CN115630482A - Water pump model selection system, method and evaluation method - Google Patents
Water pump model selection system, method and evaluation method Download PDFInfo
- Publication number
- CN115630482A CN115630482A CN202211193062.XA CN202211193062A CN115630482A CN 115630482 A CN115630482 A CN 115630482A CN 202211193062 A CN202211193062 A CN 202211193062A CN 115630482 A CN115630482 A CN 115630482A
- Authority
- CN
- China
- Prior art keywords
- water pump
- efficiency
- point
- power frequency
- value
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2111/00—Details relating to CAD techniques
- G06F2111/04—Constraint-based CAD
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Computer Hardware Design (AREA)
- Evolutionary Computation (AREA)
- Geometry (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Control Of Positive-Displacement Pumps (AREA)
Abstract
The invention provides a water pump model selection system, a water pump model selection method and an evaluation method, wherein a power frequency characteristic curve equation and an efficiency curve equation of each type of water pump are established; acquiring a high-efficiency section on a power frequency characteristic curve of each type of water pump; screening for the first time according to the design parameters of the pump set and the high-efficiency section, and screening out the water pump model meeting the preset constraint condition; and screening the water pump model forming the pump group with the lowest total power value from the water pump models screened for the first time, and outputting the water pump model. The intelligent water pump model selection is realized, the cost is reduced, the efficiency is improved, and the equipment is kept to operate efficiently.
Description
Technical Field
The invention relates to the technical field of water pumps, in particular to a water pump model selection system, a water pump model selection method and an evaluation method.
Background
The model selection scheme of the pump set can determine the running state of the water supply equipment to a certain degree, and a good model selection scheme is one of important conditions for keeping the equipment running efficiently. Most of the model selection schemes of equipment units in the same industry are finished through manual experience at present, the intelligent degree is low, the randomness is high, and the consumption of labor and time cost is huge. After the model selection scheme of the water pump unit of the equipment is determined, the evaluation means is single, and an intelligent evaluation flow is lacked.
Disclosure of Invention
Based on the existing problems, the invention provides a water pump model selection system, a water pump model selection method and an evaluation method, and aims to solve the technical problem that the existing water pump model selection is not intelligent enough.
The invention provides a water pump model selection system, which comprises:
the characteristic establishing module is used for establishing a power frequency characteristic curve equation and a corresponding power frequency characteristic curve of each type of water pump, and an efficiency curve equation and a corresponding efficiency curve when the power frequency is in operation;
the characteristic extraction module is connected with the characteristic establishment module and is used for acquiring a high-efficiency section on a power frequency characteristic curve of each type of water pump based on a power frequency characteristic curve equation and an efficiency curve equation;
the storage module is respectively connected with the characteristic establishing module and the characteristic extracting module and is used for storing a power frequency characteristic curve equation, an efficiency curve equation and an efficient section;
the parameter input module is used for inputting design parameters of the pump set, wherein the design parameters comprise design flow, design lift and design number;
the first screening module is respectively connected with the storage module and the parameter input module and is used for carrying out first screening according to the design parameters and the efficient section of the pump set and screening out the water pump model meeting the preset constraint condition;
and the second screening module is connected with the first screening module and used for screening and outputting the water pump model forming the pump group with the lowest total power value from the water pump models screened for the first time.
The invention provides a water pump model selection method, which uses the water pump model selection system and comprises a pre-performed feature extraction step and a model screening step, wherein the feature extraction step comprises the following steps:
a1, pre-establishing and storing a power frequency characteristic curve equation of each type of water pump and an efficiency curve equation during power frequency operation;
a2, acquiring and storing the high-efficiency sections on the power frequency characteristic curve of each type of water pump based on a power frequency characteristic curve equation and an efficiency curve equation;
the model screening step comprises the following steps:
b1, screening for the first time according to input design parameters of a pump set and the high-efficiency sections to screen out the water pump models meeting the preset constraint conditions, wherein the design parameters comprise design flow, design lift and design number;
and B2, screening the water pump model forming the pump set with the lowest total power value from the water pump models screened for the first time, and outputting a model selection result.
Further, in step A1, a power frequency characteristic curve equation is obtained by performing curve fitting on the flow-actual head data of the water pump, and an efficiency curve equation is obtained by performing curve fitting on the flow-actual efficiency data of the water pump.
Further, step A2 includes the steps of:
a21, solving a highest efficiency point on an efficiency curve according to an efficiency curve equation;
step A22, calculating a left efficiency point corresponding to a first preset percentage point of the highest efficiency point which is decreased leftwards on the efficiency curve, and a right efficiency point corresponding to a second preset percentage point of the highest efficiency point which is decreased rightwards;
and A22, substituting the flow value of the highest efficiency point into a power frequency characteristic curve equation to obtain an optimal working condition point, substituting the flow value of the left efficiency point into the power frequency characteristic curve equation to obtain a left working condition point, substituting the flow value of the right efficiency point into the power frequency characteristic curve equation to obtain a right working condition point, and taking a section formed by all working condition points between the left working condition point and the right working condition point as an efficient section of the power frequency characteristic curve.
Further, the first preset percentage point and the second preset percentage point are both 10%.
Further, in step B1, the predetermined constraint condition includes:
selecting the water pump model with the average flow between the flow value of the left working condition point and the flow value of the right working condition point, wherein the average flow is the ratio of the design flow to the number of the designed units; and
selecting a water pump model of which the lift value on the high-efficiency section corresponding to the average flow is not less than the designed lift; and
and selecting the water pump model satisfying the preset label value.
Further, the design parameters further include a manufacturer, and the preset label value is the manufacturer.
Further, step B2 includes:
step B21, forming a data candidate set by the optimal working condition points corresponding to the water pump models screened for the first time, screening the data candidate set for the second time, screening the optimal working condition points with the preset number closest to the target point in the data candidate set, and acquiring the corresponding water pump models; the target point is a coordinate point formed by average flow and design lift;
step B22, combining the models of the water pumps screened for the second time according to the number of the designed pumps to form a plurality of pump groups;
step B23, calculating the total power value of each pump group;
and step B24, selecting the pump group with the lowest total power value as an output result, wherein the output result comprises the type of the water pump, the number of the water pumps and the total power value.
The invention relates to a water pump model selection evaluation method, which is used for evaluating a pump set to be evaluated and is characterized in that the water pump model selection system comprises a pre-performed characteristic extraction step and a pre-performed pump set evaluation step;
the characteristic extraction step comprises:
a1, pre-establishing and storing a power frequency characteristic curve equation of each type of water pump and an efficiency curve equation during power frequency operation;
a2, acquiring and storing efficient sections on the power frequency characteristic curve of each type of water pump based on a power frequency characteristic curve equation and an efficiency curve equation;
the pump set evaluation step comprises:
step C1, obtaining basic data for evaluating a pump group to be evaluated, wherein the basic data comprises the type of a water pump, the rated flow, the given pressure, the inlet pressure and the number of the water pumps corresponding to the pump group to be evaluated;
step C2, acquiring the corresponding high-efficiency section of the pump group to be evaluated according to the model of the pump group water pump to be evaluated, and judging whether the pump group to be evaluated meets the preset judgment condition or not by combining the basic data:
if yes, executing step C3;
if not, executing the step C4;
c3, outputting a reasonable judgment result of the pump group to be evaluated;
step C4, taking the rated flow as the design flow, the number of water pumps as the design number, and the difference value between the given pressure and the inlet pressure as the design lift, and taking the design flow, the design lift and the design number as design parameters;
c5, performing primary screening according to the design parameters and the stored high-efficiency sections of various water pump models, and screening out the water pump models which meet the preset constraint condition;
and C6, screening the water pump model forming the pump group with the lowest total power value from the water pump models screened for the first time, and outputting a model selection result.
Further, the preset judgment condition includes:
the ratio of the rated flow/the number of the water pumps is between the flow value of the left working condition point and the flow value of the right working condition point of the high-efficiency section of the pump group to be evaluated;
the difference value of the given pressure and the inlet pressure is smaller than a lift value on a high-efficiency section of the pump group to be evaluated corresponding to the ratio of the rated flow to the number of the water pumps;
the difference value between the given pressure and the inlet pressure is not less than a preset value, and the preset value is the difference value between the lift value of the right working point of the high-efficiency section and a preset constant.
The invention has the beneficial technical effects that: by obtaining a power frequency characteristic curve equation and an efficiency curve equation, calculating the efficient section of each water pump type to perform water pump type selection, realizing the intellectualization of water pump type selection, reducing the cost, improving the efficiency and keeping the equipment to operate efficiently.
Drawings
FIGS. 1-3 are schematic block diagrams of a water pump model selection system according to the present invention;
4-6 are flow charts illustrating steps of a water pump model selection method according to the present invention;
FIG. 7 is a flowchart illustrating steps of a water pump model selection evaluation method according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It should be noted that the embodiments and features of the embodiments of the present invention may be combined with each other without conflict.
The invention is further described with reference to the following drawings and specific examples, which are not intended to be limiting.
Referring to fig. 1, the present invention provides a water pump model selection system, including:
the characteristic establishing module (1) is used for establishing a power frequency characteristic curve equation and a corresponding power frequency characteristic curve of each type of water pump, and an efficiency curve equation and a corresponding efficiency curve when the power frequency is in operation;
the characteristic extraction module (2) is connected with the characteristic establishment module (1) and is used for acquiring a high-efficiency section on a power frequency characteristic curve of each type of water pump based on a power frequency characteristic curve equation and an efficiency curve equation;
the storage module (3) is respectively connected with the characteristic establishing module (1) and the characteristic extracting module (2) and is used for storing a power frequency characteristic curve equation, an efficiency curve equation and an efficient section;
the parameter input module (4) is used for inputting design parameters of the pump set, and the design parameters comprise design flow, design lift and design number;
the first screening module (5) is respectively connected with the storage module (3) and the parameter input module (4) and is used for carrying out first screening according to the design parameters and the efficient sections of the pump set to screen out the models of the water pumps meeting the preset constraint conditions;
and the second screening module (6) is connected with the first screening module (5) and is used for screening the water pump model forming the pump group with the lowest total power value from the water pump models screened for the first time and outputting the water pump model.
Specifically, the feature establishing module (1) is configured to: carrying out curve fitting on the flow-actual lift data of the water pump to obtain a power frequency characteristic curve equation, and carrying out curve fitting on the flow-actual efficiency data of the water pump to obtain an efficiency curve equation; and drawing a power frequency characteristic curve according to the power frequency characteristic curve equation, and drawing an efficiency curve equation according to the efficiency curve equation.
Referring to fig. 2, specifically, the feature extraction module (2) includes:
a first extraction unit (21) for finding a highest efficiency point on the efficiency curve according to the efficiency curve equation;
the second extraction unit (22) is connected with the first extraction unit (21) and is used for calculating a left efficiency point corresponding to the fact that the highest efficiency point on the efficiency curve is decreased leftwards by a first preset percentage point and a right efficiency point corresponding to the fact that the highest efficiency point is decreased rightwards by a second preset percentage point;
and the third extraction unit (23) is connected with the second extraction unit (22) and is used for substituting the flow value of the highest efficiency point into the power frequency characteristic curve equation to obtain an optimal working condition point, substituting the flow value of the left efficiency point into the power frequency characteristic curve equation to obtain a left working condition point, substituting the flow value of the right efficiency point into the power frequency characteristic curve equation to obtain a right working condition point, and taking a section formed by all working condition points between the left working condition point and the right working condition point as an efficient section of the power frequency characteristic curve.
Specifically, the first preset percentage and the second preset percentage may be different or the same, for example, both are 10%.
Specifically, the predetermined constraint condition includes:
selecting the type of the water pump with the average flow between the left working condition point and the right working condition point, wherein the average flow is the ratio of the design flow to the number of the designed units;
selecting a high-efficiency section corresponding to the average flow, wherein the lift value of the high-efficiency section is greater than the design lift;
and selecting the water pump model satisfying the preset label value.
Specifically, the design parameters further include a manufacturer, and the preset tag value is the manufacturer.
Referring to fig. 3, in particular, the second screening module (6) comprises:
the first calculation unit (61) is used for forming a data candidate set by the optimal working condition points corresponding to the water pump models screened for the first time, screening the data candidate set for the second time, and screening the water pump model corresponding to the optimal working condition point closest to the target point in the data candidate set; the target point is a coordinate point formed by average flow and design lift;
the second calculating unit (62) is connected with the first calculating unit (61) and is used for combining the water pump models screened out for the second time according to the number of the designed pumps to form a plurality of pump groups and calculating the total power value of each pump group;
and the third calculating unit (63) is connected with the second calculating unit (61) and is used for selecting the pump group with the lowest total power value as an output result, and the output result comprises the type of the water pump, the number of the water pumps and the total power value.
Referring to fig. 4, the present invention further provides a water pump model selection method, using the water pump model selection system, including a pre-performed feature extraction step and a model selection step, where the feature extraction step includes:
a1, pre-establishing and storing a power frequency characteristic curve equation of each type of water pump and an efficiency curve equation during power frequency operation;
a2, acquiring and storing the high-efficiency sections on the power frequency characteristic curve of each type of water pump based on a power frequency characteristic curve equation and an efficiency curve equation;
the model screening step comprises the following steps:
b1, screening for the first time according to input design parameters of a pump set and the high-efficiency sections to screen out the water pump models meeting the preset constraint conditions, wherein the design parameters comprise design flow, design lift and design number;
and B2, screening the water pump model forming the pump set with the lowest total power value from the water pump models screened for the first time, and outputting a model selection result.
Further, in step A1, curve fitting is performed on the flow-actual lift data of the water pump to obtain a power frequency characteristic curve equation, and curve fitting is performed on the flow-actual efficiency data of the water pump to obtain an efficiency curve equation.
And solving the model parameters according to the flow-actual lift data and the flow-actual efficiency data by establishing a model, and fitting to obtain a power frequency characteristic curve equation and an efficiency curve equation.
Specifically, the power frequency characteristic curve equation is as follows: h = H 0 +s 0 *Q 2 ；
Wherein H is the actual lift of the water pump, H 0 Is the virtual total head, s, of Q =0 water pump 0 Is the virtual drag coefficient in the pump body and Q is the flow through the water pump.
Specifically, the efficiency curve equation is as follows:
η(Q,w)＝w 0 +w 1 Q 1 +…+w n Q M ；
where η is the pump operating efficiency, Q is the flow, M is the order of the polynomial, w = (w) 0 ,w 1 ,…,w M ) Representing the polynomial coefficients.
Judging the fitting effect of the equation under different order selection based on a cross validation method, selecting a proper polynomial order, and reserving order and coefficient item data after the fitting process is completed to serve as a data source for subsequent use.
Referring to fig. 5, further, step A2 includes the following steps:
step A21, solving a highest efficiency point on an efficiency curve according to an efficiency curve equation;
step A22, calculating a left efficiency point corresponding to a first preset percentage point of the highest efficiency point on the efficiency curve, which is decreased to the left, and a right efficiency point corresponding to a second preset percentage point of the highest efficiency point, which is decreased to the right;
and A22, substituting the flow value of the highest efficiency point into a power frequency characteristic curve equation to obtain an optimal working condition point, substituting the flow value of the left efficiency point into the power frequency characteristic curve equation to obtain a left working condition point, substituting the flow value of the right efficiency point into the power frequency characteristic curve equation to obtain a right working condition point, and taking a section formed by all working condition points between the left working condition point and the right working condition point as an efficient section of the power frequency characteristic curve.
Maximum efficiency point as optimum operating point (Q) high ,H high )。
The abscissa of the left working point is the flow value of the left working point, and the ordinate is the corresponding lift value.
The abscissa of the right working point is the flow value of the right working point, and the ordinate is the corresponding lift value.
Further, the first preset percentage point and the second preset percentage point are both 10%.
Further, in step B1, the predetermined constraint condition includes:
selecting the type of the water pump with the average flow between the flow value of the left working condition point and the flow value of the right working condition point, wherein the average flow is the ratio of the design flow to the number of the designed units; selecting a water pump model of which the lift value on the high-efficiency section corresponding to the average flow is not less than the designed lift; and
and selecting the water pump model satisfying the preset label value.
Further, the design parameters further include a manufacturer, and the preset label value is the manufacturer.
A certain manufacturer can be selected, and the model of the water pump of the manufacturer can be specially selected.
Input is design flow Q Is provided with Design lift H Is provided with The number of water pumps needed by the unit is the designed number n Is provided with (default 2), i.e., average flow = design flow/number of design units, i.e., Q Is provided with /n；
Q left <＝Q Is provided with /n Is provided with <＝Q right Is the first presetThe beam condition.
Point C (Q) Is provided with /n Is provided with ,H Is provided with ) Falling below the high-efficiency section of the power frequency operation of the water pump as a second preset condition, and selecting the second preset condition as Q Is provided with /n Is provided with The lift value of the corresponding high-efficiency section is more than or equal to H Is provided with I.e. a second preset constraint is fulfilled.
Referring to fig. 6, further, step B2 includes:
step B21, forming a data candidate set by the optimal working condition points corresponding to the water pump models screened for the first time, screening the data candidate set for the second time, screening the optimal working condition points with the preset number, which are closest to the target point, in the data candidate set, and acquiring the corresponding water pump models; the target point is a coordinate point formed by average flow and design lift;
step B22, combining the models of the water pumps screened for the second time according to the number of the designed pumps to form a plurality of pump groups;
step B23, calculating the total power value of each pump group;
and step B24, selecting the pump group with the lowest total power value as an output result, wherein the output result comprises the type of the water pump, the number of the water pumps and the total power value.
Based on the nearest neighbor algorithm, screening out the optimal working condition points with the preset number closest to the target point in the data candidate set and obtaining the corresponding water pump models,
the preset number is 5, for example, 5 optimal working condition points closest to the target point are selected, water pump models corresponding to the optimal working condition points are further obtained, pump groups are formed by the water pump models, the power value of the water pump is obtained according to the water pump models, the total power value of each pump group is calculated, and the lowest total power value is selected as the optimal water pump output.
Referring to fig. 7, the invention further provides a water pump model selection evaluation method, which is used for evaluating a pump set to be evaluated, and the water pump model selection system comprises a feature extraction step and a pump set evaluation step which are performed in advance;
the characteristic extraction step comprises:
a1, pre-establishing and storing a power frequency characteristic curve equation of each type of water pump and an efficiency curve equation during power frequency operation;
a2, acquiring and storing the high-efficiency sections on the power frequency characteristic curve of each type of water pump based on a power frequency characteristic curve equation and an efficiency curve equation;
the pump set evaluation step includes:
step C1, obtaining basic data for evaluating the pump group to be evaluated, wherein the basic data comprises the type, rated flow, given pressure, inlet pressure and the number of the water pumps corresponding to the pump group to be evaluated;
step C2, acquiring a corresponding high-efficiency section of the pump set to be evaluated according to the type of the pump set water pump to be evaluated, and judging whether the pump set to be evaluated meets a preset judgment condition or not by combining basic data:
if yes, executing step C3;
if not, executing the step C4;
c3, outputting a reasonable judgment result of the pump group to be evaluated;
step C4, taking the rated flow as the design flow, the number of water pumps as the design number, and the difference value between the given pressure and the inlet pressure as the design lift, and taking the design flow, the design lift and the design number as design parameters;
c5, performing primary screening according to the design parameters and the stored high-efficiency sections of various water pump models, and screening out the water pump models which meet the preset constraint condition;
and C6, screening the water pump model forming the pump group with the lowest total power value from the water pump models screened for the first time, and outputting a model selection result.
The model selection result comprises the model number of the water pump, the quantity of the water pumps and the total power value of the water pumps.
The invention can also evaluate some selected pump groups, the basic data also comprises the type of water supply equipment, if the equipment is non-negative pressure equipment, the inlet pressure is processed to be an abnormal value, and if the equipment is not non-negative pressure equipment, the inlet pressure is 0.
And acquiring a high-efficiency section obtained by pre-calculation according to the water pump model of the pump set, and evaluating the pump set.
Further, the preset judgment condition includes:
the ratio of the rated flow/the number of the water pumps is between the flow value of the left working condition point and the flow value of the right working condition point of the high-efficiency section of the pump group to be evaluated;
the difference value of the given pressure and the inlet pressure is smaller than a lift value on a high-efficiency section of the pump group to be evaluated corresponding to the ratio of the rated flow to the number of the water pumps;
the difference value between the given pressure and the inlet pressure is not less than a preset value, and the preset value is the difference value between the lift value of the right working condition point of the high-efficiency section and a preset constant.
Rated flow rate Q Rated value Given pressure H Given a Inlet pressure H in And the number n of water pumps;
Q rated value A first preset judgment condition is set between the left working condition point and the right working condition point;
dot (Q) Rated value /n，H Given a ) A second preset judgment condition is set below the high-efficiency section;
H given a -H in >H right C (C is a predetermined constant, H) right The lift value of the right operating point of the high-efficiency section) as a third preset judgment condition.
The water pump model selection system and the water pump model selection method automatically perform water pump model selection, can assist subsequent data analysis work on the operation state of water supply equipment (especially constructed equipment), give a reasonable model selection diagnosis report, output the reasonable diagnosis report if the diagnosis is reasonable, and give a model selection suggestion through an automatic model selection method if the diagnosis is unreasonable.
While the invention has been described with reference to a preferred embodiment, it will be understood by those skilled in the art that various changes in form and detail may be made therein without departing from the spirit and scope of the invention.
Claims (10)
1. A water pump model selection system, comprising:
the characteristic establishing module is used for establishing a power frequency characteristic curve equation and a corresponding power frequency characteristic curve of each type of water pump, and an efficiency curve equation and a corresponding efficiency curve when power frequency operates;
the characteristic extraction module is connected with the characteristic establishment module and used for acquiring the high-efficiency section on the power frequency characteristic curve of each type of water pump based on a power frequency characteristic curve equation and an efficiency curve equation;
the storage module is respectively connected with the characteristic establishing module and the characteristic extracting module and is used for storing the power frequency characteristic curve equation, the efficiency curve equation and the efficient section;
the pump set comprises a parameter input module, a parameter output module and a parameter output module, wherein the parameter input module is used for inputting design parameters of a pump set, and the design parameters comprise design flow, design lift and design number;
the first screening module is respectively connected with the storage module and the parameter input module and is used for carrying out first screening according to the design parameters of the pump set and the high-efficiency section to screen out the water pump model meeting the preset constraint condition;
and the second screening module is connected with the first screening module and used for screening and outputting the water pump model forming the pump group with the lowest total power value from the water pump models screened for the first time.
2. A water pump model selection method, characterized in that a water pump model selection system according to claim 1 is used, and the method comprises a pre-performed feature extraction step and a model selection step, wherein the feature extraction step comprises:
a1, pre-establishing and storing a power frequency characteristic curve equation of each type of water pump and an efficiency curve equation during power frequency operation;
a2, acquiring and storing efficient sections on the power frequency characteristic curve of each type of water pump based on a power frequency characteristic curve equation and an efficiency curve equation;
the model screening step comprises the following steps:
b1, performing first screening according to input design parameters of a pump set and the efficient sections to screen out the models of the water pumps meeting preset constraint conditions, wherein the design parameters comprise design flow, design lift and design number;
and B2, screening the water pump model forming the pump group with the lowest total power value from the water pump models screened for the first time, and outputting a model selection result.
3. The water pump model selection method according to claim 2, wherein in step A1, the power frequency characteristic curve equation is obtained by performing curve fitting on the flow-actual head data of the water pump, and the efficiency curve equation is obtained by performing curve fitting on the flow-actual efficiency data of the water pump.
4. The water pump model selection method as claimed in claim 2, wherein the step A2 comprises the steps of:
step A21, solving a highest efficiency point on the efficiency curve according to the efficiency curve equation;
step A22, calculating a left efficiency point corresponding to a first preset percentage point of the highest efficiency point which is decreased leftwards on the efficiency curve, and a right efficiency point corresponding to a second preset percentage point of the highest efficiency point which is decreased rightwards;
and A22, substituting the flow value of the highest efficiency point into the power frequency characteristic curve equation to obtain an optimal working condition point, substituting the flow value of the left efficiency point into the power frequency characteristic curve equation to obtain a left working condition point, substituting the flow value of the right efficiency point into the power frequency characteristic curve equation to obtain a right working condition point, and taking a section formed by all working condition points between the left working condition point and the right working condition point as an efficient section of the power frequency characteristic curve.
5. The water pump model selection method as recited in claim 4, wherein the first predetermined percentage point and the second predetermined percentage point are both 10%.
6. The water pump model selection method according to claim 4, wherein in the step B1, the predetermined constraint condition comprises:
selecting the water pump model with the average flow between the flow value of the left working condition point and the flow value of the right working condition point, wherein the average flow is the ratio of the design flow to the number of the design units; and
and selecting the type of the water pump of which the lift value on the high-efficiency section corresponding to the average flow is not less than the designed lift.
7. The water pump model selection method as claimed in claim 6, wherein the predetermined constraint condition further comprises:
selecting a water pump model meeting a preset label value;
the design parameters further comprise manufacturers, and the preset label value is the manufacturers.
8. The water pump model selection method as claimed in claim 6, wherein the step B2 comprises:
step B21, forming a data candidate set by the optimal working condition points corresponding to the water pump models screened for the first time, screening the data candidate set for the second time, screening the optimal working condition points which are closest to a target point and are in the preset number in the data candidate set, and acquiring the corresponding water pump models; the target point is a coordinate point formed by the average flow and the design head;
step B22, combining the water pump models screened for the second time according to the designed number to form a plurality of pump groups;
step B23, calculating the total power value of each pump group;
and step B24, selecting the pump group with the lowest total power value as an output result, wherein the output result comprises the type of the water pump, the number of the water pumps and the total power value.
9. A water pump model selection evaluation method is used for evaluating a pump group to be evaluated, and is characterized in that the water pump model selection system according to claim 1 is used, and comprises a characteristic extraction step and a pump group evaluation step which are carried out in advance;
the feature extraction step includes:
a1, pre-establishing and storing a power frequency characteristic curve equation of each type of water pump and an efficiency curve equation during power frequency operation;
a2, acquiring and storing efficient sections on the power frequency characteristic curve of each type of water pump based on a power frequency characteristic curve equation and an efficiency curve equation;
the pump set evaluation step includes:
step C1, obtaining basic data for evaluating the pump group to be evaluated, wherein the basic data comprises the water pump model, the rated flow, the given pressure, the inlet pressure and the number of water pumps corresponding to the pump group to be evaluated;
step C2, acquiring the corresponding high-efficiency section of the pump group to be evaluated according to the water pump model of the pump group to be evaluated, and judging whether the pump group to be evaluated meets a preset judgment condition or not by combining the basic data:
if yes, executing step C3;
if not, executing the step C4;
c3, outputting a reasonable judgment result of the pump group to be evaluated;
step C4, taking the rated flow as a design flow, the number of water pumps as a design number, and the difference value between the given pressure and the inlet pressure as a design lift, and taking the design flow, the design lift and the design number as design parameters;
c5, screening for the first time according to the design parameters and the stored high-efficiency sections of various water pump models to screen out the water pump models which meet preset constraint conditions;
and C6, screening the water pump model forming the pump group with the lowest total power value from the water pump models screened for the first time, and outputting a model selection result.
10. The water pump model selection evaluation method as claimed in claim 9, wherein the preset judgment condition comprises:
the ratio of the rated flow to the number of the water pumps is between the flow value of the left working point and the flow value of the right working point of the high-efficiency section of the pump group to be evaluated;
the difference value of the given pressure and the inlet pressure is smaller than a lift value on the high-efficiency section of the pump group to be evaluated corresponding to the ratio of the rated flow to the number of the water pumps;
and the difference value between the given pressure and the inlet pressure is not less than a preset value, and the preset value is the difference value between the lift value of the right working condition point of the high-efficiency section and a preset constant.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211193062.XA CN115630482A (en) | 2022-09-28 | 2022-09-28 | Water pump model selection system, method and evaluation method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211193062.XA CN115630482A (en) | 2022-09-28 | 2022-09-28 | Water pump model selection system, method and evaluation method |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN115630482A true CN115630482A (en) | 2023-01-20 |
Family
ID=84904538
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202211193062.XA Pending CN115630482A (en) | 2022-09-28 | 2022-09-28 | Water pump model selection system, method and evaluation method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN115630482A (en) |
-
2022
- 2022-09-28 CN CN202211193062.XA patent/CN115630482A/en active Pending
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN112257296B (en) | Improved genetic algorithm-based job shop scheduling method with cache constraint | |
| CN109946965B (en) | Discrete manufacturing workshop scheduling method based on improved multi-target Jaya algorithm | |
| CN106971236A (en) | A kind of flexible job shop based on genetic algorithm dispatching method in batches | |
| CN116827350B (en) | Flexible work platform intelligent supervision method and system based on cloud edge cooperation | |
| CN112232548A (en) | Machining workshop intelligent scheduling optimization method and system based on genetic algorithm | |
| CN114576554B (en) | Hydrogen compression module control method and device based on neural network | |
| CN112686474A (en) | Parallel assembly line balancing method based on improved water wave optimization algorithm | |
| CN115630482A (en) | Water pump model selection system, method and evaluation method | |
| CN113836756A (en) | Intelligent monitoring method and system for annealing process of three-dimensional wound core transformer | |
| CN112348323A (en) | Multi-target energy supply and operation flexible scheduling method | |
| CN113268946B (en) | Chip layout method based on minimum connection sum | |
| CN112922569B (en) | Method for determining optimal operation state of pressurization and partial pressure mode of oil field water injection pipe network | |
| CN117113127A (en) | Oil pumping well energy consumption analysis method based on K-means clustering | |
| CN110956675B (en) | Method and device for automatically generating technology maturity curve | |
| CN106683141A (en) | Configurable quick texture compressing method | |
| CN115526484A (en) | Flexible comprehensive scheduling method considering equipment loss | |
| CN116050559A (en) | Electronic device and method for screening and dispatching work rules for work stations | |
| CN115796464A (en) | Worker distribution optimization method and device for production line | |
| CN107766290A (en) | Convergent multiple regression engineering statistics new method | |
| CN113821951A (en) | Intelligent method for identifying and combining cavities of solder layer of IGBT power module | |
| CN113595152A (en) | Power grid AGC instruction optimal distribution method and system based on thermal power generating unit regulating rate envelope curve | |
| CN112560947A (en) | Clustering method and device based on energy supply and demand structure analysis | |
| CN113505818A (en) | Aluminum melting furnace energy consumption abnormity diagnosis method, system and equipment with improved decision tree algorithm | |
| CN111734674A (en) | Centrifugal pump multi-working-condition energy-saving optimization method based on genetic algorithm | |
| CN108345999B (en) | Manufacturing system production process information reduction method based on dynamic programming |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |