A modal parameter identification method based on environmental random excitation

Abstract

The present invention discloses a modal parameter identification method based on environmental random excitation, comprising: performing dynamic stress patching on a target blade whose modal parameters are to be identified; performing a vibration stress test on the target blade based on the dynamic stress patching to obtain a test data set, and preprocessing the test data set; determining a frequency response curve of the target blade based on the test data set; eliminating false modes in the frequency response curve to obtain a target frequency response curve; and determining the modal parameters of the target blade based on the target frequency response curve. The modal parameter identification method provided by the present invention utilizes the environmental random excitation during operation of an aircraft engine to excite various modes of the blade, and combined with dynamic stress testing, can identify various modal parameters at any stationary speed, solving the problem in the prior art that modal parameters can only be identified for blades at resonant speeds, while high-order modal parameters are difficult to identify.

Description

Technical Field

[0001] The present invention relates to the technical field of aero-engine blade measurement, and in particular to a modal parameter identification method based on environmental random excitation. Background Art

[0002] Modal frequency and modal damping are two key parameters of blade modal behavior. Identifying experimental modal parameters of aeroengine blades is crucial for blade vibration analysis and design. Modal frequency is the foundation of blade vibration reduction and avoidance design, while modal damping is a fundamental input parameter for blade forced response analysis and can also be used to assess the risk of modal resonance and the effectiveness of blade damping. In engineering, blade modal parameter testing is often performed under static (non-rotating) conditions. However, actual blades operate in a rotating state. Due to factors such as temperature differences, stress stiffening, and aerodynamic damping, modal frequencies and damping can differ significantly under rotating conditions compared to static conditions. Currently, experimental modal parameter identification of rotating aeroengine blades is primarily performed using dynamic stress testing based on the principle of blade resonance. Excitation from interference sources such as the front and rear stators during blade operation can induce blade resonance. Dynamic stress testing can generate frequency-response curves near the resonance point, allowing the blade's modal frequency and damping to be identified. However, this method can only identify modal parameters at resonant speeds and is difficult to identify at non-resonant speeds. At some resonant speeds, resonance may not be excited, and obvious resonant responses may not be measured on the blades, resulting in some modes being difficult to identify. In addition, for modes with dense frequencies, the vibration stresses of adjacent modes may be superimposed, resulting in large errors in the frequency and damping identification of modes with similar frequencies. Summary of the Invention

[0003] The present invention aims to at least partially address one of the technical problems in the above-mentioned technologies. To this end, the present invention aims to propose a modal parameter identification method based on environmental random excitation, aiming to provide a method for identifying modal parameters of various orders and higher-frequency modes at any dwell speed, thereby resolving the problem that existing methods can only identify some resonant modes at resonant speeds.

[0004] To achieve the above objectives, the present invention proposes a modal parameter identification method based on environmental random excitation, comprising:

[0005] Perform dynamic stress patching on the target blade whose modal parameters are to be identified;

[0006] Performing a vibration stress test on the target blade based on the dynamic stress patch to obtain a test data set, and preprocessing the test data set;

[0007] determining a frequency response curve of the target blade according to the test data set;

[0008] Eliminating false modes in the frequency response curve to obtain a target frequency response curve;

[0009] The modal parameters of the target blade are determined according to the target frequency response curve.

[0010] Preferably, performing dynamic stress patching on a target blade whose modal parameters are to be identified includes:

[0011] Calculating the modal frequency and stress distribution of each mode of the target blade;

[0012] Determining a plurality of dynamic stress measurement points on the target blade according to the modal frequencies and stress distributions of each mode of the target blade;

[0013] screening the plurality of dynamic stress measuring points to obtain a plurality of target measuring points;

[0014] A strain gauge is provided on the target blade according to the position information of the target measuring point.

[0015] Preferably, the plurality of dynamic stress measuring points are screened to obtain a plurality of target measuring points, including:

[0016] Selecting a dynamic stress measuring point from the plurality of dynamic stress measuring points as a candidate measuring point;

[0017] Acquiring stress data of the target blade and the number of modes measured at the selected measuring points when performing a dynamic stress test on the target blade;

[0018] Calculating the measuring point sensitivity of the to-be-selected measuring point according to the stress data;

[0019] When the modal number measured at the candidate measuring point is higher than a preset modal number value and the measuring point sensitivity is higher than a preset measuring point sensitivity value, the candidate measuring point is used as the target measuring point, and the above method is repeated to screen each of the multiple dynamic stress measuring points to obtain the multiple target measuring points.

[0020] Preferably, providing a strain gauge on the target blade according to the position information of the target measuring point includes:

[0021] Calculating frequency differences between a plurality of modal frequencies corresponding to the target blade;

[0022] Selecting two modal frequencies whose frequency difference is less than a preset frequency difference value from the plurality of modal frequencies and using them as the first modal frequency and the second modal frequency respectively;

[0023] Two strain gauges are selected as the first strain gauge and the second strain gauge respectively;

[0024] calculating a first sensitivity of the first strain gauge to the first modal frequency and a second sensitivity of the first strain gauge to the second modal frequency, and placing the first strain gauge at a measuring point corresponding to the first modal frequency when the first sensitivity is higher than a first preset sensitivity value and the second sensitivity is lower than a second preset sensitivity value;

[0025] A third sensitivity of the second strain gauge to the first modal frequency and a fourth sensitivity of the second strain gauge to the second modal frequency are calculated, and when the third sensitivity is lower than a third sensitivity preset value and the fourth sensitivity is lower than a fourth sensitivity preset value, the second strain gauge is disposed at a measuring point corresponding to the second modal frequency.

[0026] Preferably, performing a vibration stress test on the target blade based on the dynamic stress patch to obtain a test data set includes:

[0027] determining an operating speed range of the target blade;

[0028] Setting at least one dwell speed in the operating speed range;

[0029] The rotation speed of the target blade is controlled according to the working rotation speed range and the parking rotation speed, and vibration response data of the target blade is measured according to the strain gauge on the target blade to obtain the test data set.

[0030] Preferably, preprocessing the test data set includes:

[0031] The data segment corresponding to the dwell speed in the test data set is used as the data segment to be processed;

[0032] Acquire a first rate of change of the rotational speed of a target blade and a second rate of change of the modal frequency of each order mode of the target blade in the data segment to be processed;

[0033] The change rate of the modal frequency in the data segment to be processed with the test time is determined according to the first change rate and the second change rate, and the data segment whose modal frequency change rate is lower than a preset value is intercepted to obtain a valid data segment.

[0034] Preferably, determining the frequency response curve of the target blade according to the test data set includes:

[0035] Selecting a plurality of sub-data segments from the valid data segment;

[0036] Performing a fast Fourier transform on each of the plurality of sub-data segments to obtain a frequency spectrum corresponding to each sub-data segment, and averaging the amplitude components in the frequency spectrum of each sub-data segment to obtain a plurality of average amplitude spectrums;

[0037] The frequency response curve is drawn according to the plurality of average amplitude spectra.

[0038] Preferably, before performing fast Fourier transform on each of the plurality of sub-data segments, the method further includes: performing windowing processing on each sub-data segment.

[0039] Preferably, when a plurality of sub-data segments are selected from the valid data segment, the plurality of sub-data segments have the same length and are allowed to overlap with each other.

[0040] Preferably, removing the false modes in the frequency response curve to obtain the target frequency response curve includes:

[0041] Obtaining a dwell speed frequency corresponding to the dwell speed;

[0042] obtaining an operating frequency of a current signal in a blade testing device, a number of front stator blades of the target blade, and a number of rear stator blades of the target blade when performing a dynamic stress test on the target blade, and calculating a difference between the number of front stator blades and the number of rear stator blades as a stator blade number difference;

[0043] Using a plurality of multiple frequencies corresponding to the dwell frequency conversion as the first frequency;

[0044] The product of the dwell speed frequency and the number of the front stator blades is used as the second frequency;

[0045] The product of the dwell speed frequency and the number of the rear stator blades is used as the third frequency;

[0046] The product of the dwell rotation frequency and the difference in the number of stator blades is used as a fourth frequency;

[0047] multiplying the operating frequency of the current signal in the blade testing device by a number of operating frequencies corresponding to the operating frequency as a fifth frequency;

[0048] The target frequency response curve is obtained by removing the peak corresponding to the first frequency, the peak corresponding to the second frequency, the peak corresponding to the third frequency, the peak corresponding to the fourth frequency, and the peak corresponding to the fifth frequency from the frequency response curve.

[0049] Compared with the prior art, the present invention has the following beneficial effects:

[0050] 1. The modal parameter identification method provided by the present invention utilizes random excitation from the operating environment of an aircraft engine to excite the various modes of the blade. Combined with dynamic stress testing, it can identify the various modal parameters at any dwell speed, solving the problem in the prior art that modal parameters can only be identified for blades at resonant speeds.

[0051] 2. The modal parameter identification method provided by the present invention is used to process dynamic stress test data, and the resulting random noise spectrum is wide, which can identify higher-order modes with higher frequencies, thus solving the problem that existing methods can only identify some resonant modes.

[0052] 3. By processing the dynamic stress test data using the modal parameter identification method provided by the present invention, the noise component of the signal in the dynamic stress test can be effectively reduced. The obtained frequency response curve has a high signal-to-noise ratio, which is conducive to the identification of modal parameters.

[0053] Other features and advantages of the present invention will be described in the following description, and in part will become apparent from the description, or will be understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description and the accompanying drawings.

[0054] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0056] Figure 1 A schematic diagram of a modal parameter identification method based on environmental random excitation according to an embodiment of the present invention;

[0057] Figure 2 A schematic diagram of a parking speed setting scheme provided in an embodiment of the present invention;

[0058] Figure 3 A schematic diagram of random vibration data processing according to an embodiment of the present invention;

[0059] Figure 4 A schematic diagram of a blade vibration stress spectrum under random excitation measured according to a prior art solution provided in an embodiment of the present invention;

[0060] Figure 5 This is a schematic diagram of a blade vibration stress spectrum under random excitation measured according to the technical solution of the present invention, provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0061] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0062] like Figure 1As shown, the present invention provides a modal parameter identification method based on environmental random excitation, comprising:

[0063] Perform dynamic stress patching on the target blade whose modal parameters are to be identified;

[0064] Performing a vibration stress test on the target blade based on the dynamic stress patch to obtain a test data set, and preprocessing the test data set;

[0065] determining a frequency response curve of the target blade according to the test data set;

[0066] Eliminating false modes in the frequency response curve to obtain a target frequency response curve;

[0067] The modal parameters of the target blade are determined according to the target frequency response curve.

[0068] In an embodiment of the present invention, performing dynamic stress patching on a target blade whose modal parameters are to be identified includes:

[0069] Perform finite element calculation on the blade to be tested to obtain the frequency and stress distribution of each mode of the blade. Select the appropriate measuring point location for dynamic stress patching. The principles are as follows:

[0070] (a) Measure as many modes as possible at a single measuring point. The modes tested should have the highest possible sensitivity, and each mode should be tested using as few measuring points as possible. The sensitivity of a particular mode is the ratio of the vibration stress at the measuring point to the maximum vibration stress at all blade locations.

[0071] (b) For two modes with similar frequencies (within the operating speed range and a frequency difference of less than 1%), two strain gauges are used to measure them separately. The two strain gauges have high sensitivity to the modes to be measured and low sensitivity to the other mode, thus reducing the mutual interference between the two modes during dynamic stress testing.

[0072] (c) Avoid high strain gradient areas. For turbine blades, it is also necessary to consider avoiding high temperature areas to improve test accuracy.

[0073] In an embodiment of the present invention, performing a vibration stress test on the target blade based on the dynamic stress patch includes:

[0074] Determine the engine operating speed at which blade modes need to be identified, develop a speed dwell plan for blade dynamic stress testing, and perform dynamic stress testing on the engine. The dwell speed can be one or more, see Figure 2(This figure shows only two dwell speeds.) Because random signals are strong at each dwell speed, the blade dwell time must be sufficiently long to facilitate signal denoising in subsequent steps; a minimum of three minutes is recommended. At non-dwell speeds, if comparative modal parameter analysis under resonant conditions is required, the engine's acceleration / deceleration rate should not exceed 80 rpm. Otherwise, the engine can pass quickly. The maximum engine speed is 100% of the engine's allowable physical speed or converted speed.

[0075] In an embodiment of the present invention, preprocessing the test data set and determining the frequency response curve of the target blade according to the test data set includes:

[0076] The engine blades may operate at a relatively high ambient temperature. The vibration response of the blades is affected not only by the excitation but also by the ambient temperature. When the engine just reaches a certain stationary speed, the blade frequency is unstable due to the unstable blade temperature. It is necessary to select effective data from the stationary random vibration response stage for modal parameter identification, such as Figure 2 As shown. Under the action of random environmental excitation, various modes of the blade can be excited. The test data is analyzed using short-time Fourier transform to obtain the time-frequency response diagram of the blade vibration stress. On this basis, the data segments are selected according to the following principles:

[0077] (a) The engine speed is stable;

[0078] (b) The magnitude of each order frequency does not change at the engine stall speed;

[0079] (c) The selected data segment should be as long as possible.

[0080] The effective data segment obtained in the previous step is subjected to signal denoising to obtain a smooth frequency response curve. Figure 3 As shown in the figure, assuming that the duration of effective test data at a certain dwell speed is N, data of equal length with a duration of L are gradually selected. Each segment of data is allowed to overlap. The start time difference between the latter segment and the previous segment is ΔL. The overlap ratio ρ of two adjacent segments of data can be expressed as:

[0081]

[0082] Assume that there are n segments of data in total, and the i-th segment of data is represented by Si. Perform fast Fourier transform (FFT) on each segment of data. To improve the accuracy of analysis, window processing is required. The discrete frequency points f after spectrum analysis of the i-th segment of data are i and the corresponding amplitude a i Can be expressed as:

[0083] f i =[f i_1 fi_2 f i_3 ... f i_m ]

[0084] a i =[a i_1 a i_2 a i_3 ... a i_m ]

[0085] The average amplitude can be obtained by averaging the amplitude data corresponding to each frequency point of n segments of data:

[0086] a=[a1 a2 a3 ... a j ... a m ]

[0087] The amplitude a corresponding to the j-th frequency component j It can be expressed as:

[0088]

[0089] Based on the frequency component f and amplitude component a obtained from the above calculations, a frequency-amplitude curve can be plotted, representing the blade's frequency response function. Because this curve has been averaged, signal interference is reduced, resulting in a smoother frequency response curve.

[0090] In an embodiment of the present invention, removing the false modes in the frequency response curve to obtain the target frequency response curve includes:

[0091] Some peaks of the frequency response curve obtained in the previous step are not peaks corresponding to real modes. False modes need to be identified and eliminated. Peaks corresponding to false modes include:

[0092] (a) Peaks corresponding to the power frequency and frequency multiples of the current signal in the blade test equipment;

[0093] (b) The peak corresponding to the frequency obtained by multiplying the number of front stator blades and the number of rear stator blades by the rotation frequency;

[0094] (c) The peak corresponding to the frequency obtained by multiplying the difference between the number of front stator blades and the number of rear stator blades by the rotation frequency;

[0095] (d) Other mechanisms have obvious peaks corresponding to the frequency doubling.

[0096] In an embodiment of the present invention, determining the modal parameters of the target blade according to the target frequency response curve includes:

[0097] After removing the false modes, the response peaks of the frequency response curve are analyzed by using the half-power bandwidth method. Assuming that a peak value of the frequency response curve is a max, the corresponding frequency peak is f max , 0.707a on both sides of the peak max The corresponding frequencies are f l and f h , then the modal frequency corresponding to this peak of the blade is f max , the corresponding modal damping ratio ζ is:

[0098]

[0099] This method is used to analyze the random vibration response signal of the engine blade at the stationary speed. The original test signal spectrum of the vibration stress is as follows: Figure 4 As shown in the figure, the spectrum obtained by this method is as follows Figure 5 According to the analysis results, the modes of the blade can be obtained under the random excitation of the environment at the stationary speed. The frequency response curve obtained by this method is relatively smooth, and the true modes and false modes of each order can be identified.

[0100] Accuracy was also verified using simulated signals. Random signals were used to stimulate single-degree-of-freedom responses and identify modal parameters. Table 1 shows a comparison of the modal parameter identification results and theoretical values. Because the simulated excitation signals were randomly generated, the analysis results may vary. Each set of modal parameters was analyzed three times, with the results shown in Table 1 below. The error in modal frequency identification was no greater than 0.054%, and the error in modal damping identification was no greater than 5%.

[0101] Table 1 Comparison of modal parameter identification results and theoretical values

[0102]

[0103] Obviously, those skilled in the art may make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if such changes and modifications fall within the scope of the claims and their equivalents, the present invention is intended to include such changes and modifications.

Claims

1. A modal parameter identification method based on environmental random excitation, characterized in that: include: Perform dynamic stress patching on the target blade whose modal parameters are to be identified; Performing a vibration stress test on the target blade based on the dynamic stress patch to obtain a test data set, and preprocessing the test data set; determining a frequency response curve of the target blade according to the test data set; Eliminating false modes in the frequency response curve to obtain a target frequency response curve; determining modal parameters of the target blade according to the target frequency response curve; The step of performing dynamic stress patching on the target blade whose modal parameters are to be identified includes: Calculating the modal frequency and stress distribution of each mode of the target blade; Determining a plurality of dynamic stress measurement points on the target blade according to the modal frequencies and stress distributions of each mode of the target blade; screening the plurality of dynamic stress measuring points to obtain a plurality of target measuring points; Setting a strain gauge on the target blade according to the position information of the target measuring point; The plurality of dynamic stress measuring points are screened to obtain a plurality of target measuring points, including: Selecting a dynamic stress measuring point from the plurality of dynamic stress measuring points as a candidate measuring point; Acquiring stress data of the target blade and the number of modes measured at the selected measuring points when performing a dynamic stress test on the target blade; Calculating the measuring point sensitivity of the to-be-selected measuring point according to the stress data; When the modal number measured at the candidate measuring point is higher than a preset modal number value and the measuring point sensitivity is higher than a preset measuring point sensitivity value, the candidate measuring point is used as the target measuring point, and the above method is repeated to screen each of the plurality of dynamic stress measuring points to obtain the plurality of target measuring points; The step of setting a strain gauge on the target blade according to the position information of the target measuring point includes: Calculating frequency differences between a plurality of modal frequencies corresponding to the target blade; Selecting two modal frequencies whose frequency difference is less than a preset frequency difference value from the plurality of modal frequencies as the first modal frequency and the second modal frequency respectively; Two strain gauges are selected as the first strain gauge and the second strain gauge respectively; calculating a first sensitivity of the first strain gauge to the first modal frequency and a second sensitivity of the first strain gauge to the second modal frequency, and placing the first strain gauge at a measuring point corresponding to the first modal frequency when the first sensitivity is higher than a first preset sensitivity value and the second sensitivity is lower than a second preset sensitivity value; A third sensitivity of the second strain gauge to the first modal frequency and a fourth sensitivity of the second strain gauge to the second modal frequency are calculated, and when the third sensitivity is lower than a third sensitivity preset value and the fourth sensitivity is lower than a fourth sensitivity preset value, the second strain gauge is disposed at a measuring point corresponding to the second modal frequency.

2. The modal parameter identification method based on environmental random excitation according to claim 1, characterized in that: Performing a vibration stress test on the target blade based on the dynamic stress patch to obtain a test data set includes: determining an operating speed range of the target blade; Setting at least one dwell speed in the operating speed range; The rotation speed of the target blade is controlled according to the working rotation speed range and the parking rotation speed, and vibration response data of the target blade is measured according to the strain gauge on the target blade to obtain the test data set.

3. The modal parameter identification method based on environmental random excitation according to claim 2, characterized in that: The test data set is preprocessed, including: The data segment corresponding to the dwell speed in the test data set is used as the data segment to be processed; Acquire a first rate of change of the rotational speed of a target blade and a second rate of change of the modal frequency of each order mode of the target blade in the data segment to be processed; The change rate of the modal frequency in the data segment to be processed with the test time is determined according to the first change rate and the second change rate, and the data segment whose modal frequency change rate is lower than a preset value is intercepted to obtain a valid data segment.

4. The modal parameter identification method based on environmental random excitation according to claim 3, characterized in that: Determining a frequency response curve of the target blade according to the test data set includes: Selecting a plurality of sub-data segments from the valid data segment; Performing a fast Fourier transform on each of the plurality of sub-data segments to obtain a frequency spectrum corresponding to each sub-data segment, and averaging the amplitude components in the frequency spectrum of each sub-data segment to obtain a plurality of average amplitude spectra; The frequency response curve is drawn according to the plurality of average amplitude spectra.

5. The modal parameter identification method based on environmental random excitation according to claim 4, characterized in that: Before performing fast Fourier transform on each of the plurality of sub-data segments, the method further includes: performing windowing processing on each sub-data segment.

6. The modal parameter identification method based on environmental random excitation according to claim 4, characterized in that: When a plurality of sub-data segments are selected from the valid data segment, the plurality of sub-data segments have the same length and are allowed to overlap with each other.

7. The modal parameter identification method based on environmental random excitation according to any one of claims 1 to 6, characterized in that: Eliminating the false modes in the frequency response curve to obtain the target frequency response curve includes: Get the dwell speed frequency corresponding to the dwell speed; obtaining an operating frequency of a current signal in a blade testing device, a number of front stator blades of the target blade, and a number of rear stator blades of the target blade when performing a dynamic stress test on the target blade, and calculating a difference between the number of front stator blades and the number of rear stator blades as a stator blade number difference; Using a plurality of multiple frequencies corresponding to the dwell frequency conversion as the first frequency; The product of the dwell speed frequency and the number of the front stator blades is used as the second frequency; The product of the dwell speed frequency and the number of the rear stator blades is used as the third frequency; The product of the dwell rotation frequency and the difference in the number of stator blades is used as a fourth frequency; multiplying the operating frequency of the current signal in the blade testing device by a number of operating frequencies corresponding to the operating frequency as a fifth frequency; The target frequency response curve is obtained by removing the peak corresponding to the first frequency, the peak corresponding to the second frequency, the peak corresponding to the third frequency, the peak corresponding to the fourth frequency, and the peak corresponding to the fifth frequency from the frequency response curve.

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