Aero-engine test bed performance test analysis method and system

Abstract

The invention discloses an aero-engine test bed performance test analysis method and system, and relates to the technical field of test bed performance tests.The aero-engine test bed performance test analysis method comprises the steps that the error times in error records caused by error objects representing test bed parts and the error total value representing the sum of error values generating all error values are obtained; evaluation values of the error objects are obtained after calculation, and high-frequency labels, conventional labels and low-frequency labels are sequentially marked on the error objects according to a set proportion according to the descending order of the evaluation values; the problems of the test bed, which are long-term or high-frequency problems, can be determined; then, for the test object capable of detecting the fault of the error object, determining verification detection according to the data distribution condition of the previous detection time of the test object, and giving different weights in combination with the detection accuracy of the test object and a compatible value representing the number of the error objects capable of being detected by the test object, so as to obtain an available value of the test object; and marking the test object with the maximum available value as the selected test object.

Description

Technical Field

[0001] The present invention belongs to the technical field of test bench performance testing, and in particular relates to an aero-engine test bench performance testing and analysis method and system. Background Art

[0002] Inaccurate test results on aircraft engine test benches may be caused by hardware system defects, environmental simulation deviations, data acquisition errors, control logic defects, installation errors, etc. For example, the following problems may cause inaccuracies in sensor accuracy and calibration; Sensor drift, such as the loss of sensitivity of thermocouples caused by long-term high-temperature operation, can also occur. Calibration cycles are too long and not dynamically adjusted based on frequency of use. For example, pressure sensors experience zero offset due to temperature fluctuations. This directly leads to measurement errors in key parameters such as thrust, temperature, and vibration, with errors reaching 5% to 10%.

[0003] Mechanical vibration and resonance interference, insufficient stiffness of the test bench foundation, causing low-frequency resonance such as below 30Hz, interfering with high-frequency vibration signals such as blade passing frequency.

[0004] Drive shaft misalignment, such as a coupling installation error >0.05mm, can cause additional vibration and noise. Impact: Vibration spectrum data is distorted, masking true fault characteristics, such as the frequency of blade cracks.

[0005] Under these circumstances, abnormalities may occur in the performance test of the aircraft engine on the test bench. Therefore, how to troubleshoot the test bench and select appropriate methods to troubleshoot different situations is a difficult problem. Based on this, a solution is provided. Summary of the Invention

[0006] The present invention aims to solve at least one of the technical problems existing in the prior art; To this end, the present invention proposes an aerospace engine test bench performance test and analysis method, comprising the following steps: Obtain the number of errors in the error records caused by the error objects representing the test bench components and the total error value representing the sum of the error values that produce all error values. After adding different weights, the evaluation value of the error object is obtained. According to the evaluation value from large to small, the error object is labeled with a high-frequency label, a regular label, and a low-frequency label in a set proportion. For test targets that can detect faulty objects, the approved detection time is determined based on the data distribution of its past detection time. Then, the detection accuracy of the test target and the compatibility value representing the number of faulty objects that the test target can detect are combined, and different weights are assigned to obtain the available value of the test target. The test target with the largest available value is marked as the selected test target.

[0007] Furthermore, when calculating the evaluation value, the total error value needs to generate a fixed signal, a fluctuation signal, and a deviation signal according to the data distribution of the error value; When a fixed signal is generated, the total error value remains unchanged. When a fluctuating signal is generated, the total error value should be expanded by 1.1 times. When a deviation signal is generated, the total error value should be expanded by 1.3 times.

[0008] Furthermore, the ratio is set to 2.5:4:3.5.

[0009] Furthermore, the deviation value is obtained by dividing the number of error values whose difference between the error value and the average value exceeds the set value X1 by the total number of error values; When the deviation value is zero, a fixed signal is generated; when the deviation value is between 0 and the set value X2, a fluctuation signal is generated; otherwise, a deviation signal is generated.

[0010] Furthermore, the verification test is based on the average time taken to test the erroneous object in the past six months.

[0011] Furthermore, the approved test time is obtained by analyzing each test time in the past six months, and the test time whose difference with the average of all test times is less than or equal to the set value X3 is screened out, and the screened average test time is marked as the basic test time; Based on the relationship between the unscreened test time and the mean, determine the total value above the mean and the total value below the mean. Based on the difference between the total value above the mean and the total value below the mean, mark the basic test time as the approved test time, or multiply the basic test time by 0.9 or 1.2 to obtain the approved test time.

[0012] Furthermore, the total value exceeding the mean refers to the sum of the differences between the detection values that are not screened out and are greater than the mean and the mean; The low mean total value refers to the sum of the differences between the mean and the detection values that are not screened out and are smaller than the mean.

[0013] Furthermore, when the difference between the excess total value and the low total value exceeds the set ratio B1 of the excess total value, the basic test time is multiplied by 1.2 to obtain the approved test time; When the difference between the low average total value and the excess average total value exceeds the set ratio B1 of the low average total value, the basic test time is multiplied by 0.9 to obtain the approved test time.

[0014] Furthermore, the compatibility value is determined as follows: Select any other test target that can test any error object, temporarily mark it as a matching test target, obtain the number of identical test elements between the matching test target and any other test targets, mark the value as the same number of digits, divide the same number of digits by the total number of test elements in the test target, and obtain the value marked as the additional number, then analyze the additional numbers of all other test targets and the matching test target, add all the additional numbers to the basic number, and obtain the value marked as the compatibility value of the corresponding matching test target; process the remaining test targets to obtain the compatibility value of each test target.

[0015] An aircraft engine test bench performance test system, which uses the above-mentioned test method to perform performance testing on the aircraft engine test bench Compared with the prior art, the present invention has the following beneficial effects: By obtaining the number of errors in the error records caused by the error objects representing the test bench components and the total error value representing the sum of the error values that produce all error values, the evaluation value of the error object is obtained by adding different weights. The error objects are labeled with high-frequency labels, regular labels, and low-frequency labels in a set proportion according to the order of evaluation values from large to small. This can determine which problems on the test bench are long-term or high-frequency problems. Then, for the test target that can detect the fault of the error object, the approved detection time is determined according to the data distribution of its past detection time. Then, the detection accuracy of the test target and the compatibility value representing the number of error objects that the test target can detect are combined, and different weights are assigned to obtain the available value of the test target. The test target with the largest available value is marked as the selected test target. The most appropriate test target that can detect as many problems as possible can be selected to test the performance of the test bench. The present invention is simple, effective, and easy to use. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 The present invention provides a method for the flow chart. DETAILED DESCRIPTION

[0017] The technical solutions of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the embodiments described are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0018] See also Figure 1 , this application provides a method for testing and analyzing the performance of an aero-engine test bench; As embodiment 1 of the present application, the method specifically includes the following steps: Test bench performance data collection and modeling; Collect the operation data of the test bench in real time through a sensor network (such as vibration, temperature, pressure, flow rate, etc.), and at the same time record the key parameters (such as thrust, rotational speed, fuel consumption, etc.) during the test process of the aero-engine.

[0019] Establish a performance benchmark model for the test bench (such as the parameter range and dynamic response characteristics under normal operating conditions, etc.) as the basis for comparison in subsequent analysis. This part can be achieved with the help of existing technologies; Obtain each error record caused by the test bench. The error record includes the error object, the number of errors, and the error value for each error occurrence. Here, the error value is the absolute value representing the difference between the real-time data of the aero-engine test and the actual data of the aero-engine; for the error object in the error record, clustering analysis and machine learning algorithms such as decision trees and SVM can be used to screen out the frequently occurring fault points; these belong to existing technologies and will not be elaborated in detail. Of course, a specific method is also provided here for screening; First, obtain any error object, obtain its corresponding number of errors and the error value for each time, and mark the error value as Ci, where i = 1,..., n, indicating that the number of errors is n and there are n corresponding error values; Obtain the mean value of all error values and mark it as P. Set a screening box to screen out all the numbers of Ci that meet the conditions. The screening box is |Ci - P| ≤ X1, where X1 is the weight value preset by the administrator; obtain the number of error values that do not meet the screening box, divide it by n, and mark the resulting value as the deviation value; when the deviation value exceeds X2, a deviation signal is generated; If 0 < deviation value ≤ X2, a fluctuation signal is generated at this time; X2 is a preset value; If the deviation value is zero, a fixed signal is generated at this time; Synchronously obtain the sum of the error values corresponding to the error object and mark it as the total error value. Calculate the evaluation value of the error object according to the number of errors and the total error value. The specific calculation formula is: Evaluation value = 0.42 × total error value × K1 + 0.58 × number of errors; Here, the value of K1 depends on the generated signal. When a fixed signal is generated, the total error value remains unchanged at this time. When a fluctuation signal is generated, the value of K1 is taken as 1.1 at this time. When a deviation signal is generated, K1 is taken as 1.3; Then perform the same processing on all the remaining error objects to obtain the evaluation values of all error objects; Sort the error objects in descending order of the evaluation value, mark the top 25% of the error objects with a high-frequency label, mark the last 35% with a low-frequency label, and the rest with a regular label; In this calculation process, it is necessary to remove the dimensions of all elements before calculation; Obtain all error objects with high-frequency tags, regular tags, and low-frequency tags; Conduct test planning for error objects with high-frequency tags, regular tags, and low-frequency tags. The specific method is as follows: Arbitrarily select an error object, obtain all the methods that can detect the error of this error object, mark them as test targets, and collect the detection data when all test targets are detected. The detection data includes detection time and detection accuracy rate. The detection accuracy rate refers to the correct rate of detection; the specific collection method is as follows: Arbitrarily select a test target, obtain the average value of the time taken to detect problems when it detects this error object in the past six months, and mark it as the approved detection time; Then determine the compatibility value of the test target according to the number of error objects that the test target can test. The specific method is as follows: Obtain the number of error objects that can be detected by the same device using the test target, and mark it as the basic number. Then obtain the number of test components included in the test target. Test components refer to the components that make up the test target, such as devices like oscilloscopes and multimeters; Arbitrarily select another test target that can test any error object, mark it as the matching test target, obtain the number of the same test components between this matching test target and any other point test target, mark this value as the same-digit number, divide the same-digit number by the number of test components of the matching test target to get a value marked as the additional number. Then perform the same processing for all other test targets to obtain several additional numbers, and add all the additional numbers to the basic number to get a value marked as the compatibility value; Calculate the available value of the test target according to the formula. The specific formula is: Available value = K2 × approved detection time + K3 × detection accuracy rate + K4 × compatibility value; Here, when the error object has a high-frequency tag, K2 takes the value of 0.22, K3 is 0.52, and K4 takes the value of 0.26; When the error object has a regular tag, K2 takes the value of 0.31, K3 is 0.36, and K4 takes the value of 0.33; When the error object has a low-frequency tag, K2 takes the value of 0.22, K3 is 0.33, and K4 takes the value of 0.45; Perform the same processing for the remaining test targets to obtain the available values of all test targets, and mark the test target with the largest available value as the selected test target for the corresponding error object; Perform the same processing for the remaining error objects to obtain the selected test targets for all error objects; As the second embodiment of the present application, this embodiment is implemented on the basis of the first embodiment. The difference from the first embodiment is that when calculating the evaluation value of the corresponding error object, the time point at which the error value occurs also needs to be considered, that is, the time point at which each error value Ci is generated. Then, the time intervals between several front and back time points are obtained, that is, n - 1 time intervals can be obtained; then the average value of the time intervals is automatically marked as the approved interval; Synchronously obtain the sum of the error values of the corresponding error object, mark it as the total error value, and calculate the evaluation value of the error object according to the number of errors and the total error value. The specific calculation formula is: Evaluation value = 0.38 × total error value × K1 + 0.42 × number of errors + 0.2 / approved interval; Here, the value of K1 depends on the generated signal. When a fixed signal is generated, the total error value remains unchanged at this time. When a fluctuating signal is generated, the value of K1 is taken as 1.1 at this time. When a deviation signal is generated, the value of K1 is taken as 1.3; Then perform the same processing on all the remaining error objects to obtain the evaluation values of all the error objects; As the third embodiment of the present application, this embodiment is implemented on the basis of the first embodiment. The difference is that screening needs to be carried out before determining the approved detection. The specific screening method is: mark the detection time as Tj, j = 1,..., m, indicating that the detection has been carried out m times in the past six months, and the duration of each detection is Tj. Then, the average value U of Tj is obtained; Use the screening method of |Tj - U| ≤ X3 to screen out all the detection times that meet the conditions, and automatically obtain the average value of the screened detection times, and mark it as the basic detection time; X3 is a preset value. Of course, the value of X3 here can also be the same as X1; Then obtain the sum of the differences between all Tj values that satisfy Tj - U > X3 and U, and mark it as the total over - average value. Here, that is, after screening out all Tj values that satisfy Tj - U > X3, subtract the mean value U from this value and sum all the differences; similarly, obtain the sum of the absolute values of the differences between all Tj values that satisfy Tj - U < -X3 and U, and mark it as the total under - average value; If (total over - average value - total under - average value) / total over - average value ≥ B1, where B1 is a preset value, generally taken as 0.15 in this case, then the value obtained by multiplying the corresponding basic detection time by 1.2 is marked as the approved detection time; here, B1 is greater than zero, indicating that the total over - average value is greater than the total under - average value; If (total under - average value - total over - average value) / total under - average value ≥ B1, then the value obtained by multiplying the basic detection time by 0.9 is marked as the approved detection time; indicating that the total over - average value is less than the total under - average value; If the above two situations are not met, then the basic detection time is marked as the approved detection time.

[0020] Certainly, as the fourth embodiment of the present application, this embodiment is used to implement the integration of all the above embodiments; On the basis of the above embodiments, the present application further provides a performance test and analysis system for an aero-engine test bench. This system uses the performance test and analysis methods mentioned in all the foregoing embodiments to conduct performance tests on the aero-engine test bench; Some of the data in the above formula are calculated by removing the dimension and taking its numerical value. The formula is the one closest to the actual situation obtained through software simulation of a large amount of collected data; the preset parameters and preset thresholds in the formula are set by those skilled in the art according to the actual situation or obtained through simulation of a large amount of data.

[0021] The above embodiments are only used to illustrate the technical method of the present invention and not to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical method of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the technical method of the present invention.

Claims

1. A method for performance test and analysis of an aero-engine test bed, characterized in that It includes the following steps: Obtain the error times in the error record caused by the error object representing the test bench components and the total error value representing the sum of all error values. Assign different weights to them, add them up to obtain the evaluation value of the error object, and sequentially label the error objects with high-frequency labels, regular labels, and low-frequency labels according to the set ratio in descending order of the evaluation value; For the test targets that can detect the faults of the error objects, determine the approved detection time according to the data distribution of the past detection times, and then combine the detection accuracy of the test targets and the compatibility value representing the number of error objects that the test targets can detect. After assigning different weights according to the high-frequency labels, regular labels, and low-frequency labels, obtain the available value of the test targets, and mark the test target with the largest available value as the selected test target.

2. The performance test analysis method of an aero-engine test bench according to claim 1, characterized in that When calculating the evaluation value, the total error value needs to generate a fixed signal, a fluctuation signal, and a deviation signal according to the data distribution of the error value; When generating a fixed signal, the total error value remains unchanged. When generating a fluctuation signal, the total error value is enlarged by 1.1 times. When generating a deviation signal, the total error value is enlarged by 1.3 times.

3. A performance test analysis method for an aero-engine test bench according to claim 1, characterized in that The set ratio is 2.5:4:3.

5.

4. A performance test analysis method for an aero-engine test bench according to claim 2, characterized in that Divide the number of error values whose difference from the average value exceeds the set value X1 by the total number of error values to obtain the deviation value; When the deviation value is zero, generate a fixed signal. When the deviation value is between 0 and the set value X2, generate a fluctuation signal. Otherwise, generate a deviation signal.

5. A performance test analysis method for an aero-engine test bench according to claim 1, characterized in that, The approved detection time is the average value of the time when the test target detected the error object in the past six months.

6. The performance test analysis method of an aero-engine test bench according to claim 1, wherein The approved detection time is obtained by analyzing each detection time in the past six months. Screen out the detection times whose difference from the average value of all detection times is less than or equal to the set value X3, and mark the average value of the screened detection times as the basic detection time; According to the size relationship between the detection times not screened out and the average value, determine the over-average total value and the under-average total value. According to the difference between the over-average total value and the under-average total value, determine whether to mark the basic detection time as the approved detection time, or multiply the basic detection time by 0.9 or 1.2 to obtain the approved detection time.

7. A performance test and analysis method for an aeroengine test bench according to claim 6, characterized in that The over-average total value refers to the sum of the differences between the detection times not screened out and greater than the average value and the average value; The under-average total value refers to the sum of the differences between the detection times not screened out and less than the average value and the average value.

8. The performance test analysis method of an aero-engine test bench according to claim 6, characterized in that, When the difference between the over-average total value and the under-average total value exceeds the set ratio B1 of the over-average total value, multiply the basic detection time by 1.2 at this time to obtain the approved detection time; When the difference between the under-average total value and the over-average total value exceeds the set ratio B1 of the under-average total value, multiply the basic detection time by 0.9 at this time to obtain the approved detection time.

9. The performance test analysis method of an aero-engine test bench according to claim 1, characterized in that The compatibility value is determined in the following way: Optionally select another test target that can test any error object, temporarily mark it as the matching test target, obtain the number of the same test components between the matching test target and any other test target, mark this value as the same-digit number, divide the same-digit number by the total number of test components of the test target to obtain a value marked as the additional number, and then analyze the additional numbers of all other test targets and the matching test target, and add all the additional numbers to the basic number to obtain a value marked as the compatibility value of the corresponding matching test target; Process the remaining test objects to obtain the compatibility value of each test object.

10. An aero-engine test bench performance testing system, characterized in that, The system performs a performance test on the aero-engine test bed by using the test method described in any one of claims 1-9.

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