Flow field distribution measurement method and device, electronic equipment and storage medium

Abstract

The invention discloses a flow field distribution measurement method and device, electronic equipment and a storage medium, and relates to a flow field measurement technology, and the method comprises the steps: determining the total uncertainty of a flow field distribution measurement system according to an initial uncertainty component corresponding to each measurement unit group; establishing an objective function based on the total uncertainty, and establishing at least one constraint condition according to the measurement characteristics corresponding to each measurement unit group; determining a target uncertainty component corresponding to each measurement unit group based on a preset optimization algorithm, a target function, at least one constraint condition and the initial uncertainty component corresponding to each measurement unit group, and controlling the corresponding measurement unit group to perform flow field distribution measurement based on the target uncertainty component corresponding to each measurement unit group. On the basis of improving the multi-phase flow parameter measurement accuracy according to the target uncertainty component, automation and intelligence of the measurement process are realized, and the measurement efficiency is improved.

Description

Technical Field

[0001] The present application relates to the field of flow field measurement technology, and in particular to a flow field distribution measurement method, device, electronic equipment and storage medium. Background Art

[0002] In the field of multiphase flow field distribution measurement, accurate measurement of each phase flow parameter is critical to optimizing process flow, improving equipment efficiency, and ensuring safe system operation. When measuring the same flow field by different research teams or under different experimental conditions, the measurement results may be different due to differences in measurement methods, measurement equipment, and measurement environment. Uncertainty provides a unified standard for comparing these different measurement results. Only by clarifying the uncertainty of each measurement result can we accurately judge whether the difference between different measurements is due to changes in the real flow field or is simply caused by the uncertainty of the measurement itself, thereby achieving effective result comparison and improvement.

[0003] Therefore, in the actual measurement process, how to achieve accurate measurement of each phase flow parameter based on the uncertainty in the measurement system is a key issue that needs to be solved urgently. Summary of the invention

[0004] The present application provides a flow field distribution measurement method, device, electronic equipment and storage medium, which can improve the measurement accuracy of multiphase flow parameters.

[0005] In a first aspect, the present application provides a flow field distribution measurement method, which is applied to a flow field distribution measurement system, wherein the system includes a plurality of measurement unit groups, and the method includes:

[0006] Determine the total uncertainty of the flow field distribution measurement system according to the initial uncertainty components corresponding to each of the measurement unit groups;

[0007] Establishing an objective function based on the total uncertainty, and establishing at least one constraint condition according to the measurement characteristics corresponding to each of the measurement unit groups;

[0008] Based on the preset optimization algorithm, the objective function, at least one constraint condition and the initial uncertainty component corresponding to each measurement unit group, the target uncertainty component corresponding to each measurement unit group is determined, so as to control the corresponding measurement unit group to perform flow field distribution measurement based on the target uncertainty component corresponding to each measurement unit group.

[0009] In a second aspect, the present application provides a flow field distribution measurement device, the device comprising:

[0010] Integrated in a flow field distribution measurement system, the system includes a plurality of measurement unit groups, the device includes:

[0011] A first determination module, used to determine the total uncertainty of the flow field distribution measurement system according to the initial uncertainty components corresponding to each of the measurement unit groups;

[0012] A function establishment module, used to establish an objective function based on the total uncertainty, and to establish at least one constraint condition according to the measurement characteristics corresponding to each of the measurement unit groups;

[0013] The second determination module is used to determine the target uncertainty component corresponding to each measurement unit group based on a preset optimization algorithm, the objective function, at least one constraint condition and the initial uncertainty component corresponding to each measurement unit group, so as to control the corresponding measurement unit group to perform flow field distribution measurement based on the target uncertainty component corresponding to each measurement unit group.

[0014] In a third aspect, the present application further provides an electronic device, the electronic device comprising:

[0015] at least one processor; and

[0016] a memory communicatively connected to the at least one processor; wherein,

[0017] The memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the flow field distribution measurement method described in any embodiment of the present application.

[0018] In a fourth aspect, the present application further provides a computer-readable storage medium, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the flow field distribution measurement method described in any embodiment of the present application when executed.

[0019] In a fifth aspect, the present application also provides a computer program product, including a computer program, which, when executed by a processor, implements the flow field distribution measurement method described in any embodiment of the present application.

[0020] The embodiment of the present invention provides a flow field distribution measurement scheme, which is applied to a flow field distribution measurement system. The flow field distribution measurement system includes multiple measurement unit groups. The scheme first determines the total uncertainty of the flow field distribution measurement system according to the initial uncertainty components corresponding to each measurement unit group, so as to establish an objective function through the total uncertainty, and establish at least one constraint condition through the measurement characteristics corresponding to each measurement unit group. This method helps to optimize the measurement process in the subsequent process to ensure that the measurement results meet the predetermined accuracy requirements; further, the scheme adopts a preset optimization algorithm, combined with the objective function, the constraint conditions and the initial uncertainty components corresponding to each measurement unit group, to determine the target uncertainty components corresponding to each measurement unit group, so that each measurement unit group can perform flow field distribution measurement according to the target uncertainty components. The scheme provided by this embodiment, on the basis of improving the accuracy of multiphase flow parameter measurement according to the target uncertainty components, realizes the automation and intelligence of the measurement process at the same time, and achieves the beneficial effect of improving measurement efficiency.

[0021] It should be noted that the above computer instructions may be stored in whole or in part on a computer-readable storage medium, wherein the computer-readable storage medium may be packaged together with the processor of the flow field distribution measurement device, or may be packaged separately from the processor of the flow field distribution measurement device, and this application does not limit this.

[0022] The description of the second, third, fourth and fifth aspects of the present application can refer to the detailed description of the first aspect; and the beneficial effects of the description of the second, third, fourth and fifth aspects can refer to the beneficial effect analysis of the first aspect, which will not be repeated here.

[0023] It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present application, nor is it intended to limit the scope of the present application. Other features of the present application will become easily understood through the following description.

[0024] It is understandable that before using the technical solutions disclosed in the embodiments of this application, the type, scope of use, and usage scenarios of the personal information involved in this application should be informed to the user and the user's authorization should be obtained in an appropriate manner in accordance with relevant laws and regulations. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the embodiments will be briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0026] Figure 1 It is a flow chart of the flow field distribution measurement method provided in the embodiment of the present application;

[0027] Figure 2 is a structural schematic diagram of a flow field distribution measurement system provided in an embodiment of the present application;

[0028] Figure 3 is a structural schematic diagram of a flow field distribution measurement device provided in an embodiment of the present application;

[0029] Figure 4 It is a structural schematic diagram of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0030] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the present application will be clearly and completely described below in conjunction with the drawings in the present embodiment. Obviously, the described embodiment is only a part of the embodiment of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in the field without creative work should fall within the scope of protection of the present application.

[0031] It should be noted that the terms "target", "initial", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0032] The present application will be further described in detail below in conjunction with the accompanying drawings and embodiments. It is to be understood that the specific embodiments described herein are only used to explain the present application, rather than to limit the present application. It should also be noted that, for ease of description, only the parts related to the present application, rather than all structures, are shown in the accompanying drawings.

[0033] Figure 1A flow chart of a flow field distribution measurement method provided in an embodiment of the present application. This embodiment is applicable to the case where a flow field distribution measurement system is used to accurately measure the flow field distribution of a multiphase flow. The method can be performed by a flow field distribution measurement device, which can be implemented in the form of hardware and / or software and integrated in an electronic device that performs the method. Preferably, the electronic device in the embodiment of the present application can be a computer device integrated in the flow field distribution measurement system.

[0034] Specifically, before introducing the solution provided by this embodiment, the flow field distribution measurement system is introduced in advance. The flow field distribution measurement system provided by this embodiment includes multiple measurement unit groups. Among them, the measurement unit group represents the measurement equipment used in different fluid measurement scenarios, etc., so that the weight or flow rate of the corresponding fluid state recorded by each measurement unit group is sent to the computer device, so that the computer device performs operations such as calculation of the flow field distribution according to the received relevant parameters. Exemplarily, the multiple measurement unit groups may include a camera unit group, a particle spreading unit group, and a lighting unit group, etc. The composition of the multiple measurement unit groups in the specific flow field distribution measurement system shall be based on the actual measurement requirements.

[0035] For a preferred embodiment, please refer to Figure 2 , Figure 2 1 is a schematic diagram of a flow field distribution measurement system provided by an embodiment of the present application. In the example in the figure, at least two measurement unit groups include: an electronic balance measurement unit group, a mass flow meter measurement unit group, a thermal mass flow meter measurement unit group, an ultrasonic flow meter measurement unit group, a high-speed camera measurement unit group, and a laser measurement unit group.

[0036] Among them, the electronic balance measurement unit group may include tracer particles and an electronic balance, and the electronic balance is used to measure the solid of preset weight (such as tracer particles) entering the flow field; the mass flowmeter measurement unit group may include a liquid container and a liquid flowmeter, and the liquid flowmeter is used to measure the liquid flow rate flowing out of the liquid container; the thermal mass flowmeter measurement unit group may include a gas container and a thermal mass flowmeter, and the thermal mass flowmeter is used to measure the amount of gas flowing out of the side gas container, etc.; the ultrasonic flowmeter measurement unit group may be an ultrasonic flowmeter, which is used to measure the liquid flow currently flowing through the tank channel; the high-speed camera measurement unit group may include a high-speed camera, a guide rail, and a fixed column for fixing the camera, etc.; the high-speed camera is used to shoot the flow field distribution of the transparent pipe based on a certain slicing rate and exposure time; the laser measurement unit group may include a laser and a lifting platform, and the laser is used to emit a certain intensity of light beam to the transparent tank channel, etc. Based on the flow field distribution measurement system provided in this embodiment, the uncertainty corresponding to each measurement unit can be analyzed, thereby improving the accuracy of the flow field measurement corresponding to each measurement unit. Furthermore, this embodiment provides a standard device for measuring the flow velocity distribution of multiphase flow, so that the standard device provided by this embodiment is applicable to application scenarios of various types of flow field distribution measurements, without the need to improve the device according to the different measured fluids, thereby improving the universality of the device.

[0037] refer to Figure 1 The flow field distribution measurement method of this embodiment includes but is not limited to the following steps:

[0038] S110, determining the total uncertainty of the flow field distribution measurement system according to the initial uncertainty components corresponding to each measurement unit group.

[0039] The uncertainty of flow field distribution measurement can quantify the reliability of the measurement results. It reflects the possible deviation range between the measured value and the actual flow field distribution. By determining the uncertainty, we can know the accuracy of the obtained flow field distribution parameters (such as velocity, pressure, temperature, etc.), so as to judge whether the measurement results are sufficient to meet specific scientific research, engineering or other application requirements. For example, we can select appropriate measuring instruments, determine the number and distribution of measurement points, etc. according to the expected uncertainty requirements. In the subsequent experimental process, we can also adjust and optimize the experimental settings according to the uncertainty analysis results to improve the measurement quality.

[0040] The initial uncertainty components corresponding to each measurement unit group are related to the uncertainty sources corresponding to each measurement unit. For example, the initial uncertainty of the electronic balance measurement unit is related to the instrument accuracy (accuracy indicators given in the manual, such as the minimum graduation value, maximum allowable error, etc.), calibration error and environmental factors, so the initial uncertainty of the electronic balance measurement unit can be determined according to each uncertainty source.

[0041] In this embodiment, taking n measurement unit groups as an example, the initial uncertainty component corresponding to each measurement unit group can be expressed as U i (i=1, 2, 3…, n). When the total uncertainty is represented based on U, the total uncertainty of the flow field distribution measurement system can be expressed as follows based on the initial uncertainty components corresponding to each measurement unit group:

[0042]

[0043] A preferred embodiment, the solution provided in this embodiment, the above step S110 can be implemented in the following way: obtain the influencing factors corresponding to each measurement unit group, and determine the corresponding initial uncertainty components according to the influencing factors; determine the total uncertainty of the flow field distribution measurement system according to the initial uncertainty components corresponding to each measurement unit group.

[0044] Specifically, the influencing factors corresponding to each measurement unit group are related to the actual equipment setting accuracy, calibration uncertainty and environmental factors.

[0045] For example, taking the measurement unit group as an electronic balance measurement unit group, assuming that the setting accuracy of the electronic balance is ±a (a is the specific value in the equipment manual). Assuming that the measured values ​​are uniformly distributed within the accuracy range, the method of determining the corresponding initial uncertainty components according to the influencing factors can be: If the electronic balance has been calibrated, the equipment manual will give the calibration uncertainty u 校准 , this value can be directly used as the uncertainty component caused by the calibration process; if the electronic balance is affected by temperature, assuming that it is known through experiments or experience that the deviation of the electronic balance measurement value is b (unit: g / ℃) for every 1℃ change in temperature, in a certain measurement process, the temperature fluctuation range is ±c℃, and assuming that the temperature change is uniformly distributed within this range, then the standard uncertainty temperature caused by temperature is (Unit: grams). Then, in the electronic balance measurement unit group, the method of determining the corresponding initial uncertainty component according to the influencing factors can be:

[0046] For other measurement unit groups, such as the mass flow meter measurement unit group, the corresponding influencing factors may include flow meter accuracy, particle concentration and ambient temperature, etc.; for the ultrasonic flow meter measurement unit group, the corresponding influencing factors may include ultrasonic flow meter accuracy, calibration degree and ambient temperature; for the high-speed camera measurement unit group, the corresponding influencing factors may include camera resolution, camera exposure time, camera fixing method and camera fixing height, etc.; for the laser measurement unit group, the corresponding influencing factors may include laser brightness and laser setting height, etc.; the specific influencing factors corresponding to each measurement unit group are not limited to the current examples, and are subject to actual analysis.

[0047] For each measurement unit group listed above, the above steps are also followed to first analyze the influencing factors of each measurement unit group, and then determine the corresponding initial uncertainty components based on the standard uncertainty components corresponding to each influencing factor. The specific method of determining the initial uncertainty components for each measurement unit is not exemplified here one by one.

[0048] After further obtaining the initial uncertainty components corresponding to each measurement unit group, the total uncertainty of the flow field distribution measurement system can be obtained based on the above formula (1). The advantage of determining the total uncertainty provided by this embodiment is that the influence of the corresponding uncertainty of each measurement unit is fully considered, so that the evaluation result is more in line with the actual situation. It is of great significance to improve the measurement accuracy of each phase flow parameter in the subsequent steps.

[0049] S120: Establish an objective function based on the total uncertainty, and establish at least one constraint condition according to the measurement characteristics corresponding to each measurement unit group.

[0050] In this embodiment, the objective function is constructed with the goal of minimizing the total uncertainty, which can be specifically expressed as the following formula:

[0051]

[0052] Among them, f(U) min represents the objective function, U represents the total uncertainty, u 1 ,u 2 ,u 3 ,…,u n Respectively represent the uncertainty components corresponding to each of the measurement unit groups.

[0053] When at least one constraint condition is established according to the measurement characteristics corresponding to each measurement unit group, the current measurement characteristics may include the equipment characteristics, cost characteristics, time characteristics, etc. corresponding to each measurement unit group.

[0054] Preferably, the device characteristics may include upper and lower limit values ​​corresponding to the device accuracy; wherein the current device accuracy is determined according to the actual measurement conditions of the device. For example, the device characteristics corresponding to the electronic balance may include upper and lower limit values ​​for accuracy, upper and lower limit values ​​for mass, and upper and lower limit values ​​for temperature and humidity, etc.; the device characteristics corresponding to the mass flow meter may include upper and lower limit values ​​for accuracy, upper and lower limit values ​​for measurement range, upper and lower limit values ​​for density, and upper and lower limit values ​​corresponding to installation position and angle deviation, etc.

[0055] Preferably, in this embodiment, the method of establishing at least one constraint condition according to the measurement characteristics corresponding to each measurement unit group can be implemented by the following steps a) to c):

[0056] a) Determine the equipment performance constraints according to the equipment characteristics corresponding to each measurement unit group.

[0057] In this embodiment, the device performance constraint conditions are determined by taking the device characteristics corresponding to the electronic balance measurement unit group and the mass flow meter measurement unit group as an example, which may include the following:

[0058] Electronic balance measurement unit group: upper and lower limits of balance accuracy constraints P 天平min <u 天平 ≤P 天平max ; Upper and lower limits of solid mass measured by electronic balance m 天平min <m≤m 天平max ; Environmental conditions impose upper and lower limits on the electronic balance, such as temperature T 天平min <T≤T 天平max , humidity H 天平min <H≤H 天平max . Mass flow meter measurement unit group: flow meter accuracy upper and lower limits q 流量计min <u 流量计 ≤q 流量计max ; Flow meter measurement range constraint Q 流量计min <Q≤Q 流量计max ; Installation position constraint Δx 流量计max ≤Δx<0; installation angle constraint Δθ 流量计max ≤Δθ<0, etc.

[0059] b) Determine the cost constraint conditions according to the design cost corresponding to each measurement unit group.

[0060] When considering adjusting each measurement unit group, there may be budget constraints and high-precision equipment cannot be replaced indefinitely. Assume that the cost corresponding to each measurement unit group is C 1 , C 2 , C 3 ,…,C n , under a total cost budget cap C max, then the cost constraint can be expressed as: C 1 +C 2 +C 3 +C n …≤C max .

[0061] c) Determine the time constraint condition according to the measurement time corresponding to each measurement unit group.

[0062] In terms of time, it may be required to complete the measurement and adjustment within a certain period of time. Then, the time required to adjust each measurement unit group can be set as T 1 , T 2 , CT 3 ,…,T n , there is a total time upper limit T max , then the time constraint can be expressed as T 1 +T 2 +T 3 +T n …≤T max .

[0063] This embodiment helps to improve measurement accuracy by determining device performance constraints for device characteristics corresponding to each measurement unit group; by considering cost constraints, it can ensure the rational use of resources, reduce measurement costs, and improve economic benefits; by establishing time constraints, it can ensure the smooth progress of the measurement process, shorten the measurement cycle, and improve measurement efficiency.

[0064] S130. Determine the target uncertainty component corresponding to each measurement unit group based on a preset optimization algorithm, an objective function, at least one constraint condition, and the initial uncertainty component corresponding to each measurement unit group, so as to control the corresponding measurement unit group to perform flow field distribution measurement based on the target uncertainty component corresponding to each measurement unit group.

[0065] In this embodiment, the preset optimization algorithm can be selected according to the relationship between each uncertainty component and the total uncertainty component. That is, if each uncertainty component is caused by independent factors, and the influence of these factors on the total uncertainty is linearly superimposed, then the uncertainty component and the total uncertainty can be a linear relationship, and the preset optimization algorithm can be implemented based on a linear optimization algorithm, such as the simplex method. It can efficiently find the optimal solution for the objective function under the condition of satisfying linear constraints; if there is a correlation between the uncertainty components, and the uncertainty components and the total uncertainty are nonlinear, then it can be implemented based on a nonlinear optimization algorithm, such as the sequential quadratic programming (SQP) algorithm, the interior point method, etc. These algorithms gradually approach the optimal solution through iteration, and can better handle nonlinear problems.

[0066] Then, in this embodiment, according to the rules of the optimization algorithm, the uncertainty components of each measurement unit group are updated. For example: in the genetic algorithm, new individuals (i.e., new uncertainty component combinations) are generated through selection, crossover and mutation operations. Specifically, individuals with high fitness values ​​(fitness values ​​are usually related to the objective function value, such as for minimizing the objective function, the fitness value can be set to the inverse of the objective function value) are selected as the parent generation, and then crossover and mutation operations are performed to generate new offspring individuals, which are the updated uncertainty component combinations. In the nonlinear programming algorithm, the search direction and step length are determined according to information such as the gradient of the objective function and the Hessian matrix, and then the uncertainty components are updated. For example, using the gradient information of the current solution, a certain step length is moved in the direction that makes the objective function value decrease, and the updated uncertainty component value is obtained.

[0067] Specifically, in the solution provided by this embodiment, the above step S130 of determining the target uncertainty component corresponding to each measurement unit group can be implemented in the following manner:

[0068] Under at least one constraint condition, the objective function is solved according to the initial uncertainty components corresponding to each measurement unit group; whether the function value corresponding to the objective function satisfies the preset convergence condition is determined; if the preset convergence condition is satisfied, the initial uncertainty components corresponding to each measurement unit group are determined as the target uncertainty components; if the preset convergence condition is not satisfied, the initial uncertainty components corresponding to each measurement unit group are iteratively updated based on the preset optimization algorithm until the objective function reaches the preset convergence condition, and the target uncertainty components corresponding to at least two measurement unit groups are obtained.

[0069] When the initial uncertainty components of each measurement unit group are substituted into the objective function and the value of the objective function is calculated, the calculation of the objective function should take into account all measurement unit groups and constraints to ensure that the result is the optimal solution under the constraints; the value of the objective function is compared with the preset convergence condition. When the objective function reaches the preset convergence condition, the iterative update is stopped. At this time, the uncertainty components of each measurement unit group are the target uncertainty components. These target uncertainty components are the optimal solutions under the constraints and can provide more accurate uncertainty assessment for the measurement process.

[0070] In another preferred embodiment, when the above step d is iteratively updated, the preset convergence conditions include: the change in the objective function value is less than a first preset threshold, or the objective function value reaches a second preset threshold, or the number of iterations reaches a preset number.

[0071] Specifically, in a number of consecutive iterations, the change in the objective function (total uncertainty) is very small, less than the preset first preset threshold δ, δ is a very small positive number, which represents the tolerance for changes in the objective function value. This means that in the current iteration, the improvement in total uncertainty is already very small, and it can be considered that the algorithm has converged to a better solution; the above-mentioned second preset threshold is a preset specific target value, and the algorithm stops when the total uncertainty is expected to be reduced to a specific value; optionally, a maximum number of iterations is preset. When the number of iterations executed by the algorithm reaches this value, the algorithm stops regardless of whether it converges or not. This is suitable for situations where there are strict restrictions on computing resources and time. For example, if the algorithm has not converged after iterations, but cannot continue due to time or resource constraints, the algorithm can be stopped and the current solution can be accepted as the final result.

[0072] The flow field distribution measurement method provided in this embodiment is applied to a flow field distribution measurement system, in which a plurality of measurement unit groups are included. This scheme first determines the total uncertainty of the flow field distribution measurement system according to the initial uncertainty components corresponding to each measurement unit group, so as to establish an objective function through the total uncertainty, and establish at least one constraint condition through the measurement characteristics corresponding to each measurement unit group. This method is helpful in optimizing the measurement process in the subsequent process to ensure that the measurement results meet the predetermined accuracy requirements; further, this scheme adopts a preset optimization algorithm, combined with the objective function, the constraint conditions and the initial uncertainty components corresponding to each measurement unit group, to determine the target uncertainty components corresponding to each measurement unit group, so that each measurement unit group can perform flow field distribution measurement according to the target uncertainty components. The scheme provided in this embodiment, on the basis of improving the accuracy of multiphase flow parameter measurement according to the target uncertainty components, realizes the automation and intelligence of the measurement process at the same time, and achieves the beneficial effect of improving measurement efficiency.

[0073] Figure 3 Schematic diagram of a flow field distribution measurement device provided in an embodiment of the present application, which is suitable for executing the flow field distribution measurement method provided in an embodiment of the present application. Figure 3 As shown, the device can be integrated into a flow field distribution measurement system, the system includes a plurality of measurement unit groups, and the device may include: a first determination module 310, a function establishment module 320, and a second determination module 330, wherein:

[0074] A first determination module 310 is used to determine the total uncertainty of the flow field distribution measurement system according to the initial uncertainty components corresponding to each of the measurement unit groups;

[0075] A function establishment module 320, configured to establish an objective function based on the total uncertainty, and to establish at least one constraint condition according to the measurement characteristics corresponding to each of the measurement unit groups;

[0076] The second determination module 330 is used to determine the target uncertainty component corresponding to each measurement unit group based on a preset optimization algorithm, the objective function, at least one constraint condition and the initial uncertainty component corresponding to each measurement unit group, so as to control the corresponding measurement unit group to perform flow field distribution measurement based on the target uncertainty component corresponding to each measurement unit group.

[0077] The flow field distribution measurement device provided in this embodiment is applied to the flow field distribution measurement system, which includes multiple measurement unit groups. This scheme first determines the total uncertainty of the flow field distribution measurement system according to the initial uncertainty components corresponding to each measurement unit group, so as to establish the objective function through the total uncertainty, and establish at least one constraint condition through the measurement characteristics corresponding to each measurement unit group. This method is helpful in optimizing the measurement process in the future to ensure that the measurement results meet the predetermined accuracy requirements; further, this scheme adopts a preset optimization algorithm, combined with the objective function, constraint conditions and the initial uncertainty components corresponding to each measurement unit group, to determine the target uncertainty components corresponding to each measurement unit group, so that each measurement unit group can perform flow field distribution measurement according to the target uncertainty components. The scheme provided in this embodiment, on the basis of improving the accuracy of multiphase flow parameter measurement according to the target uncertainty components, realizes the automation and intelligence of the measurement process at the same time, and achieves the beneficial effect of improving measurement efficiency.

[0078] In one embodiment, the first determination module 310 is specifically used to obtain the influencing factors corresponding to each of the measurement unit groups, determine the corresponding initial uncertainty components according to the influencing factors; and determine the total uncertainty of the flow field distribution measurement system according to the initial uncertainty components corresponding to each of the measurement unit groups.

[0079] In one embodiment, the function establishment module 320 is specifically used to determine the equipment performance constraint conditions according to the equipment characteristics corresponding to each of the measurement unit groups; determine the cost constraint conditions according to the design cost corresponding to each of the measurement unit groups; and determine the time constraint conditions according to the measurement time corresponding to each of the measurement unit groups.

[0080] In one embodiment, the second determination module 330 is specifically used to solve the objective function according to the initial uncertainty components corresponding to each of the measurement unit groups under at least one of the constraints; determine whether the function value corresponding to the objective function satisfies a preset convergence condition; if the preset convergence condition is satisfied, determine the initial uncertainty components corresponding to each of the measurement unit groups as the target uncertainty components; if the preset convergence condition is not satisfied, iteratively update the initial uncertainty components corresponding to each measurement unit group based on the preset optimization algorithm until the objective function reaches the preset convergence condition, and obtain the target uncertainty components corresponding to at least two measurement unit groups.

[0081] In one embodiment, the preset convergence condition includes: the change in the objective function value is less than a first preset threshold, or the objective function value reaches a second preset threshold, or the number of iterations reaches a preset number.

[0082] In one embodiment, at least two of the measurement unit groups include: an electronic balance measurement unit group, a mass flow meter measurement unit group, a thermal mass flow meter measurement unit group, an ultrasonic flow meter measurement unit group, a high-speed camera measurement unit group and a laser measurement unit group.

[0083] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional modules is used as an example for illustration. In actual applications, the above-mentioned functions can be assigned to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. The specific working process of the functional modules described above can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0084] An embodiment of the present application also provides an electronic device, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the flow field distribution measurement method described in any embodiment of the present application.

[0085] An embodiment of the present application further provides a computer-readable medium, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the flow field distribution measurement method described in any embodiment of the present application when executed.

[0086] Reference below Figure 4 , Figure 41 is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application, and shows a schematic diagram of the structure of a computer system 500 suitable for implementing the electronic device in an embodiment of the present application. Figure 4 The electronic device shown is merely an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0087] like Figure 4 As shown, the computer system 500 includes a central processing unit (CPU) 501, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 502 or a program loaded from a storage part 508 into a random access memory (RAM) 503. In the RAM 503, various programs and data required for the operation of the system 500 are also stored. The CPU 501, the ROM 502, and the RAM 503 are connected to each other via a bus 504. An input / output (I / O) interface 505 is also connected to the bus 504.

[0088] The following components are connected to the I / O interface 505: an input section 506 including a keyboard, a mouse, etc.; an output section 507 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 508 including a hard disk, etc.; and a communication section 509 including a network interface card such as a LAN card, a modem, etc. The communication section 509 performs communication processing via a network such as the Internet. A drive 510 is also connected to the I / O interface 505 as needed. A removable medium 511, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 510 as needed, so that a computer program read therefrom is installed into the storage section 508 as needed.

[0089] In particular, according to the embodiments disclosed in the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, the embodiments disclosed in the present application include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from the network through the communication part 509, and / or installed from the removable medium 511. When the computer program is executed by the central processing unit (CPU) 501, the above-mentioned functions defined in the system of the present application are executed.

[0090] It should be noted that the computer-readable medium shown in the present application may be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present application, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, device or device. In the present application, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, which carries a computer-readable program code. This propagated data signal may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. The computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium, which may send, propagate or transmit a program for use by or in conjunction with an instruction execution system, apparatus or device. The program code contained on the computer-readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, optical cable, etc., or any suitable combination of the above.

[0091] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present application. In this regard, each box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the above-mentioned module, program segment or a part of a code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flow chart, and the combination of the boxes in the block diagram or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0092] The modules and / or units involved in the embodiments described in the present application may be implemented by software or hardware. The modules and / or units described may also be set in a processor, for example, it may be described as: a processor includes a first determination module, a function establishment module, and a second determination module. The names of these modules do not constitute a limitation on the modules themselves in some cases.

[0093] As another aspect, the present application also provides a computer-readable medium, which may be included in the device described in the above embodiment; or it may exist independently and not be assembled into the device. The above computer-readable medium carries one or more programs. When the above one or more programs are executed by a device, the device includes: determining the total uncertainty of the flow field distribution measurement system according to the initial uncertainty components corresponding to each of the measurement unit groups; establishing an objective function based on the total uncertainty, and establishing at least one constraint condition according to the measurement characteristics corresponding to each of the measurement unit groups; determining the target uncertainty component corresponding to each of the measurement unit groups based on the preset optimization algorithm, the objective function, at least one constraint condition and the initial uncertainty component corresponding to each of the measurement unit groups, so as to control the corresponding measurement unit group to perform flow field distribution measurement based on the target uncertainty component corresponding to each of the measurement unit groups. .

[0094] According to the technical solution of this embodiment, the target uncertainty component corresponding to each measurement unit group is determined in combination with the objective function, the constraint conditions and the initial uncertainty component corresponding to each measurement unit group, so that each measurement unit group can perform flow field distribution measurement according to the target uncertainty component. The solution provided by this embodiment, on the basis of improving the accuracy of multiphase flow parameter measurement according to the target uncertainty component, realizes the automation and intelligence of the measurement process at the same time, and achieves the beneficial effect of improving measurement efficiency.

[0095] The above specific implementations do not constitute a limitation on the protection scope of this application. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions may occur depending on design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of this application should be included in the protection scope of this application.

Claims

1. A flow field distribution measurement method, characterized in that: Applied to a flow field distribution measurement system, the system includes a plurality of measurement unit groups, and the method includes: Determine the total uncertainty of the flow field distribution measurement system according to the initial uncertainty components corresponding to each of the measurement unit groups; Establishing an objective function based on the total uncertainty, and establishing at least one constraint condition according to the measurement characteristics corresponding to each of the measurement unit groups; Based on the preset optimization algorithm, the objective function, at least one constraint condition and the initial uncertainty component corresponding to each measurement unit group, the target uncertainty component corresponding to each measurement unit group is determined, so as to control the corresponding measurement unit group to perform flow field distribution measurement based on the target uncertainty component corresponding to each measurement unit group.

2. The flow field distribution measurement method according to claim 1, characterized in that: Determining the total uncertainty of the flow field distribution measurement system according to the initial uncertainty components corresponding to each of the measurement unit groups includes: Obtaining the influencing factors corresponding to each of the measurement unit groups, and determining the corresponding initial uncertainty components according to the influencing factors; The total uncertainty of the flow field distribution measurement system is determined according to the initial uncertainty components corresponding to each of the measurement unit groups.

3. The flow field distribution measurement method according to claim 1, characterized in that: The establishing of an objective function based on the total uncertainty comprises: Among them, f(U) min represents the objective function, U represents the total uncertainty, u1, u2, u3, …, u n Respectively represent the uncertainty components corresponding to each of the measurement unit groups.

4. The flow field distribution measurement method according to claim 1, characterized in that: The establishing of at least one constraint condition according to the measurement characteristics respectively corresponding to each of the measurement unit groups comprises: Determine device performance constraints according to device characteristics corresponding to each of the measurement unit groups; Determining a cost constraint condition according to the design cost corresponding to each of the measurement unit groups; The time constraint condition is determined according to the measurement time corresponding to each of the measurement unit groups.

5. The flow field distribution measurement method according to claim 1, characterized in that: The determining of the target uncertainty component corresponding to each of the measurement unit groups based on the preset optimization algorithm, the objective function, at least one of the constraints, and the initial uncertainty component corresponding to each of the measurement unit groups comprises: Solving the objective function according to the initial uncertainty components corresponding to each of the measurement unit groups under at least one of the constraints; Determining whether the function value corresponding to the objective function satisfies a preset convergence condition; If the preset convergence condition is met, determining the initial uncertainty component corresponding to each of the measurement unit groups as the target uncertainty component; If the preset convergence condition is not met, the initial uncertainty components corresponding to each measurement unit group are iteratively updated based on the preset optimization algorithm until the objective function reaches the preset convergence condition, thereby obtaining target uncertainty components corresponding to at least two measurement unit groups.

6. The flow field distribution measurement method according to claim 5, characterized in that: The preset convergence condition includes: the change amount of the objective function value is less than a first preset threshold, or the objective function value reaches a second preset threshold, or the number of iterations reaches a preset number.

7. The flow field distribution measurement method according to claim 1, characterized in that: At least two of the measuring unit groups include: an electronic balance measuring unit group, a mass flow meter measuring unit group, a thermal mass flow meter measuring unit group, an ultrasonic flow meter measuring unit group, a high-speed camera measuring unit group and a laser measuring unit group.

8. A flow field distribution measuring device, characterized in that: Integrated in a flow field distribution measurement system, the system includes a plurality of measurement unit groups, the device includes: A first determination module, used to determine the total uncertainty of the flow field distribution measurement system according to the initial uncertainty components corresponding to each of the measurement unit groups; A function establishment module, used to establish an objective function based on the total uncertainty, and to establish at least one constraint condition according to the measurement characteristics corresponding to each of the measurement unit groups; The second determination module is used to determine the target uncertainty component corresponding to each measurement unit group based on a preset optimization algorithm, the objective function, at least one constraint condition and the initial uncertainty component corresponding to each measurement unit group, so as to control the corresponding measurement unit group to perform flow field distribution measurement based on the target uncertainty component corresponding to each measurement unit group.

9. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the flow field distribution measurement method according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the flow field distribution measurement method according to any one of claims 1 to 7 is implemented.

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