage test data corresponds to a trigger timestamp indicating the data generation time and a reception timestamp indicating the data reception time, and the acquisition process of the initial drainage test data corresponds to a response delay and a communication delay; performing data synchronization preprocessing on the initial drainage test data to obtain the target drainage test data includes: Summing the response delay and the communication delay to obtain a total delay; Performing delay compensation on the reception timestamp of the initial drainage test data according to the total delay so that the reception timestamp is consistent with the trigger timestamp to obtain the target drainage test data.

8. A drainage test data processing device, characterized in that, The device includes: A drainage data test module for obtaining the target drainage test data of the preset drainage fluid; wherein, the target drainage test data includes the drainage data to be processed and a plurality of drainage condition data corresponding to the drainage data to be processed; A drainage capacity prediction module for predicting the drainage capacity of the preset drainage fluid based on the drainage data to be processed when the drainage data to be processed meets the preset data error condition to obtain the drainage capacity data of the preset drainage fluid; A capacity model fitting module for constructing a drainage capacity model of the preset drainage fluid according to the drainage capacity data and the plurality of drainage condition data; wherein, the drainage capacity model is used to describe the drainage capacity data of the preset drainage fluid under the target drainage conditions; the target drainage conditions correspond to any one of the plurality of drainage condition data.

9. A computer device, characterized in that, Includes: A memory and a processor, which are communicatively connected to each other. The memory stores computer instructions, and the processor executes the computer instructions to execute the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, Computer instructions are stored on the computer-readable storage medium, and the computer instructions are used to cause a computer to execute the method according to any one of claims 1 to 7.

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