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CN-121980710-A - Multi-objective optimization design method for magnetic pump impeller

CN121980710ACN 121980710 ACN121980710 ACN 121980710ACN-121980710-A

Abstract

The invention provides a multi-target optimization design method for a magnetic pump impeller, which relates to the technical field of multi-target optimization design methods for impellers, and comprises the steps of sampling a design parameter space by adopting optimal Latin hypercube sampling to generate a first sample set, and obtaining the total rotational inertia corresponding to each sample point through a total rotational inertia model; the method comprises the steps of adopting an NSGA-III algorithm to randomly generate new sample points with target number, selecting next generation father sample points from the front grade, generating child sample points until reaching the maximum evolution algebra of the sample points, setting a magnetic transmission stability dominant screening criterion, and obtaining geometrical parameters corresponding to the front sample points meeting the screening condition as optimized data. The total rotational inertia is used as a pre-physical screening criterion, so that the transmission stability requirement of the magnetic pump is synchronously considered from the source in the optimization process, and a set of efficient intelligent optimization flow is formed by combining the optimal Latin hypercube sampling, the physical pre-screening based on the rotational inertia and the NSGA-III multi-objective evolutionary algorithm.

Inventors

  • WANG MENG
  • CHEN JIEDI

Assignees

  • 江苏爱马仕泵业制造有限公司

Dates

Publication Date
20260505
Application Date
20260227

Claims (10)

  1. 1. The multi-objective optimization design method for the magnetic pump impeller is characterized by comprising the following steps of: S1, carrying out structure distinction on impellers to determine a plurality of structures, determining geometric parameters of each structure, setting upper and lower limits of the geometric parameters, counting the upper and lower limits of all the geometric parameters to form a design parameter space, constructing a total rotational inertia model of the impellers based on the types of the geometric parameters, and constructing a CFD simulation model taking the geometric parameters as input and taking a target coefficient as output, wherein the target coefficient is pump hydraulic efficiency, cavitation performance index and torque pulsation coefficient; S2, sampling a design parameter space by adopting optimal Latin hypercube sampling to generate a first sample set, obtaining total rotational inertia corresponding to each sample point through a total rotational inertia model, and screening the first sample set through the total rotational inertia to obtain a second sample set; S3, simulating sample points in the second sample set through a CFD simulation model to obtain pump hydraulic efficiency, cavitation performance indexes and torque pulsation coefficients corresponding to each sample point, and updating the upper limit and the lower limit of the geometric parameters according to the geometric parameters corresponding to the three sample points when the pump hydraulic efficiency, the cavitation performance indexes and the torque pulsation coefficients are optimal; S4, based on the upper limit and the lower limit of the updated geometric parameters, adopting an NSGA-III algorithm to randomly generate new sample points with target numbers, simulating each new sample point through a CFD simulation model to obtain a target coefficient of each new sample point, adopting a Pareto domination method to divide the target coefficient of the new sample point into different leading edge grades, and selecting a next generation of father sample point from the leading edge grades; S5, simulating binary cross and polynomial mutation on parent sample points, generating child sample points until reaching the maximum evolution algebra of the sample points, extracting the leading edge sample points of the first leading edge level in the maximum evolution algebra to form a pareto solution set, setting a magnetic transmission stability dominant screening criterion, screening the leading edge sample points in the pareto solution set, and obtaining geometrical parameters corresponding to the leading edge sample points meeting screening conditions as optimized data.
  2. 2. The method for optimizing the design of the pump impeller of the magnetic pump with multiple targets according to claim 1, wherein the calculating of the total moment of inertia corresponding to each sample point comprises the following specific steps: carrying out structure division on the impeller to determine a plurality of structures, dividing the structures into a main disc, single blades and a hub, determining geometric parameters of each structure and setting upper and lower limits of the geometric parameters, wherein the geometric parameters comprise impeller outlet diameter, impeller inlet diameter, impeller outlet width, blade inlet mounting angle, blade outlet mounting angle, blade number, blade wrap angle and hub ratio; the moment of inertia of each region, the moment of inertia of the body disc, is calculated separately, from its own mass multiplied by the square of the radius of the outlet, multiplied by a factor of one half. The moment of inertia of an individual blade is then equal to the square of the blade mass times the sum of the inlet and outlet diameters. The moment of inertia of the hub is calculated in a similar way to a disc, and is the mass of the hub multiplied by half of the square of the radius of the hub; The total moment of inertia of the impeller is equal to the inertia of the main body disc, plus the sum of the inertia of all the blades, i.e. the inertia of a single blade multiplied by the total number of blades, plus the inertia of the hub.
  3. 3. The method for optimizing the design of the pump impeller of the magnetic pump with multiple targets according to claim 2, wherein the target coefficient is calculated by the specific steps of: Constructing a CFD simulation model taking geometric parameters as input and target coefficients as output, determining each characteristic flow point of the impeller, namely a characteristic flow point, a zero eight-time characteristic flow small flow point and a point two-time characteristic flow large flow point, respectively calculating the pump hydraulic efficiency of the impeller at each characteristic flow point by using the CFD simulation model, and carrying out weighted summation on the three pump hydraulic efficiencies according to preset weight coefficients, wherein the weight of the pump hydraulic efficiency of the characteristic flow point is zero six, and the weight of the pump hydraulic efficiency of two non-characteristic flow points is zero two, so as to form a first target coefficient for evaluating the impeller characteristics; Acquiring cavitation performance indexes of the impeller at the characteristic flow points through a CFD simulation model, and directly taking the indexes as second target coefficients for evaluating the cavitation resistance of the impeller; in CFDF simulation model, setting rotation period of impeller and sampling interval, obtaining instantaneous fluid torque time sequence data of impeller in rotation period by transient simulation, determining maximum and minimum values of torque of impeller in rotation period according to time sequence data, calculating average value of torque, dividing difference between maximum and minimum values of torque by average value of torque to obtain third target coefficient.
  4. 4. The method for optimizing the design of the pump impeller of the magnetic pump with multiple targets according to claim 1, wherein the step of obtaining the second sample set comprises the following specific steps: sampling the design parameter space with optimal Latin hypercube sampling to generate a first sample set, i.e. generating Sample points And screening out sample points with total moment of inertia exceeding a preset allowable range based on the total moment of inertia of each sample point to obtain a second sample set, and respectively simulating the sample points in the second sample set through a CFD simulation model to obtain pump hydraulic efficiency, cavitation performance indexes and torque pulsation coefficients corresponding to each sample point.
  5. 5. The method for multi-objective optimization design of a magnetic pump impeller according to claim 4, wherein the analyzing of the second sample set comprises the following specific steps: carrying out global Sobol sensitivity analysis on the second sample set, and calculating a first-order sensitivity index of each geometrical parameter on pump hydraulic efficiency, cavitation performance index and torque pulsation coefficient, wherein the first-order sensitivity index is specifically as follows: For each target coefficient, calculating the ratio of the expected variance of the target coefficient condition to the total variance of the target coefficient when a certain geometric parameter is fixed to obtain a first-order sensitivity index of the geometric parameter independent change to the target coefficient, wherein the target coefficient condition is expected to refer to the variance of a sequence formed by the expected values of the target coefficient on all possible values of the target coefficient when the certain geometric parameter is fixed, and the total variance of the target coefficient is the total variance of the values of the target coefficient on all sample points in the second sample set.
  6. 6. The method for optimizing the design of the pump impeller of the magnetic pump with multiple targets according to claim 5, wherein the updating of the upper limit and the lower limit of the geometric parameter is carried out, and the specific steps are as follows: Respectively positioning three optimal sample points with highest hydraulic efficiency, lowest cavitation performance index and lowest torque pulsation coefficient of the pump, determining that the first-order sensitivity index is higher than a preset highest index threshold value as a high-sensitivity index, analyzing the distribution characteristics of the high-sensitivity index in the sample points, namely that the value of the high-sensitivity index in the optimal sample points continuously approaches the boundary of the original design parameter space, indicating that the optimization direction of the geometric parameter is definitely directed to the outer side of the boundary, and symmetrically expanding the boundary outwards according to a preset expansion proportion; For the geometric parameters of which the first-order sensitivity indexes are lower than a preset lowest index threshold, judging the geometric parameters as non-sensitive parameters, calculating the value distribution of the non-sensitive parameters on all sample points in a second sample set, determining the mean value and the distribution range of the non-sensitive parameters, and symmetrically shrinking the upper and lower value limits of the non-sensitive parameters according to a preset shrinkage proportion by taking the mean value point as the center to form a new narrower and more focused value range; the upper and lower limits of the geometric parameters are updated in this way.
  7. 7. The method for optimizing the design of the pump impeller of the magnetic pump with multiple targets according to claim 6, wherein the sample points are divided into different leading edge grades, and the method comprises the following specific steps: Based on the upper limit and the lower limit of the updated geometric parameters, adopting an NSGA-III algorithm to randomly generate new sample points with target numbers, simulating each new sample point through a CFD simulation model to obtain a target coefficient of each new sample point, adopting a Pareto dominance method to divide the new sample points into different leading edge grades, and selecting a next generation of father sample points from the leading edge grades; The specific method for dividing the sample points into different front-edge grades is that the dominant condition of the sample points is set, if the dominant condition is not worse than other sample points on the target coefficient and is strictly better than at least one target coefficient, the dominant condition is called that the sample points are dominant, the points which are not dominant by any other sample points are found out from all the sample points, the points which are not dominant by any other sample points are classified into first front-edge grades, then the points of the first grades are temporarily removed, the points which are not dominant are found out again in the rest points, a second front-edge grade is formed, and the process is repeated until all the sample points are allocated with the front-edge grades.
  8. 8. The multi-objective optimization design method for the pump impeller of the magnetic pump according to claim 7, wherein the most suitable next generation parent sample point is selected from the leading edge level, and the specific steps are as follows: According to the target coefficient distribution in the first front grade, dynamically generating a group of reference points uniformly distributed on a standardized hyperplane, mapping each first front grade sample point to the hyperplane, calculating the vertical distance between each first front grade sample point and all the reference points, correlating each first front grade sample point to the reference point closest to the reference point, preferentially selecting the sample points corresponding to the reference points with fewer correlated sample points as the father sample points by evaluating the number of the sample points correlated to each reference point, performing simulated binary crossover and polynomial variation on the father sample points, generating child sample points, and repeating calculation until the maximum evolution algebra is reached.
  9. 9. The method for optimizing the design of the pump impeller of the magnetic pump according to claim 8, wherein the method for optimizing the design of the pump impeller of the magnetic pump is characterized by comprising the following steps of: The parent sample points are paired randomly pairwise. For each pair of father and all variables, firstly, performing cross operation, namely independently generating a random number between zero and one for each variable, calculating the expansion factor of the variable based on the random number, and if the random number is smaller than or equal to zero point five, the expansion factor is equal to twenty-one power of two times of the random number; And respectively generating new values of the two children on the variable by using the calculated expansion factors, wherein the value of the first child is equal to the value of the first parent multiplied by an added expansion factor, the value of the second parent multiplied by a subtracted expansion factor, and the sum obtained is multiplied by zero point five. The value of the second child is obtained by multiplying the value of the first parent by a decreasing expansion factor, multiplying the value of the second parent by a increasing expansion factor and multiplying the obtained sum by a zero point; After the crossover is completed, a mutation operation is carried out, a new mutation judgment random number between zero and one is generated for each variable in the offspring, if the random number is not smaller than zero and one and two and five, the variable is kept unchanged, if the random number is smaller than zero and one and five, mutation calculation is carried out, firstly, a new mutation parameter is generated for the variable, which is a random number between zero and one, then, the proportion of the distance from the current variable value to the lower limit of the value of the new mutation parameter to the total value range of the new mutation parameter is calculated, the proportion of the distance from the upper limit of the new mutation parameter to the current value of the new mutation parameter to the same range is calculated, the disturbance factor of the variable is calculated based on the mutation parameter, if the mutation parameter is smaller than zero and five, the disturbance factor is determined by a series of calculation comprising the proportion, if the mutation parameter is larger than zero and five, the disturbance factor is determined by another group of calculation, and finally, the new mutation parameter value is equal to the product of the original variable value plus the disturbance factor and the total value range of the new mutation parameter is independently carried out on all dimensions of each child individual, and all child individual offspring sample points are formed after crossover and mutation are completed.
  10. 10. The method for multi-objective optimization design of a magnetic pump impeller according to claim 9, wherein the method for multi-objective optimization design of the magnetic pump impeller is characterized by comprising the following specific steps: extracting all the sample points of the first leading edge level of the sample points of the maximum evolution algebra to form a pareto optimal solution set, setting a magnetic transmission stability dominant screening criterion, and screening the sample points in the pareto optimal solution set, wherein the method specifically comprises the following steps: Setting an ideal matching space of total moment of inertia, directly removing sample points of the pareto optimal solution set, which deviate from an ideal matching interval, carrying out normalization processing on target coefficients of the rest sample points, presetting a group of weight coefficients, respectively carrying out weighted calculation on the preset weight coefficients and the target coefficients, constructing a weighted comprehensive performance index integrating the highest hydraulic efficiency, the highest cavitation performance index and the highest torque pulsation index of the pump, simultaneously calculating the variance of the relative deviation between the target coefficient of each sample point and the optimal value on the front edge of each pareto, and selecting geometric parameters corresponding to the sample points with high weighted comprehensive performance index and smaller variance as optimization data.

Description

Multi-objective optimization design method for magnetic pump impeller Technical Field The invention relates to the technical field of impeller multi-objective optimization design methods, in particular to a magnetic pump impeller multi-objective optimization design method. Background The magnetic pump is widely applied in fields with severe sealing requirements such as chemical industry, medicine and the like due to the non-leakage characteristic, and the efficiency and reliability of the pump are directly determined by the performance of a core transmission component, namely an impeller, and the stability of a magnetic transmission system. Traditional magnetic pump impeller designs tend to focus on single hydraulic performance such as efficiency, cavitation margin, lacking systematic consideration of magnetic drive smoothness. The slip and the heating risk of the magnetic coupler can be aggravated due to the overlarge impeller rotational inertia, and the fluid induced torque pulsation in the operation of the impeller can be directly transmitted to the external magnetic steel, so that the vibration and the noise of the whole transmission system are caused, and the service life and the operation stability of the bearing are influenced. Although the existing optimization methods attempt to introduce multiple targets, the initial design space is usually defined at random, and the moment of inertia and dynamic torque pulsation are not used as explicit and independent optimization targets to carry out collaborative optimization on the hydraulic performance, so that the optimization results are difficult to meet the comprehensive requirements of high efficiency, low cavitation, low pulsation and magnetic transmission stability; In the prior art, publication No. CN117807893A discloses a method which adopts a non-dominant sorting genetic algorithm based on a reference point, takes the highest hydraulic efficiency and the smallest cavitation margin of a high-speed centrifugal pump as optimization targets, constructs corresponding optimization target functions, screens out three parameters of impeller inlet diameter, impeller outlet width and blade outlet angle according to sensitivity analysis, takes the three parameters as the reference point and combines the non-dominant sorting genetic algorithm to carry out multi-target optimization calculation to obtain optimal geometric parameters corresponding to the three parameters, but the method does not take the total moment of inertia of the impeller as an initial screening criterion, takes the torque pulsation coefficient as one of three core optimization targets parallel to efficiency and cavitation performance, does not integrate the special transmission stability requirement of the magnetic pump into an optimization system from a design source, can not rapidly identify key parameters sensitive to the target functions and the optimization directions thereof in the early stage of iteration through combination with optimal Latin hypercube, global sensitivity analysis and self-adaptive design space updating strategy, does not set a secondary screening criterion of magnetic transmission stability, comprehensively considers the moment of inertia and does not have a requirement of magnetic transmission stability to be matched with the magnetic pump, and the method has multiple requirements of the magnetic pump to be optimized. The above information disclosed in the background section is only for enhancement of understanding of the background of the disclosure and therefore it may include information that does not form the prior art that is already known to a person of ordinary skill in the art. Disclosure of Invention The invention aims to provide a multi-objective optimal design method for a magnetic pump impeller, which aims to solve the problems in the background technology. In order to achieve the above purpose, the present invention provides the following technical solutions: A multi-objective optimization design method for a magnetic pump impeller comprises the following specific steps: s1, carrying out structure distinction on impellers to determine a plurality of structures, determining geometric parameters of each structure, setting upper and lower limits of the geometric parameters, counting the upper and lower limits of all the geometric parameters to form a design parameter space, constructing a total rotational inertia model of the impellers based on the types of the geometric parameters, and constructing a CFD simulation model taking the geometric parameters as input and taking a target coefficient as output, wherein the target coefficient is the hydraulic efficiency, the cavitation performance index and the torque pulsation coefficient of the pump; S2, sampling a design parameter space by adopting optimal Latin hypercube sampling to generate a first sample set, obtaining total rotational inertia corresponding to each sample point through a total rotational i