Compressor sand swallowing wear robustness optimization design method and system, equipment and medium

Abstract

The invention discloses a gas compressor sand swallowing wear robustness optimization design method and system, equipment and a medium, and the method comprises the steps: carrying out the preliminary optimization of a pneumatic scheme, and guaranteeing that the delivery performance of a gas compressor is not reduced compared with the conventional design; then, a high-precision real-time simulation method for compressor blade abrasion is constructed, and the coupling relation between blade geometry and the abrasion rate is updated in real time, so that blade geometric abrasion and aerodynamic performance decline caused by sand swallowing when the compressor works in an external field environment are accurately simulated; thirdly, based on the real-time simulation method, sand swallowing uncertainty analysis is conducted on the preliminary design scheme, wear sensitive design parameters are optimized, the sand swallowing wear robustness of the gas compressor is improved, and an optimized design scheme is obtained; and finally, the aerodynamic performance of the optimization design scheme is verified. According to the method, the wear resistance of the compressor can be improved on the basis that the aerodynamic performance of the traditional designed compressor is not reduced, manual design experience is not needed in the whole optimization process, and performance degradation of the turboshaft engine can be relieved.

Description

Technical Field

[0001] The present invention relates to the technical field of compressor aerodynamics and thermodynamics, and in particular to a compressor sand engulfment wear robustness optimization design method and system, electronic equipment, and a computer-readable storage medium. Background Art

[0002] When gas turbine engines, especially turboshaft engines, operate in harsh outdoor environments, they inhale particles and impurities such as sand and dust, which are eroded and worn for a long time, causing changes in the blade profile and flow path, resulting in the compressor aerodynamic performance deviating from the design state, reducing the compressor efficiency and surge margin, reducing the performance of the bleed air engine, and even causing surge, which seriously endangers outdoor use or flight safety.

[0003] When considering the impact of external foreign matter or dust wear, the existing compressor design method, on the one hand, reduces the impact of dust wear by adding external equipment such as particle separators or adding compressor blade coatings, but this is not conducive to engine performance, reliability and cost control; on the other hand, based on engineering experience, it resists wear by increasing geometric parameters such as compressor blade thickness and chord length, or increases design indicators to increase margins, but this is subjective and has limitations. Different designers may have different understandings and judgments, resulting in unstable design results. It is difficult to ensure that the impact of dust wear on compressor performance can be effectively reduced under various complex working conditions.

[0004] Furthermore, compressor blade wear research is primarily based on experimental and simulation methods. Experimental methods, due to their high cost and long cycle times, have certain limitations in engineering applications. Simulation methods, based on existing wear models, offer the advantages of low cost and short cycle times. Currently, compressor blade wear simulation methods fail to account for the real-time changes in wear rate during the wear process, lack understanding of the wear process, and inaccurately simulate wear volume. Summary of the Invention

[0005] The present invention provides a compressor sand swallowing wear robustness optimization design method and system, electronic equipment, and computer-readable storage medium, which can improve the wear resistance without affecting the aerodynamic performance of the compressor. The entire optimization process does not require manual design experience and can effectively reduce the impact of sand and dust wear on compressor performance under complex operating conditions of the turboshaft engine.

[0006] According to one aspect of the present invention, a method for optimizing the robustness of compressor sand engulfment wear is provided, comprising the following: Optimize the aerodynamic performance of the compressor before leaving the factory and obtain a preliminary design scheme; Develop a high-precision real-time simulation method for blade wear to update the coupling relationship between blade geometry and wear rate in real time, thereby accurately calculating the amount of blade geometric wear and aerodynamic performance degradation caused by sand ingestion when the compressor operates in an outdoor environment; Uncertainty analysis was performed on the changes in blade aerodynamic performance caused by sand ingestion during the compressor's first overhaul period. Using a high-precision real-time simulation method for blade wear, the design parameters of wear-sensitive blades in the preliminary design were further optimized, resulting in an optimized design for compressor wear resistance. The aerodynamic performance of the compressor wear-resistant optimization design scheme is verified. If its aerodynamic performance meets the design indicators, the optimized design scheme will be used as the final design scheme, otherwise, iterative optimization will continue.

[0007] Furthermore, the process of constructing a high-precision real-time simulation method for blade wear includes the following: Generate the compressor blade mesh, set the blade surface solid wall boundary as the UDF motion boundary, set the corresponding contact mesh as the deforming mesh, and set the compressor sand swallowing wear simulation conditions; The compressor flow field is calculated to obtain the blade surface wear rate, and the total sand engulfment wear time is divided into multiple wear periods; At the end of the current wear period, the blade surface wear amount in the three-dimensional direction is calculated based on the blade surface wear rate and the duration of the wear period; The blade surface wear amount in the three-dimensional direction during the current wear period is used to determine the coordinates of the blade surface solid wall boundary position after wear. The coordinates of the wall grid points are updated through UDF, and the computational domain grid is updated before the sand swallowing wear simulation is performed for the next wear period. The iterations are continued until the sand swallowing wear simulation is completed for all wear periods. The total wear amount is obtained by accumulating the blade surface wear amount in all wear periods. The degradation of the compressor's aerodynamic performance during the first turnaround period is determined based on the blade surface wear amount in different wear periods.

[0008] Furthermore, the amount of blade surface wear within a certain period of time is calculated based on the following formula: ; Where ΔH i represents the amount of blade surface wear during the i-th wear period, E i represents the wall wear rate during the i-th wear period, ρ represents the blade material density, and Δt i represents the duration of the i-th wear period.

[0009] Furthermore, the total sand swallowing wear time is divided into multiple wear periods of equal length; or, the total sand swallowing wear time is divided into segmented time distribution curves with approximately constant wear rates, and the length of each wear period is obtained through the corresponding curves.

[0010] Furthermore, the uncertainty analysis of the changes in blade aerodynamic performance caused by sand ingestion during the first turn-over period of the compressor is performed, and the design parameters of the wear-sensitive blades in the preliminary design scheme are further optimized based on the high-precision real-time simulation method of blade wear. The process of obtaining the wear-resistant optimization design scheme of the compressor includes the following: Set uncertainty parameters for compressor blade wear, perform sensitivity analysis on the uncertainty parameters, and determine the key wear design parameters that are sensitive to blade wear; Based on key wear design parameters, a high-precision real-time blade wear simulation method is used to simulate blade wear in real time to construct sample data on the impact of key wear design parameters on compressor aerodynamic performance; A data-driven model for the impact of key wear design parameters on aerodynamic performance is trained based on a sample data set. The expectation and variance of the compressor's first turnover period aerodynamic performance are used as the objective function to obtain the optimal design scheme for compressor wear resistance.

[0011] Furthermore, the process of optimizing the aerodynamic performance of the compressor before leaving the factory includes the following: Conduct sensitivity analysis based on the compressor design parameters to determine the key design parameters that are sensitive to aerodynamic performance; An aerodynamic performance model was constructed to simulate the impact of key design parameters on aerodynamic performance. After training the aerodynamic performance model, a multi-objective genetic algorithm was used to optimize the key design parameters, resulting in a preliminary design scheme for the compressor before delivery. The preliminary design scheme is verified for aerodynamic performance. If its aerodynamic performance does not meet the design index requirements, the number of samples of the aerodynamic performance model is increased and it is iterated again until the aerodynamic performance of the preliminary design scheme meets the design index.

[0012] Furthermore, the process of verifying the aerodynamic performance of the optimized design solution includes the following: Statistical index analysis is performed on the efficiency and surge margin of the compressor design point at the end of the first overhaul period. If the statistical index results meet the design index requirements, the optimized design scheme will be used as the final design scheme. Otherwise, it will return to the factory optimization design stage for iteration.

[0013] In addition, the present invention also provides a compressor sand swallowing wear robustness optimization design system, comprising: The factory performance optimization module is used to optimize the aerodynamic performance of the compressor before leaving the factory and obtain a preliminary design solution; The blade wear real-time simulation module is used to build a high-precision real-time simulation method for blade wear. It updates the coupling relationship between blade geometry and wear rate in real time, thereby accurately calculating the blade geometric wear and aerodynamic performance degradation caused by sand ingestion when the compressor operates in an outdoor environment. The wear resistance optimization module is used to perform uncertainty analysis on the changes in blade aerodynamic performance caused by sand ingestion during the compressor's first turnaround period. Based on a high-precision real-time simulation method for blade wear, the design parameters of wear-sensitive blades in the preliminary design scheme are further optimized to obtain an optimized design scheme for compressor wear resistance. The aerodynamic performance verification module is used to verify the aerodynamic performance of the compressor wear resistance optimization design scheme. If its aerodynamic performance meets the design indicators, the optimized design scheme will be used as the final design scheme, otherwise iterative optimization will continue.

[0014] In addition, the present invention also provides an electronic device, including a processor and a memory, wherein the memory stores a computer program, and the processor is configured to execute the steps of the above method by calling the computer program stored in the memory.

[0015] In addition, the present invention also provides a computer-readable storage medium for storing a computer program for optimizing the robustness design of compressor sand swallowing and wear, wherein the computer program executes the steps of the above-mentioned method when running on a computer.

[0016] The present invention has the following beneficial effects: The present invention provides a method for optimizing the robustness of compressor sand swallowing wear. The method first performs a preliminary design of the aerodynamic scheme based on the traditional compressor factory aerodynamic performance optimization design method to ensure that the compressor factory performance does not decline compared with the traditional design; then, a high-precision real-time simulation method for compressor blade wear is proposed. By updating the coupling relationship between blade geometry and wear rate in real time, the blade geometry wear and aerodynamic performance degradation caused by sand swallowing when the compressor works in an outdoor environment are accurately simulated; then, based on the real-time simulation method, the preliminary design scheme of the compressor is further analyzed for sand swallowing uncertainty, the compressor wear-sensitive design parameters are optimized, the sand swallowing wear robustness of the compressor is improved, and the compressor wear-resistant optimization design scheme is obtained; finally, the aerodynamic performance of the optimized design scheme is verified; the method can improve the wear resistance of the traditional design compressor without reducing its aerodynamic performance. The entire optimization process does not require manual design experience, and can effectively improve the statistical performance of the expectation, variance, and other aerodynamic performance of the compressor efficiency, margin, etc. during the first turnaround period, which helps to alleviate the performance degradation of the turboshaft engine.

[0017] In addition, the compressor sand swallowing wear robustness optimization design system of the present invention also has the above advantages.

[0018] In addition to the above-described objects, features and advantages, the present invention has other objects, features and advantages. The present invention will be further described in detail below with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] The accompanying drawings, which constitute part of this application, are intended to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are intended to explain the present invention and do not constitute an undue limitation of the present invention. In the accompanying drawings: Figure 1 1 is a flow chart of a method for optimizing the robustness of compressor sand engulfment wear according to a preferred embodiment of the present application; Figure 2 yes Figure 1 Schematic diagram of the sub-process of step S10; Figure 3 yes Figure 1 Schematic diagram of the sub-process of step S20; Figure 4 is a schematic diagram of dividing the total wear time into multiple wear periods in a preferred embodiment of the present application; Figure 5 yes Figure 1 Schematic diagram of the sub-process of step S30; Figure 6 This is a structural diagram of a combined compressor selected for example verification in a preferred embodiment of the present application; Figure 7 This is a schematic diagram of the wear rate distribution of the combined compressor obtained through simulation analysis during the example verification in the preferred embodiment of the present application; Figure 8 This is a schematic diagram showing the sensitivity of blade geometry parameters to average wear, obtained during example verification in a preferred embodiment of the present application; Figure 9 This is a schematic diagram showing the sensitivity of the centrifugal impeller blade profile and flow channel geometric parameters to the average wear amount obtained during the example verification in the preferred embodiment of the present application; Figure 10 Schematic diagram of the probability density distribution of the amount of sand swallowed per unit time during the example verification in the preferred embodiment of the present application; Figure 11 Schematic diagram of the uncertainty range of the inlet blade angle of the axial flow rotor blade tip profile obtained during the example verification in the preferred embodiment of the present application; Figure 12 Schematic diagram of the uncertainty range of the leading edge radius of the axial flow rotor blade tip obtained during the example verification in the preferred embodiment of the present application; Figure 13 Schematic diagram of the uncertainty range of the chord length of the axial flow rotor blade tip profile obtained during the example verification in the preferred embodiment of the present application; Figure 14 Schematic diagram of the uncertainty range of the outlet blade angle of the root section of the centrifugal impeller obtained during the example verification in the preferred embodiment of the present application; Figure 15Schematic diagram of the uncertainty range of the second flow channel control point of the root section of the centrifugal impeller obtained during the example verification in the preferred embodiment of the present application; Figure 16 Schematic diagram of the uncertainty range of the third flow channel control point of the root section of the centrifugal impeller obtained during the example verification in the preferred embodiment of the present application; Figure 17 Schematic diagram of the prediction accuracy of the compressor efficiency by the aerodynamic performance model constructed during the example verification in the preferred embodiment of the present application; Figure 18 Schematic diagram of the prediction accuracy of the compressor surge margin by the aerodynamic performance model constructed during the example verification in the preferred embodiment of the present application; Figure 19 This is a schematic diagram of a solution set for multi-objective optimization using a multi-objective genetic algorithm when performing example verification in a preferred embodiment of the present application; Figure 20 1 is a schematic diagram of the mean distribution of compressor efficiency of a combined compressor prototype solution under the influence of blade wear, obtained during an example verification in a preferred embodiment of the present application; Figure 21 1 is a schematic diagram of the variance distribution of the compressor efficiency of the combined compressor prototype solution under the influence of blade wear obtained during the example verification in the preferred embodiment of the present application; Figure 22 1 is a schematic diagram of the mean distribution of the compressor surge margin of the combined compressor prototype solution under the influence of blade wear obtained during the example verification in the preferred embodiment of the present application; Figure 23 1 is a schematic diagram of the variance distribution of the compressor surge margin of the combined compressor prototype solution under the influence of blade wear obtained during the example verification in the preferred embodiment of the present application; Figure 24 1 is a schematic diagram of the mean distribution of compressor efficiency under the influence of blade wear of the combined compressor optimization design scheme obtained during the example verification in the preferred embodiment of the present application; Figure 25 1 is a schematic diagram of the variance distribution of the compressor efficiency of the combined compressor optimization design scheme under the influence of blade wear obtained during the example verification in the preferred embodiment of the present application; Figure 26 1 is a schematic diagram of the mean distribution of the compressor surge margin of the combined compressor optimization design solution under the influence of blade wear obtained during the example verification in the preferred embodiment of the present application; Figure 27 1 is a schematic diagram of the variance distribution of the compressor surge margin of the combined compressor optimization design solution under the influence of blade wear obtained during the example verification of the preferred embodiment of the present application; Figure 28It is a schematic diagram of the module structure of a compressor sand swallowing wear robustness optimization design system according to another embodiment of the present application. DETAILED DESCRIPTION

[0020] It should be noted that, in the absence of conflict, the embodiments and features of the embodiments in this application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0021] Reference Figure 1 The preferred embodiment of the present application provides a method for optimizing the robustness of compressor sand swallowing wear, including the following contents: Step S10: Optimizing the aerodynamic performance of the compressor before leaving the factory to obtain a preliminary design scheme; Step S20: constructing a high-precision real-time simulation method for blade wear to update the coupling relationship between blade geometry and wear rate in real time, thereby accurately calculating the blade geometric wear and aerodynamic performance degradation caused by sand ingestion when the compressor operates in an outdoor environment; Step S30: Perform uncertainty analysis on the changes in blade aerodynamic performance caused by sand ingestion during the first turn-over period of the compressor, and further optimize the wear-sensitive blade design parameters in the preliminary design scheme based on a high-precision real-time simulation method for blade wear to obtain an optimized design scheme for compressor wear resistance; Step S40: verifying the aerodynamic performance of the compressor wear resistance optimization design scheme. If the aerodynamic performance meets the design specifications, the optimized design scheme is used as the final design scheme; otherwise, iterative optimization is continued.

[0022] It can be understood that the compressor sand swallowing wear robustness optimization design method of this embodiment first performs a preliminary aerodynamic design based on the traditional compressor factory aerodynamic performance optimization design method to ensure that the compressor factory performance does not decline compared to the traditional design; then, a high-precision real-time simulation method for compressor blade wear is proposed. By updating the coupling relationship between blade geometry and wear rate in real time, the blade geometric wear and aerodynamic performance degradation caused by sand swallowing when the compressor is working in an outdoor environment are accurately simulated; then, based on the real-time simulation method, the sand swallowing uncertainty analysis of the preliminary design scheme of the compressor is further performed, the compressor wear-sensitive design parameters are optimized, the sand swallowing wear robustness of the compressor is improved, and the compressor wear-resistant optimization design scheme is obtained; finally, the aerodynamic performance of the optimized design scheme is verified; this method can improve the wear resistance performance of the traditional design compressor without reducing its aerodynamic performance. The entire optimization process does not require manual design experience, and can effectively improve the statistical performance of the expectation, variance, and other aerodynamic performance of the compressor efficiency, margin, etc. during the first overhaul period, which helps to alleviate the performance degradation of the turboshaft engine.

[0023] Among them, such as Figure 2As shown, in step S10, the process of optimizing the aerodynamic performance of the compressor before leaving the factory includes the following: Step S11: performing sensitivity analysis based on the compressor design parameters to determine key design parameters that are sensitive to aerodynamic performance; Step S12: constructing an aerodynamic performance model to simulate the impact of key design parameters on aerodynamic performance. After training the aerodynamic performance model, a multi-objective genetic algorithm is used to optimize the key design parameters to obtain a preliminary design scheme for the compressor before delivery. Step S13: performing aerodynamic performance verification on the preliminary design scheme. If the aerodynamic performance does not meet the design index requirements, increasing the number of samples of the aerodynamic performance model and re-iterating until the aerodynamic performance of the preliminary design scheme meets the design index.

[0024] Specifically, the styling design parameters that affect the aerodynamic performance of the compressor are first set, and then the active subspace method is used to perform a sensitivity analysis on the styling design parameters, so as to determine the key styling design parameters that are sensitive to aerodynamic performance, and use them as the key parameters for aerodynamic performance optimization. Among them, the active subspace method belongs to the existing technology, and the specific principles will not be repeated here. Then, a neural network is used to construct an aerodynamic performance model to simulate the influence of key styling design parameters on aerodynamic performance. After the training data set is produced, the aerodynamic performance model is trained. Among them, the production process of the training data set belongs to the existing technology and will not be repeated here. Next, a multi-objective genetic algorithm is used to perform multi-objective optimization solution for the efficiency and surge margin of the compressor under the pressure ratio constraint, and the optimal solution in the Pareto frontier is selected as the preliminary design solution for the factory optimization of the compressor. Then, a high-precision CFD simulation method is used to verify the aerodynamic performance of the preliminary design scheme. If the compressor efficiency and surge margin of the preliminary design scheme meet the design index requirements, the preliminary design scheme is judged to meet the requirements. If the compressor efficiency and surge margin of the preliminary design scheme do not meet the design index requirements, the sample data volume of the key design parameters is increased, and the aerodynamic performance model is retrained and iterated until the compressor efficiency and surge margin of the preliminary design scheme meet the design index requirements.

[0025] It can be understood that the present invention can accurately determine the key design parameters that are sensitive to aerodynamic performance by performing sensitivity analysis on the compressor design parameters, providing an optimization direction for subsequent factory aerodynamic performance optimization, and then optimizing by constructing an agent model of the influence of the key design parameters of the compressor on the aerodynamic performance to achieve the optimal design of the key design parameters and obtain a preliminary design scheme. Finally, the preliminary design scheme is subjected to aerodynamic performance verification to ensure that the aerodynamic performance of the compressor meets the design indicators when it leaves the factory.

[0026] In addition, if Figure 3As shown, in step S20, the process of constructing a high-precision real-time simulation method for blade wear includes the following: Step S21: Generate compressor blade mesh, set the blade surface solid wall boundary as the UDF motion boundary, set the corresponding contact mesh as the deforming mesh, and set the compressor sand swallowing wear simulation conditions; Step S22: Calculate the compressor flow field to obtain the blade surface wear rate, and divide the total sand engulfment wear time into multiple wear periods; Step S23: at the end of the current wear period, the blade surface wear amount in the three-dimensional direction of the blade is calculated based on the blade surface wear rate and the duration of the wear period; Step S24: Determine the coordinates of the blade surface solid wall boundary position after wear based on the blade surface wear amount in the three-dimensional direction during the current wear period, update the wall grid point coordinates through UDF, and update the computational domain grid before performing sand swallowing wear simulation for the next wear period. Step S25: Continuously iterate until the sand swallowing wear simulation of all wear periods is completed, the total wear amount is obtained based on the accumulation of blade surface wear amounts of all wear periods, and the aerodynamic performance degradation of the compressor during the first turn-over period is determined based on the blade surface wear amounts of different wear periods.

[0027] Specifically, the compressor blade mesh is first generated based on conventional methods. The blade surface solid wall boundary is then set as the UDF moving boundary, the corresponding contact mesh is set as the deforming mesh, and the conditions for the compressor sand ingestion wear simulation are given, such as the flow field boundary conditions, turbulence model, sand particle inlet velocity, particle size distribution, mass flow rate, and wear model. Then, the compressor flow field is calculated to obtain the wall wear rate (i.e., blade surface wear rate), and the total sand ingestion wear time is divided into multiple wear periods, where, for example, Figure 4 As shown in , the total wear time can be divided into multiple wear periods of equal length, namely Figure 4 The straight line segment in , or the total wear time is divided into multiple time distribution curves with approximately constant wear rates, that is, Figure 4 The length of each wear period in the curve segment is determined through experiments or simulation results using high-density, equally divided time periods. The curve corresponds to the duration of each wear period. Furthermore, the specific steady and unsteady flow field calculation processes are state-of-the-art, and the detailed principles will not be elaborated here.

[0028] Then, at the end of the current wear period, the blade surface wear amount in the x, y, and z directions is calculated based on the wall wear rate and the duration of the wear period. Specifically, the blade surface wear amount in each dimension in a certain period is calculated based on the following formula: ; Where ΔH i represents the amount of blade surface wear during the i-th wear period, Ei represents the wall wear rate during the i-th wear period, ρ represents the blade material density, and Δt i represents the duration of the i-th wear period.

[0029] Then, based on the blade surface wear amount in the three-dimensional direction during the current wear period, the position coordinates of the blade solid wall boundary after wear damage can be determined, and the wall grid point coordinates are updated through UDF. At the same time, the computational domain grid is updated through the elastic light-smoothing mesh algorithm, and then the sand swallowing wear simulation of the next wear period is carried out.

[0030] The sand swallowing wear simulation is continuously iterated until the sand swallowing wear simulation of all wear periods is completed. The total wear amount (i.e., the geometric wear amount of the blades caused by sand swallowing) can be obtained by accumulating the blade surface wear amount of all wear periods, and the degradation of the aerodynamic performance of the compressor during the first turn-over period can be determined based on the blade surface wear amount of different wear periods. The principle of determining the degradation of the aerodynamic performance of the compressor during the first turn-over period based on the blade surface wear amount of different wear periods belongs to the existing technology and will not be repeated here. The total wear amount is calculated based on the following formula: ; Where N represents the total wear time and M represents the number of divided wear periods.

[0031] It can be understood that the present invention sets the blade surface solid wall boundary as the UDF motion boundary, the corresponding contact grid as the deformation grid, and divides the total wear time into multiple wear periods. After the end of each wear period, the blade surface wear amount of the blade in each wear period can be calculated, and the calculation domain grid is updated according to the blade surface wear amount of the current wear period before the sand swallowing wear simulation of the next wear period is performed, thereby realizing real-time blade wear simulation. Compared with the conventional flow field simulation method of setting the blade surface solid wall boundary as a fixed boundary and the blade surface wear rate as a fixed value, the real-time blade wear simulation of the present invention takes into account the damage and deformation of the blade geometry under the action of sand swallowing wear, which in turn affects the flow field, resulting in a change in the blade surface wear rate distribution, realizing fluid-solid coupling analysis under wear, thereby realizing high-precision simulation of blade sand swallowing wear, and greatly improving the accuracy and precision of blade wear simulation analysis.

[0032] In addition, if Figure 5 As shown, the step S30 specifically includes the following contents: Step S31: setting uncertainty parameters of compressor blade wear, and performing sensitivity analysis on the uncertainty parameters to determine key wear design parameters that are sensitive to blade wear; Step S32: performing blade real-time wear simulation based on the key wear design parameters using a high-precision real-time blade wear simulation method to construct sample data on the impact of the key wear design parameters on the aerodynamic performance of the compressor; Step S33: Based on the sample data set, a data-driven model of the impact of key wear design parameters on aerodynamic performance is trained, and the expectation and variance of the compressor's first overturn period aerodynamic performance are used as the objective function to obtain the compressor wear resistance optimization design scheme.

[0033] Specifically, to optimize the wear robustness of the compressor, uncertainty parameters for compressor blade wear are first set. A sensitivity analysis is then performed using the active subspace method to identify geometric parameters sensitive to blade wear (i.e., key wear design parameters). A high-precision real-time blade wear simulation is then performed based on the key wear design parameters. This real-time blade wear simulation accurately simulates the aerodynamic performance degradation during sand ingestion wear, assesses the impact of key design parameters on the compressor's aerodynamic performance loss during sand ingestion wear, constructs sample data between key wear design parameters and compressor aerodynamic performance loss, and constructs a sample point dataset. Next, a data-driven model for the impact of blade wear-sensitive design parameters on aerodynamic performance is constructed based on a neural network. The model is trained using the previously constructed sample point dataset until the model meets accuracy requirements. The trained data-driven model accurately reflects the mapping relationship between key wear design parameters and aerodynamic performance loss.

[0034] Then, taking the expectation and variance of the aerodynamic performance (such as efficiency and surge margin) under the influence of sand swallowing uncertainty during the first turnaround period of the compressor as the objective function, a multi-objective genetic algorithm is used to optimize the design parameters, and the optimization scheme in the Pareto front is selected as the design result of the sand swallowing wear robustness, thus obtaining the compressor wear resistance optimization design scheme.

[0035] In addition, in step S40, the process of verifying the aerodynamic performance of the optimized design solution includes the following: Statistical index analysis is performed on the efficiency and surge margin of the compressor design point at the end of the first overhaul period. If the statistical index results meet the design index requirements, the optimized design scheme will be used as the final design scheme. Otherwise, it will return to the factory optimization design stage for iteration.

[0036] Specifically, the Monte Carlo method is used to analyze the expectation and variance of the efficiency and surge margin of the compressor design point after the compressor reaches the first overrun period. If the expectation and variance of the efficiency and surge margin both meet the design index requirements, the optimized design solution is used as the final design solution. If it does not meet the design index requirements, the process returns to step S10 and uses the suboptimal solution in the Pareto front as the preliminary design solution for iterative optimization again until the design index requirements are met. Optionally, step S40 can also use a high-precision CFD simulation method to verify the aerodynamic performance of the optimized design solution. If the compressor efficiency and surge margin of the optimized design solution meet the design index requirements, it can also be used as the final design solution.

[0037] In addition, in order to prove the effectiveness of the optimization design method, this application also conducts an example verification. Specifically, a sand swallowing simulation is conducted on a certain type of three-stage axial flow plus one-stage centrifugal combined compressor. The structure of the combined compressor is as follows: Figure 6 As shown in the figure, the first 7 rows of blades are axial stages, namely the 0-stage guide vanes (S0), the axial first-stage rotor and stator (R1, S1), the second-stage rotor and stator (R2, S2), and the third-stage rotor and stator (R3, S3). The last 3 rows of blades are centrifugal stages, namely the centrifugal impeller (IM), radial diffuser (RD), and axial diffuser (AD). After sand particles enter the compressor, the solid particles collide with the metal wall of the compressor, which leads to wear and tear of the blades and flow channels. Figure 7 From the wear distribution cloud map of the combined compressor obtained by simulation analysis, it can be found that the axial stage rotor blade tip section blade shape, centrifugal impeller blade shape and centrifugal hub are areas with more serious wear. Therefore, this application conducts a sensitivity analysis of the styling design parameters to geometric wear in these two typical areas to clarify the key styling design parameters that are sensitive to wear.

[0038] Among them, the DOE method is used to discretize the sample points of the axial flow first-stage rotor blade tip cross-section design parameters, and the blade tip geometry under 50 different parameters is obtained. Sand swallowing simulation is carried out on a single rotor with 50 different blade tip blade profile schemes to obtain the average blade wear. In addition, the active subspace method is used to study the sensitivity analysis of the combined compressor blade profile parameters to the average sand wear, and the sensitivity of the blade geometry parameters to the average wear is obtained. Figure 8 As shown, Figure 8 The vertical axis represents various geometric parameters, and the horizontal axis represents the average wear amount. It can be seen that the inlet blade angle, leading edge radius and chord length ( Figure 8 Items 1, 3, and 7 from the bottom up are the three parameters that have the most significant impact on the average wear. Similarly, the sensitivity of the centrifugal impeller blade profile and flow channel parameters to the average wear of sand swallowing is analyzed. Based on the active subspace method, the sensitivity of the centrifugal impeller blade profile and flow channel geometric parameters to the average wear is obtained as follows: Figure 9As shown, Figure 9 The vertical axis represents various geometric parameters, and the horizontal axis represents the average wear amount. For the centrifugal impeller, the outlet blade angle, the coordinates of the second and third flow channel control points ( Figure 9 Items 2, 23, and 24 from bottom to top are the three parameters that have the most obvious impact on average wear.

[0039] Assume that the sand intake per unit time of the turboshaft engine within the flight envelope obeys the normal distribution, such as Figure 10 As shown in the figure, the expected value of sand swallowing per unit time is 1.62g / h, with a variance of 0.3. Figure 10 The 16 different sand swallowing conditions shown in Figure 10 The hollow circle on the horizontal axis) is calculated based on the first turnover period of 1000h to calculate the values of the inlet blade angle, leading edge radius and chord length of the key wear design parameters of the axial flow rotor blade tip, and the uncertainty ranges of the three are as follows: Figures 11 to 13 As shown in the figure, the horizontal axis is the parameter change relative to the value before wear, and the vertical axis is the probability density corresponding to the wear amount. Figures 11 to 13 As can be seen from the above, the wear variation statistics of the inlet blade angle, leading edge radius, and chord length are relatively complex and do not follow a common probability distribution form. They can be approximately regarded as non-central normal distributions. Similar to the axial flow stage rotor, the uncertainty ranges of the outlet blade angle of the root section of the centrifugal impeller and the coordinates of the second and third flow channel control points are obtained as follows: Figures 14 to 16 shown.

[0040] This application establishes a database of 300 sample points of the influence of key three-dimensional modeling parameters of the combined compressor on aerodynamic performance through design experience, and uses artificial neural network method to train a proxy model of the influence of key three-dimensional modeling parameters of the combined compressor on aerodynamic performance. The model has a good prediction accuracy for the efficiency and surge margin of the combined compressor. Figure 17 and Figure 18 In addition, the present invention uses a multi-objective genetic algorithm to perform multi-objective optimization on the factory performance of the combined compressor, and the distribution of the sample point solution set is shown as follows: Figure 19 As shown in the figure, a typical scheme on the Pareto front was selected to carry out robust optimization design of aerodynamic performance. After verification by three-dimensional numerical simulation method, the aerodynamic performance of the factory-optimized preliminary design scheme was compared with the prototype scheme. Under the condition that the flow rate and pressure ratio did not decrease, the design point efficiency was improved by 0.48%, and the surge margin was improved by 1.46%.

[0041] By optimizing the wear resistance robustness of the initial design scheme at the factory, and through sensitivity analysis, it was found that the key wear design parameters are the inlet blade angle, leading edge radius and chord length of the axial stage rotor tip section blade, and the outlet blade angle, the coordinates of the second and third flow channel control points of the centrifugal impeller root section blade. Considering that the combined compressor includes three stages of axial flow and one stage of centrifugal, there are 14 corresponding key wear design parameters. An artificial neural network is used to establish a proxy model between the key wear design parameters and the aerodynamic performance loss of the combined compressor, and based on Figures 11 to 16 The probability density function within the range of key wear design parameters is given, and the Monte Carlo method is used to analyze the expectation (i.e., mean) and variance of the aerodynamic performance of the combined compressor during the first overhaul period. Multiple samples are randomly selected from the proxy model data set of key wear design parameters and the aerodynamic performance loss of the combined compressor. The expectation and variance are calculated for each sample respectively, and the overall expectation and variance are estimated by the average value of the sample statistics. Finally, the distribution of the sample statistics is shown in the chart. Among them, the distribution histogram of the mean and variance of the compressor efficiency of the prototype scheme of the combined compressor under the influence of blade wear is shown in the figure below. Figure 20 and Figure 21 As shown, the overall expectation of the compressor efficiency is 0.7638, the overall variance is 0.0005, and the distribution histogram of the mean and variance of the compressor surge margin of the prototype scheme of the combined compressor under the influence of blade wear is shown in Figure 22 and Figure 23 As shown in Figure 2, the overall expectation of the surge margin is 0.1148 and the overall variance is 0.0004. The distribution histogram of the mean and variance of the compressor efficiency under the influence of blade wear using the Monte Carlo method is shown in Figure 2. Figure 24 and Figure 25 As shown in the figure, the overall expectation of the compressor efficiency is 0.7745, the overall variance is 0.0003, and the distribution histogram of the mean and variance of the compressor surge margin under the influence of blade wear of the optimized design scheme is shown in the figure. Figure 26 and Figure 27 As shown in FIG, the overall expectation of the surge margin is 0.1285 and the overall variance is 0.0001. It can be seen that the optimized design of the present invention has significant improvements in both the expected value and variance of the compressor efficiency and surge margin compared to the prototype variance.

[0042] In summary, the optimization design method of the present invention improves the compressor efficiency by 0.48% and the surge margin by 1.46% under the condition that the compressor factory performance design point flow rate and pressure ratio do not decrease. At the design point flow rate and pressure ratio, and considering the sand intake during the first turnover period of 1000 hours, the optimized design scheme improves the expected efficiency by 1.07 percentage points and reduces the variance by 40% compared with the prototype scheme. It also improves the expected surge margin by 1.37 percentage points and reduces the variance by 75%, indicating a significant performance optimization effect.

[0043] In addition, if Figure 28 As shown, another embodiment of the present invention further provides a compressor sand swallowing wear robustness optimization design system, preferably using the compressor sand swallowing wear robustness optimization design method described above, the system comprising: The factory performance optimization module is used to optimize the aerodynamic performance of the compressor before leaving the factory and obtain a preliminary design solution; The blade wear real-time simulation module is used to build a high-precision real-time simulation method for blade wear. It updates the coupling relationship between blade geometry and wear rate in real time, thereby accurately calculating the blade geometric wear and aerodynamic performance degradation caused by sand ingestion when the compressor operates in an outdoor environment. The wear resistance optimization module is used to perform uncertainty analysis on the changes in blade aerodynamic performance caused by sand ingestion during the compressor's first turnaround period. Based on a high-precision real-time simulation method for blade wear, the design parameters of wear-sensitive blades in the preliminary design scheme are further optimized to obtain an optimized design scheme for compressor wear resistance. The aerodynamic performance verification module is used to verify the aerodynamic performance of the compressor wear resistance optimization design scheme. If its aerodynamic performance meets the design indicators, the optimized design scheme will be used as the final design scheme, otherwise iterative optimization will continue.

[0044] It can be understood that the compressor sand swallowing wear robustness optimization design system of this embodiment first performs a preliminary aerodynamic design based on the traditional compressor factory aerodynamic performance optimization design method to ensure that the compressor factory performance does not decline compared to the traditional design; then, a high-precision real-time simulation method for compressor blade wear is proposed. By updating the coupling relationship between blade geometry and wear rate in real time, the blade geometric wear and aerodynamic performance degradation caused by sand swallowing when the compressor is working in an outdoor environment are accurately simulated; then, based on the real-time simulation method, the sand swallowing uncertainty analysis of the preliminary compressor design scheme is further performed, the compressor wear-sensitive design parameters are optimized, the sand swallowing wear robustness of the compressor is improved, and the compressor wear-resistant optimization design scheme is obtained; finally, the aerodynamic performance of the optimized design scheme is verified; the system can improve the wear resistance performance of the traditional design compressor without reducing its aerodynamic performance. The entire optimization process does not require manual design experience, and can effectively improve the statistical performance of the expected and variance of aerodynamic performance such as compressor efficiency and margin during the first overhaul period, which helps to alleviate the performance degradation of the turboshaft engine.

[0045] In addition, another embodiment of the present invention further provides an electronic device, including a processor and a memory, wherein the memory stores a computer program, and the processor is configured to execute the steps of the above method by calling the computer program stored in the memory.

[0046] In addition, another embodiment of the present invention further provides a computer-readable storage medium for storing a computer program for optimizing the robustness design of compressor sand engulfment and wear, wherein the computer program executes the steps of the above-described method when running on a computer.

[0047] Common forms of computer-readable storage media include floppy disks, flexible disks, hard disks, magnetic tape, any other magnetic media, CD-ROMs, any other optical media, punch cards, paper tape, any other physical medium with a pattern of holes, random access memory (RAM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), flash-EPROM, any other memory chip or cartridge, or any other medium that can be read by a computer. Instructions can further be transmitted or received via a transmission medium. The term transmission medium may include any tangible or intangible medium that can be used to store, encode, or carry instructions for execution by a machine, including digital or analog communication signals or other intangible media that facilitate communication of such instructions. Transmission media include coaxial cables, copper wire, and fiber optics, including the wires of a bus used to transmit computer data signals.

[0048] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may take the form of a fully hardware embodiment, a fully software embodiment, or an embodiment combining software and hardware. Furthermore, the present application may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code. The solutions in the embodiments of the present application may be implemented in various computer languages, such as the object-oriented programming language Java and the interpreted scripting language JavaScript.

[0049] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 a process or multiple processes and / or boxes Figure 1A device that provides the functions specified in a block or multiple blocks.

[0050] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0051] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0052] Although the preferred embodiments of the present application have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present application.

[0053] Obviously, those skilled in the art may make various changes and modifications to this application without departing from the spirit and scope of this application. Thus, if these modifications and variations of this application fall within the scope of the claims of this application and their equivalents, this application is intended to include these modifications and variations.

[0054] The foregoing description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Those skilled in the art will readily appreciate that various modifications and variations of the present invention are possible. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention are intended to be within the scope of protection of the present invention.

Claims

1. A method for optimizing the robustness of compressor sand swallowing wear, characterized in that: Includes the following: Optimize the aerodynamic performance of the compressor before leaving the factory and obtain a preliminary design scheme; Develop a high-precision real-time simulation method for blade wear to update the coupling relationship between blade geometry and wear rate in real time, thereby accurately calculating the amount of blade geometric wear and aerodynamic performance degradation caused by sand ingestion when the compressor operates in an outdoor environment; Uncertainty analysis was performed on the changes in blade aerodynamic performance caused by sand ingestion during the compressor's first overhaul period. Using a high-precision real-time simulation method for blade wear, the design parameters of wear-sensitive blades in the preliminary design were further optimized, resulting in an optimized design for compressor wear resistance. The aerodynamic performance of the compressor wear-resistant optimization design scheme is verified. If its aerodynamic performance meets the design indicators, the optimized design scheme will be used as the final design scheme, otherwise, iterative optimization will continue.

2. The compressor sand engulfment wear robustness optimization design method according to claim 1, characterized in that: The process of constructing a high-precision real-time simulation method for blade wear includes the following: Generate the compressor blade mesh, set the blade surface solid wall boundary as the UDF motion boundary, set the corresponding contact mesh as the deforming mesh, and set the compressor sand swallowing wear simulation conditions; The compressor flow field is calculated to obtain the blade surface wear rate, and the total sand engulfment wear time is divided into multiple wear periods; At the end of the current wear period, the blade surface wear amount in the three-dimensional direction is calculated based on the blade surface wear rate and the duration of the wear period; The blade surface wear amount in the three-dimensional direction during the current wear period is used to determine the coordinates of the blade surface solid wall boundary position after wear. The coordinates of the wall grid points are updated through UDF, and the computational domain grid is updated before the sand swallowing wear simulation is performed for the next wear period. The iterations are continued until the sand swallowing wear simulation is completed for all wear periods. The total wear amount is obtained by accumulating the blade surface wear amount in all wear periods. The degradation of the compressor's aerodynamic performance during the first turnaround period is determined based on the blade surface wear amount in different wear periods.

3. The method for optimizing the robustness of compressor sand engulfment wear according to claim 2, wherein: The blade surface wear in a certain period of time is calculated based on the following formula: Where ΔH i represents the amount of blade surface wear during the i-th wear period, E i represents the wall wear rate during the i-th wear period, ρ represents the blade material density, and Δt i represents the duration of the i-th wear period.

4. The method for optimizing the robustness of compressor sand engulfment wear according to claim 2, wherein: The total sand swallowing wear time is divided into multiple wear periods of equal length; or, the total sand swallowing wear time is divided into segmented time distribution curves with approximately constant wear rates, and the length of each wear period is obtained through the corresponding curves.

5. The method for optimizing the robustness of compressor sand engulfment wear according to claim 1, wherein: The process of performing uncertainty analysis on the changes in blade aerodynamic performance caused by sand ingestion during the first overhaul period of the compressor, further optimizing the design parameters of wear-sensitive blades in the preliminary design scheme based on a high-precision real-time simulation method for blade wear, and obtaining a wear-resistant optimized design scheme for the compressor includes the following: Set uncertainty parameters for compressor blade wear, perform sensitivity analysis on the uncertainty parameters, and determine the key wear design parameters that are sensitive to blade wear; Based on key wear design parameters, a high-precision real-time blade wear simulation method is used to simulate blade wear in real time to construct sample data on the impact of key wear design parameters on compressor aerodynamic performance; A data-driven model for the impact of key wear design parameters on aerodynamic performance is trained based on a sample data set. The expectation and variance of the compressor's first turnover period aerodynamic performance are used as the objective function to obtain the optimal design scheme for compressor wear resistance.

6. The method for optimizing the robustness of compressor sand engulfment wear according to claim 1, wherein: The process of optimizing the aerodynamic performance of the compressor before leaving the factory includes the following: Conduct sensitivity analysis based on the compressor design parameters to determine the key design parameters that are sensitive to aerodynamic performance; An aerodynamic performance model was constructed to simulate the impact of key design parameters on aerodynamic performance. After training the aerodynamic performance model, a multi-objective genetic algorithm was used to optimize the key design parameters, resulting in a preliminary design scheme for the compressor before delivery. The preliminary design scheme is verified for aerodynamic performance. If its aerodynamic performance does not meet the design index requirements, the number of samples of the aerodynamic performance model is increased and it is iterated again until the aerodynamic performance of the preliminary design scheme meets the design index.

7. The method for optimizing the robustness of compressor sand engulfment wear according to claim 1, wherein: The process of verifying the aerodynamic performance of the optimized design solution includes the following: Statistical index analysis is performed on the efficiency and surge margin of the compressor design point at the end of the first overhaul period. If the statistical index results meet the design index requirements, the optimized design scheme will be used as the final design scheme. Otherwise, it will return to the factory optimization design stage for iteration.

8. A compressor sand swallowing wear robustness optimization design system, characterized by: include: The factory performance optimization module is used to optimize the aerodynamic performance of the compressor before leaving the factory and obtain a preliminary design solution; The blade wear real-time simulation module is used to build a high-precision real-time simulation method for blade wear. It updates the coupling relationship between blade geometry and wear rate in real time, thereby accurately calculating the blade geometric wear and aerodynamic performance degradation caused by sand ingestion when the compressor operates in an outdoor environment. The wear resistance optimization module is used to perform uncertainty analysis on the changes in blade aerodynamic performance caused by sand ingestion during the compressor's first turnaround period. Based on a high-precision real-time simulation method for blade wear, the design parameters of wear-sensitive blades in the preliminary design scheme are further optimized to obtain an optimized design scheme for compressor wear resistance. The aerodynamic performance verification module is used to verify the aerodynamic performance of the compressor wear resistance optimization design scheme. If its aerodynamic performance meets the design indicators, the optimized design scheme will be used as the final design scheme, otherwise iterative optimization will continue.

9. An electronic device, characterized in that: The method comprises a processor and a memory, wherein the memory stores a computer program, and the processor is configured to execute the steps of the method according to any one of claims 1 to 7 by calling the computer program stored in the memory.

10. A computer-readable storage medium for storing a computer program for optimizing the robustness design of compressor sand swallowing wear, characterized in that: When the computer program is run on a computer, the steps of the method according to any one of claims 1 to 7 are executed.

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