Blade strain field prediction method and system based on tip timing band-pass reconstruction technology

Abstract

The invention discloses a blade strain field prediction method and system based on a blade tip timing band-pass reconstruction technology. The method comprises the following steps: firstly, constructing a three-dimensional finite element model of a rotor blade; secondly, establishing a generalized band-pass sampling model of a blade tip timing signal; determining a sensor arrangement scheme; constructing a frequency domain band-pass filtering model and solving a tip timing signal time domain interpolation reconstruction function; building a to-be-tested rotor test platform according to the sensor arrangement scheme; performing time sequence reconstruction of the blade tip timing signal, and calculating to obtain a blade vibration displacement reconstruction signal by using the measured blade tip timing signal and the interpolation reconstruction function; establishing a transient strain field reconstruction model based on a displacement-modal transfer ratio; and finally, blade transient strain field reconstruction and result visual output are carried out. According to the method, the number of the sensors and the sampling period can be controlled to be minimized while the blade tip timing signal reconstruction accuracy is ensured, so that the applicable range of the method is widened.

Description

Technical Field

[0001] The present invention belongs to the technical field of blade vibration analysis, and in particular relates to a blade strain field prediction method and system based on blade tip timing bandpass reconstruction technology. Background Art

[0002] As the power output device of aircraft, aircraft engine is a high-speed rotating power machine. As the core component of aircraft engine, rotor blades undertake the energy conversion work inside the engine by rotating at high speed. However, working in the harsh working environment of high temperature, high pressure and high speed, rotor blades need to bear centrifugal load, temperature load and aerodynamic load of continuous impact of high-speed airflow. In the unsteady complex flow field, the action of various excitation sources will cause blades to have various vibration forms, such as forced vibration (synchronous vibration) caused by upstream wake disturbance and asynchronous vibration (non-synchronous vibration) caused by aerodynamic instability such as rotating stall, flutter, surge or aeroelastic self-excited vibration. Complex and strong vibration phenomenon will cause local high stress concentration of rotor blades, causing crack extension and blade deformation, and then cause fatigue fracture of blades, that is, high cycle fatigue failure (HCF) of blades. This fatigue failure is very fatal to the engine, which will directly affect the working state, working efficiency and fuel efficiency of the whole engine, and even seriously threaten the safety performance of the engine, resulting in serious engine damage accidents. Therefore, high-cycle fatigue failure of blades must be a priority engine failure risk issue in the design and optimization stage of high-performance engine rotor systems. Therefore, the most effective way to avoid fatigue fracture of blades and ensure engine stability, reliability and safety is to monitor the dynamic strain field of high-speed rotating blades in real time, master the stress distribution and strain field state of their key operating states, and then evaluate the fatigue life of blades.

[0003] At present, there are two common methods for measuring dynamic strain of structures, namely the contact strain gauge method and the non-contact measurement method based on blade tip timing. Both of them have the following two main defects in actual engineering applications: First, as a contact measurement method, the strain gauge method uses strain gauges attached to the surface of the structure and connecting leads to achieve strain measurement of discrete points. Therefore, in actual use, there are disadvantages such as difficult installation, easy to fall off at high speed, many additional equipment, large flow field influence, long measurement cycle and high measurement cost (strain gauges need to be rearranged when measuring different points), which cannot meet the requirements of real-time monitoring of the dynamic strain field of the blade. Second, the non-contact measurement method based on blade tip timing uses the blade tip vibration information and blade modal information obtained by the non-contact blade vibration measurement technology based on blade tip timing technology to calculate the strain value at a limited point or all coordinate points on the blade, thereby realizing the mastery of the dynamic strain field of the blade. Although this technology has many advantages such as easy installation of test equipment and little influence on flow field, the overall architecture of this technology is not yet perfect at this stage. It has technical difficulties in many aspects such as identification of true vibration displacement of blade tip, identification of vibration characteristic parameters, comparison and extraction of complex modal information of blades, and calculation of dynamic strain field of multi-mode (modal aliasing) of blades. As a result, the prior conditions of the test object are strictly restricted, and multi-modal vibration identification and dynamic strain reconstruction of actual blade disks are difficult. Summary of the invention

[0004] In order to overcome the shortcomings of the prior art, the present invention provides a blade strain field prediction method and system based on blade tip timing bandpass reconstruction technology, firstly constructing a three-dimensional finite element model of the rotor blade; secondly establishing a generalized bandpass sampling model of the blade tip timing signal; then determining the sensor layout scheme; constructing a frequency domain bandpass filtering model and solving the time domain interpolation reconstruction function of the blade tip timing signal; building a rotor test platform to be tested according to the sensor layout scheme; carrying out time series reconstruction of the blade tip timing signal, using the measured blade tip timing signal and the interpolation reconstruction function, calculating the blade vibration displacement reconstruction signal; establishing a transient strain field reconstruction model based on the displacement-modal transfer ratio; and finally carrying out the reconstruction of the blade transient strain field and visualizing the output of the results. While ensuring the accuracy of the blade tip timing signal reconstruction, the present invention can minimize the number of sensors and the sampling period, thereby broadening the scope of application of the proposed method.

[0005] The technical solution adopted by the present invention to solve the technical problem is as follows:

[0006] Step 1: Based on the geometric dimensions and material parameters of the rotor blade to be tested, a three-dimensional finite element model of the rotor blade is constructed; modal analysis of a single blade is performed to obtain modal information and Campbell diagram of the finite element model;

[0007] Step 2: Based on the blade tip timing sampling principle and the generalized sampling theorem of the bandpass signal, a generalized bandpass sampling model of the blade tip timing signal is established;

[0008] Step 3: Based on the frequency range of the multi-modal vibration that can be excited in the Campbell diagram, determine the measurement speed and the frequency range of the vibration to be identified, the sampling frequency, and the number and arrangement angle of the blade tip timing sensors, that is, the sensor arrangement plan;

[0009] Step 4: Based on the multi-frequency resonance interval information of finite element analysis, a frequency domain bandpass filter model is constructed and the time domain interpolation reconstruction function of the blade tip timing signal is solved;

[0010] Step 5: Build a rotor test platform according to the sensor arrangement plan, and obtain the blade tip timing signal measured by the sensor when the rotor blades undergo multi-modal vibration through actual high-speed test experiments;

[0011] Step 6: Reconstruct the time series of the blade tip timing signal, and use the measured blade tip timing signal and the interpolation reconstruction function to calculate the blade vibration displacement reconstruction signal;

[0012] Step 7: Based on the modal order information under the measured speed state, a transient strain field reconstruction model based on the displacement-modal transfer ratio is established;

[0013] Step 8: Based on the blade vibration displacement reconstruction signal, transient strain field reconstruction model and modal vibration shape information, the blade transient strain field is reconstructed and the result is visualized.

[0014] Preferably, the vibration frequency multiple range to be identified is the difference between the maximum excitation frequency multiple and the minimum excitation frequency multiple that can be excited at the corresponding rotation speed.

[0015] Preferably, the step 1 is specifically:

[0016] Step 1-1: Establish a three-dimensional geometric model of the rotor blade to be tested according to the geometric dimensions and material parameters of the rotor blade to be tested; divide the mesh based on the three-dimensional geometric model to establish a three-dimensional finite element model of the rotor blade, and use the three-dimensional finite element model of the rotor blade to complete modal analysis at different speeds and draw a Campbell diagram;

[0017] Step 1-2: Determine the speed range and corresponding excitation order of the blade multi-modal vibration through the Campbell diagram. The i-th order excitation frequency multiplication EO in the Campbell diagram i The frequency corresponding to the intersection with the R-order natural frequency line is the resonant frequency f R,i , that is, f R,i =f r *EO i ; The multi-mode vibration of the blade is shown in the Campbell diagram as the same speed range f rThere are two or more intersection points on the natural frequency line, and the excitation order value corresponding to each intersection point is a rational number N, EO i is the excitation order corresponding to the Rth mode;

[0018] Step 1-3: Determine the maximum synchronous excitation frequency EO that can be excited at the corresponding speed L The difference between the minimum synchronous excitation frequency and EO U , thereby obtaining the vibration frequency range to be identified m = EO U -EO L The minimum and maximum vibration frequencies f can be identified correspondingly L =f r EO L 、f U =f r EO U ;

[0019] Step 1-4: Extract the front R of the finite element model M The first-order modal parameters are used as preliminary information for the test, including the multi-modal resonance speed f S , multi-modal resonance frequency f R,i , the number of excitable modes is K, the size is N d ×1 modal displacement mode shapes of each order and size N dof ×1 strain mode shape φ R ; where N dof =6*N num is the number of degrees of freedom of the model, N num is the number of mesh nodes, and the strain value of each node includes three principal strains ε x , ε y , ε z , three shear strains γ x , γ y , γ z , N d =3*N num Indicates that the displacement value of each node contains three X x , X y , X z .

[0020] Preferably, the step 2 is specifically:

[0021] Step 2-1: According to the blade tip timing measurement principle, every time the rotor blade rotates one circle, the reference sensor provides a reference time as the time reference for each circle, so that the duration T of the nth circle can be obtained. n , from which we can know the speed of each circle; the arrival time of the blade passing through the circumferential sensor when there is no vibration is called the theoretical arrival time, then the theoretical arrival time of a blade in the nth circle passing through the i-th sensor is:

[0022]

[0023] Among them, α i is the reference sensor installation angle S0 and the i-th sensor layout angle S i , β is the angle between the blade and the reference sensor, T[n] and T[k] are the rotation period of the nth circle and the rotation period of the kth circle before the current circle respectively;

[0024] If the blade vibrates, its actual arrival time will deviate from the theoretical arrival time. The difference between the two arrival times can be used to obtain the blade tip vibration displacement sequence collected by the i-th sensor:

[0025]

[0026] In the formula, R tip is the distance from the blade tip to the axis, t i [n] is the actual arrival time of the blade passing the i-th sensor in the n-th circle, is the theoretical arrival time of the blade passing the i-th sensor in the n-th circle;

[0027] Step 2-2: In the blade tip timing measurement, it is assumed that the rotor blade speed is constant; let the continuous time blade tip vibration displacement of the blade to be measured be x(t), then the blade tip vibration displacement sequence under constant speed is:

[0028] x i [n] = x(nT s +△ i ) (3)

[0029] Where, T s is the rotation period at constant speed, then the rotation frequency f s =1 / T s ; is the time delay of the vibration displacement sequence of sensor No. i;

[0030] Step 2-3: In the frequency range that can excite multi-modal vibration, there are blade vibration displacement signals with synchronous and asynchronous vibration multiples p at the blade tip measurement point, and the corresponding spectrum distribution contains 2p narrow frequency bands with equally sparse bandwidth and non-overlapping. The spectrum distribution is concentrated around f c In the frequency band with the center frequency bandwidth as B, the frequency range of the vibration signal is:

[0031] Ω=(-f U ,-f L )∪(f L ,f U ) (4)

[0032] In the formula, f L and f U They represent the upper and lower limits of the frequency band of the spectrum F(f) on the positive half axis of frequency respectively;

[0033] Step 2-4: According to the generalized bandpass sampling theorem, the vibration displacement signal at the blade tip measurement point is equated to a signal with a bandwidth of B and a center frequency of f. c The discrete-time blade tip timing signal x measured by M sensors is converted into a bandpass signal i [n] Pass through the bandpass filter of the corresponding channel respectively After that, the discrete time signal is interpolated and restored through the interpolation function to obtain a continuous time signal. The generalized bandpass sampling and interpolation reconstruction model of the blade tip timing signal is:

[0034]

[0035] In the formula, y i (t) is the interpolation function:

[0036]

[0037] g i [nT s ] is the time series collected after the corresponding channel is pre-bandpass filtered:

[0038]

[0039] In the formula, H i (f) is the bandpass filter function of the corresponding sampling channel, F i (f) is the blade tip timing displacement sequence x collected by the i-th sensor i The Fourier transform of [n] is:

[0040]

[0041] Where F(f) is the Fourier transform of the original vibration signal f(t), and k is the number of steps of the spectrum mirror copy;

[0042] Step 2-5: According to Papoulis's generalized sampling expansion principle, Y i (f, t) is obtained by solving the following system of equations:

[0043]

[0044] In the formula, f∈(-f U ,-f U +f s );

[0045] The process of solving equation (9) is the process of solving the following matrix:

[0046] HY=R (10)

[0047] Wherein, H is the m×m matrix composed of the frequency domain functions corresponding to the bandpass filters of each channel; Y is the frequency domain result of the interpolation function corresponding to each channel; and R is the aliasing parameter of the spectral component replica.

[0048] Preferably, the step 3 is specifically:

[0049] Step 3-1: According to the spectrum aliasing distribution method of the bandpass signal sampling theorem, the positive and negative frequency bands of F(f) are divided into m equal parts with f. r is a narrow frequency band of unit interval; the sampling frequency f of each channel s =f r ; The number of times the mirror-shifted copies of each unit frequency interval in the resonant frequency range are aliased with other intervals is M=2m, that is, the order of frequency band aliasing is M; therefore, the frequency band distribution relationship is:

[0050]

[0051] Where k0 is a positive integer;

[0052]

[0053] In order to solve the aliasing of the under-sampled blade tip timing signal, the number of sampling channels must be greater than or equal to the frequency band aliasing order, so the number of sensors is M;

[0054] Step 3-2: Since the phase superposition effect of the synchronization signal will cause the measurement signals with installation angles differing by 180 degrees to overlap and fail, the sensor layout angles must avoid a difference of 180 degrees.

[0055] Preferably, the step 4 is specifically:

[0056] Step 4-1: According to formula (9), we can get the matrix H M×M for:

[0057]

[0058] Construct each channel bandpass filter as:

[0059]

[0060] In the formula, f∈(-f U ,-f U +f s ), k is the number of translation steps required when the mirror-shifted copy of the selected unit frequency interval is aliased with other intervals;

[0061] Step 4-2: For the sampling model with M>2 and k0≥1, set H M×M Optimize and organize it into the form of Vandermonde determinant, and construct the corresponding simplified frequency domain bandpass filter model:

[0062]

[0063] In the formula, is the filtering delay component of the corresponding sensor:

[0064]

[0065] Vector Y M×1 for:

[0066]

[0067] Vector R M×1 for:

[0068]

[0069] Step 4-3: By constructing the matrix H M×M With vector R M×1 , and import it into equation (9), and solve it by the following formula to get Y M×1 :

[0070] Y=H -1 R (19)

[0071] Solve for Y M×1 Substituting into formula (6), we can obtain the time domain interpolation reconstruction function y of the blade tip timing signal: i (t).

[0072] Preferably, the step 6 is specifically:

[0073] Based on the frequency domain bandpass filtering model in step 3 and the time domain interpolation reconstruction function of the blade tip timing signal, the time series collected after the measured blade tip timing signal passes through the pre-bandpass filter is substituted into formula (5) to complete the interpolation reconstruction of the blade tip timing signal measured by the sensor and obtain the blade vibration displacement reconstruction signal f r (t).

[0074] Preferably, the step 7 is specifically:

[0075] Step 7-1: Based on the front R of the rotor blade to be tested M The displacement and strain modal vibration information of the order is used to construct the full-field strain modal vibration matrix of the blade and displacement mode shape matrix φ i and are the strain value and displacement value of the i-th order modal vibration type respectively; extract the modal vector of the blade tip measurement position point in each order modal displacement matrix is the displacement value of the p-th node in the i-th mode;

[0076] Step 7-2: According to different modal orders, calculate the displacement-strain transfer ratio between the blade tip measurement point and the remaining nodes:

[0077]

[0078] In the formula, φ p,i is the strain value of the p-th node in the i-th mode.

[0079] Preferably, the step 8 is specifically:

[0080] Based on the displacement-strain transfer ratio T between the blade tip measurement point and the other nodes and the obtained blade vibration displacement reconstruction signal f r (t), when the rotating blades undergo multi-modal vibration at time t, the strains of all nodes on the blade surface and inside are calculated by the formula:

[0081]

[0082] Calculate and obtain the transient full-field dynamic strain of the rotor blade for:

[0083]

[0084] In the formula, ε p,x , ε p,x With ε p,x are the principal strain values ​​of the pth node in the x, y and z directions, respectively, p,x , γ p,y With γ p,z is the shear strain value of the pth node in the x, y and z directions.

[0085] A blade strain field prediction system based on blade tip timing bandpass reconstruction technology, comprising a blade tip timing signal measurement module, a blade tip timing signal reconstruction and parameter identification module and a blade transient strain field prediction module;

[0086] The blade tip timing signal measurement module is equipped with a non-contact optical fiber sensor, a preamplifier, a timer, a pre-bandpass filter, a data acquisition device, and a storage card; it is used to measure the time pulse sequence formed by the light intensity pulse signal when the blade passes through the optical fiber sensor and the blade speed sequence measured by the OPR sensor, and the blade tip timing signal can be collected, pre-filtered and stored through the built-in threshold trigger module;

[0087] The blade tip timing signal reconstruction and parameter identification module is configured with blade tip timing signal processing software, and the blade tip timing signal processing software is embedded with a frequency domain bandpass filtering algorithm and a blade tip timing signal interpolation reconstruction algorithm; the blade tip timing signal reconstruction and parameter identification module is connected to the blade tip timing signal measurement module, and can construct a blade tip timing signal interpolation reconstruction function according to the multi-frequency resonance interval information and measurement setting parameters obtained by finite element analysis, and perform interpolation calculation on the collected blade tip timing signal to obtain the vibration displacement reconstruction signal and spectrum of the blade tip measurement point;

[0088] The blade transient strain field prediction module is configured with a transient strain field prediction software based on the blade tip timing signal, and the transient strain field prediction software is embedded with a transient strain field reconstruction algorithm based on the displacement-modal transfer ratio; the blade transient strain field prediction module is connected to the blade tip timing signal reconstruction and parameter identification module, and can be used to predict the blade tip timing signal according to the front R of the rotor blade to be tested. M The displacement-strain transfer ratio matrix of the blade is constructed based on the first-order displacement and strain modal vibration type information. The vibration displacement reconstruction signal of the blade tip measured point obtained by the blade tip timing signal reconstruction and parameter identification module is combined to obtain the transient dynamic strain value of each node of the rotor blade through calculation.

[0089] The beneficial effects of the present invention are as follows:

[0090] (1) The present invention optimizes the blade tip timing sampling model by introducing the generalized sampling theorem of bandpass signals, which does not require prior information such as the frequency and bandwidth range to be identified. In addition, while ensuring the accuracy of blade tip timing signal reconstruction, this method can minimize the number of sensors and the sampling period compared to other interpolation reconstruction methods, thereby broadening the scope of application of the proposed method.

[0091] (II) The present invention adopts a method combining generalized bandpass sampling and interpolation reconstruction method and strain field reconstruction method to solve the transient strain field of the blade. On the one hand, the blade tip timing technology combined with the bandpass sampling method can directly output the vibration displacement of the blade tip to be measured, avoiding errors in the optimization iteration process such as amplitude and phase, and can improve the accuracy of vibration displacement signal restoration. On the other hand, the introduction of the strain field reconstruction method can ensure the visualization calculation and analysis from the blade tip vibration displacement measurement to the strain field, and can analyze the multi-modal resonance phenomenon in the system from the perspective of stress and strain, thereby improving the applicability of the blade transient strain field prediction method.

[0092] (III) The present invention takes into account various factors in engineering practice. The introduction of generalized bandpass sampling and interpolation reconstruction methods makes the measurable vibration frequency range of the blade tip timing signal processing method wider than that of traditional methods. The identification restrictions on synchronous and asynchronous vibrations in the actual measurement process are smaller, and the frequency components of both can be identified at the same time. In addition, the present invention also takes into account the frequency aliasing problem of undersampled blade tip timing signals. Through the design of the anti-aliasing filter, a more accurate blade tip vibration displacement reconstruction result that is more in line with the actual engineering situation can be obtained. BRIEF DESCRIPTION OF THE DRAWINGS

[0093] Figure 1 It is a specific flow chart of the method of the present invention;

[0094] Figure 2 It is a schematic diagram of the processing flow of blade tip timing signal sampling and interpolation reconstruction provided by the present invention;

[0095] Figure 3 is a schematic diagram of a rotor blade to be tested in an embodiment of the present invention;

[0096] Figure 4 is a Campbell diagram obtained through finite element analysis in an embodiment of the present invention;

[0097] Figure 5 is a schematic diagram of sensor arrangement angles in an embodiment of the present invention;

[0098] Figure 6 It is the blade tip timing signal and speed result measured by blade No. 1 using the sensor arrangement scheme in the embodiment of the present invention;

[0099] Figure 7 is the blade vibration displacement reconstruction signal result obtained by using the proposed method in the embodiment of the present invention;

[0100] Figure 8 is the reconstructed signal spectrum analysis result obtained by using the proposed method in an embodiment of the present invention;

[0101] Fig. 9 is a schematic diagram of two points of the three-dimensional model of the blade in the embodiment of the present invention;

[0102] Fig.10 is the prediction result of the transient strain value in the X direction of two points of the blade obtained by using the proposed method in the embodiment of the present invention;

[0103] Fig.11 It is the prediction result of the transient strain field in the Z direction of two points of the blade obtained by using the proposed method in the embodiment of the present invention. DETAILED DESCRIPTION

[0104] The present invention is further described below in conjunction with the accompanying drawings and embodiments.

[0105] The purpose of the present invention is to provide a method for predicting the transient strain field of rotor blades based on blade tip timing bandpass sampling and reconstruction technology. Aiming at the problems of low prediction accuracy and poor method adaptability in the current blade tip timing technology in non-contact measurement of blade vibration and transient strain field prediction, the present invention adopts a generalized bandpass signal sampling method, a frequency domain bandpass filtering model, a time domain interpolation reconstruction function and a transient strain field reconstruction model, and reasonably designs signal measurement conditions and combines the proposed reconstruction method to accurately predict the transient strain field of the blade.

[0106] The present invention comprises the following steps:

[0107] 1. Construct a three-dimensional finite element model of the rotor blade based on the geometric dimensions and material parameters of the rotor blade to be tested. Perform modal analysis of a single blade to obtain the modal information and Campbell diagram of the finite element model.

[0108] According to the geometric dimensions and material parameters of the rotor blade to be tested, a three-dimensional geometric model of the rotor blade to be tested is established. Based on the three-dimensional geometric model, a three-dimensional finite element model of the rotor blade is established by dividing the grid. The three-dimensional finite element model is used to complete the modal analysis at different speeds and draw the Campbell diagram. The speed range and corresponding excitation order of the blade multimodal vibration are determined by the Campbell diagram. The i-th order excitation frequency multiplication EO in the Campbell diagram i The frequency corresponding to the intersection with the R-order natural frequency line is the resonant frequency f R,i , that is, f R,i =f r *EO i The multi-mode vibration of the blade is shown in the Campbell diagram as the same speed range f r There are two or more intersection points on the natural frequency line, and the excitation order value corresponding to each intersection point is a rational number N, EO i is the excitation order corresponding to the Rth order mode. Determine the maximum synchronous excitation frequency EO that can be excited at the corresponding speed L The difference between the minimum synchronous excitation frequency and EO U , thereby obtaining the vibration frequency range to be identified m = EO U -EO L The minimum and maximum vibration frequencies f can be identified correspondingly L =f r EO L 、f U =f r EO U .

[0109] Extract the front R of the finite element model M The first-order modal parameters are used as preliminary information for the test, including the multi-modal resonance speed f S ; Multimodal resonance frequency f R,i; The number of excitable modes is K; the size is N d ×1 modal displacement mode shapes of each order and size N dof ×1 strain mode shape φ R , where N dof =6*N num is the number of degrees of freedom of the model, N num is the number of mesh nodes, and the strain value of each node includes the principal strain ε in the three directions of xyz x , ε y , ε z , and shear strain γ in the xyz directions x , γ y , γ z , N d =3*N num Indicates that each node also contains X in the three directions of xyz x , X y , X z Displacement value.

[0110] 2. Based on the blade tip timing sampling principle and the generalized sampling theorem of bandpass signals, a generalized bandpass sampling model of blade tip timing signals is established.

[0111] According to the blade tip timing measurement principle, every time the rotor blade rotates one circle, the reference sensor provides a reference time as the time base for each circle, so that the duration T of the nth circle can be obtained. n , from which we can know the rotation speed of each circle. The arrival time of the blade passing through the circumferential sensor when there is no vibration is called the theoretical arrival time. Then the theoretical arrival time of a blade in the nth circle passing through the i-th sensor is:

[0112]

[0113] α i is the reference sensor installation angle S0 and the i-th sensor layout angle S i , β is the angle between the blade and the reference sensor, T[n] and T[k] are the rotation period of the nth circle and the rotation period of the kth circle before the current circle, respectively. If the blade vibrates, its actual arrival time will deviate from the theoretical arrival time. The difference between these two arrival times can be used to obtain the blade tip vibration displacement sequence collected by the i-th sensor:

[0114]

[0115] In the formula, R tip is the distance from the blade tip to the axis, t i [n] is the actual arrival time of the blade passing the i-th sensor in the n-th circle, It is the theoretical arrival time of the blade passing the i-th sensor in the n-th circle.

[0116] In the blade tip timing measurement, it is assumed that the rotor blade speed is constant. Let the continuous time blade tip vibration displacement of the blade to be measured be x(t), then the blade tip vibration displacement sequence under constant speed is:

[0117] x i [n] = x(nT s +△ i ) (3)

[0118] Where, T s is the rotation period at constant speed, then the rotation frequency f s =1 / T s . is the time delay of the vibration displacement sequence of sensor No. i.

[0119] Since there are blade vibration displacement signals with synchronous and asynchronous vibration multiples p at the blade tip measuring point in the frequency range that can excite multi-modal vibration, the corresponding spectrum distribution contains 2p narrow frequency bands with equally sparse bandwidth and non-overlapping. The spectrum distribution is concentrated around f c In the frequency band with the bandwidth of the center frequency as B, the frequency range of the vibration signal distributed as above is:

[0120] Ω=(-f U ,-f L )∪(f L ,f U ) (4)

[0121] In the formula, f L and f U They respectively represent the upper and lower limits of the frequency band of the spectrum F(f) on the positive half axis of frequency.

[0122] Therefore, according to the generalized bandpass sampling theorem, the vibration displacement signal at the blade tip measurement point is equivalent to a signal with a bandwidth of B and a center frequency of f. c The discrete-time blade tip timing signal x measured by M sensors is converted into a bandpass signal i [n] Pass through the bandpass filter of the corresponding channel respectively After that, the discrete time signal is interpolated and restored through the interpolation function to obtain a continuous time signal. The specific implementation process is as follows Figure 2 As shown in the figure, the generalized bandpass sampling and interpolation reconstruction model of the blade tip timing signal is:

[0123]

[0124] In the formula, y i (t) is the interpolation function:

[0125]

[0126] Where B = f U -f L , Y i (f, t) is the frequency domain function of the interpolation function.

[0127] g i [nT s ] is the time series collected after the corresponding channel is pre-bandpass filtered:

[0128]

[0129] In the formula, H i (f) is the bandpass filter function of the corresponding sampling channel, F i (f) is the blade tip timing displacement sequence x collected by the i-th sensor i The Fourier transform of [n].

[0130]

[0131] Where F(f) is the Fourier transform of the original vibration signal f(t), and k is the number of steps of the spectrum mirror copy.

[0132] According to Papoulis's generalized sampling expansion principle, Y i (f, t) can be obtained by solving the following system of equations:

[0133]

[0134] In the formula, f∈(-f U ,-f U +f s ). The process of solving the above system of equations is the process of solving the following matrix:

[0135] HY=R (10)

[0136] Wherein, H is the m×m matrix composed of the frequency domain functions corresponding to the bandpass filters of each channel; Y is the frequency domain result of the interpolation function corresponding to each channel; and R is the aliasing parameter of the spectral component replica.

[0137] 3. Based on the frequency range of multi-modal vibration that can be excited in the Campbell diagram, determine the measurement speed and the vibration frequency range to be identified (that is, the difference between the maximum excitation frequency and the minimum excitation frequency that can be excited at the corresponding speed), the sampling frequency, and the number of blade tip timing sensors (number of channels) and the layout angle, that is, the sensor layout plan.

[0138] According to the spectrum aliasing distribution of the bandpass signal sampling theorem, the positive and negative frequency bands of F(f) can be equally divided into m frequency bands with the frequency of f.r is a narrow frequency band in the unit interval. Since each sensor used in this method is an independent sampling channel, the sampling frequency f of each channel is s =f r The number of times the mirror-shifted copies of each unit frequency interval in the resonant frequency range are aliased with other intervals is M = 2m, that is, the order of frequency band aliasing is M. Therefore, the frequency band distribution relationship is:

[0139]

[0140] Where k0 is a positive integer;

[0141]

[0142] In order to solve the aliasing of the under-sampled blade tip timing signal, the number of sampling channels must be greater than or equal to the frequency band aliasing order, so the number of sensors should be M.

[0143] Since this method adopts a periodic non-uniform sampling model, each sampling channel is independent of each other, and the time delay of the blade tip timing displacement sequence collected by the corresponding channel sensor will not affect each other, so the sensor layout angle is not mandatory. However, considering that the phase superposition effect of the synchronous signal will cause the measurement signals with an installation angle difference of 180 degrees to overlap and fail, the sensor layout angle must avoid a difference of 180 degrees.

[0144] 4. Based on the multi-frequency resonance interval information of finite element analysis, a frequency domain bandpass filter model is constructed and the time domain interpolation reconstruction function of the blade tip timing signal is solved.

[0145] According to formula (9), we can get the matrix H M×M for:

[0146]

[0147] Construct each channel bandpass filter as:

[0148]

[0149] Where k is the number of translation steps required when the mirror-shifted copy of the selected unit frequency interval is aliased with other intervals.

[0150] For the sampling model with M>2 and k0≥1, H M×M Optimize and organize it into the form of Vandermonde determinant, and construct the corresponding simplified frequency domain bandpass filter model:

[0151]

[0152] In the formula, is the filtering delay component of the corresponding sensor, σ k It is composed of S1, S2, S3, …, S M The polynomial composed of

[0153]

[0154] The vector Y is:

[0155]

[0156] The vector R is:

[0157]

[0158] Therefore, by constructing the matrix H and the vector R and importing them into equation (9), Y can be obtained by solving the following equation:

[0159] Y=H -1 R (19)

[0160] Substitute the solved Y into formula (6) to obtain the time domain interpolation reconstruction function y of the blade tip timing signal i (t).

[0161] 5. Build a rotor test platform according to the sensor layout plan, and obtain the blade tip timing signal measured by the sensor when the rotor blades undergo multi-modal vibration through actual high-speed test.

[0162] 6. Carry out time series reconstruction of blade tip timing signal, and use the measured blade tip timing signal and interpolation reconstruction function to calculate the blade vibration displacement reconstructed signal.

[0163] Based on the frequency domain bandpass filtering model in step 3 and the time domain interpolation reconstruction function of the blade tip timing signal, the time series collected after the measured blade tip timing signal passes through the pre-bandpass filter is substituted into formula (5) to complete the interpolation reconstruction of the blade tip timing signal measured by the sensor and obtain the blade vibration displacement reconstruction signal f r (t).

[0164] 7. Based on the modal order information under the measured speed state, a transient strain field reconstruction model based on the displacement-modal transfer ratio is established.

[0165] Based on the front R of the rotor blade to be measured M The displacement and strain modal vibration information of the order is used to construct the full-field displacement modal vibration matrix of the blade and displacement mode shape matrix φ i and are the strain value and displacement value of the i-th order modal vibration mode respectively. Extract the modal vector of the blade tip measurement point in each modal displacement matrix is the displacement value of the p-th node in the i-th mode.

[0166] According to different modal orders, the displacement-strain transfer ratio between the blade tip measurement point and the remaining nodes is calculated as:

[0167]

[0168] In the formula, φ p,i is the strain value of the p-th node in the i-th mode.

[0169] 8. Based on the blade vibration displacement reconstruction signal, transient strain field reconstruction model and modal vibration type information, the blade transient strain field is reconstructed and the results are visualized.

[0170] Based on the displacement-strain transfer ratio T between the blade tip measurement point and the other nodes and the obtained blade vibration displacement reconstruction signal f r (t), when the rotating blades undergo multi-modal vibration at time t, the strains of all nodes on the blade surface and inside are calculated by the formula:

[0171]

[0172] Calculate and obtain the transient full-field dynamic strain of the rotor blade Said for:

[0173]

[0174] In the formula, ε p,x , ε p,x With ε p,x are the principal strain values ​​of the pth node in the x, y and z directions, respectively, p,x , γ p,y With γ p,z is the shear strain value of the pth node in the x, y and z directions.

[0175] On the other hand, the present invention also provides a rotor blade transient strain field prediction system based on blade tip timing bandpass sampling reconstruction technology, comprising:

[0176] 1. Blade tip timing signal measurement module: This module is equipped with a non-contact optical fiber sensor, a preamplifier, a timer, a pre-bandpass filter, a data collector, and a storage card. This module is used to measure the time pulse sequence formed by the light intensity pulse signal when the blade passes through the optical fiber sensor and the blade speed sequence measured by the OPR sensor. The built-in threshold trigger module can realize the acquisition, pre-filtering and storage of the blade tip timing signal.

[0177] 2. Blade tip timing signal reconstruction and parameter identification module: This module is equipped with blade tip timing signal processing software, which has frequency domain bandpass filtering algorithm and blade tip timing signal interpolation reconstruction algorithm embedded in it. This module is connected to the blade tip timing signal measurement module, and can construct the blade tip timing signal interpolation reconstruction function based on the multi-frequency resonance interval information and measurement setting parameters obtained by finite element analysis, and perform interpolation calculation on the collected blade tip timing signal to obtain the vibration displacement reconstruction signal and spectrum of the measured point at the blade tip.

[0178] 3. Blade transient strain field prediction module: This module is equipped with a transient strain field prediction software based on the blade tip timing signal. The software is embedded with a transient strain field reconstruction algorithm based on the displacement-modal transfer ratio. This module is connected to the blade tip timing signal reconstruction and parameter identification module, and can predict the transient strain field of the rotor blade to be tested according to the front R M The displacement-strain transfer ratio matrix of the blade is constructed based on the first-order displacement and strain modal vibration type information. The vibration displacement reconstruction signal of the blade tip measured point obtained by the blade tip timing signal reconstruction and parameter identification module is combined to obtain the transient dynamic strain value of each node of the rotor blade through calculation.

[0179] Example:

[0180] 1. Using the geometric dimensions and material parameters of the rotor blades shown, a three-dimensional finite element model of the rotor blades is constructed, and modal information and Campbell diagrams are obtained through simulation analysis, such as Figure 4 shown.

[0181] 2. According to the Campbell diagram, the frequency range f that can excite vibration r =87HZ, the corresponding frequency multiplication EO is 4, and the selected rotation frequency is f r The blade tip timing signal at =87HZ is the object of analysis.

[0182] 3. Set the lower limit frequency of the frequency band to 3.5f r HZ, upper frequency band 4.5f r HZ, band center frequency f c =4f r HZ, sampling frequency f s =f r =B=87HZ, the frequency band aliasing order M=2, k0=7. Select the number of sensors as 2, set the sensor number to increase in counterclockwise direction, then the number of circular layout equal divisions (angle equal divisions) is 51, the sensor layout angle is θ1=21°, θ2=143°, such as Figure 5 shown.

[0183] 4. Take the time point when blade 1 first passes the sensor with a sensor angle of θ1 = 21° as the measurement start time point, and construct the bandpass filter model as follows:

[0184]

[0185] pass

[0186]

[0187] Solving the frequency domain interpolation functions Y1(f, t) and Y2(f, t), we get:

[0188]

[0189] Then the time domain interpolation reconstruction function y1(t), y2(t) of the blade tip timing signal is solved:

[0190]

[0191] The formula for obtaining the blade tip timing reconstruction signal is:

[0192] f r (t) = ∑[f(nT s )y1(t-nT s )+f(nT s +△)y2(t-nT s )] (27)

[0193] 5. Conduct experiments to measure the tip timing signal and speed signal. Select the tip timing signal of blade No. 1 for analysis. Select the signal such as Figure 6 As shown in the figure, the blade tip timing signal reconstruction formula is used to solve the blade vibration displacement reconstruction signal (such as Figure 7 ), and obtain the corresponding spectrum (as shown Figure 8 shown).

[0194] 6. According to the modal order, calculate the displacement-strain transfer ratio between the blade tip measurement point and the remaining nodes. Input the blade vibration displacement reconstruction signal at the measurement point into the strain field reconstruction formula to calculate the transient full-field dynamic strain of the rotor blade. Special attention: Since the blade vibration displacement reconstruction signal has theoretical deviations within 0-0.01s, there will be large local errors. Therefore, in the strain value calculation process of this part, the blade vibration displacement reconstruction signal within 0.01s-0.22s is selected for calculation. ( Fig. 9 The figure shows the location selection diagram for selecting two points. Fig.10 and Fig.11 Shown are the predicted calculated values ​​of strain in the X and Y directions at the two points).

Claims

1. A blade strain field prediction method based on blade tip timing bandpass reconstruction technology, characterized in that: The steps include: Step 1: Based on the geometric dimensions and material parameters of the rotor blade to be tested, a three-dimensional finite element model of the rotor blade is constructed; modal analysis of a single blade is performed to obtain modal information and Campbell diagram of the finite element model; Step 2: Based on the blade tip timing sampling principle and the generalized sampling theorem of the bandpass signal, a generalized bandpass sampling model of the blade tip timing signal is established; Step 3: Based on the frequency range of the multi-modal vibration that can be excited in the Campbell diagram, determine the measurement speed and the frequency range of the vibration to be identified, the sampling frequency, and the number and arrangement angle of the blade tip timing sensors, that is, the sensor arrangement plan; Step 4: Based on the multi-frequency resonance interval information of finite element analysis, a frequency domain bandpass filter model is constructed and the time domain interpolation reconstruction function of the blade tip timing signal is solved; Step 5: Build a rotor test platform according to the sensor arrangement plan, and obtain the blade tip timing signal measured by the sensor when the rotor blades undergo multi-modal vibration through actual high-speed test experiments; Step 6: Reconstruct the time series of the blade tip timing signal, and use the measured blade tip timing signal and the interpolation reconstruction function to calculate the blade vibration displacement reconstruction signal; Step 7: Based on the modal order information under the measured speed state, a transient strain field reconstruction model based on the displacement-modal transfer ratio is established; Step 8: Based on the blade vibration displacement reconstruction signal, transient strain field reconstruction model and modal vibration shape information, the blade transient strain field is reconstructed and the result is visualized.

2. The blade strain field prediction method based on blade tip timing bandpass reconstruction technology according to claim 1 is characterized in that: The vibration frequency multiple range to be identified is the difference between the maximum excitation frequency multiple and the minimum excitation frequency multiple that can be excited at the corresponding rotation speed.

3. The blade strain field prediction method based on blade tip timing bandpass reconstruction technology according to claim 2 is characterized in that: The step 1 is specifically as follows: Step 1-1: Establish a three-dimensional geometric model of the rotor blade to be tested according to the geometric dimensions and material parameters of the rotor blade to be tested; divide the mesh based on the three-dimensional geometric model to establish a three-dimensional finite element model of the rotor blade, and use the three-dimensional finite element model of the rotor blade to complete modal analysis at different speeds and draw a Campbell diagram; Step 1-2: Determine the speed range and corresponding excitation order of the blade multi-modal vibration through the Campbell diagram. The i-th order excitation frequency multiplication EO in the Campbell diagram i The frequency corresponding to the intersection with the R-order natural frequency line is the resonant frequency f R,i , that is, f R,i =f r *EO i ; The multi-mode vibration of the blade is shown in the Campbell diagram as the same speed range f r There are two or more intersection points on the natural frequency line, and the excitation order value corresponding to each intersection point is a rational number N, EO i is the excitation order corresponding to the Rth mode; Step 1-3: Determine the maximum synchronous excitation frequency EO that can be excited at the corresponding speed L The difference between the minimum synchronous excitation frequency and EO U , thereby obtaining the vibration frequency range to be identified m = EO U -EO L The minimum and maximum vibration frequencies f can be identified correspondingly L =f r EO L 、f U =f r EO U ; Step 1-4: Extract the front R of the finite element model M The first-order modal parameters are used as preliminary information for the test, including the multi-modal resonance speed f S , multi-modal resonance frequency f R,i , the number of excitable modes is K, the size is N d ×1 modal displacement mode shapes of each order and size N dof ×1 strain mode shape φ R ; where N dof =6*N num is the number of degrees of freedom of the model, N num is the number of mesh nodes, and the strain value of each node includes three principal strains ε x , ε y , ε z , three shear strains γ x , γ y , γ z , N d =3*N num Indicates that the displacement value of each node contains three X x , X y , X z .

4. The blade strain field prediction method based on blade tip timing bandpass reconstruction technology according to claim 3 is characterized in that: The step 2 is specifically as follows: Step 2-1: According to the blade tip timing measurement principle, every time the rotor blade rotates one circle, the reference sensor provides a reference time as the time reference for each circle, so that the duration T of the nth circle can be obtained. n , from which we can know the speed of each circle; the arrival time of the blade passing through the circumferential sensor when there is no vibration is called the theoretical arrival time, then the theoretical arrival time of a blade in the nth circle passing through the i-th sensor is: Among them, α i is the reference sensor installation angle S0 and the i-th sensor layout angle S i , β is the angle between the blade and the reference sensor, T[n] and T[k] are the rotation period of the nth circle and the rotation period of the kth circle before the current circle respectively; If the blade vibrates, its actual arrival time will deviate from the theoretical arrival time. The difference between the two arrival times can be used to obtain the blade tip vibration displacement sequence collected by the i-th sensor: In the formula, R tip is the distance from the blade tip to the axis, t i [n] is the actual arrival time of the blade passing the i-th sensor in the n-th circle, is the theoretical arrival time of the blade passing the i-th sensor in the n-th circle; Step 2-2: In the blade tip timing measurement, it is assumed that the rotor blade speed is constant; let the continuous time blade tip vibration displacement of the blade to be measured be x(t), then the blade tip vibration displacement sequence under constant speed is: x i [n]=x(nT s +△ i ) (3) Where, T s is the rotation period at constant speed, then the rotation frequency f s =1 / T s ; is the time delay of the vibration displacement sequence of sensor No. i; Step 2-3: In the frequency range that can excite multi-modal vibration, there are blade vibration displacement signals with synchronous and asynchronous vibration multiples p at the blade tip measurement point, and the corresponding spectrum distribution contains 2p narrow frequency bands with equally sparse bandwidth and non-overlapping. The spectrum distribution is concentrated around f c In the frequency band with the center frequency bandwidth as B, the frequency range of the vibration signal is: Ω=(-f U ,-f L )∪(f L ,f U ) (4) In the formula, f L and f U They represent the upper and lower limits of the frequency band of the spectrum F(f) on the positive half axis of frequency respectively; Step 2-4: According to the generalized bandpass sampling theorem, the vibration displacement signal at the blade tip measurement point is equated to a signal with a bandwidth of B and a center frequency of f. c The discrete-time blade tip timing signal x measured by M sensors is converted into a bandpass signal i [n] Pass through the bandpass filter of the corresponding channel respectively After that, the discrete time signal is interpolated and restored through the interpolation function to obtain a continuous time signal. The generalized bandpass sampling and interpolation reconstruction model of the blade tip timing signal is: In the formula, y i (t) is the interpolation function: g i [nT s ] is the time series collected after the corresponding channel is pre-bandpass filtered: In the formula, H i (f) is the bandpass filter function of the corresponding sampling channel, F i (f) is the blade tip timing displacement sequence x collected by the i-th sensor i The Fourier transform of [n] is: Where F(f) is the Fourier transform of the original vibration signal f(t), and k is the number of steps of the spectrum mirror copy; Step 2-5: According to Papoulis's generalized sampling expansion principle, Y i (f, t) is obtained by solving the following system of equations: In the formula, f∈(-f U ,-f U +f s ); The process of solving equation (9) is the process of solving the following matrix: HY=R (10) Wherein, H is the m×m matrix composed of the frequency domain functions corresponding to the bandpass filters of each channel; Y is the frequency domain result of the interpolation function corresponding to each channel; and R is the aliasing parameter of the spectral component replica.

5. The blade strain field prediction method based on blade tip timing bandpass reconstruction technology according to claim 4 is characterized in that: The step 3 is specifically as follows: Step 3-1: According to the spectrum aliasing distribution method of the bandpass signal sampling theorem, the positive and negative frequency bands of F(f) are divided into m equal parts with f. r is a narrow frequency band of unit interval; the sampling frequency f of each channel s =f r ; The number of times the mirror-shifted copies of each unit frequency interval in the resonant frequency range are aliased with other intervals is M=2m, that is, the order of frequency band aliasing is M; therefore, the frequency band distribution relationship is: Where k0 is a positive integer; In order to solve the aliasing of the under-sampled blade tip timing signal, the number of sampling channels must be greater than or equal to the frequency band aliasing order, so the number of sensors is M; Step 3-2: Since the phase superposition effect of the synchronization signal will cause the measurement signals with installation angles differing by 180 degrees to overlap and fail, the sensor layout angles must avoid a difference of 180 degrees.

6. The blade strain field prediction method based on blade tip timing bandpass reconstruction technology according to claim 5 is characterized in that: The step 4 is specifically as follows: Step 4-1: According to formula (9), we can get the matrix H M×M for: Construct each channel bandpass filter as: In the formula, f∈(-f U ,-f U +f s ), k is the number of translation steps required when the mirror-shifted copy of the selected unit frequency interval is aliased with other intervals; Step 4-2: For the sampling model with M>2 and k0≥1, set H M×M Optimize and organize it into the form of Vandermonde determinant, and construct the corresponding simplified frequency domain bandpass filter model: In the formula, is the filtering delay component of the corresponding sensor: Vector Y M×1 for: Vector R M×1 for: Step 4-3: By constructing the matrix H M×M With vector R M×1 , and import it into equation (9), and solve it by the following formula to get Y M×1 : Y=H -1 R (19) Solve for Y M×1 Substituting into formula (6), we can obtain the time domain interpolation reconstruction function y of the blade tip timing signal: i (t).

7. The blade strain field prediction method based on blade tip timing bandpass reconstruction technology according to claim 6 is characterized in that: The step 6 is specifically as follows: Based on the frequency domain bandpass filtering model in step 3 and the time domain interpolation reconstruction function of the blade tip timing signal, the time series collected after the measured blade tip timing signal passes through the pre-bandpass filter is substituted into formula (5) to complete the interpolation reconstruction of the blade tip timing signal measured by the sensor and obtain the blade vibration displacement reconstruction signal f r (t).

8. The blade strain field prediction method based on blade tip timing bandpass reconstruction technology according to claim 7 is characterized in that: The step 7 is specifically as follows: Step 7-1: Based on the front R of the rotor blade to be tested M The displacement and strain modal vibration information of the order is used to construct the full-field strain modal vibration matrix of the blade and displacement mode shape matrix φ i and are the strain value and displacement value of the i-th order modal vibration type respectively; extract the modal vector of the blade tip measurement position point in each order modal displacement matrix is the displacement value of the p-th node in the i-th mode; Step 7-2: According to different modal orders, calculate the displacement-strain transfer ratio between the blade tip measurement point and the remaining nodes: In the formula, φ p,i is the strain value of the p-th node in the i-th mode.

9. The blade strain field prediction method based on blade tip timing bandpass reconstruction technology according to claim 8 is characterized in that: The step 8 is specifically as follows: Based on the displacement-strain transfer ratio T between the blade tip measurement point and the other nodes and the obtained blade vibration displacement reconstruction signal f r (t), when the rotating blades undergo multi-modal vibration at time t, the strains of all nodes on the blade surface and inside are calculated by the formula: Calculate and obtain the transient full-field dynamic strain of the rotor blade for: In the formula, ε p,x , ε p,x With ε p,x are the principal strain values ​​of the pth node in the x, y and z directions, respectively, p,x , γ p,y With γ p,z is the shear strain value of the pth node in the x, y and z directions.

10. A blade strain field prediction system using the blade strain field prediction method according to claim 1, characterized in that: It includes a blade tip timing signal measurement module, a blade tip timing signal reconstruction and parameter identification module, and a blade transient strain field prediction module; The blade tip timing signal measurement module is equipped with a non-contact optical fiber sensor, a preamplifier, a timer, a pre-bandpass filter, a data acquisition device, and a storage card; it is used to measure the time pulse sequence formed by the light intensity pulse signal when the blade passes through the optical fiber sensor and the blade speed sequence measured by the OPR sensor, and the blade tip timing signal can be collected, pre-filtered and stored through the built-in threshold trigger module; The blade tip timing signal reconstruction and parameter identification module is configured with blade tip timing signal processing software, and the blade tip timing signal processing software is embedded with a frequency domain bandpass filtering algorithm and a blade tip timing signal interpolation reconstruction algorithm; the blade tip timing signal reconstruction and parameter identification module is connected to the blade tip timing signal measurement module, and can construct a blade tip timing signal interpolation reconstruction function according to the multi-frequency resonance interval information and measurement setting parameters obtained by finite element analysis, and perform interpolation calculation on the collected blade tip timing signal to obtain the vibration displacement reconstruction signal and spectrum of the blade tip measurement point; The blade transient strain field prediction module is configured with a transient strain field prediction software based on the blade tip timing signal, and the transient strain field prediction software is embedded with a transient strain field reconstruction algorithm based on the displacement-modal transfer ratio; the blade transient strain field prediction module is connected to the blade tip timing signal reconstruction and parameter identification module, and can be used to predict the blade tip timing signal according to the front R of the rotor blade to be tested. M The displacement-strain transfer ratio matrix of the blade is constructed based on the first-order displacement and strain modal vibration type information. The vibration displacement reconstruction signal of the blade tip measured point obtained by the blade tip timing signal reconstruction and parameter identification module is combined to obtain the transient dynamic strain value of each node of the rotor blade through calculation.

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