CN116384009B - Simulation prediction method, device and equipment for energy efficiency level of canned motor pump - Google Patents
Simulation prediction method, device and equipment for energy efficiency level of canned motor pump Download PDFInfo
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- 238000004088 simulation Methods 0.000 title claims abstract description 131
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- 239000004973 liquid crystal related substance Substances 0.000 description 2
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- G06F—ELECTRIC DIGITAL DATA PROCESSING
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- G—PHYSICS
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- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
- G06F30/28—Design optimisation, verification or simulation using fluid dynamics, e.g. using Navier-Stokes equations or computational fluid dynamics [CFD]
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- G—PHYSICS
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- G06F2119/00—Details relating to the type or aim of the analysis or the optimisation
- G06F2119/06—Power analysis or power optimisation
Abstract
The invention relates to a simulation prediction method, a device and equipment for energy efficiency level of a canned motor pump, wherein the method establishes a simulation model based on canned motor pump parameters; applying a plurality of sample points to the simulation model in parallel under the rated working condition, and calculating to obtain an optimal solution of the objective function; under the optimal solution of the objective function, adjusting the nominal working condition to a full-flow working condition, and calculating the performance data of the working condition points under the simulation model; and applying the performance data to the simulation model, and calculating to obtain energy efficiency grade data. According to the technical scheme provided by the embodiment of the invention, a simulation model about the shielding pump is established, a fitting response surface is generated through sample point calculation in sequence, and an optimal solution is selected; calculating performance data of the working point under the condition of the full-flow working condition and generating a performance curve graph; the performance data is utilized to generate working condition rotating speed and the working condition rotating speed and flow are used for calculating together to obtain energy efficiency grade data, the defect that a prototype is required to be manufactured in the existing energy efficiency grade test is overcome, and the test cost is reduced.
Description
Technical Field
The invention relates to the technical field of canned motor pumps, in particular to a simulation prediction method, a simulation prediction device and simulation prediction equipment for energy efficiency level of a canned motor pump.
Background
EEI (Energy Efficiency Index, energy efficiency grade) is a grading method for representing the difference of energy efficiency of products. By detecting the working state of the canned motor pump and the working efficiency of the canned motor pump under different rated flows (25% -100%), the energy-saving effect of the canned motor pump can be reflected more accurately than by singly detecting the working efficiency of the canned motor pump.
EEI prediction of the canned motor pump at the present stage is obtained through test, a prototype is required to be manufactured according to a related scheme in the test process, and related tests are carried out on the prototype, so that the predicted time cost and the labor cost are increased, and the prototype cannot give consideration to updating of the canned motor pump, so that the predicted cost is further increased.
Disclosure of Invention
The invention provides a simulation prediction method, device and equipment for energy efficiency level of a canned motor pump, and aims to reduce cost of energy efficiency prediction of the canned motor pump.
In a first aspect, an embodiment of the present invention provides a method for predicting a performance level of a canned motor pump, including:
establishing a simulation model based on the parameters of the canned motor pump;
applying a plurality of sample points to the simulation model in parallel under the rated working condition, and calculating to obtain an optimal solution of the objective function;
under the optimal solution of the objective function, adjusting the nominal working condition to a full-flow working condition, and calculating the performance data of the working condition points under the simulation model;
and applying the performance data to the simulation model, and calculating to obtain energy efficiency grade data.
Optionally, after calculating the energy efficiency level data, the method further includes:
evaluating whether the energy efficiency grade data reach the standard;
if not, the parameters of the shielding pump are adjusted to reestablish the simulation model.
Optionally, establishing a simulation model based on the parameters of the canned motor pump specifically comprises:
confirming a hydraulic model according to the parameters of the canned motor pump;
adjusting the geometric parameters of the hydraulic model and extracting a fluid domain according to the geometric parameters;
dividing a fluid domain into a plurality of grids, and obtaining a shielding pump output function corresponding to the grids by defining boundary conditions of a simulation model;
and calculating to obtain the output parameters of the shielding pump corresponding to the simulation model according to the output functions of the shielding pump.
Optionally, applying a plurality of sample points in parallel to the simulation model under the rated working condition, and calculating to obtain an optimal solution of the objective function, wherein the method specifically comprises the following steps:
selecting a plurality of sample points to apply to the simulation model, and calculating to obtain sample parameters;
selecting geometric parameters and establishing a coordinate system related to an objective function;
fitting sample parameters under a coordinate system to obtain a fitting response surface;
and optimizing and fitting extreme points in the response surface to obtain an optimal solution of the objective function.
Optionally, under the optimal solution of the objective function, the nominal working condition is adjusted to the full-flow working condition, and the performance data of the working condition point under the simulation model is calculated, which specifically comprises:
selecting a plurality of flow points under the full-flow working condition, wherein the flow points respectively have a given multiple relation with the rated flow points;
and respectively calculating to obtain the performance data of the flow points through the simulation model.
Optionally, applying the performance data to the simulation model, and calculating to obtain energy efficiency level data specifically includes:
calculating a theoretical lift according to an energy efficiency grade formula;
according to the theoretical lift, calculating to obtain the corresponding theoretical rotating speed of the shielding pump according to a similarity law;
according to the flow corresponding to the theoretical lift and the theoretical rotating speed, calculating to obtain the corresponding working condition rotating speed through a simulation model;
and calculating to obtain energy efficiency grade data according to the working condition rotating speed.
Optionally, before calculating the energy efficiency grade data according to the working condition rotation speed, the method further comprises:
according to the flow and the corresponding theoretical rotation speed, calculating through a simulation model to obtain a simulation lift;
judging whether the difference between the simulated lift and the theoretical lift is smaller than a deviation threshold value or not;
if not, the theoretical rotation speed is recalculated.
In a second aspect, an embodiment of the present invention provides a simulation prediction apparatus for a pump energy efficiency level, including:
the simulation model building module is used for building a simulation model based on the parameters of the canned motor pump;
the optimal solution calculation module is used for parallelly applying a plurality of sample points to the simulation model under the rated working condition, and calculating to obtain an optimal solution of the objective function;
the performance data calculation module is used for adjusting the target function from a rated working condition to a full-flow working condition under the optimal solution of the target function, and calculating the performance data of the working condition points under the simulation model;
and the energy efficiency grade data calculation module is used for applying the performance data to the simulation model and calculating to obtain the energy efficiency grade data.
In a third aspect, an embodiment of the present invention provides an electronic device, including: one or more processors;
a memory for storing one or more programs;
the one or more programs, when executed by the one or more processors, cause the one or more processors to implement a method of simulated prediction of a canned pump energy efficiency level as provided by any embodiment of the present invention.
In a fourth aspect, embodiments of the present invention provide a storage medium containing computer executable instructions that when executed by a computer processor are used to perform a simulated prediction method of a barrier pump energy efficiency level as provided by any of the embodiments of the present invention.
According to the simulation prediction method, the simulation prediction device and the simulation prediction equipment for the energy efficiency level of the canned motor pump, provided by the embodiment of the invention, a simulation model about the canned motor pump is established, a fitting response surface is generated through sample point calculation in sequence, and an optimal solution is selected; calculating performance data of the working point under the condition of the full-flow working condition and generating a performance curve graph; and then, the performance data is utilized to generate working condition rotating speed and the flow are used for calculating together to obtain energy efficiency grade data, so that the defect that a prototype is required to be manufactured in the existing energy efficiency grade test is overcome, and the test cost is reduced.
Drawings
FIG. 1 is a flowchart of a method for simulating and predicting energy efficiency level of a canned motor pump according to an embodiment of the present invention;
FIG. 2 is a flowchart of a simulation model established based on parameters of a canned motor pump in a simulation prediction method of energy efficiency level of a canned motor pump according to an embodiment of the present invention;
FIG. 3 is a flowchart of calculating an optimal solution of an objective function in a method for predicting a simulation of a pump energy efficiency level according to an embodiment of the present invention;
FIG. 4 is a flowchart of calculating performance data of a working point under a simulation model in a simulation prediction method of a canned motor pump energy efficiency level according to an embodiment of the present invention;
FIG. 5 is a flowchart of calculating energy efficiency level data in a simulation prediction method of energy efficiency level of a canned motor pump according to an embodiment of the present invention;
FIG. 6 is a schematic structural diagram of a simulation prediction apparatus for energy efficiency level of a canned motor pump according to an embodiment of the present invention;
fig. 7 is a schematic structural diagram of a simulation prediction apparatus for energy efficiency level of a canned motor pump according to an embodiment of the present invention.
Detailed Description
The invention is described in further detail below with reference to the drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not limiting thereof. It should be further noted that, for convenience of description, only some, but not all of the structures related to the present invention are shown in the drawings.
EEI prediction of the canned motor pump at the present stage is obtained through test, a prototype is required to be manufactured according to a related scheme in the test process, and related tests are carried out on the prototype, so that the predicted time cost and the labor cost are increased, and the prototype cannot give consideration to updating of the canned motor pump, so that the predicted cost is further increased.
Example 1
The present invention provides a simulation prediction method for energy efficiency level of a canned motor pump, as shown in fig. 1, comprising:
s10: establishing a simulation model based on the parameters of the canned motor pump; the parameters of the canned motor pump include, but are not limited to, geometric parameters of the impeller and the pumping chamber, extraction of the fluid domains of the impeller and the pumping chamber and division of fluid grids are achieved, and steady-state solving is performed on the divided grids to obtain objective functions of the canned motor pump under a simulation model, such as a function lift H, shaft power P, hydraulic efficiency Eff and the like.
As shown in fig. 2, step S10 specifically includes:
s11: confirming a hydraulic model according to the parameters of the canned motor pump; the above-mentioned canned motor pump parameters include a nominal flow Q, a nominal lift H and a nominal rotational speed n, by means of which the hydraulic model, for example the design and the type of canned motor pump, is determined.
After the structural form and type are determined, the geometric parameters of the impeller of the canned motor pump and the pumping chamber need to be designed with initial waterpower, in particular:
for the impeller, geometric parameters such as inlet diameter, impeller outer diameter, outlet width, inlet setting angle, blade outlet setting angle, wrap angle, blade form, blade thickness, blade inlet edge position, meridian plane streamline and the like are required to be defined;
for the pumping chamber, geometric parameters such as the section type, the flow channel width, the base circle diameter, the partition tongue placing angle, the partition tongue type and the like of the pumping chamber are required to be defined.
S12: adjusting the geometric parameters of the hydraulic model and extracting a fluid domain according to the geometric parameters; in a preferred embodiment, for the above geometric parameters, 3 to 7 geometric parameters with larger influence factors are selected, set as variables and subjected to subsequent adjustment.
And then, extracting the fluid domains in the impeller and the pumping chamber according to the geometric parameters for later simulation operation.
S13: dividing a fluid domain into a plurality of grids, and obtaining a shielding pump output function corresponding to the grids by defining boundary conditions of a simulation model;
here, since there is a difference in flow rate between the center and the edge of the fluid field, quality inspection is performed on different grids by dividing the grids.
The boundary conditions of the simulation model are defined as input conditions and output functions by preprocessing in fluid mechanics simulation software CFX-pre; for example, a ke model is selected as a turbulence model, a wall surface function is selected as a Scalable, a dynamic-static interface between an impeller and a pumping chamber is selected to freeze a rotor method, the inlet mass flow is the static pressure, and the outlet is the static pressure.
For the mass flow at the inlet of the canned motor pump in the simulation model, the mass flow is defined as a function MF, and the time step is defined as a function PT, wherein PT is the inverse of the rotational angular velocity of the impeller.
The output functions (objective functions) for the canned motor pump in the simulation model include head H, shaft power P, hydraulic efficiency Eff.
Wherein, the formula of the lift H is:
in the method, in the process of the invention,the total pressure at the outlet of the water pump is Pa;
the total pressure at the inlet of the water pump is Pa;
is the density of the fluid medium, and the unit is kg/m 3 ；
Gravitational acceleration, sign of m/s 2 ；
The formula of the shaft power P is:
wherein T is a torque value generated by the impeller in the axial direction, the unit is Oryza sativa, and the symbol is N.m;
n is the rotation speed of the water pump, the unit is revolutions per minute, and the sign is rev/min;
the formula for hydraulic efficiency Eff is:
wherein Q is volume flow, Q is cubic meters per hour, and the symbol is m 3 /h；
S14: and calculating to obtain the output parameters of the shielding pump corresponding to the simulation model according to the output functions of the shielding pump. And substituting each parameter in the output function of the canned motor pump into a specific numerical value, and calculating to obtain the output parameter of the canned motor pump, wherein the output parameter of the canned motor pump has the function of verifying whether the output function of the canned motor pump is converged and/or satisfies the function change of the monitoring point, and if the output function of the canned motor pump is not satisfied, the steps S11-S14 are required to be executed again. After the verification is completed, the establishment of the simulation model is completed. It should be added that the above-mentioned canned motor pump output parameters are calculated by the fluid mechanics simulation software CFX through the objective functions (head H, shaft power P, hydraulic efficiency Eff).
S20: applying a plurality of sample points to the simulation model in parallel under the rated working condition, and calculating to obtain an optimal solution of the objective function;
after the establishment of the simulation model is completed, a plurality of sample points composed of different geometric parameters are selected to calculate and obtain an optimal solution of the objective function, and the specific calculation process is shown in fig. 3 and comprises the following steps:
s21: selecting a plurality of sample points to apply to the simulation model, and calculating to obtain sample parameters; sample points are selected through a central composite design algorithm (Central Composite Design); in a preferred embodiment each sample point may include only a partial geometrical parameter to reduce the consumption of computational resources, while also including 3 unknown values as output parameters.
S22: selecting geometric parameters and establishing a coordinate system related to an objective function;
s23: fitting sample parameters under a coordinate system to obtain a fitting response surface; here, it should be noted that the rectangular coordinate system is preferable, wherein the coordinate axes of 2 directions are two selected from a plurality of geometric parameters, and the coordinate axis of the third direction is one of 3 objective functions. The response surface reflects the condition of the objective function in the dimension of the 2 geometric parameters. The selection is carried out according to the actual situation.
S24: and optimizing and fitting extreme points in the response surface to obtain an optimal solution of the objective function. For the extreme points of the selected objective function, the extreme points can be one or a plurality of extreme points, the optimization is performed by setting constraint conditions and optimization targets, and an optimization algorithm, such as MISTP (gradient-based single-target optimization algorithm), is adopted to generate an optimal solution of the objective function. For example, the maximum value of the hydraulic efficiency Eff is used as an optimization target, the constraint condition is that the lift H is more than or equal to 6.5m, the shaft power P is not constrained, and then the optimal solution of the corresponding objective function is obtained through the fitting response surface.
It is added here that the process files and data generated during the simulation and fitting process, such as hydraulic model parameters, fluid fields, grids, etc., will be stored for later use.
S30: under the optimal solution of the objective function, the nominal working condition is adjusted to the full-flow working condition, and the performance data of the working condition points under the simulation model are calculated, as shown in fig. 4 in detail:
s31: selecting a plurality of flow points under the full-flow working condition, wherein the flow points respectively have a given multiple relation with the rated flow points; here, the rated operation condition refers to the operation condition of the canned motor pump in an ideal state, and the full-flow operation condition may be regarded as the actual operation condition of the canned motor pump, and the full-flow operation condition includes flow points in a plurality of cases, for example, 0.1Q, 0.5Q, 0.8Q, 1.0Q, 1.2Q, 1.5Q, and 1.8Q, where Q represents the flow point in the rated operation condition.
S32: and respectively calculating to obtain the performance data of the flow points through the simulation model. By applying the 7 flow points to the simulation model and simulating the flow points through the fluid mechanics simulation software CFX, a data file containing flow and rotation speed information corresponding to the flow points to a Comma Separated Values (CSV) is required to be added in the simulation process, and the CSV data file is passed through the fluid mechanics simulation software CFX to obtain performance data and a performance graph corresponding to the flow points. The performance curves represent the objective functions (e.g., head H) corresponding to the different flow points, respectively.
S40: and applying the performance data to the simulation model, and calculating to obtain energy efficiency grade data. The simulation model is used for calculating the energy efficiency level by using an excel calculation program, calculating to obtain a theoretical lift and a theoretical rotating speed, reversely calculating according to the flow and the theoretical rotating speed to obtain a simulation lift, and calculating according to the simulation lift to obtain energy efficiency level data. Specifically, as shown in fig. 5:
s41: calculating a theoretical lift according to an energy efficiency grade formula; it should be noted that, according to EEI standard requirements, theoretical lifts of 4 flow points are required to be calculated in the process of calculating the energy efficiency level data, wherein the 4 flow points are respectively 100% flow value, 75% flow value, 50% flow value and 25% flow value, and the corresponding theoretical lifts are respectively 100%, 87.5%, 75% and 62.5%. The performance curve obtained after executing step S32 is used to provide a reference value corresponding to the theoretical head at a flow value of 100%.
S42: according to the theoretical lift, calculating to obtain the corresponding theoretical rotating speed of the shielding pump according to a similarity law;
for the same pump, by the second law of similarity, the lift relationship between the prototype pump and the model pump is:
wherein, the liquid crystal display device comprises a liquid crystal display device,is the pump lift of the model pump->Is the prototype pump head. In (1) the->Is the outer diameter of the impeller>For the rotation speed of the impeller>Is the hydraulic efficiency of the pump.
In engineering application, the prototype pump is the pump in the actual working state, and the model pump is the pump in the ideal state such as test, and the two pumps approximate to be regarded as efficiencyAnd->Equal, but for the same pump, the outer diameters are the same, so there are:
the formula can directly calculate the corresponding theoretical rotation speed under the theoretical lift.
S43: according to the flow corresponding to the theoretical lift and the theoretical rotating speed, calculating to obtain the corresponding working condition rotating speed through a simulation model; and writing the theoretical rotating speed and the flow into the CSV data respectively, and obtaining the corresponding working condition rotating speed through a simulation model and fluid mechanics simulation software CFX.
S44: and calculating to obtain energy efficiency grade data according to the working condition rotating speed. And inputting the working condition rotating speed into the excel calculation program to obtain energy efficiency grade data.
According to the simulation prediction method, the simulation prediction device and the simulation prediction equipment for the energy efficiency level of the canned motor pump, provided by the embodiment of the invention, a simulation model about the canned motor pump is established, a fitting response surface is generated through sample point calculation in sequence, and an optimal solution is selected; calculating performance data of the working point under the condition of the full-flow working condition and generating a performance curve graph; and then, the performance data is utilized to generate working condition rotating speed and the flow are used for calculating together to obtain energy efficiency grade data, so that the defect that a prototype is required to be manufactured in the existing energy efficiency grade test is overcome, and the test cost is reduced.
Example two
The embodiment of the present invention further indicates, based on the first embodiment, that, as further shown in fig. 5, before executing step S44, there is a need to:
s45: according to the flow and the corresponding theoretical rotation speed, calculating through a simulation model to obtain a simulation lift; the theoretical rotational speed is added to the simulation model and calculated by the model itself, where the calculation can be understood as a simulated process.
S46: judging whether the difference between the simulated lift and the theoretical lift is smaller than a deviation threshold value or not; the deviation threshold is preferably 3%;
if not, jumping to the step S42; if yes, step S47 is executed: and calculating to obtain energy efficiency grade data through the simulation lift.
Further, as shown in fig. 1, after the energy efficiency level data is obtained, it is also necessary that:
s50: evaluating whether the energy efficiency grade data reach the standard; the energy efficiency grade data of the shielding pumps related to the embodiment of the invention is 0.21.
S60: if not, the parameters of the shielding pump are adjusted to reestablish the simulation model. If the geometric parameters do not reach the standard, the radial shape of the vane wheel in the geometric parameters needs to be changed, and the steps S10-S60 are executed again.
Example III
The invention also provides a simulation prediction device for the energy efficiency level of the canned motor pump, which is shown in fig. 6 and comprises the following steps:
the simulation model establishing module 01 is used for establishing a simulation model based on the parameters of the canned motor pump; wherein the simulation model building module 01 is configured to perform the following operations:
confirming a hydraulic model according to the parameters of the canned motor pump;
adjusting the geometric parameters of the hydraulic model and extracting a fluid domain according to the geometric parameters;
dividing a fluid domain into a plurality of grids, and obtaining a shielding pump output function corresponding to the grids by defining boundary conditions of a simulation model;
and calculating to obtain the output parameters of the shielding pump corresponding to the simulation model according to the output functions of the shielding pump.
The optimal solution calculation module 02 is used for parallelly applying a plurality of sample points to the simulation model under the rated working condition, and calculating to obtain an optimal solution of the objective function; the optimal solution calculation module 02 of the objective function is configured to perform the following operations:
selecting a plurality of sample points to apply to the simulation model, and calculating to obtain sample parameters;
selecting geometric parameters and establishing a coordinate system related to an objective function;
fitting sample parameters under a coordinate system to obtain a fitting response surface;
and optimizing and fitting extreme points in the response surface to obtain an optimal solution of the objective function.
The performance data calculation module 03 is used for adjusting the rated working condition to a full-flow working condition under the optimal solution of the objective function, and calculating the performance data of the working condition points under the simulation model; the performance data calculation module 03 is configured to perform the following operations:
selecting a plurality of flow points under the full-flow working condition, wherein the flow points respectively have a given multiple relation with the rated flow points;
and respectively calculating to obtain the performance data of the flow points through the simulation model.
And the energy efficiency grade data calculation module 04 is used for applying the performance data to the simulation model and calculating to obtain the energy efficiency grade data. The energy efficiency level data calculation module 04 is configured to perform the following operations:
calculating a theoretical lift according to an energy efficiency grade formula;
according to the theoretical lift, calculating to obtain the corresponding theoretical rotating speed of the shielding pump according to a similarity law;
according to the flow corresponding to the theoretical lift and the theoretical rotating speed, calculating to obtain the corresponding working condition rotating speed through a simulation model;
and calculating to obtain energy efficiency grade data according to the working condition rotating speed. Before that, according to the flow and the corresponding theoretical rotation speed, calculating through a simulation model to obtain a simulation lift;
judging whether the difference between the simulated lift and the theoretical lift is smaller than a deviation threshold value or not;
if not, the theoretical rotation speed is recalculated.
In addition, the system also comprises a judging module 05 for evaluating whether the energy efficiency grade data reach the standard;
if not, the parameters of the shielding pump are adjusted to reestablish the simulation model.
The simulation prediction device for the energy efficiency level of the canned motor pump provided by the embodiment of the invention adopts the same technical means as the simulation prediction method for the energy efficiency level of the canned motor pump to achieve the same technical effects, and is not repeated here.
Example IV
Fig. 7 is a schematic structural diagram of a simulation prediction apparatus for a pump energy efficiency level according to an embodiment of the present invention, and as shown in fig. 7, the simulation prediction apparatus for a pump energy efficiency level includes a processor 710, a memory 720, an input device 730, and an output device 740; the number of processors 710 in the simulated prediction device of the canned pump energy efficiency level may be one or more, one processor 710 being taken as an example in fig. 7; processor 710, memory 720, input device 730, and output device 740 in the simulated prediction apparatus of the pump energy efficiency level may be connected by a bus or other means, for example in fig. 7.
The memory 720 is a computer readable storage medium, and may be used to store a software program, a computer executable program, and a module, such as program instructions/modules (e.g., a simulation model building module, an optimal solution calculating module, a performance data calculating module, and an energy efficiency level data calculating module) corresponding to a simulation prediction method of a canned pump energy efficiency level in an embodiment of the present invention. The processor 710 executes various functional applications and data processing of the simulation prediction apparatus of the barrier pump energy efficiency level by executing software programs, instructions and modules stored in the memory 720, i.e., implements the simulation prediction method of the barrier pump energy efficiency level described above.
Memory 720 may include primarily a program storage area and a data storage area, wherein the program storage area may store an operating system, at least one application program required for functionality; the storage data area may store data created according to the use of the terminal, etc. In addition, memory 720 may include high-speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other non-volatile solid-state storage device. In some examples, memory 720 may further include memory remotely located with respect to processor 710, which may be connected to the simulated predictive device of the canned pump energy efficiency level via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The input device 730 may be used to receive input numeric or character information and to generate key signal inputs related to user settings and function control of the simulated predictive device of the pump energy efficiency rating. The output device 740 may include a display device such as a display screen.
Example five
A fifth embodiment of the present invention also provides a storage medium containing computer-executable instructions, which when executed by a computer processor, are configured to perform a method of simulated prediction of a barrier pump energy efficiency level, comprising:
establishing a simulation model based on the parameters of the canned motor pump;
applying a plurality of sample points to the simulation model in parallel under the rated working condition, and calculating to obtain an optimal solution of the objective function;
under the optimal solution of the objective function, adjusting the nominal working condition to a full-flow working condition, and calculating the performance data of the working condition points under the simulation model;
and applying the performance data to the simulation model, and calculating to obtain energy efficiency grade data.
Of course, the storage medium containing the computer executable instructions provided in the embodiments of the present invention is not limited to the above method operations, and may also perform the related operations in the method for predicting the simulation of the energy efficiency level of the canned motor pump provided in any embodiment of the present invention.
From the above description of embodiments, it will be clear to a person skilled in the art that the present invention may be implemented by means of software and necessary general purpose hardware, but of course also by means of hardware, although in many cases the former is a preferred embodiment. Based on such understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art in the form of a software product, which may be stored in a computer readable storage medium, such as a floppy disk, a Read-Only Memory (ROM), a random access Memory (Random Access Memory, RAM), a FLASH Memory (FLASH), a hard disk or an optical disk of a computer, etc., including several instructions for causing a computer device (which may be a personal computer, a server, a network device, etc.) to execute the method of the embodiments of the present invention.
It should be noted that, in the embodiment of the simulation prediction apparatus for energy efficiency level of the canned motor pump, each unit and module included are only divided according to the functional logic, but not limited to the above-mentioned division, so long as the corresponding functions can be implemented; in addition, the specific names of the functional units are also only for distinguishing from each other, and are not used to limit the protection scope of the present invention.
While the invention has been described in detail in the foregoing general description, embodiments and experiments, it will be apparent to those skilled in the art that modifications and improvements can be made thereto. Accordingly, such modifications or improvements may be made without departing from the spirit of the invention and are intended to be within the scope of the invention as claimed.
Claims (8)
1. A simulation prediction method for energy efficiency level of a canned motor pump is characterized by comprising the following steps:
establishing a simulation model based on the canned motor pump parameters, including:
confirming a hydraulic model according to the parameters of the shielding pump;
adjusting the geometric parameters of the hydraulic model and extracting a fluid domain according to the geometric parameters;
dividing the fluid domain into a plurality of grids, and obtaining a shielding pump output function corresponding to the grids by defining boundary conditions of the simulation model;
calculating and obtaining a shielding pump output parameter corresponding to the simulation model according to the shielding pump output function;
applying a plurality of sample points to the simulation model in parallel under the rated working condition, and calculating to obtain an optimal solution of the objective function, wherein the method comprises the following steps:
selecting a plurality of sample points to be applied to the simulation model, and calculating to obtain sample parameters;
selecting the geometric parameters and establishing a coordinate system related to the objective function;
fitting the sample parameters under the coordinate system to obtain a fitting response surface;
optimizing extreme points in the fitting response surface to obtain an optimal solution of the objective function;
under the optimal solution of the objective function, adjusting the nominal working condition to a full-flow working condition, and calculating the performance data of the working condition points under the simulation model;
and applying the performance data to the simulation model, and calculating to obtain energy efficiency grade data.
2. The method for simulated prediction of energy efficiency level of canned motor pump according to claim 1, further comprising, after said calculating said energy efficiency level data:
evaluating whether the energy efficiency grade data reach the standard or not;
if not, the parameters of the shielding pump are adjusted to reestablish the simulation model.
3. The method for predicting the energy efficiency level of a canned motor pump according to claim 1, wherein the nominal condition is adjusted to a full-flow condition under the optimal solution of the objective function, and the performance data of the operating point under the simulation model is calculated, and specifically includes:
selecting a plurality of flow points under the full-flow working condition, wherein the flow points respectively have a given multiple relation with the rated flow points;
and respectively calculating the performance data of the flow points through the simulation model.
4. The method for predicting the energy efficiency level of a canned motor pump according to claim 1, wherein the performance data is applied to the simulation model to calculate energy efficiency level data, and the method specifically comprises:
calculating a theoretical lift according to an energy efficiency grade formula;
according to the theoretical lift, calculating to obtain the corresponding theoretical rotating speed of the shielding pump according to a similarity law;
according to the flow corresponding to the theoretical lift and the theoretical rotating speed, calculating to obtain a corresponding working condition rotating speed through the simulation model;
and calculating the energy efficiency grade data according to the working condition rotating speed.
5. The method for predicting the energy efficiency level of a canned motor pump according to claim 4, further comprising, before calculating the energy efficiency level data according to the operating condition rotation speed:
according to the flow and the corresponding theoretical rotating speed, calculating through the simulation model to obtain a simulation lift;
determining whether a difference between the simulated lift and the theoretical lift is less than a deviation threshold;
if not, the theoretical rotation speed is recalculated.
6. A simulated predictive device for energy efficiency level of a canned motor pump, comprising:
the simulation model building module is used for building a simulation model based on the parameters of the canned motor pump, and comprises the following steps:
confirming a hydraulic model according to the parameters of the shielding pump;
adjusting the geometric parameters of the hydraulic model and extracting a fluid domain according to the geometric parameters;
dividing the fluid domain into a plurality of grids, and obtaining a shielding pump output function corresponding to the grids by defining boundary conditions of the simulation model;
calculating and obtaining a shielding pump output parameter corresponding to the simulation model according to the shielding pump output function;
the optimal solution calculation module is used for applying a plurality of sample points to the simulation model in parallel under the rated working condition, and calculating to obtain an optimal solution of the objective function, and comprises the following steps:
selecting a plurality of sample points to be applied to the simulation model, and calculating to obtain sample parameters;
selecting the geometric parameters and establishing a coordinate system related to the objective function;
fitting the sample parameters under the coordinate system to obtain a fitting response surface;
optimizing extreme points in the fitting response surface to obtain an optimal solution of the objective function;
the performance data calculation module is used for adjusting the rated working condition to a full-flow working condition under the optimal solution of the objective function, and calculating the performance data of the working condition points under the simulation model;
and the energy efficiency grade data calculation module is used for applying the performance data to the simulation model and calculating to obtain energy efficiency grade data.
7. An electronic device, the electronic device comprising:
one or more processors;
a memory for storing one or more programs;
the one or more programs, when executed by the one or more processors, cause the one or more processors to implement the method of simulated prediction of a barrier pump energy efficiency level of any one of claims 1-5.
8. A storage medium containing computer executable instructions which, when executed by a computer processor, are for performing the method of simulated prediction of the barrier pump energy efficiency level of any one of claims 1-5.
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Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2015144310A1 (en) * | 2014-03-26 | 2015-10-01 | Wilo Se | Method for determining the hydraulic operating point of a pump assembly |
| WO2018048432A1 (en) * | 2016-09-10 | 2018-03-15 | Koop Dennis J | Geothermal heat pump design simulation and analysis |
| KR20180122054A (en) * | 2017-05-01 | 2018-11-12 | (주)가교테크 | Building control method based on load prediction based on building energy efficiency rating |
| CN110598316A (en) * | 2019-09-10 | 2019-12-20 | 大连理工大学 | Method for constructing shielded nuclear main pump digital prototype based on beam finite element model |
| CN110765619A (en) * | 2019-10-28 | 2020-02-07 | 中国人民解放军63921部队 | Short-term multi-step prediction method for failure-free canned motor pump failure based on multi-state parameters |
| CN115361841A (en) * | 2022-08-04 | 2022-11-18 | 浙江理工大学 | Shield pump control system and method adapting to all-working-condition operation of data center |
-
2023
- 2023-05-31 CN CN202310626840.8A patent/CN116384009B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2015144310A1 (en) * | 2014-03-26 | 2015-10-01 | Wilo Se | Method for determining the hydraulic operating point of a pump assembly |
| WO2018048432A1 (en) * | 2016-09-10 | 2018-03-15 | Koop Dennis J | Geothermal heat pump design simulation and analysis |
| KR20180122054A (en) * | 2017-05-01 | 2018-11-12 | (주)가교테크 | Building control method based on load prediction based on building energy efficiency rating |
| CN110598316A (en) * | 2019-09-10 | 2019-12-20 | 大连理工大学 | Method for constructing shielded nuclear main pump digital prototype based on beam finite element model |
| CN110765619A (en) * | 2019-10-28 | 2020-02-07 | 中国人民解放军63921部队 | Short-term multi-step prediction method for failure-free canned motor pump failure based on multi-state parameters |
| CN115361841A (en) * | 2022-08-04 | 2022-11-18 | 浙江理工大学 | Shield pump control system and method adapting to all-working-condition operation of data center |
Non-Patent Citations (1)
| Title |
|---|
| Three-dimensional flow field numerical simulation and performance analysis for a new type canned motor pump;CUI Jian-zhong, XIE Fang-wei, LIU Qing-yun, et al.;Proceedings of the Institution of Mechanical Engineers;第227卷(第12期);全文 * |
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