CN114492247A - Impeller high-efficiency low-vibration optimization method based on standard function of Euler lift of blade - Google Patents
Impeller high-efficiency low-vibration optimization method based on standard function of Euler lift of blade Download PDFInfo
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Abstract
The invention discloses an impeller high-efficiency low-vibration optimization method based on a blade Euler lift density function, which is characterized in that data sampling is carried out by a central test design method to obtain multiple groups of data of thickness distribution maximum values and wrap angle values of different flow surfaces of a blade; establishing a plurality of vane pump geometric models by combining other geometric parameters and performance parameters of the vane pump, and performing steady and unsteady numerical simulation on each vane pump geometric model; carrying out Euler lift image processing on the multiple vane pump models, extracting Euler lift standard functions based on Euler lift density function distribution of the impeller, and analyzing the relation between the Euler lift standard functions and the axial force vibration power level of the impeller; and optimizing the impeller efficiency and the Euler lift standard function by using a multi-objective optimization method, and obtaining the high-efficiency low-vibration impeller model of the vane pump by taking the impeller lift as constraint. The method can improve the efficiency of the impeller of the vane pump and reduce the axial force vibration of the impeller.
Description
Technical Field
The invention relates to the field of optimization of blades of fluid machinery, and provides an impeller high-efficiency low-vibration optimization method based on a standard function of Euler lifts of the blades.
Background
A vane pump refers to a power device commonly used in industrial and modern manufacturing industries, and converts electric energy into mechanical energy by using rotation of an impeller. The common types are mainly axial pumps, mixed flow pumps and centrifugal pumps. Different kinds of vane pumps are used in specific applications. The water-saving agent is used for irrigation, waterlogging drainage, a circulating water system of a large-scale power plant and the like in the aspects of industrial and agricultural application; in the aspect of new energy utilization, the method is used for industries such as nuclear pumps, seawater pumps and the like. In actual production, different pump types are selected according to different specific rotating speeds determined by design parameters. The production efficiency of the pump is mainly determined by the working performance of the impeller. Through the optimal design to impeller structure, can play the effect that promotes impeller efficiency. When the vane pump works, the flow induced excitation force among impeller runners is enhanced when the flow performance of a non-uniform flow structure generated in the runners is damaged, the axial force vibration on the surfaces of the vanes is enhanced, the energy loss and waste are further caused, and the working stability and safety of equipment are influenced. Therefore, the efficient operation and the axial force vibration suppression of the vane pump have great significance for engineering application.
At present, research methods such as an entropy change method, a speed slip coefficient method, an Euler lift analysis method and the like are commonly used for qualitatively describing the flow state distribution and the influence of the impeller when the fluid flows. Generally, the size and the direction of the outlet speed of an impeller in a vane pump are analyzed, and then the dynamic and static interference performance between the impeller and a guide vane or a volute is optimized, so that the working performance of the pump is optimized. However, most of the existing analysis and research is only established on qualitative analysis of the vane pump, and a multi-objective optimization analysis technology for predicting the impeller efficiency and the vibration performance of the vane pump only through steady numerical simulation calculation is lacked in the prior art, so that the optimization design means is complex, and the optimization analysis method is complex.
Disclosure of Invention
The invention aims to overcome the defects of the background technology, and provides an impeller high-efficiency low-vibration optimization method based on a standard Euler lift function of a blade. The efficiency and the vibration performance of the impeller optimized by the method are greatly improved.
The invention is realized by the following technical scheme:
an impeller high-efficiency low-vibration optimization method based on a standard function of the Euler lift of a blade comprises the following steps:
the method comprises the following steps: the method comprises the steps that the range of the maximum thickness value and the wrap angle range of different flow surfaces of a blade of an impeller to be designed are given, data sampling is carried out through a central test design method, and multiple groups of data of the maximum thickness distribution value and the wrap angle value of the different flow surfaces of the blade are obtained; then, combining other geometric parameters and performance parameters of the vane pump, creating a plurality of vane pump geometric models, and performing steady and unsteady numerical simulation on each vane pump geometric model;
step two: (1) for unsteady numerical simulation, extracting vibration information of axial force of the impeller with the low frequency range of 10-430 Hz, performing fast Fourier transform, and extracting a vibration power level;
(2) for the steady numerical simulation, obtaining impeller efficiency, impeller lift and Euler lift of the impeller corresponding to each geometric model of the vane pump; carrying out data processing on the obtained Euler lifts of a plurality of blades, and calculating an Euler lift density function Equal through a formula (1)
Wherein Euler (j, i) represents the value of the j point on the ith Euler lift curve; m and n respectively represent the m-th data point and the n-th data point in the flow direction from the impeller inlet to the impeller outlet on an Euler lift curve; k represents the number of data points selected in the flow direction from the impeller inlet to the impeller outlet, and k is n-m; x and y represent the x-th and y-th euler head curves in the spanwise direction from the hub surface to the rim surface, respectively; l represents the number of euler head curves selected in the spanwise direction from the hub surface to the rim surface, and l is y-x; a represents the a-th Euler head density point in the flow direction, and a is ∑ j/(k + 1); b denotes the b-th euler head density point in the spanwise direction, and b ═ Σ i/(l + 1).
Then, for each impeller, the corresponding euler head criteria function Dispersion is calculated by equation (2),
Dispersion＝σ[Equal(a,b)] (2)
step three: linearly fitting the Euler lift standard function Dispersion and the impeller axial force vibration force level corresponding to the impeller geometric models, and calculating the fitting error R of all data2；
Step four: when R is2If the number of the fitting samples is larger than the set threshold, the number of the fitting samples meeting the single factor and the fitting criterion are indicated, and a fifth step is executed; when R is2When the current value is not greater than the set threshold value, repeating the first step to the third step;
step five: selecting a multi-objective optimization model, taking the Euler lift standard function and the impeller efficiency at the moment as optimization objectives,
and (3) constraining to impeller lift, inputting the range of the maximum thickness values and the wrap angle range of different flow surfaces of the blades of the impeller into a multi-objective optimization model, performing multi-objective optimization to obtain the optimization results of the maximum thickness values and the wrap angles of the different flow surfaces of the blades of the impeller, and obtaining the optimized impeller based on the optimization results.
Further, in the second step, for unsteady numerical simulation, axial force time domain pulsation information under a rated working condition is obtained, FFT fast fourier transform is performed on the axial force time domain pulsation data to obtain axial force frequency domain pulsation data, and the axial force frequency domain pulsation data of 10-430 Hz is extracted by using formula (3) to obtain vibration force level
LF＝20lg(F/F0) (3)
Wherein, F0As a reference value of the vibration power level, F0＝1μN。
Furthermore, Euler of the impeller in the second step represents the flow state distribution condition of the fluid flowing in the impeller flow channel, the calculation formula is shown as formula (4),
wherein, VθThe method is characterized in that the method represents absolute velocity circumferential components of a certain position in a flow field, U represents circumferential velocity of a certain position in the flow field, and g represents gravitational acceleration.
Further, the set threshold in the fourth step is 0.9.
The invention has the beneficial effects that:
the Euler lift density function of the impeller is extracted based on the Euler lift, the aim is to obtain the impeller efficiency and the Euler lift of the impeller through numerical simulation calculation under a constant condition, the Euler lift density function is analyzed, and a standard function is extracted to be used for predicting and improving the vibration performance of the impeller of the vane pump. The method is simple and effective in multi-objective optimization design of the impeller of the vane pump, and the high-efficiency low-vibration vane design method is obtained, so that the optimization purpose is more clear, and the optimization analysis is simpler, more convenient and more reliable. The impeller of the vane pump optimally designed by the invention effectively reduces the influence caused by an uneven flow structure, and greatly improves the efficiency and the vibration performance of the impeller on the basis of reducing the calculation workload of unsteady numerical simulation.
Drawings
Fig. 1 is a schematic flow chart of an optimization method according to an embodiment.
Fig. 2 is a graph of euler head of an initial model impeller basin.
Fig. 3 is a distribution diagram of euler head density function of the initial model.
FIG. 4 is a frequency domain plot of axial force pulsation for an initial model impeller.
Fig. 5 is a fitting relation between euler lift standard function and axial force vibration performance.
Fig. 6 is a graph of euler head of an optimized model impeller.
Fig. 7 is a distribution diagram of euler head density function of the optimized model.
FIG. 8 is a frequency domain diagram of the axial force pulsation of the optimized model impeller.
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 the described embodiments are only a part of the embodiments of the present invention, but 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.
As shown in fig. 1, the method for optimizing the impeller high efficiency and low vibration based on the standard function of the euler lift of the blade of the present invention includes the following steps:
the method comprises the following steps: giving the range of the maximum thickness values and the wrap angle range of different flow surfaces of the blade of the impeller to be designed, and carrying out data sampling by a central test design method to obtain multiple groups of data of the maximum thickness distribution values and the wrap angle values of the different flow surfaces of the blade; and then, combining other geometric parameters and performance parameters of the vane pump, creating a plurality of vane pump geometric models, and performing constant and non-constant numerical simulation on each vane pump geometric model respectively.
Step two: (1) for unsteady numerical simulation, obtaining time domain pulsation information of axial force of the impeller under a rated working condition, and performing Fast Fourier Transform (FFT) on the time domain pulsation data of the axial force to obtain frequency domain pulsation data of the axial force; extracting axial force frequency domain pulsation data of 10-430 Hz by using a formula (1) to obtain a vibration power level;
LF＝20lg(F/F0) (1)
wherein, F0As a reference value of the vibration power level, F0＝1μN。
(2) For the steady numerical simulation, obtaining impeller efficiency, impeller lift and Euler lift of the impeller corresponding to each geometric model of the vane pump; euler of the impeller represents the flow state distribution condition of fluid flowing in the impeller flow passage, and the calculation formula is as the formula (2):
wherein, VθThe method is characterized in that the method represents absolute velocity circumferential components of a certain position in a flow field, U represents circumferential velocity of a certain position in the flow field, and g represents gravitational acceleration.
Each set of impeller models has a set of impeller euler head data representing the meridional fluid performance, i.e., from the impeller inlet to the impeller outlet, from the impeller hub to the rim.
And (3) carrying out data processing on the obtained Euler lifts of the plurality of blades to obtain an Euler lift density function Equal, representing the Euler lift density distribution condition of the research range, and calculating the Equal through a formula (3).
Wherein Euler (j, i) represents the value of the j point on the ith Euler lift curve; m and n respectively represent the m and n data points in the flow direction from the impeller inlet to the impeller outlet on an Euler lift curve; k represents the number of data points selected in the flow direction from the impeller inlet to the impeller outlet, and k is n-m; x and y represent the x-th and y-th euler head curves in the spanwise direction from the hub surface to the rim surface, respectively; l represents the number of euler head curves selected in the spanwise direction from the hub surface to the rim surface, and l is y-x; a represents the a-th Euler head density point in the flow direction, and a is ═ j/(k + 1); b denotes the b-th euler head density point in the spanwise direction, and b ═ Σ i/(l + 1).
Then, for each impeller, a corresponding euler head criterion function Dispersion is calculated by the following formula, and the euler head criterion function Dispersion of the impeller describes the degree of Dispersion of the euler head in the meridian plane of the impeller.
Dispersion＝σ[Equal(a,b)] (4)
Step three: linearly fitting the Euler lift standard function Dispersion and the impeller axial force vibration force level corresponding to the impeller geometric models, and calculating the fitting error R of all data2；
Step (ii) ofFourthly, the method comprises the following steps: get R2The set threshold value is 0.9 when R is2If the number of the fitting samples is larger than the set threshold, the number of the fitting samples meeting the single factor and the fitting criterion are indicated, and a fifth step is executed; when R is2When the threshold value is not greater than the set threshold value, repeating the first step to the third step;
step five: selecting a multi-objective optimization model, taking the Euler lift standard function and the impeller efficiency at the moment as optimization targets, constraining as impeller lift, inputting the range of the maximum thickness values and the wrap angle range of different flow surfaces of the blades of the impeller into the multi-objective optimization model, carrying out multi-objective optimization to obtain the optimization results of the maximum thickness values and the wrap angles of the different flow surfaces of the blades of the impeller, and obtaining the optimized impeller based on the optimization results.
The advantages of the method of the present invention will be illustrated by applying the method of the present invention to a specific pump design.
Taking the design and optimization of a certain axial flow pump model as an example, referring to fig. 2 to 8, the specific implementation process is as follows:
the method comprises the following steps: aiming at the calculation of the steady flow state of the hydraulic component, a full-basin model of the hydraulic pump with an impeller, a volute and a gap flow channel is completed in UG, and the number of the whole grids is about 550 ten thousand. And performing numerical simulation calculation by adopting ANSYS CFX software. The impeller part in the steady flow state calculation is a rotating area, the other parts are static areas, and the dynamic and static areas are connected with each other through an interface surface. The inlet adopts a speed inlet, the outlet adopts a pressure outlet, the solid boundary adopts a non-slip wall surface condition, and the near-wall area adopts an enhanced wall surface function.
Through numerical simulation calculation of the integral model, performance parameters under rated working conditions at the rated flow of 1300m3/h and the rotating speed of 1200rpm are obtained: impeller lift, impeller efficiency, and impeller euler lift. The axial flow pump design geometry parameters are shown in table 1.
TABLE 1 axial-flow Pump geometric parameters
| Parameter(s) | Value of |
| Outer diameter of impeller D2 | 400mm |
| Hub diameter, dh | 200mm |
| Number of blades of |
7 |
| Number of |
9 |
| Rated speed of rotation, n | 1200rpm |
| Rated flow rate, Qd | 1300m3/h |
The results of the numerical simulation of the original model were analyzed by the following procedure, and as shown in fig. 1, 2 and 3, the impeller efficiency was 86.73% and the vibration power level was 165.05.
The wrap angle value and the maximum thickness value of the three-layer flow surface of the blade are selected as input variables, sample amplification is carried out on 6 input parameters by utilizing an experimental Design method Center Combined Design (CCD), and the Design type can be automatically selected according to the number of the input variables by Design exploration. The center combination design method is the most common experimental design method because it automatically switches between goal optimization (G-optimization) and VIF optimization (VIF-optimization) if the number of input variables is 5.
When the center combination design test method is adopted, the wrap angles of the hubs are distributed at 48-64 degrees, the wrap angles of the S1 flow surfaces are distributed at 40-60 degrees, the wrap angles of the rims are distributed at 36-52 degrees, the maximum thickness of the hubs is distributed at 34-46 mm, the maximum thickness of the S1 flow surfaces is distributed at 65-83 mm, and the maximum thickness of the rims is distributed at 94-130 mm. When performing three-level response surface fitting for a single factor, at least 3 sets of samples are required. And (4) deriving impeller efficiency and impeller Euler lift data of 20 groups of blades. And deriving the number of samples to meet the fitting criterion according to the number of factors fitting to the response surface of the Euler head density function in the following steps.
Step two: (1) and performing unsteady flow state calculation on the blade model, monitoring axial force pulsation in the unsteady calculation, wherein the unsteady flow state calculation takes a steady flow state calculation result as an initial condition, and the time step length is set as the time for the impeller to rotate by 1 degree. In order to ensure that a stable pressure pulsation rule is accurately obtained, the time for the impeller to rotate for one circle is taken as a cycle to obtain axial force time domain pulsation information under a rated working condition, and time domain signals in 10 cycles after calculation and stabilization are taken to perform fast Fourier transform to obtain frequency domain information.
Performing FFT (fast Fourier transform) on the axial force time domain pulsation data, wherein the axial frequency is 20Hz, the one-time blade frequency is 140Hz, and as shown in FIG. 4, the axial force time domain pulsation data is an axial force vibration frequency domain diagram of the impeller, analyzing the axial force frequency domain vibration data by using a vibration force level formula (1), and extracting a 10-430 Hz low-frequency vibration force level and a reference value F0＝1μN。
(2) And performing steady flow state calculation on the blade model, and performing image processing and density function analysis on Euler lift data of the blade basin. The meridian plane of the impeller is taken as a research object, 30 data points are uniformly extracted in the spanwise direction, 30 data points are uniformly extracted in the flow direction, and the Euler lift of the impeller represents the flow state distribution condition of fluid flowing in an impeller flow passage.
The euler head distribution curve obtained by processing the static pressure data distribution by the formula (2) is shown in fig. 2. Performing density function analysis on the fluid in the impeller region, wherein Euler (j, i) represents the value of the j point on the ith Euler lift curve; m and n respectively represent the m-th data point and the n-th data point in the flow direction from the impeller inlet to the impeller outlet on an Euler lift curve; k represents the number of data points selected in the flow direction from the impeller inlet to the impeller outlet, wherein k is n-m and the value is 2; x and y represent the x-th and y-th euler head curves in the spanwise direction from the hub surface to the rim surface, respectively; l represents the number of euler head curves selected in the spanwise direction from the hub surface to the rim surface, and the value is 2; a represents the a-th Euler head density point in the flow direction, and a is ═ j/(k +1), and the value is 10; b represents the b th euler head density point in the spanwise direction, and b ═ Σ i/(l +1), the value of which is 10.
The Equal represents the Euler head density distribution of the fluid in the impeller part, the distribution rule of the fluid in the area is directly fed back by the vibration performance of the impeller, the larger the Equal value is, the more irregular the energy change of the fluid in the research area is, the worse the stability of energy exchange is, and the density function analysis is carried out on the original model as shown in figure 3. And the Dispersion is an Euler lift standard function, represents the Dispersion degree of the Euler lift density function of the whole research area, and is represented by the standard deviation of the Euler lift density function of the whole research area.
Step three: and (3) setting forth the relation between the Euler lift density function of the impeller during the steady simulation calculation and the axial force pulsation performance under the steady simulation calculation, wherein the physical meaning of the Equal obtained by calculation in the step two is the Euler lift distribution density of the radial surface basin of the impeller, and the stability and uniformity of energy conversion in the blade loading process are shown. When the Euler head density function is larger, the static pressure energy change in the impeller loading process is disturbed, and energy mutation caused by low-speed vortex and other flow structures exists. The complex and disordered flow structure is also the reason of causing the abnormal pulsation of the axial force vibration, the blade frequency pulsation amplitude of the axial force reflects the excitation condition caused by fluid flow caused by blades when the impeller works, and the overall vibration condition of the low frequency band reflects the influence condition of the complex flow structure of the impeller flow section on the excitation force of the impeller surface. Therefore, the response fitting relation of the sample group is obtained by taking the vibration force level of the low frequency range (10-430 Hz) as the measurement standard of the vibration performance of the axial force of the impeller as follows.
Y＝34.797X+133.42
Wherein X represents an Euler lift standard function extracted from the meridian plane of the impeller blade, and Y represents the vibration power level. In conclusion, the Euler lift density function can be used as a parameter for measuring the vibration performance of the axial force of the blade. The sample set of data is shown in table 2.
TABLE 2 impeller Performance sample set of data
Step four: according to the fitting image and the fitting result obtained in the third step, R20.9249 > 0.9, the response profile is shown in fig. 5. The accuracy of the response surface can be evaluated by analyzing the fitting degree graph, the coincidence degree of the predicted value and the observed value is good, and the fitting goodness is high, namely, the impeller data in the table 2 can be used as a reliable sample for analysis and optimization.
Step five: according to the first step, the fourth step, setting the impeller efficiency and the Euler lift standard function as optimization targets, wherein the higher the impeller efficiency, the smaller the Euler lift standard function is, the better the impeller working performance is, and setting the impeller lift to be 11.5m as a constraint value; selecting NSGA-II in a multi-objective optimization mode; according to the selection of the optimized variables of the sample group, the wrap angle value and the maximum value of the thickness distribution of the three-layer flow surface of the blade are set as the optimized variables in a multi-objective optimization mode, and the optimized variables are specifically selected as follows:
the input parameters are distributed in a certain range, the wrap angle of a hub is distributed in a range of 41.38-60.62 degrees, the wrap angle of an S1 flow surface is distributed in a range of 44.22-60 degrees, the wrap angle of a rim is distributed in a range of 33.38-48.62 degrees, the maximum thickness of the hub is distributed in a range of 36.53-43.47 mm, the maximum thickness of an S1 flow surface is distributed in a range of 65-83 mm, and the maximum thickness of the rim is distributed in a range of 94-130 mm. The NSGA-II optimizes and selects the population capacity of 16 (multiple of 4), iterates for 20 times, obtains 320 groups of blade fitting results in total, and carries out numerical simulation verification on the optimization results.
The optimization results are shown in table 3 in comparison with the simulation results, and the error analysis is as follows.
TABLE 3 analysis of optimization results and numerical simulation verification results
| Impeller head (m) | Dispersion | Efficiency of impeller | |
| Optimizing results | 11.398 | 0.406 | 89.928％ |
| Simulation results | 11.411 | 0.400 | 90.116％ |
| Error analysis | 0.11％ | 1.50％ | 0.21％ |
And the error analysis is less than 2%, the error requirement is met, and the optimization result has reliability. The optimized model and the original model are compared, for example, as shown in FIGS. 6, 7 and 8 and FIGS. 2, 3 and 4, the impeller efficiency is optimized by 3.39%; the Euler lift standard function is reduced by 0.4713, optimized by 54.09%, and the vibration power level of the optimized model is 148.84, which is optimized by 9.79% compared with the vibration power level of the original model. As can be seen from the impeller axial force frequency spectrum chart 8, the vibration performance of the impeller axial force is obviously improved; the Euler lift density function distribution diagram of the impeller shows that the density function distribution of the optimized model is more uniform than that of the original model. In conclusion, the result is determined to be the final optimization result, and the Euler lift density function and the standard function analysis of the impeller have the guiding significance of optimizing the vibration performance of the impeller.
Claims (4)
1. A high-efficiency low-vibration optimization method for an impeller based on a standard function of the Euler lift of a blade is characterized by comprising the following steps of: the method comprises the following steps:
the method comprises the following steps: the method comprises the steps that the range of the maximum thickness value and the wrap angle range of different flow surfaces of a blade of an impeller to be designed are given, data sampling is carried out through a central test design method, and multiple groups of data of the maximum thickness distribution value and the wrap angle value of the different flow surfaces of the blade are obtained; then, combining other geometric parameters and performance parameters of the vane pump, creating a plurality of vane pump geometric models, and performing steady and unsteady numerical simulation on each vane pump geometric model;
step two:
(1) for unsteady numerical simulation, extracting vibration information of axial force of the impeller with the low frequency range of 10-430 Hz, performing fast Fourier transform, and extracting a vibration power level;
(2) for the steady numerical simulation, obtaining impeller efficiency, impeller lift and Euler lift of the impeller corresponding to each geometric model of the vane pump; carrying out data processing on the obtained Euler lifts of a plurality of blades, and calculating an Euler lift density function Equal through a formula (1)
Wherein Euler (j, i) represents the value of the j point on the ith Euler lift curve; m and n respectively represent the m-th data point and the n-th data point in the flow direction from the impeller inlet to the impeller outlet on an Euler lift curve; k represents the number of data points selected in the flow direction from the impeller inlet to the impeller outlet, and k is n-m; x and y represent the x-th and y-th euler head curves in the spanwise direction from the hub surface to the rim surface, respectively; l represents the number of euler head curves selected in the spanwise direction from the hub surface to the rim surface, and l is y-x; a represents the a-th Euler head density point in the flow direction, and a is ═ j/(k + 1); b denotes the b-th euler head density point in the spanwise direction, and b ═ Σ i/(l + 1).
Then, for each impeller, the corresponding euler head criteria function Dispersion is calculated by equation (2),
Dispersion＝σ[Equal(a,b)] (2)
step three: linearly fitting the Euler lift standard function Dispersion and the impeller axial force vibration force level corresponding to the impeller geometric models, and calculating the fitting error R of all data2；
Step four: when R is2If the number of the fitting samples is larger than the set threshold, the number of the fitting samples meeting the single factor and the fitting criterion are indicated, and a fifth step is executed; when R is2When the threshold value is not greater than the set threshold value, repeating the first step to the third step;
step five: selecting a multi-objective optimization model, taking the Euler lift standard function and the impeller efficiency at the moment as optimization targets, constraining as impeller lift, inputting the range of the maximum thickness values and the wrap angle range of different flow surfaces of the blades of the impeller into the multi-objective optimization model, carrying out multi-objective optimization to obtain the optimization results of the maximum thickness values and the wrap angles of the different flow surfaces of the blades of the impeller, and obtaining the optimized impeller based on the optimization results.
2. The impeller high-efficiency low-vibration optimization method based on the standard function of the Euler lift of the blade of claim 1, wherein: in the second step, axial force time domain pulse information under a rated working condition is obtained by performing unsteady numerical simulation, FFT is performed on the axial force time domain pulse data to obtain axial force frequency domain pulse data, and 10-430 Hz axial force frequency domain pulse data is extracted by using the formula (3) to obtain a vibration force level
LF＝20lg(F/F0) (3)
Wherein, F0As a reference value of the vibration power level, F0＝1μN。
3. The impeller high-efficiency low-vibration optimization method based on the standard function of the Euler lift of the blade of claim 1, wherein: the Euler lift of the impeller in the second step represents the flow state distribution condition of the fluid flowing in the impeller flow channel, the calculation formula is shown as a formula (4),
wherein, VθThe method is characterized in that the method represents absolute velocity circumferential components of a certain position in a flow field, U represents circumferential velocity of a certain position in the flow field, and g represents gravitational acceleration.
4. The impeller high-efficiency low-vibration optimization method based on the Euler lift standard function according to claim 1, wherein: the set threshold in step four is 0.9.
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Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111911423A (en) * | 2020-07-27 | 2020-11-10 | 浙江理工大学 | Centrifugal pump impeller limit outer diameter measuring and optimizing method based on PIV |
| WO2021129261A1 (en) * | 2019-12-26 | 2021-07-01 | 浙江理工大学 | Blade load distribution-based method for designing centrifugal-pump compound impeller |
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Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
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| CN111911423A (en) * | 2020-07-27 | 2020-11-10 | 浙江理工大学 | Centrifugal pump impeller limit outer diameter measuring and optimizing method based on PIV |
Non-Patent Citations (5)
| Title |
|---|
| KEXIN PU 等: "Quantitative analysis of energy loss and vibration performance in a circulating axial pump", ENERGY 243 (2022) 122753, 26 November 2021 (2021-11-26), pages 1 - 17 * |
| 倪永燕;刘为民;潘希伟;潘中永;: "一种多目标泵的设计与分析", 流体机械, no. 10, 31 October 2013 (2013-10-31), pages 49 - 52 * |
| 吴大转 等: "泵技术进展与发展趋势", 水力发电学报, no. 06, 31 December 2020 (2020-12-31), pages 3 - 19 * |
| 袁寿其;王文杰;裴吉;张金凤;冒杰云;: "低比转数离心泵的多目标优化设计", 农业工程学报, no. 05, 8 March 2015 (2015-03-08), pages 54 - 60 * |
| 黄滨 等: "可倾瓦推力轴承惰转过程的最小膜厚预测方法", 润滑与密封, vol. 49, no. 4, 15 April 2024 (2024-04-15), pages 1 - 9 * |
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