Centrifugal water pump simulation modeling method and model based on fluid network

Abstract

The invention relates to the technical field of hydraulic characteristic simulation model modeling, in particular to a centrifugal water pump simulation modeling method and model based on a fluid network. According to the centrifugal water pump simulation modeling method based on the fluid network provided by the invention, efficient processing of external characteristic parameters of the centrifugal water pump as a simulation object can be realized, and a simulation model with high accuracy and real-time performance is established based on the processed parameter data; the model precision requirements of different design and optimization stages of the centrifugal water pump are met; according to the built centrifugal water pump simulation model, when multi-working-condition operation is simulated, the flow-lift characteristic curve of the centrifugal water pump simulation model better conforms to actual pump operation characteristics, the accuracy and adaptability requirements of hydraulic characteristic simulation of the centrifugal water pump can be effectively guaranteed, and the centrifugal water pump simulation model is high in practicability, wide in application prospect and easy to popularize.

Description

Technical Field

[0001] The present invention relates to the technical field of hydraulic characteristic simulation modeling, and in particular to a centrifugal water pump simulation modeling method and model based on a fluid network. Background Art

[0002] Centrifugal water pumps are currently widely used in industrial production, thermal power generation, and marine propulsion systems. Therefore, studying centrifugal water pump models and applying them to system simulation can provide important technical support for thermal system design and verification, system characteristic research, and system optimization.

[0003] When building a hydraulic simulation model for a centrifugal water pump, it's crucial to accurately simulate the pump's operating conditions, ensuring that both the static and dynamic characteristics of the model match those of the actual equipment. Because centrifugal pump operation involves multiple fields, including fluid mechanics, thermodynamics, heat transfer, and dynamics, and involves internal physical phenomena such as flow, heat transfer, and vibration, all of which are interconnected, ensuring accurate and real-time simulation of the centrifugal water pump model presents challenges.

[0004] In the process of thermal system design, verification and optimization, it is necessary to adapt to the level of detail of the known flow and head relationship of the water pump at different stages, or to meet the accuracy of the results required at different stages. It is of great significance to develop a centrifugal water pump model that can handle various levels of flow and head relationship details, and to improve the accuracy and adaptability of simulation in the field of thermal systems. Summary of the Invention

[0005] The technical problem to be solved by the present invention is to provide a centrifugal water pump simulation modeling method and model based on fluid network, which can effectively ensure the simulation accuracy and real-time performance of the simulation model to meet the model accuracy requirements of centrifugal water pumps in different design and optimization stages.

[0006] In order to solve the above technical problems, the technical solution adopted by the present invention is: A centrifugal water pump simulation modeling method based on fluid network mainly includes the following steps: S1, based on the pump efficiency parameters obtained from the experiment, build a pump power algorithm to simulate the output power of the simulation object pump under working conditions; S2, based on the relationship between speed and pump power, builds a speed algorithm to simulate the speed of the simulation object pump under working conditions; S3, based on the pump head parameter input type, construct the corresponding head algorithm to simulate the head of the simulation object pump under the working state; S4, constructing a corresponding pump flow capacity algorithm based on the head algorithm to simulate the flow capacity of the simulation object pump under the working state; S5, based on the test data input of the water pump, construct a pump cavitation phenomenon algorithm to simulate the cavitation phenomenon of the simulation object pump under the working state; S6, encapsulates the pump power algorithm, speed algorithm, head algorithm, pump flow capacity algorithm and pump cavitation phenomenon algorithm into an overall centrifugal water pump model algorithm, and performs real-time iterative calculation based on the parameter input of the simulation object pump and the operating condition data output by the fluid network interface to obtain the pump model data under the corresponding operating conditions.

[0007] Preferably, the pump power algorithm is as follows:

[0008] Where, is the output power of the water pump; is the working power of the water pump; is the pump efficiency.

[0009] Preferably, the rotation speed algorithm is as follows:

[0010] Where, is the input power of the water pump; is the output power of the water pump; is energy loss; is the increase in kinetic energy of the pump rotor; is the time differential; The operating speed of the water pump is calculated based on the increase in the kinetic energy of the water pump rotor and the time differential, combined with the rotational inertia parameters of the water pump. .

[0011] Preferably, the lift algorithm is divided into the following types according to the lift parameter input type of the simulation object pump: closed lift algorithm, single speed second-order curve fitting algorithm, multi-speed high-order curve fitting algorithm; When the rated head and flow of the simulation object pump are known, select the closed head algorithm as follows:

[0012] Where, It is the closed head of the water pump, output to the fluid network; is the rated lift; is the pump efficiency; is the operating speed of the water pump; is the rated speed; When the flow and head performance curve of the simulation object pump at a certain speed is known, the single-speed second-order curve fitting algorithm is selected as follows:

[0013] When the flow and head performance curves of the simulation object pump at multiple speeds are known, a multi-speed high-order curve fitting algorithm is selected, as follows:

[0014] Where, It is the working head of the water pump; is the operating speed of the water pump; The flow rate for the working condition; , b, c, x, etc. are all multi-order curve coefficients; n is the order of the curve.

[0015] Preferably, the pump flow capacity algorithm is as follows:

[0016] Where, is the flow capacity of the water pump; is the rated flow of the pump; is the closed head of the water pump; It is the working head of the water pump; is the working fluid density.

[0017] Preferably, the pump cavitation phenomenon algorithm is as follows:

[0018] Where, is the pump head fluctuation coefficient under the influence of cavitation; is the closed head of the water pump; is the cavitation coefficient; is the cavitation head influence coefficient; is the number of periodic changes.

[0019] Preferably, the centrifugal water pump model algorithm includes two parts: algorithm preprocessing and working condition simulation; The algorithm preprocessing includes: taking the rated flow, rated head, rated speed, and hydraulic efficiency parameters of the simulation object pump as input, and preprocessing them through the pump power algorithm, speed algorithm, head algorithm, pump flow capacity algorithm, and pump cavitation phenomenon algorithm described in steps S1 to S5 to obtain preprocessed data of the water pump's output power, speed, head, and flow capacity.

[0020] The working condition simulation includes: combining the pre-processed data with the working condition data output by the fluid network interface, and performing real-time iterative calculation to obtain pump model data under corresponding working conditions.

[0021] Compared with the prior art, the present invention has the following main advantages: 1. The present invention provides a centrifugal water pump simulation modeling method based on a fluid network. This method can achieve efficient processing of the external characteristic parameters of the simulation object - the centrifugal water pump, and establish a highly accurate and real-time simulation model based on the processed parameter data, thereby meeting the model accuracy requirements of the centrifugal water pump at different design and optimization stages. 2. The centrifugal water pump simulation model established by the present invention has a flow-head characteristic curve that is more consistent with the actual pump operation characteristics when simulating multiple operating conditions. It can effectively ensure the accuracy and adaptability requirements of the centrifugal water pump hydraulic characteristic simulation. It has strong practicality, broad application prospects, and is easy to promote. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 This is a flow chart of the simulation modeling method in Example 1 of the present invention; Figure 2 This is a schematic diagram of introducing the pump model into the fluid network in Example 1 of the present invention; Figure 3 Schematic diagram of inputting the pump model according to the simulation object pump data in the first embodiment of the present invention; Figure 4 Schematic diagram of the real-time operation of the fluid network in Example 1 of the present invention; Figure 5 This is a schematic diagram of the construction content of the preprocessing part in the second embodiment of the present invention; Figure 6 This is a schematic diagram of the construction of the pump body in the second embodiment of the present invention; Figure 7 This is the flow-head curve in Example 2 of the present invention. DETAILED DESCRIPTION

[0023] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely for the purpose of explaining the present invention and are not intended to limit the present invention. In addition, the technical features involved in the various embodiments of the present invention described below may be combined with each other as long as they do not conflict with each other.

[0024] It should be pointed out that, according to the needs of implementation, the various steps / components described in this application can be split into more steps / components, or two or more steps / components or partial operations of steps / components can be combined into new steps / components to achieve the purpose of the present invention.

[0025] In the present invention, unless otherwise expressly specified or limited, the terms "first" and "second" are used for descriptive purposes only and should not be understood to indicate or imply relative importance or implicitly specify the number of the technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include at least one of such features. In the description of the present invention, "plurality" means at least two, for example, two, three, etc., unless otherwise expressly specified or limited.

[0026] Example 1: This embodiment provides a centrifugal water pump simulation modeling method based on fluid network, such as Figure 1 As shown, it mainly includes the following steps: S1, based on the pump efficiency parameters obtained from the experiment, build a pump power algorithm to simulate the output power of the simulation object pump under working conditions; S2, based on the relationship between speed and pump power, builds a speed algorithm to simulate the speed of the simulation object pump under working conditions; S3, based on the pump head parameter input type, construct the corresponding head algorithm to simulate the head of the simulation object pump under the working state; S4, constructing a corresponding pump flow capacity algorithm based on the constructed head algorithm, and simulating the flow capacity of the simulation object pump under the working state; S5, based on the test data input of the water pump, construct a pump cavitation phenomenon algorithm to simulate the cavitation phenomenon of the simulation object pump under the working state; S6, encapsulates the pump power algorithm, speed algorithm, head algorithm, pump flow capacity algorithm and pump cavitation phenomenon algorithm into an overall centrifugal water pump model algorithm, and performs real-time iterative calculation based on the parameter input of the simulation object pump and the operating condition data output by the fluid network interface to obtain the pump model data under the corresponding operating conditions.

[0027] Furthermore, in step S1, a pump power algorithm is constructed based on the efficiency characteristics of the centrifugal water pump. Pump power and efficiency are generally obtained experimentally, so two pump efficiency input modes are constructed: one based on the flow rate and efficiency curve of the simulation target pump as input, and the other using a fixed efficiency.

[0028] Furthermore, in step S2, a speed algorithm is constructed based on the working principle of the centrifugal water pump, and the energy conservation equation is used to construct a differential form of the energy conservation equation of the centrifugal water pump rotor.

[0029] The relationship between speed and input and output power is derived, and parameters such as the rotational inertia of the simulation object pump are used as input to calculate the pump speed.

[0030] Furthermore, in step S3, a head algorithm is constructed based on the working principle of the centrifugal pump and the fluid network interface rules. The head algorithm is divided into closed head, single-speed second-order curve fitting, and multi-speed high-order curve fitting, which are adapted to the head parameter input type of the simulation target pump.

[0031] Given the rated head and flow of the simulation object pump, the closed head method is selected, and the rated flow, rated head, rated speed, hydraulic efficiency and other parameters of the simulation object pump are used as input.

[0032] The performance curve of flow rate and head at a certain speed of the pump is known. The single-speed second-order curve fitting method is selected. The performance curve of flow rate and head of the simulation object pump is used as input, and the second-order curve of flow rate and head is fitted using the least squares method.

[0033] The characteristic curves of flow rate and head at multiple speeds of the pump are known. The multi-speed high-order curve fitting method is selected. The performance curves of flow rate and head at multiple speeds of the simulation object pump are used as input. The high-order curves of flow rate and head at multiple speeds are fitted using high-order curves. The corresponding relationship between head, flow rate and speed is determined through the similarity principle.

[0034] Furthermore, in step S4, a pump flow capacity algorithm is constructed according to the working principle of the centrifugal water pump and the fluid network operation rules.

[0035] The closed head method is selected, and the rated flow, rated head, rated speed, hydraulic efficiency and other parameters of the simulation object pump are used as input, and the flow capacity value is obtained from the flow capacity calculation formula.

[0036] The single-speed second-order curve fitting and multi-speed high-order curve fitting methods are selected. The flow and head performance curve of the simulation object pump is used as input, and the pump flow capacity is calculated from the fitted curve coefficient.

[0037] Furthermore, in step S5, a pump cavitation phenomenon algorithm is constructed based on the external cavitation characteristics of the centrifugal water pump. Pump test data is used as input to determine the pump's cavitation conditions. The cavitation coefficient and cavitation head fluctuation coefficient are used to correct the pump model for cavitation phenomena.

[0038] Furthermore, in step S6, the algorithm preprocessing is to take the parameters of the simulation object pump such as rated flow, rated head, rated speed, hydraulic efficiency as input, and perform preprocessing through the algorithms in steps S1 to S5 above, and output data such as head and flow capacity; The working condition simulation combines the algorithm preprocessing data and the working condition data output by the flow network interface to output the head, power, speed and other data under the corresponding working conditions, which are used for display or output to the fluid network to obtain the fluid network and pump model data of the corresponding working conditions.

[0039] The following is an example of inputting a pump model based on the simulation object pump data and then bringing it into the flow network calculation.

[0040] (1) Build a fluid network. The fluid network consists of boundaries, nodes, and branches.

[0041] (2) Place the pump model in the fluid network and connect the boundaries, branches, nodes, and pumps according to the normal flow direction of the fluid, such as Figure 2 shown.

[0042] (3) Input parameters for all modules in the fluid network, including boundaries, branches, and nodes. Input preprocessing parameters for the pump, using a second-order curve fitting algorithm, such as Figure 3 .

[0043] (4) After completing the above steps, compile the fluid network to form a program. Run the program, the fluid network will iterate continuously, and obtain real-time operation data. The data will be displayed as follows: Figure 4 .

[0044] Example 2: This example uses Fortran language to write the centrifugal water pump model algorithm code, and uses DTP-CAMLIB to encapsulate the code into a centrifugal water pump model. The specific method includes the following steps: Step 1: Construct the pump model algorithm content, mainly achieved through the following technical solutions: (1) Based on the efficiency characteristics of centrifugal water pumps, a pump power algorithm is constructed. Water pump power and water pump efficiency are generally obtained from experiments. Therefore, two pump efficiency input modes are constructed: one is based on the flow rate and efficiency curve of the simulation object pump as input, and the other is a fixed efficiency. The pump power is calculated using the following formula:

[0045] Where, is the pump output shaft power; is the power acting on the working fluid; is the pump efficiency; (2) Based on the working principle of the centrifugal water pump, a speed algorithm is constructed. Using the energy conservation equation, the differential form of the energy conservation equation of the centrifugal water pump rotor is constructed as follows:

[0046] Where, is the input power, the turbine and motor output shaft power; is the pump output shaft power; is energy loss; is the increase in kinetic energy of the pump rotor; is the time differential; Using the above formula, we can finally obtain the relationship between speed and input and output power. The parameters such as the rotational inertia of the simulation object pump are used as input to calculate the pump speed.

[0047] (3) Based on the working principle of the centrifugal water pump and the fluid network interface rules, a head algorithm is constructed. The head algorithm is divided into closed head, single speed second-order curve fitting, and multi-speed high-order curve fitting, which adapts to the head parameter input type of the simulation object pump.

[0048] Given the rated head and flow of the simulation target pump, the closed head method is selected. The rated flow, rated head, rated speed, hydraulic efficiency and other parameters of the simulation target pump are used as input. The head calculation formula of the pump model is as follows:

[0049] Where, It is a closed head and output to the fluid network; is the rated lift; is the pump hydraulic efficiency; is the operating speed under working condition; is the rated speed; Given the performance curve of flow and head at a certain speed of the pump, the single-speed second-order curve fitting method is selected. The performance curve of flow and head of the simulation object pump is used as input, and the second-order curve of flow and head is fitted using the least squares method, as shown below:

[0050] Where, The working head is the working head; is the operating speed under working condition; The flow rate for the working condition; , b, c are the coefficients of the second-order curve; Given the characteristic curves of flow and head at multiple speeds of the pump, the multi-speed high-order curve fitting method is selected. The performance curves of flow and head at multiple speeds of the simulation object pump are used as input, and the high-order curves of flow and head at multiple speeds are fitted using the high-order curve fitting method, as shown below:

[0051] Where, The working head is the working head; is the operating speed under working condition; The flow rate for the working condition; , b, c, x, etc. are high-order curve coefficients; n is the order, the highest is 6; Through the principle of similarity, the corresponding relationship between head, flow rate and speed is determined.

[0052] (4) Based on the working principle of the centrifugal water pump and the fluid network operation rules, a pump flow capacity algorithm module is constructed.

[0053] The closed head method is used, and the rated flow, rated head, rated speed, hydraulic efficiency and other parameters of the simulation object pump are used as input. The pump flow capacity is calculated as follows:

[0054] Where, is the pump flow capacity; is the rated flow rate; For closed lift; The working head is the working head; is the working fluid density; The single-speed second-order curve fitting and multi-speed high-order curve fitting methods are selected. The flow and head performance curve of the simulation object pump is used as input, and the pump flow capacity is calculated from the fitted curve coefficient.

[0055] (5) Based on the test data input of the pump, it is used to simulate the cavitation phenomenon of the pump under certain working conditions and construct a pump cavitation phenomenon algorithm.

[0056] The calculation formula for the influence coefficient of cavitation on lift is as follows:

[0057] Where, is the head fluctuation coefficient; is the closed head of the water pump; is the cavitation coefficient; is the cavitation head influence coefficient; is the number of periodic changes.

[0058] Step 2: Using the centrifugal pump model algorithm, construct the module content under the fluid network rules. The module consists of two parts: algorithm preprocessing and operating condition simulation.

[0059] (1) The preprocessing part takes the parameters of the simulation object as input, and processes them into model parameters through algorithm preprocessing. The parameters such as the rated flow, rated head, rated speed, hydraulic efficiency of the simulation object pump are taken as input, and after algorithm processing, the data such as head and flow capacity are output. Figure 5 shown.

[0060] The input data interface includes the following: Select the lift algorithm. This includes closed lift, second-order curve fitting, and higher-order curve fitting. Set closed lift to 0, second-order curve fitting to 1, and higher-order curve fitting to 2.

[0061] Select the order of the curve fit. Set it to 2 for second-order curve fit and 3 to 6 for higher-order curve fit.

[0062] Data input for the closed head method. Use the rated parameter data of the simulation object pump to input, including centrifugal pump inlet gauge pressure, centrifugal pump inlet temperature, centrifugal pump rated flow, centrifugal pump rated head, centrifugal pump hydraulic efficiency, and centrifugal pump inlet working fluid density.

[0063] Second-order and higher-order curve fitting data input. Use the flow-head correspondence table of the simulation target pump as input and enter multiple sets of flow, head, speed, and density data.

[0064] The output data interface content includes the following: When the closed head method is selected, the closed head and flow capacity are output.

[0065] When using the second-order and higher-order curve fitting methods, the output flow-head fitting polynomial and flow capacity are obtained.

[0066] (2) The working condition simulation part combines the data processed by the pre-processing part and the working condition data output by the flow network interface. After the working condition simulation processing, the head, power, speed and other data of the corresponding working condition are output for display or output to the fluid network. Figure 6 shown.

[0067] Input interface data, from the fluid network to the pump model, includes the following: Branch inlet port parameters: including branch inlet pressure, branch inlet temperature, branch inlet flow rate, branch inlet working fluid density, branch inlet enthalpy, branch inlet gas content, branch inlet working fluid specific heat, etc.

[0068] Branch outlet port parameters: including branch outlet pressure, branch outlet temperature, branch outlet flow rate, branch outlet working fluid density, branch outlet enthalpy, branch outlet gas content, branch outlet working fluid specific heat, etc.

[0069] Gas composition at the branch inlet: includes the water vapor mass content at the branch inlet, etc.

[0070] Gas composition at the branch outlet: includes the water vapor mass content at the branch inlet, etc.

[0071] Output interface data from the pump model to the fluid network, including the following: branch flow capacity and branch lift pressure. The pump model's flow capacity and lift are output to the fluid network, where it is iteratively solved to obtain real-time fluid network operating parameters.

[0072] The intermediate variable data uses the input interface data and pre-processed data, and is processed through working condition simulation operations to obtain working condition operation data, which includes working power, actual speed, etc.

[0073] Constant data, which uses the pre-processed data, other pump parameters, pump correction coefficients, etc. as pump model attributes, does not change with changes in fluid network operating parameters. It includes the following: Closed head, second-order or higher-order curve fitting polynomial coefficients. Resulted from the preprocessing part.

[0074] Pump moment of inertia. Obtained from the parameters of the simulation target pump and used to calculate the model pump speed.

[0075] Pump rated speed and rated speed friction power. These are obtained from the parameters of the simulated pump and used to calculate the friction power of the pump model at different speeds.

[0076] The relationship between pump flow rate and efficiency is obtained by simulating the pump parameters and used to calculate pump power at different flow rates.

[0077] Backflow work adjustment coefficient. Used to calculate the pump power when backflow occurs.

[0078] Cavitation head fluctuation system and cavitation coefficient. Used to simulate the phenomenon of cavitation in pump models.

[0079] Furthermore, according to the pump input, the closed head method and characteristic curve fitting method were used to build models, and the actual pump characteristic curve was compared, such as Figure 7 As shown in the figure, the characteristic curve fitting method's flow-head characteristic curve more closely matches the actual pump operating characteristics under various operating conditions compared to the closed head method. Therefore, when multiple sets of actual pump flow-head relationships are known, the characteristic curve fitting pump model is more accurate.

[0080] Furthermore, in the process of thermal system design, verification, and optimization, it is necessary to adapt to the different levels of detail of the flow and head relationship of the known water pumps at different stages, or to meet the different levels of accuracy of the results required at different stages. The centrifugal water pump model in the present invention that handles multiple levels of detail of the flow and head relationship is of great significance to improving the accuracy and adaptability of thermal system simulation.

[0081] Embodiment 3: Based on the same inventive concept, this embodiment further provides a centrifugal water pump simulation model based on a fluid network, which is established using the centrifugal water pump simulation modeling method based on a fluid network as described above.

[0082] Furthermore, all parts of this application that are not described in detail are the same as the existing technology or are implemented using the existing technology.

[0083] In summary: 1. The present invention provides a centrifugal water pump simulation modeling method based on a fluid network. This method can achieve efficient processing of the external characteristic parameters of the simulation object - the centrifugal water pump, and establish a highly accurate and real-time simulation model based on the processed parameter data, thereby meeting the model accuracy requirements of the centrifugal water pump at different design and optimization stages. 2. The centrifugal water pump simulation model established by the present invention has a flow-head characteristic curve that is more consistent with the actual pump operation characteristics when simulating multiple operating conditions. It can effectively ensure the accuracy and adaptability requirements of the centrifugal water pump hydraulic characteristic simulation. It has strong practicality, broad application prospects, and is easy to promote.

[0084] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware. Furthermore, the present application may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0085] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0086] It will be easily understood by those skilled in the art that the above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A centrifugal water pump simulation modeling method based on fluid network, characterized in that: The steps include: S1, based on the pump efficiency parameters obtained from the experiment, build a pump power algorithm to simulate the output power of the simulation object pump under working conditions; S2, based on the relationship between speed and pump power, builds a speed algorithm to simulate the speed of the simulation object pump under working conditions; S3, based on the pump head parameter input type, construct the corresponding head algorithm to simulate the head of the simulation object pump under the working state; S4, constructing a corresponding pump flow capacity algorithm based on the head algorithm to simulate the flow capacity of the simulation object pump under the working state; S5, based on the test data input of the water pump, construct a pump cavitation phenomenon algorithm to simulate the cavitation phenomenon of the simulation object pump under the working state; S6, encapsulates the pump power algorithm, speed algorithm, head algorithm, pump flow capacity algorithm and pump cavitation phenomenon algorithm into an overall centrifugal water pump model algorithm, and performs real-time iterative calculation based on the parameter input of the simulation object pump and the operating condition data output by the fluid network interface to obtain the pump model data under the corresponding operating conditions.

2. A centrifugal water pump simulation modeling method based on fluid network according to claim 1, characterized in that: The pump power algorithm is as follows: Where, is the output power of the water pump; is the working power of the water pump; is the pump efficiency.

3. The centrifugal water pump simulation modeling method based on fluid network according to claim 1, characterized in that: The speed algorithm is as follows: Where, is the input power of the water pump; is the output power of the water pump; is energy loss; is the increase in kinetic energy of the pump rotor; is the time differential; The operating speed of the water pump is calculated based on the increase in the kinetic energy of the water pump rotor and the time differential, combined with the rotational inertia parameters of the water pump. .

4. The centrifugal water pump simulation modeling method based on fluid network according to claim 1, characterized in that: The lift algorithm is divided into the following types according to the lift parameter input type of the simulation object pump: closed lift algorithm, single speed second-order curve fitting algorithm, and multi-speed high-order curve fitting algorithm; When the rated head and flow of the simulation object pump are known, select the closed head algorithm as follows: Where, It is the closed head of the water pump, output to the fluid network; is the rated lift; is the pump efficiency; is the operating speed of the water pump; is the rated speed.

5. The centrifugal water pump simulation modeling method based on fluid network according to claim 4 is characterized in that: When the flow and head performance curve of the simulation object pump at a certain speed is known, the single-speed second-order curve fitting algorithm is selected as follows: When the flow and head performance curves of the simulation object pump at multiple speeds are known, a multi-speed high-order curve fitting algorithm is selected, as follows: Where, It is the working head of the water pump; is the operating speed of the water pump; The flow rate for the working condition; , b, c, x, etc. are all multi-order curve coefficients; n is the order of the curve.

6. The centrifugal water pump simulation modeling method based on fluid network according to claim 4, characterized in that: The pump flow capacity algorithm is as follows: Where, is the flow capacity of the water pump; is the rated flow of the pump; is the closed head of the water pump; It is the working head of the water pump; is the working fluid density.

7. The centrifugal water pump simulation modeling method based on fluid network according to claim 1, characterized in that: The pump cavitation phenomenon algorithm is as follows: Where, is the pump head fluctuation coefficient under the influence of cavitation; is the closed head of the water pump; is the cavitation coefficient; is the cavitation head influence coefficient; is the number of periodic changes.

8. The centrifugal water pump simulation modeling method based on fluid network according to claim 1, characterized in that: The centrifugal water pump model algorithm includes two parts: algorithm preprocessing and working condition simulation; The algorithm preprocessing includes: taking the rated flow, rated head, rated speed, and hydraulic efficiency parameters of the simulation object pump as input, and preprocessing them through the pump power algorithm, speed algorithm, head algorithm, pump flow capacity algorithm, and pump cavitation phenomenon algorithm described in steps S1 to S5 to obtain preprocessed data of the water pump's output power, speed, head, and flow capacity.

9. The centrifugal water pump simulation modeling method based on fluid network according to claim 8, characterized in that: The working condition simulation includes: combining the pre-processed data with the working condition data output by the fluid network interface, and performing real-time iterative calculation to obtain pump model data under corresponding working conditions.

10. A centrifugal water pump simulation model based on fluid network, characterized in that: The centrifugal water pump simulation modeling method based on fluid network as described in any one of claims 1 to 9 is used for establishment.

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