Parameter design method of aero-engine sand swallowing test equipment

Abstract

The invention belongs to the technical field of aero-engines, and particularly relates to an aero-engine sand swallowing test equipment parameter design method, which comprises the following steps: S1, determining an assessment amount of a test model, selecting a plurality of key factors influencing the assessment amount, and setting a plurality of gradients for each key factor; s2, a test design table is constructed based on the selected key factors and the gradients of the key factors, and the test design table is used for arranging part of representative test combinations; s3, performing a simulation test on the verified simulation model according to each test combination in the test design table, and obtaining an assessment value result corresponding to each test combination; and S4, carrying out data analysis on all the obtained assessment value results to determine the influence degree of each key factor on the assessment value, and selecting an equipment parameter combination enabling the assessment value to be optimal according to the influence degree.

Description

Technical Field

[0001] This application belongs to the field of aero-engine technology, and specifically relates to a method for designing parameters of aero-engine sand ingestion test equipment. Background Technology

[0002] With the frequent use of aircraft, the environmental adaptability of aero engines has become an urgent requirement, especially in the face of dusty environments in regions such as the Middle East. In the early stages of aero engine development, engine failures caused by environmental factors attracted the attention of various countries. Statistics show that environmental factors account for as much as 52% of failures; among them, dust-related failures account for 7%, demonstrating that the impact of dust on engines cannot be ignored. The dust ingestion test is an essential assessment test in the design finalization process of aero engines, and the dust ingestion equipment is crucial in this test. Traditional dust ingestion test equipment is as follows: Figure 1 As shown, it mainly includes sandblasting nozzles, air filter system and sand feeding mechanism.

[0003] Currently, research in the field of aero-engine sand ingestion testing focuses too much on the functional design of equipment. The selection of test equipment parameters relies too heavily on past design experience, lacking a complete method for determining test equipment parameters. Furthermore, some test equipment suffers from unreasonable parameter settings. This may lead to the failure to meet test requirements for performance metrics such as cross-sectional uniformity.

[0004] Currently, research in the field of aero-engine sand ingestion testing focuses too much on the functional design of equipment. The selection of test equipment parameters relies too much on past design experience, and there is no complete method for determining test equipment parameters. Some test equipment has unreasonable parameter settings. Summary of the Invention

[0005] To address the aforementioned problems, this application provides a method for designing parameters for an aero-engine sand ingestion test equipment, including:

[0006] Step S1: Determine the assessment metrics of the experimental model, select multiple key factors that affect the assessment metrics, and set multiple gradients for each key factor;

[0007] Step S2: Based on the selected key factors and their gradients, construct an experimental design table, which is used to arrange some representative experimental combinations;

[0008] Step S3: Based on each test combination in the test design table, conduct simulation tests on the verified simulation model and obtain the assessment results corresponding to each test combination;

[0009] Step S4: Perform data analysis on all obtained assessment results to determine the degree of influence of each key factor on the assessment, and select the optimal combination of equipment parameters to achieve the assessment.

[0010] Preferably, in step S1, the evaluation metric is the uniformity γ of sand particle concentration at the outlet section of the sand ingestion test equipment. a .

[0011] Preferably, in step S1, the key factors include at least one of the following: the angle θ of the sandblasting nozzle baffle, the diameter D of the rectifier cylinder, and the distance L between the test equipment and the engine inlet.

[0012] Preferably, the experimental design table constructed in step S2 is an orthogonal experimental table or a uniform experimental table.

[0013] Preferably, the data analysis in step S4 includes range analysis, which includes the following sub-steps:

[0014] Calculate the mean of the assessment values ​​for all test results for each key factor at the same gradient;

[0015] For each key factor, identify the maximum and minimum values ​​among the average assessment values ​​at different gradients;

[0016] Calculate the range R of this key factor;

[0017] The order of influence of each key factor on the assessment quantity is determined by the size of its range R. The larger the range, the more significant the influence of the factor on the assessment quantity.

[0018] Preferably, in addition to range analysis, the data analysis further includes analysis of variance to quantify the significance gradient of the impact of each key factor on the assessment quantity.

[0019] Preferably, the step S4 of “selecting the equipment parameter combination that optimizes the assessment quantity” specifically means: for each key factor, selecting the gradient with the best average assessment quantity, and combining the optimal gradients of all key factors together to form the optimal equipment parameter combination.

[0020] Preferably, the method is applicable to the design phase of a sand-swallowing test device, used to determine its key structural and layout parameters.

[0021] This application can evaluate and optimize the equipment used in sand blasting tests, ensure the rationality of the selection of sandblasting equipment parameters, and effectively improve the uniformity of sand particles blasted by the equipment to meet the needs of actual tests. Attached Figure Description

[0022] Figure 1 This is a diagram illustrating the independent variable parameters. Detailed Implementation

[0023] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions in the embodiments of this application will be described in more detail below with reference to the accompanying drawings. In the drawings, the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The described embodiments are only some, not all, of the embodiments of this application. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain this application, and should not be construed as limiting this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application. The embodiments of this application will be described in detail below with reference to the accompanying drawings.

[0024] This project proposes a method for selecting parameters of an aero-engine sand ingestion test equipment. By designing experiments on a validated model and analyzing the experimental results, optimal equipment parameters are obtained. This experimental design method selects representative points from a comprehensive test, and the selected experimental scheme is sufficient to capture the overall characteristics of the comprehensive test. A specific scheme is as follows (taking a three-factor, three-gradient approach as an example):

[0025] Select cross-sectional uniformity γ a As an assessment metric, Factor 1 is the angle θ of the sandblasting nozzle baffle, with three gradients of three different θ values, namely θ1, θ2, and θ3 (from smallest to largest); Factor 2 is the diameter D of the rectifier cylinder, with gradients of D1, D2, and D3; and Factor 3 is the distance L between the equipment and the engine, with gradients of L1, L2, and L3.

[0026] The validated simulation model was subjected to simulation experiments. Taking a three-factor, three-gradient model as an example, the experimental design table is as follows. The gradient direction represents the factors and the evaluation quantity, and the vertical direction represents the experiment number. For example, experiment number 3 is conducted under the conditions of equipment angle θ1, diameter D3, and distance L2, and the result is denoted as γ. a3 Test No. 8 involves conducting an experiment with the equipment at an angle of θ3, a diameter of D2, and a distance of L1, and obtaining the result γ. a8 Continue until all the required results in the table are obtained, i.e., γ. a1 γ a2 、…、γ a9 In addition, the error groups in the table are used for the final control data analysis.

[0027] Experimental Design Table

[0028] serial number Angle θ Diameter D Distance L e <![CDATA[Uniformity γ a > 1 <![CDATA[θ1]]> <![CDATA[D1]]> <![CDATA[L1]]> <![CDATA[e1]]> <![CDATA[γ a1 ]]> 2 <![CDATA[θ1]]> <![CDATA[D2]]> <![CDATA[L3]]> <![CDATA[e2]]> <![CDATA[γ a2 ]]> 3 <![CDATA[θ1]]> <![CDATA[D3]]> <![CDATA[L2]]> <![CDATA[e3]]> <![CDATA[γ a3 ]]> 4 <![CDATA[θ2]]> <![CDATA[D1]]> <![CDATA[L3]]> <![CDATA[e3]]> <![CDATA[γ a4 ]]> 5 <![CDATA[θ2]]> <![CDATA[D2]]> <![CDATA[L2]]> <![CDATA[e1]]> <![CDATA[γ a5 ]]> 6 <![CDATA[θ2]]> <![CDATA[D3]]> <![CDATA[L1]]> <![CDATA[e2]]> <![CDATA[γ a6 ]]> 7 <![CDATA[θ3]]> <![CDATA[D1]]> <![CDATA[L2]]> <![CDATA[e2]]> <![CDATA[γ a7 ]]> 8 <![CDATA[θ3]]> <![CDATA[D2]]> <![CDATA[L1]]> <![CDATA[e3]]> <![CDATA[γ a8 ]]> 9 <![CDATA[θ3]]> <![CDATA[D3]]> <![CDATA[L3]]> <![CDATA[e1]]> <![CDATA[γ a9 ]]>

[0029] All results are analyzed to obtain the optimal parameters of the experimental equipment.

[0030] Perform range analysis on the entire design table: This analysis method can determine the order of importance of factors and observe the range (R value) of each factor. The larger the R value, the better the factor, meaning it has a greater influence on the data results. The formula for the range (R value) is:

[0031] R = max{k1,k2,…,k i}- min{k1,k2,…,k i}

[0032] Where, k i For any column, the experimental result γ corresponding to gradient i. a The mean, calculated using the complete formula for each factor and its gradient, is as follows:

[0033]

[0034] Range R θ For k θ1 k θ2 k θ3 The formula for calculating the difference between the maximum and minimum values ​​is:

[0035]

[0036] Range R θ R D R L The magnitude of θ represents the degree of influence of the three factors, D and L, on the outcome. Assume R... θ＞ R D＞ R L Therefore, when selecting parameters, θ should be considered first, followed by D, and finally L.

[0037] A direct analysis is conducted: the evaluation metric is the uniformity of the sand grain cross-section; under normal circumstances, the higher the uniformity, the better. The k-values ​​of each factor are observed. Each factor has three values: k1, k2, and k3. The gradient with the largest k-value is the optimal gradient for that factor. The optimal gradient is the combination of one optimal gradient for each of the three factors.

[0038] Assume the experimental result is: k θ1＜ k θ2＜ k θ3 k D1＜ k D3＜ k D2 k L2＜ k L3＜ k L1 R θ＞ R D＞ R L .

[0039] The k-value can reflect the change of the assessment quantity with the change of parameters. The experimental results show that k... θ1＜ kθ2＜ k θ3 It can be seen that the assessment quantity γ a The angle increases with increasing θ, therefore the optimal baffle angle is θ3; k D1＜ k D3＜ k D2 It can be seen that γ a As D increases, the diameter first increases and then decreases, with the optimal rectifier diameter being D²; k L2＜ k L3＜ k L1 It can be seen that the optimal device distance is L1, and the optimal parameter combination is θ3, D2, L1. The result obtained here does not necessarily correspond to a certain experiment in the table. If the number of experiments listed in the table does not include the optimal solution, the optimal solution can also be determined by combining the results of the nine experiments in the table with the parameter change relationship obtained by data analysis methods.

[0040] If there are size constraints, the selection should be made in the order of θ > D > L, prioritizing the selection of the independent variable θ.

[0041] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for designing parameters of an aero-engine sand ingestion test equipment, characterized in that, include: Step S1: Determine the assessment metrics of the experimental model, select multiple key factors that affect the assessment metrics, and set multiple gradients for each key factor; Step S2: Based on the selected key factors and their gradients, construct an experimental design table, which is used to arrange some representative experimental combinations; Step S3: Based on each test combination in the test design table, conduct simulation tests on the verified simulation model and obtain the assessment results corresponding to each test combination; Step S4: Perform data analysis on all obtained assessment results to determine the degree of influence of each key factor on the assessment, and select the optimal combination of equipment parameters to achieve the assessment.

2. The method for selecting parameters of the aero-engine sand ingestion test equipment according to claim 1, characterized in that, In step S1, the evaluation metric is the uniformity γ of sand particle concentration at the outlet section of the sand swallowing test equipment. a .

3. The method for selecting parameters of the aero-engine sand ingestion test equipment according to claim 1 or 2, characterized in that, In step S1, the key factors include at least one of the following: the angle θ of the sandblasting nozzle baffle, the diameter D of the rectifier cylinder, and the distance L between the test equipment and the engine inlet.

4. The method for selecting parameters of the aero-engine sand ingestion test equipment according to claim 1, characterized in that, The experimental design table constructed in step S2 is either an orthogonal experimental table or a uniform experimental table.

5. The method for selecting parameters of the aero-engine sand ingestion test equipment according to claim 1, characterized in that, The data analysis in step S4 includes range analysis, which includes the following sub-steps: Calculate the mean of the assessment values ​​for all test results for each key factor at the same gradient; For each key factor, identify the maximum and minimum values ​​among the average assessment values ​​at different gradients; Calculate the range R of this key factor; The order of influence of each key factor on the assessment quantity is determined by the size of its range R. The larger the range, the more significant the influence of the factor on the assessment quantity.

6. The method for selecting parameters of the aero-engine sand ingestion test equipment according to claim 5, characterized in that, Based on range analysis, the data analysis further includes analysis of variance, which is used to quantify the significance gradient of the impact of each key factor on the assessment quantity.

7. The method for selecting parameters of the aero-engine sand ingestion test equipment according to claim 1, characterized in that, The step S4, "selecting the optimal combination of equipment parameters for assessment", specifically means: for each key factor, selecting the gradient with the best average assessment value, and combining the optimal gradients of all key factors together to form the optimal combination of equipment parameters.

8. The method for selecting parameters of the aero-engine sand ingestion test equipment according to claim 1, characterized in that, The method is applicable to the design phase of sand-swallowing test equipment and is used to determine its key structural and layout parameters.

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