Semi-spiral suction chamber optimization method based on lip angle

Abstract

The application discloses a semi-spiral suction chamber optimization method based on a lip angle, and aims at solving the problem of poor stability of the existing suction chamber. The application can more accurately simulate the flow field distribution by using the computational fluid dynamics method, thereby guaranteeing the effectiveness of the simulation result. The application simulates and analyzes the flow field distribution by using the computational fluid dynamics method, combines the flow field characteristic analysis with the physical verification, and embodies the scientific nature of the combination of theory and practice. Through in-depth analysis of the simulation data and the physical verification result, the generated optimization rule can improve the performance of the suction chamber in a targeted manner. The comprehensive performance evaluation considers the optimization rule from multiple dimensions, balances the relationship between different performance indexes, and ensures that the finally obtained engineering application scheme reaches the optimal balance in terms of technical feasibility, economic rationality and operation stability.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of double-suction pump optimization, in particular to a semi-spiral suction chamber optimization method based on a lip angle. BACKGROUND

[0002] As a key component of a double-suction pump, the internal flow field characteristics of a semi-spiral suction chamber directly affect the efficiency, stability, cavitation performance and operating noise of the entire machine. The core of the design of the suction chamber lies in guiding the fluid to enter the impeller smoothly and uniformly, and reducing flow loss, flow separation and vortex generation as much as possible. The lip, as an important structural feature of the semi-spiral suction chamber, its geometry, especially the angle, plays a decisive role in guiding the fluid to the impeller inlet, suppressing backflow and vortex, and reducing pressure pulsation. The existing technology still has the following problems:

[0003] 1. No three-dimensional model of the suction chamber is constructed according to the actual design of the suction chamber, resulting in distortion of the three-dimensional model of the suction chamber.

[0004] 2. The three-dimensional model of the suction chamber is not effectively simulated, so that the complex flow state inside the flow field cannot be intuitively presented.

[0005] 3. The performance of the suction chamber is not analyzed in depth, and the optimization rules are not considered from multiple angles, resulting in poor applicability of the suction chamber. SUMMARY

[0006] The purpose of the present application is to provide a semi-spiral suction chamber optimization method based on a lip angle, which can more accurately simulate the flow field distribution using computational fluid dynamics methods, ensuring the effectiveness of the simulation results. The flow field distribution is simulated using computational fluid dynamics methods, combined with flow field characteristic analysis and physical verification, embodying the scientific nature of the combination of theory and practice. Through in-depth analysis of the simulation data and physical verification results, the generated optimization rules can improve the performance of the suction chamber, and the comprehensive performance evaluation considers the optimization rules from multiple dimensions, weighs the relationship between different performance indicators, and ensures that the final engineering application scheme reaches an optimal balance in terms of technical feasibility, economic rationality and operating stability. It can solve the problems in the prior art.

[0007] To achieve the above-mentioned purpose, the present application provides the following technical scheme:

[0008] The semi-spiral suction chamber optimization method based on the lip angle comprises:

[0009] According to the design data of the semi-spiral suction chamber, the geometric parameters of the semi-spiral suction chamber are confirmed, a three-dimensional model of the suction chamber is established according to the confirmed geometric parameters, the three-dimensional model of the suction chamber is meshed, the three-dimensional model of the suction chamber after meshing is simulated by a computational fluid dynamics method, the flow field characteristics are analyzed according to the simulation results, the analysis results are physically verified, optimization rules of the semi-spiral suction chamber are generated according to the simulation data and the physical verification results, and finally the generated optimization rules are comprehensively evaluated to obtain an engineering application scheme.

[0010] Preferably, the geometric parameters of the semi-spiral suction chamber are confirmed according to the design data of the semi-spiral suction chamber, including:

[0011] The basic design parameters of the semi-spiral suction chamber are extracted from the database, including performance parameters and structure reference parameters, wherein the performance parameters include design flow, design head, rated speed and impeller inlet target flow velocity range; the structure reference parameters include impeller inlet diameter, impeller inlet center height, suction chamber outlet width and tongue starting position radius;

[0012] According to the extracted basic design parameters, the geometric parameters of the semi-spiral suction chamber cross section are defined, including cross section division and cross section area gradient design;

[0013] The cross section division is to calculate the number of cross sections with the suction chamber outlet center as the reference point;

[0014] The cross section area gradient design is that the cross sections of the semi-spiral suction chamber are divided into an a cross section with an angle θ of 0 and n other cross sections, the cross section area gradually increases from Sa to Sn, wherein n is an integer, the size of n depends on the included angle between the cross sections, and the included angle is calculated by the formula

[0015] The cross section Sn calculation formula is V im is the flow velocity of the fluid entering the impeller, when n≥2, Sn=KS n-1 wherein θ n is the angle of the cross section.

[0016] Preferably, the geometric parameters of the semi-spiral suction chamber are confirmed according to the design data of the semi-spiral suction chamber, further including:

[0017] After the geometric parameters of the semi-spiral suction chamber cross section are defined, the geometric parameters are calibrated;

[0018] The calibration of the geometric parameters is to set the adjustment range of the baffle tongue angle a to 0-60°, set a group of test parameters every 10°, and correspond the baffle tongue angle to the outlet section position of the suction chamber, and at the same time, the axial distance between the baffle tongue tip and the impeller inlet meets the fluid smooth transition requirement;

[0019] After the calibration of the geometric parameters, the impeller parameters are integrated, the impeller parameter integration is to match the outlet section size of the suction chamber with the impeller inlet diameter and the blade inlet setting angle, and then the number of blades of the double-suction pump impeller is confirmed, wherein the suction chamber section distribution corresponds to the number of blades in even multiples;

[0020] After the integration of the impeller parameters, the geometric parameters of the semi-spiral suction chamber are sorted out, including section number, angle, area, baffle tongue angle, inlet diameter, axial length and impeller number;

[0021] After sorting out, the complete geometric parameters of the semi-spiral suction chamber are obtained.

[0022] Preferably, according to the confirmed geometric parameters, a three-dimensional model of the semi-spiral suction chamber is established, including:

[0023] According to the two-dimensional engineering drawings in the database, the two-dimensional engineering drawings are exported, and the coordinate origin in the two-dimensional engineering drawings is taken as the reference;

[0024] Then the reference coordinate system is established, the reference coordinate system is established by taking the center axis of the impeller as the Z-axis reference, taking the center of the suction chamber outlet as the coordinate origin, establishing a rectangular coordinate system including X-axis, Y-axis and Z-axis, and at the same time, marking the position of the impeller inlet installation plane and the position of the suction chamber inlet end surface;

[0025] On the X-axis and Y-axis reference surface, taking the Z-axis as the center, according to the confirmed section area and shape, a closed sketch is drawn, and on each angle reference surface in turn, the sketch is drawn according to the confirmed section area and recursive relationship;

[0026] Using the sweep tool, taking each section sketch as the cross-sectional contour, and taking the Z-axis as the center axis, the semi-spiral flow passage body is generated, and during the sweeping process, according to the confirmed axial length parameter, the extension range of the flow passage in the Z-axis direction is limited;

[0027] After the sweeping is completed, the baffle structure is constructed, wherein first, according to the confirmed baffle starting position radius, the coordinates of the baffle tip are marked in the section sketch, and the baffle contour is extended along the inner wall of the semi-spiral flow passage, in the three-dimensional modeling of the baffle, the inclination angle of the baffle is adjusted according to the confirmed inclination angle range, and the head of the baffle adopts a circular arc transition;

[0028] After the completion of the construction of the tongue structure, the impeller structure is matched, wherein, at the outlet end surface of the water suction chamber, a circular contour is drawn according to the confirmed impeller inlet diameter, and is aligned with the center of the water suction chamber outlet section, and at the same time, a transition fillet is added between the water suction chamber outlet and the impeller inlet;

[0029] After the completion of the matching of the impeller structure, the three-dimensional model of the suction chamber is obtained.

[0030] Preferably, the established three-dimensional model of the suction chamber is meshed, including:

[0031] First, the fluid region in the three-dimensional model of the suction chamber is confirmed, and then the mesh type of the three-dimensional model of the suction chamber is confirmed, including structured mesh, unstructured mesh and hybrid mesh;

[0032] After the confirmation of the mesh type, the mesh is divided according to the fluid region, and the basic framework of the spatial mesh distribution is obtained;

[0033] At the same time, the local area of the mesh is encrypted, and the local encryption includes setting the mesh encryption area at the tongue tip and the cross section area mutation, the encryption radius is 5-10mm, the mesh size is reduced to 1 / 2-1 / 3 of the whole, the boundary layer mesh is arranged along the wall surface, the mesh layer number is 3-5 layers, the first layer thickness is 10-50μm, and the growth rate is 1.2-1.5;

[0034] After encryption, the mesh division of the three-dimensional model of the suction chamber is completed.

[0035] Preferably, the three-dimensional model of the suction chamber after the completion of the mesh division is simulated and simulated by the computational fluid dynamics method, including:

[0036] Before the flow field distribution simulation and simulation, the physical model is selected, and the physical model adopts the SSTk-ω model, wherein the fluid medium is clear water, and the flow state is steady incompressible flow;

[0037] Then, the solver type is selected, including steady-state solution and transient solution;

[0038] Then, the boundary conditions of the physical model are set, including the inlet boundary, the outlet boundary and the wall boundary;

[0039] After the confirmation of the physical model and the solver, the flow field is initialized by mixed initialization, and at the same time, the first order format is calculated for 500-1000 steps until the residual error is reduced, the second order format is switched to continue iteration, and then the velocity and pressure values of the key positions including the tongue tip and the cross section mutation are monitored in real time;

[0040] Finally, the physical model is simulated, and when the simulation is performed, the change curve of the important variable is monitored in real time, and the iteration is continued until the residual error completely meets the control standard, wherein the important variable includes flow, pressure loss and velocity field distribution.

[0041] Preferably, the flow field characteristic analysis is performed according to the simulation results of the flow field distribution, including:

[0042] First, the parameter data in the simulation results are extracted, including velocity distribution data, pressure distribution data, turbulent flow characteristics and vortex data;

[0043] The parameter data is analyzed respectively, wherein the analysis of the velocity distribution data includes overall velocity nephogram analysis, cross-section velocity analysis and velocity vector diagram analysis; the pressure distribution data includes global pressure nephogram analysis, pressure loss calculation analysis and local abnormal pressure analysis; the analysis of the flow characteristics and vortex data is turbulent energy analysis, turbulent kinetic energy distribution analysis, vorticity and vortex structure analysis;

[0044] The key parameters in the analysis results are counted, including flow passability, characteristic variable trend graph, maximum, minimum and mean square deviation of velocity and pressure;

[0045] The key parameters are compared, wherein the flow passability is compared with the actual flow capacity and the design flow to judge the influence of the suction chamber structure on the fluid passability; the characteristic variable trend graph is extracted to extract the velocity and pressure of the tongue tip and the cross-section mutation, and the change trend with the iteration step or different schemes is compared to compare the flow field reaction under different structure parameters; the maximum, minimum and mean square deviation of velocity and pressure reflect the overall uniformity and skewness of the flow field;

[0046] Then, the cross-section velocity distribution is compared, the flow uniformity coefficient is used to quantitatively analyze the flow uniformity, and the pressure loss and energy consumption level under unit flow are calculated to locate the high loss area;

[0047] Finally, the flow field characteristic analysis data is obtained.

[0048] Preferably, the flow field characteristic analysis results are physically verified, including:

[0049] Before physical verification, an experimental platform is built, wherein according to the design parameters of the semi-spiral suction chamber, a centrifugal pump is selected as the test pump body, and the structure of the pump body is consistent with the simulation model, and high-precision flow measurement devices, pressure measurement instruments, vibration measurement equipment and noise measurement instruments are equipped, and the centrifugal pump is installed on a stable test bench, and the water inlet pipe, water outlet pipe and measurement instruments are connected;

[0050] Referring to the simulation conditions, the flow rate and rotational speed parameters of the test are set, 3-5 different flow rate points are selected, including the design flow rate point and the flow rate points deviating from the design flow rate;

[0051] After the selection of the working condition points, physical quantity measurement is performed, including flow rate measurement, pressure measurement, vibration measurement and noise measurement;

[0052] According to the measurement results, data comparison and analysis are performed, including flow rate comparison and analysis, pressure comparison and analysis, speed comparison and analysis, vibration comparison and analysis and noise comparison and analysis;

[0053] According to the results of the data comparison and analysis, the accuracy of the simulation model is comprehensively evaluated, and the results of the physical verification are fed back to the optimization design of the semi-spiral suction chamber.

[0054] Preferably, the semi-spiral suction chamber is optimized according to the flow field distribution simulation data and the physical verification results, including:

[0055] First, the flow field distribution simulation data and the physical verification results are extracted;

[0056] After extraction, data comparison is performed, which is to compare the simulation data and the physical verification results under different tongue inclination angles, and to compare the design target deviation, including simulation efficiency not meeting the expectation, vibration value exceeding the standard and cavitation area being too large;

[0057] Then, according to the flow field characteristic analysis results, the performance deviation is associated with the flow field characteristics, wherein if the efficiency is insufficient, the outlet cross-section speed standard deviation is too large, indicating that the flow field is not uniform; if the vibration exceeds the standard, the pressure fluctuation frequency near the tongue is consistent with the blade passing frequency, indicating that the vortex causes resonance; if the cavitation is serious, the area of the region where the tongue tip pressure is less than or equal to the saturated steam pressure is greater than or equal to 5 cm 2 ;

[0058] According to the association of the performance deviation and the flow field characteristics, the mapping relationship between geometry, flow field and performance is obtained, and the parameter sensitivity matrix is established according to the mapping relationship;

[0059] Then, the optimization rule framework is formulated, including parameter adjustment strategy and structure optimization rule;

[0060] According to the formulated optimization rule framework, the comparison results of the flow field distribution simulation data and the physical verification results and the parameter sensitivity matrix are used to generate optimization rules;

[0061] The generated optimization rules are presented in the form of parameter range, structure design suggestion and process requirement.

[0062] Preferably, the generated optimization rules are comprehensively evaluated, and an engineering application scheme is obtained according to the comprehensive performance evaluation, including:

[0063] The generated optimization rules are applied to the structural design of the semi-spiral suction chamber to form an optimized design scheme, and a corresponding three-dimensional model is established according to the optimized design scheme, and the established three-dimensional model is structurally refined and parameter-adjusted;

[0064] The three-dimensional model after structural refinement and parameter adjustment is meshed, a physical model is set, and boundary conditions are set, and the three-dimensional model is simulated in multiple working conditions and multiple indexes by using a fluid dynamics method, including flow rate, head, efficiency, pressure loss, flow field uniformity, cavitation performance, vibration and noise, and finally the performance index data are extracted and analyzed;

[0065] According to the analysis results of the performance index data, the optimization scheme with the best analysis result is selected for physical prototype manufacturing, and the performance of flow rate, pressure, efficiency, vibration and noise of the physical prototype is tested on an experimental platform, and the simulation and experimental results are compared to verify the accuracy of the simulation prediction, and the simulation data are supplemented and corrected;

[0066] According to the simulation and experimental results, a comprehensive performance evaluation index system is established, each index is weighted according to the actual engineering requirements and application scenarios, each index of each optimization scheme is standardized, and the comprehensive score is calculated by weighting according to the weight, and the performance of multiple schemes is sorted;

[0067] According to the comprehensive score, the applicability of each optimization scheme in the actual engineering is analyzed, including manufacturing difficulty, cost, reliability and maintainability;

[0068] According to the comprehensive score, the best engineering application scheme is obtained.

[0069] Compared with the prior art, the beneficial effects of the present application are as follows:

[0070] 1. The semi-spiral suction chamber optimization method based on the inclination angle of the tongue provided by the present application deeply excavates the internal relationship between the basic parameters through data processing technology, integrates variables such as fluid flow rate and section angle into the calculation formula, makes the section geometry parameter definition closely fit the fluid dynamics principle, takes the center axis of the impeller as the Z axis and the center of the water suction chamber outlet as the origin to construct a rectangular coordinate system, and labels the key positions to provide an accurate spatial positioning framework for subsequent modeling, and ensures that the model can truly restore the actual structure of the suction chamber, effectively avoiding the model distortion problem caused by data conversion deviation.

[0071] 2. The semi-spiral suction chamber optimization method based on the lip angle of the invention can more accurately simulate the flow field distribution using the computational fluid dynamics (CFD) method, ensuring the effectiveness of the simulation results. The CFD method is used to simulate the flow field distribution, combined with flow field characteristic analysis and physical verification, embodying the scientific nature of the combination of theory and practice. By reasonably planning the grid type, a scientific data processing framework is established for subsequent grid division, ensuring the fit of grid division and actual flow field characteristics.

[0072] 3. The semi-spiral suction chamber optimization method based on the lip angle of the invention can improve the performance of the suction chamber by in-depth analysis of the simulation data and physical verification results. Comprehensive performance evaluation considers the relationship between different performance indicators, ensuring that the final engineering application scheme achieves optimal balance in terms of technical feasibility, economic rationality and operational stability, effectively improving the applicability and reliability of the semi-spiral suction chamber in actual engineering. BRIEF DESCRIPTION OF DRAWINGS

[0073] Figure 1 The semi-spiral suction chamber optimization steps of the invention are shown in the figure. DETAILED DESCRIPTION

[0074] The technical solutions in the embodiments of the invention will be described clearly and completely below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the invention, not all. Based on the embodiments in the invention, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the invention.

[0075] To solve the problem of distortion of the three-dimensional model of the suction chamber in the prior art without targeted three-dimensional model construction of the suction chamber according to the actual design of the suction chamber, please refer to Figure 1 The technical solutions provided in the embodiment are as follows:

[0076] The semi-spiral suction chamber optimization method based on the lip angle includes:

[0077] The geometric parameters of the semi-spiral suction chamber are confirmed according to the design data of the semi-spiral suction chamber, a three-dimensional model of the suction chamber is established according to the confirmed geometric parameters, the three-dimensional model of the suction chamber after grid division is simulated by a computational fluid dynamics method, the flow field characteristics are analyzed according to the simulation results, the physical verification is performed on the flow field characteristic analysis results, the optimization rules of the semi-spiral suction chamber are generated according to the simulation data and the physical verification results, and finally the comprehensive performance evaluation is performed on the generated optimization rules, and the engineering application scheme is obtained according to the comprehensive performance evaluation.

[0078] Specifically, in the initial stage of the optimization process, the geometric parameters are confirmed and the three-dimensional model is established according to the design data, which can accurately restore the actual structure of the semi-spiral suction chamber. Through accurate modeling, a reliable foundation is provided for subsequent simulation, ensuring the authenticity and accuracy of the research object and avoiding errors caused by model deviation. Grid division and numerical preprocessing further refine the model, enabling the computational fluid dynamics (CFD) method to more accurately simulate the flow field distribution, ensuring the effectiveness of the simulation results. The use of the CFD method for flow field distribution simulation, combined with flow field characteristic analysis and physical verification, reflects the scientific nature of the combination of theory and practice. CFD simulation can efficiently and intuitively present the complex flow state inside the flow field, and can dig out potential flow problems; physical verification ensures the reliability of the simulation results from the actual operation point of view, avoiding the deviation of pure theoretical research from the actual working condition. The two complement each other and provide comprehensive and accurate basis for optimization. Through in-depth analysis of the simulation data and the physical verification results, the generated optimization rules can improve the performance of the suction chamber, such as improving fluid delivery efficiency, reducing energy consumption, and reducing flow loss. Comprehensive performance evaluation considers the relationship between different performance indicators from multiple dimensions, ensuring that the final engineering application scheme achieves the optimal balance in terms of technical feasibility, economic rationality and operation stability, effectively improving the applicability and reliability of the semi-spiral suction chamber in actual engineering, and providing a scientific and efficient solution for industrial production and engineering design.

[0079] The geometric parameters of the semi-spiral suction chamber are confirmed according to the design data of the semi-spiral suction chamber, including:

[0080] The basic design parameters of the semi-spiral suction chamber are extracted from the database, including performance parameters and structure reference parameters. The performance parameters include design flow, design head, rated speed and impeller inlet target flow velocity range; the structure reference parameters include impeller inlet diameter, impeller inlet center height, suction chamber outlet width and tongue starting position radius;

[0081] According to the extracted basic design parameters, the geometric parameters of the semi-spiral suction chamber cross section are defined, including cross section division and cross section area gradient design;

[0082] The cross section division is to calculate the number of cross sections with the center of the water suction chamber outlet as the reference point;

[0083] The cross section area gradient design is that the cross sections of the semi-spiral water suction chamber are divided into an a cross section with an angle θ of 0 and n other cross sections, and the cross section area gradually increases from Sa to Sn, where n is an integer, and the size of n depends on the included angle between each cross section. The calculation formula of the included angle is

[0084] The calculation formula of the cross section Sn is V im is the flow rate of the fluid entering the impeller, when n≥2, S n =KS n-1 wherein θ n is the angle of the cross section.

[0085] After the geometric parameters of the semi-spiral suction chamber cross section are defined, the geometric parameters are calibrated;

[0086] The calibration of the geometric parameters is to set the adjustment range of the tongue inclination angle α to 0°-60°, and set a group of test parameters every 10°, and the tongue inclination angle corresponds to the position of the water suction chamber outlet cross section, at the same time, the axial distance between the tongue tip and the impeller inlet meets the smooth transition requirements of the fluid;

[0087] After the calibration of the geometric parameters is completed, the impeller parameters are integrated, which is to match the water suction chamber outlet cross section size with the impeller inlet diameter and blade inlet installation angle, and then to confirm the number of blades of the double suction pump impeller, wherein the cross section distribution of the water suction chamber corresponds to the even number of blades;

[0088] After the integration of the impeller parameters is completed, the geometric parameters of the semi-spiral suction chamber are arranged, including cross section number, angle, area, tongue inclination angle, inlet diameter, axial length and impeller number;

[0089] After the arrangement is completed, the complete geometric parameters of the semi-spiral suction chamber are obtained.

[0090] Specifically, in the data accurate extraction link, the basic design parameters are extracted from the database, covering performance and structure benchmark parameters, realizing comprehensive data collection and accurate screening. Through the directional extraction of key data such as design flow and impeller inlet diameter, it is ensured that the geometric parameter confirmation is consistent with the actual engineering requirements from the source, avoiding design errors caused by data loss or deviation, and reflecting the core value of data-driven design. In the parameter definition and data correlation stage, the outlet center of the suction chamber is taken as the benchmark to divide the section, and the section area gradient is designed according to the scientific formula. Through data processing technology, the internal relationship between basic parameters is deeply excavated, and variables such as fluid velocity and section angle are integrated into the calculation formula, so that the definition of section geometric parameters is closely related to the principle of fluid dynamics. This parameter definition method based on data correlation can effectively optimize the flow path of fluid in the suction chamber, reduce energy loss, and improve equipment operation efficiency. In the parameter calibration and data optimization process, multiple test parameters are set for the lip angle, and the impeller parameters are integrated. Through systematic data calibration and analysis, the optimal configuration of the lip angle is found, while ensuring the accurate matching of the suction chamber and impeller parameters. Especially the correspondence between the suction chamber section distribution and the even multiple of the number of blades, based on data optimization processing to achieve the balance between structure and performance, and enhance the stability of equipment operation. Finally, through the systematic arrangement of the geometric parameters of the semi-spiral suction chamber, a complete and accurate data system is formed, which provides reliable data support for subsequent links such as three-dimensional modeling and simulation analysis, effectively reduces the risk of engineering design, and improves the design efficiency and quality.

[0091] According to the confirmed geometric parameters, the suction chamber three-dimensional model of the semi-spiral suction chamber is established, including:

[0092] According to the two-dimensional engineering drawings in the database, the two-dimensional engineering drawings are exported, and the coordinate origin in the two-dimensional engineering drawings is taken as the benchmark;

[0093] Then the reference coordinate system is established, which is a rectangular coordinate system with the impeller center axis as the Z-axis reference and the suction chamber outlet center as the coordinate origin, including X-axis, Y-axis and Z-axis. At the same time, the impeller inlet installation plane position and the suction chamber inlet end face position are labeled;

[0094] On the X-axis and Y-axis reference surface, take Z-axis as the center, draw closed sketches according to the confirmed section area and shape, and on each angle reference surface, draw sketches according to the confirmed section area and recursive relationship;

[0095] Use the sweep tool to generate the main body of the semi-spiral flow channel with each section sketch as the cross-sectional contour and Z-axis as the center axis, and during the sweeping process, according to the confirmed axial length parameter, limit the extension range of the flow channel in the Z-axis direction;

[0096] After the sweep is completed, the tongue structure is constructed, wherein, first, the coordinates of the tongue tip are marked in the cross-sectional sketch according to the confirmed tongue starting position radius, and the tongue profile is extended along the inner wall of the half-spiral flow channel, in the three-dimensional modeling of the tongue, the inclination angle of the tongue is adjusted according to the confirmed inclination angle range, and the head of the tongue adopts a circular arc transition;

[0097] After the tongue structure is constructed, the impeller structure is matched, wherein, at the outlet end surface of the suction chamber, a circular profile is drawn according to the confirmed impeller inlet diameter, and is aligned with the center of the suction chamber outlet cross section, at the same time, a transition fillet is added between the suction chamber outlet and the impeller inlet;

[0098] After the impeller structure is matched, the three-dimensional model of the suction chamber is obtained.

[0099] Specifically, in the data accurate conversion link, taking the two-dimensional engineering drawing as the data basis, the drawing is exported and a reference coordinate system is established with the coordinate origin as the reference. This operation converts the planar data on the drawing into three-dimensional space data accurately through coordinate positioning and axis setting. The center axis of the impeller is taken as the Z axis, and the center of the suction chamber outlet is taken as the origin to construct a rectangular coordinate system, and key positions are labeled, providing an accurate spatial positioning framework for subsequent modeling, ensuring that the model can truly restore the actual structure of the suction chamber, effectively avoiding model distortion caused by data conversion deviation. In the process of flow channel modeling and data association, a half-spiral flow channel body is generated by drawing a sketch according to the cross-sectional area and shape, and using a sweep tool. Through in-depth analysis and processing of the cross-sectional area recursive relationship and axial length parameters, the flow channel shape and size strictly meet the design requirements. This way of deeply integrating data into modeling simulates the real flow path of the fluid in the suction chamber with the help of data processing technology, providing an intuitive basis for predicting the flow field state and optimizing the fluid dynamics performance, effectively reducing energy loss caused by unreasonable flow channel design. In terms of structure optimization and data application, the construction of the tongue and the impeller structure is closely optimized based on data. The tongue modeling is accurately constructed based on the starting position radius and inclination angle range, and the head adopts a circular arc transition. The impeller structure is ensured to smoothly connect with the suction chamber by accurately drawing a circular profile and adding a transition fillet. These operations are based on the fine processing of data, which not only meets the principles of fluid mechanics, but also enhances the structural strength and stability, greatly improving the equipment operation reliability and efficiency. The whole scheme runs through the modeling process through data processing, laying a solid foundation for subsequent simulation analysis and engineering application.

[0100] To solve the problem in the prior art that the three-dimensional model of the suction chamber is not effectively simulated, thereby failing to intuitively present the complex flow state inside the flow field, please refer to Figure 1 The embodiment provides the following technical scheme:

[0101] The established three-dimensional model of the suction chamber is meshed, including:

[0102] Confirm the fluid region in the suction chamber three-dimensional model first, and then confirm the grid type of the suction chamber three-dimensional model, including structured grid, unstructured grid and hybrid grid;

[0103] After the grid type is confirmed, the grid is divided according to the fluid region, and the basic framework of the spatial grid distribution is obtained;

[0104] At the same time, the local area of the grid is encrypted, and the local encryption includes setting the grid encryption area at the tip of the tongue, the cross-sectional area mutation, the encryption radius is 5-10mm, the grid size is reduced to 1 / 2-1 / 3 of the whole, the boundary layer grid is set along the wall surface, the grid layer is 3-5 layers, the first layer thickness is 10-50μm, and the growth rate is 1.2-1.5;

[0105] After encryption, the grid division of the suction chamber three-dimensional model is completed.

[0106] Specifically, in the data area accurate identification and grid rule link, the fluid region is first confirmed, and then the structured, unstructured or hybrid grid type is selected, which reflects the pertinence and systematicness of data processing. According to the characteristics of the fluid region, the grid type is selected, which can efficiently utilize the data processing resources and avoid the problems of calculation redundancy or insufficient precision caused by improper grid type. Through reasonable planning of grid type, a scientific data processing framework is built for subsequent grid division, which guarantees the fit degree of grid division and actual flow field characteristics. In the process of grid division and framework construction, the grid is divided according to the fluid region and the basic framework of spatial grid distribution is obtained, which is a deep integration and structured processing of data. This grid division method based on data characteristics can effectively capture the macro characteristics of fluid flow and provide reliable data basis for flow field simulation analysis, ensuring that the calculation results can truly reflect the flow state of fluid in the suction chamber. Grid local encryption and data optimization are the core highlights of this scheme. The grid encryption area is set at the tip of the tongue and the cross-sectional area mutation, and the boundary layer grid is constructed along the wall surface. Through the operation of reducing the grid size and increasing the grid layer, the fine processing of the key area data is realized. These areas often have complex fluid mechanics phenomena, such as turbulence and pressure mutation. The encrypted grid can capture the local data characteristics more accurately and greatly improve the calculation accuracy. At the same time, the encryption parameters are reasonably controlled to avoid the calculation burden caused by excessive encryption under the premise of ensuring the accuracy, and the balance between data processing efficiency and accuracy is realized, which provides high-quality data support for subsequent flow field analysis, performance evaluation and other based on grid division, effectively enhancing the reliability of semi-spiral suction chamber design optimization.

[0107] The three-dimensional model of the suction chamber after grid division is simulated and simulated by computational fluid dynamics method, including:

[0108] Before the flow field distribution simulation is carried out, the physical model is selected first, the physical model adopts SSTk-omega model, wherein the fluid medium is clear water, and the flow state is steady incompressible flow;

[0109] Then, the solver type is selected, including steady-state solving and transient-state solving;

[0110] Then, the boundary conditions of the physical model are set, including the inlet boundary, the outlet boundary and the wall boundary;

[0111] After the physical model and the solver are confirmed, the flow field is initialized by mixed initialization, and then, the first-order format is used to calculate 500-1000 steps until the residual error is reduced, the second-order format is switched to continue iteration, and then, the velocity and pressure values at key positions including the tongue tip and the cross-section mutation are monitored in real time;

[0112] Finally, the physical model is simulated and calculated, when the simulation and calculation are carried out, the change curves of important variables including flow, pressure loss and velocity field distribution are monitored in real time, and the iteration is continued until the residual error completely meets the control standard.

[0113] Specifically, in the data model accurate selection link, SSTk-omega model is selected as the physical model, clear water is defined as the medium, steady incompressible flow is defined as the state, and the solver type is reasonably selected, which reflects the pertinence of data processing. The model and parameter setting closely match the actual working condition of the semi-spiral suction chamber, can efficiently process fluid dynamics data, avoid calculation deviation caused by model mismatch, build a reliable data processing foundation for flow field simulation, accurately set the inlet, outlet and wall boundary conditions in the boundary condition and data setting process, which is a systematic analysis and standard processing of data. Reasonable boundary condition setting can truly restore the flow environment of the fluid in the suction chamber, make the simulation result closer to the actual running state, provide accurate data basis for subsequent data analysis and performance evaluation, enhance the credibility of the simulation result, and the calculation process and data optimization are the core highlights of the scheme. Mixed initialization processing and step-by-step iteration calculation, combined with real-time monitoring of the velocity and pressure values at key positions, realize dynamic optimization and deep processing of data. First, the first-order format is used to quickly reduce the residual error, and then the second-order format is switched to improve the calculation accuracy, balancing the calculation efficiency and accuracy; important variables such as flow and pressure loss are monitored in real time, and the iteration is continued until the residual error meets the standard, ensuring that the simulation result converges to the optimal solution. This refined data processing process can not only efficiently capture the macro characteristics of the flow field, but also accurately depict the data characteristics of the key areas, providing high-quality data support for performance analysis and structure optimization of the semi-spiral suction chamber, effectively improving the scientificity and reliability of design optimization.

[0114] According to the flow field distribution simulation result, the flow field characteristics are analyzed, including:

[0115] The parameter data in the simulation results is extracted first, including velocity distribution data, pressure distribution data, turbulent flow characteristics and vortex data;

[0116] The parameter data is analyzed respectively, wherein the analysis of the velocity distribution data includes overall velocity nephogram analysis, cross-section velocity analysis and velocity vector diagram analysis; the analysis of the pressure distribution data includes global pressure nephogram analysis, pressure loss calculation analysis and local abnormal pressure analysis; and the analysis of the flow characteristics and vortex data is turbulent flow energy analysis, turbulent kinetic energy distribution analysis, vorticity and vortex structure analysis;

[0117] The key parameters in the analysis results are counted, including flow passing property, characteristic variable trend graph, maximum, minimum and mean square deviation of velocity and pressure;

[0118] The key parameters are compared, wherein the flow passing property is used to compare the actual flow capacity with the design flow to determine the influence of the suction chamber structure on the fluid passing capacity; the characteristic variable trend graph is used to extract the change trend of the velocity and pressure at the tip of the baffle and the cross-section mutation with the iteration step or different schemes to compare the flow field reaction under different structural parameters; and the maximum, minimum and mean square deviation of the velocity and pressure reflect the overall uniformity and skewness of the flow field;

[0119] The flow uniformity coefficient is used to quantitatively analyze the flow uniformity by comparing the cross-section velocity distribution, and the pressure loss and energy consumption level under unit flow are calculated to locate the high loss area;

[0120] Finally, the flow field characteristic analysis data is obtained.

[0121] Specifically, in the data comprehensive extraction and integration link, the scheme synchronously extracts multi-dimensional parameter data such as speed, pressure and turbulence, and constructs a complete flow field data set. This data acquisition strategy avoids information omission and ensures that the analysis is based on comprehensive fluid dynamics data, laying a foundation for subsequent in-depth research. By integrating different types of data, the flow field characteristics can be cross-verified from multiple perspectives, enhancing the reliability of the analysis results. Multi-dimensional data analysis fully demonstrates the depth of data processing. For speed, pressure and other parameters, various analysis dimensions are designed, such as visual data processing through speed cloud maps and vector diagrams to intuitively present fluid motion trends; pressure loss measurement combines mathematical models to convert raw data into quantifiable performance indicators. In turbulence characteristic analysis, the study of energy and kinetic energy distribution further explores the potential value of data, providing key clues for understanding complex flow mechanisms. Key parameter quantification and comparison are the core advantages of the scheme. By statistically analyzing key parameters such as flow through capacity and characteristic variable trends, abstract flow field characteristics are converted into specific data indicators for multi-dimensional comparative analysis. Comparison of actual flow capacity with design flow capacity quickly locates structural defects based on data processing; characteristic variable trend graphs intuitively reflect the impact of different design schemes on the flow field through longitudinal data comparison; statistical quantities such as mean square error quantitatively measure flow field uniformity from a mathematical perspective, providing precise data guidance for structural optimization. Finally, using quantitative indicators such as flow uniformity coefficient and unit flow pressure loss, qualitative analysis is upgraded to quantitative evaluation, making flow field characteristic analysis results more practical for engineering, significantly improving the scientific nature and efficiency of semi-spiral suction chamber optimization design.

[0122] To solve the problem in the prior art that the performance of the suction chamber is not analyzed in depth and the optimization rules are not considered from multiple angles, resulting in poor applicability of the suction chamber, please refer to Figure 1 The embodiment provides the following technical solutions:

[0123] The physical verification of the flow field characteristic analysis results includes:

[0124] Before the physical verification, an experimental platform is built, wherein a centrifugal pump is selected as the test pump body according to the design parameters of the semi-spiral suction chamber, and the structure of the pump body is consistent with the simulation model, and meanwhile, high-precision flow measurement devices, pressure measurement instruments, vibration measurement equipment and noise measurement instruments are provided, the centrifugal pump is installed on a stable test bench, and the water inlet pipe, the water outlet pipe and the measurement instruments are connected;

[0125] Referring to the working condition conditions of the simulation, the flow rate and rotational speed parameters of the test are set, and 3-5 different flow rate working condition points are selected, including a design flow rate point and working condition points deviating from the design flow rate;

[0126] After the working condition points are selected, physical quantity measurement is performed, including flow rate measurement, pressure measurement, vibration measurement and noise measurement;

[0127] According to the measurement results, data comparison and analysis are performed, including flow comparison and analysis, pressure comparison and analysis, speed comparison and analysis, vibration comparison and analysis, and noise comparison and analysis;

[0128] According to the results of data comparison and analysis, the accuracy of the simulation model is comprehensively evaluated, and the results of physical verification are fed back to the optimization design of the semi-spiral suction chamber.

[0129] Specifically, in the data comprehensive extraction and integration link, the scheme synchronously extracts multi-dimensional parameter data such as speed, pressure, and turbulent flow, and constructs a complete flow field data set. This data acquisition strategy avoids information omission and ensures that the analysis is based on comprehensive fluid dynamics data, laying a foundation for subsequent in-depth research. By integrating different types of data, the flow field characteristics can be cross-verified from multiple perspectives, enhancing the reliability of the analysis results. Multi-dimensional data analysis fully demonstrates the depth of data processing. For speed, pressure and other parameters, multiple analysis dimensions are designed, such as visual data processing through speed cloud chart and vector diagram to intuitively present the fluid motion trend; pressure loss measurement combines mathematical models to convert raw data into quantifiable performance indicators. In the analysis of turbulent flow characteristics, the study of energy and kinetic energy distribution further explores the potential value of data, providing key clues for understanding complex flow mechanisms. Key parameter quantification and comparison are the core advantages of the scheme. By statistically analyzing the flow through nature, characteristic variable trends, and other key parameters, abstract flow field characteristics are converted into specific data indicators and subjected to multi-dimensional comparison and analysis. The comparison between actual flow capacity and designed flow capacity quickly locates structural defects based on data processing; the characteristic variable trend chart intuitively reflects the influence of different design schemes on the flow field through longitudinal data comparison; and statistical quantities such as mean square deviation quantitatively measure the uniformity of the flow field from a mathematical perspective, providing precise data guidance for structural optimization. Finally, using quantitative indicators such as flow uniformity coefficient and unit flow pressure loss, qualitative analysis is upgraded to quantitative evaluation, making the flow field characteristic analysis results more practical for engineering, and significantly improving the scientific nature and efficiency of semi-spiral suction chamber optimization design.

[0130] According to the flow field distribution simulation data and the physical verification results, optimization rules for the semi-spiral suction chamber are generated, including:

[0131] First, the flow field distribution simulation data and the physical verification results are extracted;

[0132] After extraction, data comparison is performed, which involves sorting and comparing simulation data and physical verification results under different tongue inclination angles, and confirming design target deviations, including unmet simulation efficiency expectations, excessive vibration values, and excessively large cavitation areas;

[0133] According to the flow field characteristic analysis results, the performance deviation is associated with the flow field characteristics. If the efficiency is insufficient, the outlet section velocity standard deviation is too large, which indicates that the flow field is uneven. If the vibration is excessive, the pressure fluctuation frequency near the tongue is consistent with the blade passing frequency, which indicates that the vortex induces resonance. If the cavitation is serious, the area of the tongue tip pressure ≤ saturated steam pressure is ≥ 5cm 2 ;

[0134] According to the association of performance deviation and flow field characteristics, the mapping relationship between geometry, flow field and performance is obtained, and the parameter sensitivity matrix is established according to the mapping relationship. The parameter sensitivity matrix chart is as follows:

[0135] Geometric parameter Flow field influence Performance correlation Tongue angle Change inlet vortex position Influence on vibration and noise Cross-sectional area gradient Control diffuser expansion rate Influence on pressure loss and efficiency Tongue arc radius Mitigate tongue tip flow velocity surge Inhibit cavitation Axial length Influence on fluid acceleration smoothness Influence on exit flow field uniformity

[0136] Then, the optimization rule framework is formulated, including parameter adjustment strategy and structure optimization rule;

[0137] According to the formulated optimization rule framework, the optimization rule is generated based on the comparison results of flow field distribution simulation data and physical verification results and the parameter sensitivity matrix;

[0138] The generated optimization rule is presented in the form of parameter range, structure design suggestion and process requirement.

[0139] Specifically, in the multi-source data integration and comparison link, the scheme synchronously extracts the flow field simulation data and the physical verification results, realizes the organic combination of theoretical and practical data, and accurately identifies the design target deviation by comparing the two types of data under different lip angles, avoiding the limitations of single data source. This data integration strategy provides a comprehensive and reliable basis for subsequent optimization, ensuring the accuracy of the optimization direction, and the performance, flow field, and geometry correlation analysis fully demonstrates the depth of data processing. The performance deviation and flow field characteristics are quantitatively correlated, such as evaluating the efficiency by the standard deviation of the outlet cross-section velocity and determining the vibration reason by the pressure pulsation frequency, which converts abstract performance problems into specific flow field indicators. Then, the mapping relationship between geometric parameters, flow field influence, and performance is established, revealing the internal relationship among the three from the data level, providing a logical and clear data link for the establishment of optimization rules, effectively avoiding the blindness of empirical optimization, and the parameter sensitivity matrix construction and rule generation are the core highlights of the scheme. The parameter sensitivity matrix constructed based on the mapping relationship clearly shows the influence mechanism of each geometric parameter on the performance in a structured data form, providing an intuitive reference for parameter adjustment. Combined with the optimization rule framework, the simulation and verification comparison results and matrix data are converted into specific parameter ranges, design suggestions, and process requirements, realizing efficient conversion from data to rules. This data-driven optimization rule generation method not only guarantees the scientificity and systematicness of the optimization strategy, but also enhances the operability of the rules in actual engineering, significantly improving the efficiency and reliability of the semi-spiral suction chamber optimization design and helping to achieve the engineering goal of optimal performance.

[0140] The generated optimization rules are subjected to comprehensive performance evaluation, and an engineering application scheme is obtained based on the comprehensive performance evaluation, including:

[0141] The generated optimization rules are applied to the structural design of the semi-spiral suction chamber to form an optimized design scheme, and a corresponding three-dimensional model is established based on the optimized design scheme. Meanwhile, the established three-dimensional model is subjected to structural refinement and parameter adjustment;

[0142] The three-dimensional model subjected to structural refinement and parameter adjustment is subjected to meshing, physical model setting, and boundary condition setting, and a fluid dynamics method is used to perform performance simulation of the three-dimensional model under multiple working conditions and multiple indicators, including flow rate, head, efficiency, pressure loss, flow field uniformity, cavitation performance, vibration, and noise. Finally, the performance indicator data are extracted and analyzed;

[0143] Based on the analysis results of the performance indicator data, an optimization scheme with optimal analysis results is selected for physical prototype manufacturing, and performance tests of flow rate, pressure, efficiency, vibration, and noise are performed on the physical prototype on an experimental platform. The simulation and experimental results are compared to verify the accuracy of the simulation prediction and supplement and correct the simulation data;

[0144] According to the simulation and experimental results, a comprehensive performance evaluation index system is established. According to the actual needs of engineering and application scenarios, the weights of each index are allocated, and the standardized processing of each index of each optimization scheme is carried out. The comprehensive score is calculated by weighting, and the performance ranking of multiple schemes is formed.

[0145] Combined with the comprehensive score results, the applicability of each optimization scheme in actual engineering is analyzed, including manufacturing difficulty, cost, reliability and maintainability.

[0146] According to the comprehensive score results, the best engineering application scheme is obtained.

[0147] Specifically, in the multiple rounds of data verification and correction link, the scheme converts the optimization rules into a three-dimensional model and carries out simulation, and then verifies the simulation results through physical prototype experiment. This dual verification mechanism of theory and practice ensures the performance stability of the design scheme in different scenarios. By comparing simulation and experimental data, not only can the simulation model parameters be corrected to improve the prediction accuracy, but also potential design defects can be found to provide reliable basis for subsequent optimization, effectively avoiding the limitations of single verification method. The construction of comprehensive performance evaluation index system fully shows the systematicness of data processing. The scheme establishes an index system covering multiple dimensions such as flow, efficiency and cavitation performance, and allocates weights according to engineering needs to realize comprehensive quantitative evaluation of optimization schemes. The standardized processing and weighted calculation of comprehensive score convert complex performance parameters into intuitive quantitative results, providing objective and scientific basis for scheme ranking, making the evaluation process more transparent and fair. Multi-dimensional engineering applicability analysis is the core advantage of the scheme. On the basis of comprehensive scoring, further analysis of manufacturing difficulty, cost and other actual engineering factors is carried out to deeply integrate technical indicators and engineering feasibility. This multi-dimensional evaluation strategy avoids the problem of pursuing only the best performance while ignoring the actual application restrictions, ensuring that the finally selected scheme is advanced in technology and feasible in engineering. Through data-driven decision support, the reliability and economy of the engineering application scheme are significantly improved, the research and development cycle is shortened, and the engineering risk is reduced, providing a solid guarantee for the practical application of semi-spiral suction chamber.

[0148] It should be noted that in this paper, relationship terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between the entities or operations. Moreover, the terms "include", "contain" or any other variants thereof are intended to cover non-exclusive inclusion, so that the process, method, article or equipment including a series of elements not only includes those elements, but also includes other elements not explicitly listed or inherent to such process, method, article or equipment.

[0149] While embodiments of the application have been shown and described, it is to be understood that the embodiments described are merely exemplary of the principles and application of the present application. Numerous modifications and changes can be made by those skilled in the art without departing from the spirit and principles of the present application.

Claims

1. A method for optimization of a semi-spiral suction chamber based on the lip angle, characterized by, Comprise: According to the design data of the semi-spiral suction chamber, the geometric parameters of the semi-spiral suction chamber are confirmed, and the three-dimensional model of the suction chamber is established according to the confirmed geometric parameters. The three-dimensional model of the suction chamber is divided into grids, and the flow field distribution simulation of the three-dimensional model of the suction chamber is carried out by the computational fluid dynamics method. According to the flow field distribution simulation result, the flow field characteristic analysis is carried out, and the physical verification of the flow field characteristic analysis result is carried out. According to the flow field distribution simulation data and the physical verification result, the optimization rule of the semi-spiral suction chamber is generated, and finally the generated optimization rule is comprehensively evaluated, and the engineering application scheme is obtained according to the comprehensive performance evaluation; The physical verification of the flow field characteristic analysis result comprises: Before physical verification, an experimental platform is built first. According to the design parameters of the semi-spiral suction chamber, a centrifugal pump is selected as the test pump body, and the structure of the pump body is consistent with the simulation model. At the same time, high-precision flow measurement devices, pressure measurement instruments, vibration measurement equipment and noise measurement instruments are equipped. The centrifugal pump is installed on a stable test bench, and the water inlet pipe, water outlet pipe and measurement instruments are connected. Referring to the working condition of the simulation, the flow rate and rotational speed parameters of the test are set, and 3-5 different flow rate working points are selected, including the design flow rate point and the working point deviating from the design flow rate. After the working point selection is completed, the physical quantity measurement is carried out, including flow measurement, pressure measurement, vibration measurement and noise measurement. According to the measurement results, data comparison and analysis are carried out, including flow comparison and analysis, pressure comparison and analysis, speed comparison and analysis, vibration comparison and analysis and noise comparison and analysis. According to the results of data comparison and analysis, the accuracy of the simulation model is comprehensively evaluated, and the results of physical verification are fed back to the optimization design of the semi-spiral suction chamber. According to the flow field distribution simulation data and the physical verification result, the optimization rule of the semi-spiral suction chamber is generated, comprising: First, the flow field distribution simulation data and the physical verification result are extracted. After extraction, data comparison is carried out. The data comparison is to compare the simulation data and the physical verification result under different tongue inclination angles, and to compare them at the same time. At the same time, the design target deviation is confirmed, including the simulation efficiency not reaching the expectation, the vibration value exceeding the standard and the cavitation area being too large. According to the flow field characteristic analysis result, the performance deviation is associated with the flow field characteristics. If the efficiency is insufficient, the outlet cross-section velocity standard deviation is too large, which indicates that the flow field is not uniform. If the vibration exceeds the standard, the pressure fluctuation frequency near the tongue is consistent with the blade passing frequency, which indicates that the vortex causes resonance. If the cavitation is serious, the area of the region where the tongue tip pressure is less than or equal to the saturated steam pressure is greater than or equal to 5 cm². According to the mapping relationship between the performance deviation and the flow field characteristics, the parameter sensitivity matrix is established. Then, the optimization rule framework is formulated, including the parameter adjustment strategy and the structure optimization rule. According to the formulated optimization rule framework, the comparison results of the flow field distribution simulation data and the physical verification result and the parameter sensitivity matrix are used to generate the optimization rule. The generated optimization rules are presented in the form of parameter ranges, structural design suggestions, and process requirements.

2. The method of claim 1, wherein, According to the design data of the semi-spiral suction chamber, the geometric parameters of the semi-spiral suction chamber are confirmed, including: The basic design parameters of the semi-spiral suction chamber are extracted from the database, including performance parameters and structural reference parameters, wherein the performance parameters include design flow, design head, rated speed, and impeller inlet target flow velocity range; the structural reference parameters include impeller inlet diameter, impeller inlet center height, suction chamber outlet width, and tongue starting position radius; According to the extracted basic design parameters, the geometric parameters of the semi-spiral suction chamber cross section are defined, including cross section division and cross section area gradient design; The cross section division is to calculate the number of cross sections based on the center of the suction chamber outlet; 3. The method of claim 2, wherein, According to the design data of the semi-spiral suction chamber, the geometric parameters of the semi-spiral suction chamber are confirmed, including: After the geometric parameter definition of the semi-spiral suction chamber cross section is completed, the geometric parameters are calibrated; The calibration of the geometric parameters is to set the adjustment range of the tongue inclination angle α to 0°-60°, and set a group of test parameters every 10°, and the tongue inclination angle corresponds to the suction chamber outlet cross section position, and the axial distance between the tongue tip and the impeller inlet meets the fluid smooth transition requirement; After the geometric parameter calibration is completed, the impeller parameters are integrated, which is to match the suction chamber outlet cross section size with the impeller inlet diameter and blade inlet setting angle, and then to confirm the number of double suction pump blades, wherein the suction chamber cross section distribution corresponds to the number of blades in even multiples; After the geometric parameter calibration is completed, the geometric parameters of the semi-spiral suction chamber are integrated, including cross section number, angle, area, tongue inclination angle, inlet diameter, axial length, and number of impellers; After the integration is completed, the complete geometric parameters of the semi-spiral suction chamber are obtained.

4. The method of claim 3, wherein, According to the confirmed geometric parameters, a three-dimensional model of the semi-spiral suction chamber is established, including: According to the two-dimensional engineering drawings in the database, the two-dimensional engineering drawings are exported, and the coordinate origin in the two-dimensional engineering drawings is taken as the reference; Then the reference coordinate system is established, which is to take the impeller center axis as the Z-axis reference, take the center of the suction chamber outlet as the coordinate origin, and establish a rectangular coordinate system including X-axis, Y-axis and Z-axis, and mark the impeller inlet installation plane position and the suction chamber inlet end face position; On the X-axis and Y-axis reference surface, take the Z-axis as the center, draw the closed sketch according to the confirmed cross section area and shape, and on each angle reference surface, draw the sketch according to the confirmed cross section area and recursive relationship; Using the sweep tool, take each cross section sketch as the cross section contour, take the Z-axis as the center axis, generate the semi-spiral flow passage main body, and during the sweeping process, according to the confirmed axial length parameter, limit the extension range of the flow passage in the Z-axis direction; After the sweep is completed, the tongue structure is constructed, wherein, first, the coordinates of the tongue tip are marked in the cross-sectional sketch according to the confirmed tongue starting position radius, and the tongue profile is extended along the inner wall of the half-spiral flow channel, in the three-dimensional modeling of the tongue, the inclination angle of the tongue is adjusted according to the confirmed inclination angle range, and the head of the tongue adopts a circular arc transition; After the tongue structure is constructed, the impeller structure is matched, wherein, at the outlet end surface of the suction chamber, a circular profile is drawn according to the confirmed impeller inlet diameter, and is aligned with the center of the suction chamber outlet cross section, at the same time, a transition fillet is added between the suction chamber outlet and the impeller inlet; After the impeller structure is matched, the suction chamber three-dimensional model is obtained.

5. The method of claim 4, wherein, The established suction chamber three-dimensional model is meshed, including: First, the fluid region in the suction chamber three-dimensional model is confirmed, then the mesh type of the suction chamber three-dimensional model is confirmed, the mesh type includes structured mesh, unstructured mesh and hybrid mesh; After the mesh type is confirmed, the mesh is divided according to the fluid region, and the basic framework of the space mesh distribution is obtained; At the same time, the local area of the mesh is encrypted, the local encryption includes setting the mesh encryption area at the tongue tip and the cross-sectional area mutation, the encryption radius is 5-10mm, the mesh size is reduced to 1 / 2-1 / 3 of the whole, the boundary layer mesh is set along the wall surface, the mesh layer number is 3-5 layers, the first layer thickness is 10-50μm, and the growth rate is 1.2-1.5; After encryption, the mesh division of the suction chamber three-dimensional model is completed.

6. The method of claim 5, wherein the semi-spiral suction chamber is optimized based on the lip angle. The three-dimensional model of the suction chamber with completed mesh division is simulated and simulated by computational fluid dynamics method, including: Before the flow field distribution simulation is simulated, the physical model is selected first, the physical model adopts SSTk-ω model, wherein, the fluid medium is clear water, and the flow state is steady incompressible flow; Then the solver type is selected, including steady-state solution and transient solution; Then the boundary conditions of the physical model are set, including inlet boundary, outlet boundary and wall boundary; After the physical model and the solver are confirmed, the flow field is initialized by mixed initialization, at the same time, the first order format is calculated for 500-1000 steps until the residual error is reduced, the second order format is switched to continue iteration, and the velocity and pressure values of the key positions including the tongue tip and the cross-sectional mutation are monitored in real time; Finally, the physical model is simulated and calculated, when the simulation calculation is carried out, the change curve of the important variable is monitored in real time, and the iteration is continued until the residual error completely reaches the control standard, wherein, the important variable includes flow, pressure loss and velocity field distribution.

7. The method of claim 6, wherein the semi-spiral suction chamber is optimized based on the lip angle. According to the flow field distribution simulation result, the flow field characteristic analysis is carried out, including: First, the parameter data in the simulation result is extracted, including velocity distribution data, pressure distribution data, turbulence characteristics and vortex data; The parameter data are analyzed respectively, wherein the analysis of the speed distribution data includes overall speed cloud map analysis, cross-section speed analysis and speed vector diagram analysis; the analysis of the pressure distribution data includes global pressure cloud map analysis, pressure loss calculation analysis and local abnormal pressure analysis; and the analysis of the flow characteristics and vortex data includes turbulent energy analysis, turbulent kinetic energy distribution analysis, vorticity and vortex structure analysis; The key parameters in the analysis results are counted, including flow passability, characteristic variable trend chart, maximum, minimum and mean square deviation of speed and pressure; The key parameters are compared, wherein the flow passability is compared between actual passability and design flow to determine the influence of the suction chamber structure on the fluid passability; the characteristic variable trend chart is used to extract the change trend of the speed and pressure at the tip of the baffle and the cross-section mutation with the iteration step or different schemes to compare the flow field response under different structural parameters; and the maximum, minimum and mean square deviation of the speed and pressure reflect the overall uniformity and skewness of the flow field; The flow uniformity coefficient is used to quantitatively analyze the flow uniformity through cross-section speed distribution comparison, and the pressure loss and energy consumption level under unit flow are calculated to locate the high loss area; Finally, the flow field characteristic analysis data are obtained.

8. The method of claim 1, wherein, The generated optimization rules are comprehensively evaluated, and the engineering application scheme is obtained according to the comprehensive performance evaluation, including: The generated optimization rules are applied to the structural design of the semi-spiral suction chamber to form an optimized design scheme, and a corresponding three-dimensional model is established according to the optimized design scheme, and the established three-dimensional model is refined in structure and adjusted in parameters; The three-dimensional model refined in structure and adjusted in parameters is meshed, the physical model is set and the boundary conditions are set, and the three-dimensional model is simulated in multiple working conditions and multiple indexes by using fluid dynamics method, including flow, head, efficiency, pressure loss, flow field uniformity, cavitation performance, vibration and noise, and finally the performance index data are extracted and analyzed; According to the analysis results of the performance index data, the optimization scheme with the best analysis result is selected to make a physical prototype, and the performance of the physical prototype is tested in flow, pressure, efficiency, vibration and noise on an experimental platform, and the simulation and experimental results are compared to verify the accuracy of the simulation prediction and supplement and correct the simulation data; According to the simulation and experimental results, an comprehensive performance evaluation index system is established, each index is weighted according to the actual engineering requirements and application scenarios, each index of each optimization scheme is standardized, the comprehensive score is calculated by weighting according to the weight, and the performance ranking of multiple schemes is formed; Combined with the comprehensive score results, the applicability of each optimization scheme in actual engineering is analyzed, including manufacturing difficulty, cost, reliability and maintainability; The best engineering application scheme is obtained according to the comprehensive score results.

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