CN112100874A - Rotor blade health monitoring method and monitoring system based on digital twinning - Google Patents
Rotor blade health monitoring method and monitoring system based on digital twinning Download PDFInfo
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Abstract
The invention discloses a rotor blade health monitoring method and system based on digital twinning, wherein the method comprises the following steps: establishing a three-dimensional model of a single blade, calculating modal natural frequencies of various orders of the blade at different rotating speeds through finite element software, taking the difference value of the vibration frequency of the rotor blade measured by a sensor and the modal natural frequencies of various orders calculated by a finite element model as a target function, taking the material parameters and the geometric parameters of the finite element model as design variables, constructing a finite element model correction equation, and solving by using an evolutionary algorithm to obtain a corrected finite element reference model; constructing a model update sensitivity matrix to reflect the influence of the change of the unit stiffness matrix on the natural frequency of the rotor blade; establishing a real-time updating equation of the digital twin model in the service state based on the model updating sensitivity matrix; based on the real-time update equation, establishing a base lpA sparse optimization model of norm; solving by convex optimization method to obtain reflection rotationThe unit stiffness damage factor vector of the position and extent of the sub-leaf damage.
Description
Technical Field
The invention belongs to the field of mechanical fault diagnosis, and relates to a rotor blade health monitoring method and system based on digital twinning.
Background
Rotor blades are important components in aircraft engines. The blade is easy to vibrate under severe working conditions of high temperature, high pressure, high rotating speed and the like when the aircraft engine works, and further high-cycle fatigue of the blade is caused, so that the blade is damaged by cracks and the like. Damage to the blade of an aircraft engine often results in changes in some vibration parameters of the blade, such as vibration frequency, amplitude, etc. In the operation process of the blade, the vibration parameter of the blade is accurately monitored, the damage position of the blade is positioned, and the evaluation of the damage condition of the blade plays an important role in reducing the operation and maintenance cost of an engine and guaranteeing the operation safety of an aeroengine.
The above information disclosed in this background section is only for enhancement of understanding of the background of the invention and therefore it may contain information that does not form the prior art that is already known in this country to a person of ordinary skill in the art.
Disclosure of Invention
Aiming at the problems in the prior art, the invention provides a rotor blade health monitoring method and a rotor blade health monitoring system based on digital twinning, and the blade damage positioning and damage degree evaluation are realized by exchanging data between a finite element reference model and blade vibration parameters measured by an actual sensor.
The invention establishes a digital twin model corresponding to the physical entity model, and performs data association by using the actual sensor measurement result and the digital twin model calculation result, thereby realizing real-time update of the digital twin model and accurately reflecting the working state of the physical entity object. Traditional aeroengine fault detection goes on through the mode of artifical tearing open and examining, and its diagnosis cycle is long, detection efficiency is low, can't realize real-time rotor blade health monitoring. The vibration parameters of the blade can be measured by installing a sensor on an actual engine, and the digital twin finite element model is corrected by using the measurement result of the vibration parameters of the blade in a normal state to obtain a finite element reference model. And updating the digital twin model in real time through the difference between the actual measurement result and the finite element reference model, further positioning the blade fault, and evaluating the damage degree of the blade so as to realize the purpose of monitoring the real-time health of the rotor blade.
The invention aims to realize the technical scheme that a rotor blade health monitoring method based on digital twinning comprises the following steps:
in the first step, a three-dimensional model of the rotor blade is established, and the modal natural frequency f of each order of the blade at different rotating speeds is calculated through finite elementsFECorrecting the finite element model according to the modal information measured in the initial crack-free state of the rotor blade to obtain a finite element reference model for digital twinning, wherein the modal natural frequency f of each order calculated by finite elementsFEWith actual blade vibration frequency f measured by the sensormAs an objective function, with the material parameter M ═ E ρ μ of the rotor blade]And the geometric parameter G ═ l w h α]For designing variables, establishing a finite element model correction equation by taking the supremum VHB and the infimum VLB of the material parameters and the geometric parameters as constraint conditions:
e is the elastic modulus of the material, rho is the density, mu is the Poisson ratio, l is the blade length, w is the blade width, h is the blade thickness, and alpha is the blade attack angle, and the material parameters and the geometric parameters in the finite element model correction equation are continuously adjusted based on the evolutionary algorithm so as to ensure that the value of the objective function reaches the minimum value, thereby obtaining a finite element reference model for digital twinning;
in a second step, a sensitivity matrix is constructed:
wherein psijIs the j-th order mass normalized mode shape of the finite element model of the rotor blade,
for the finite element reference modelCell stiffness matrix, Q, of the ith celliA relation matrix between a unit stiffness matrix and an overall stiffness matrix in a finite element reference model is shown, and superscript T represents the transposition of a matrix or a vector;
in the third step, a digital twin real-time updating model in a service state is established, wherein a parameterized stiffness damage model is established based on the overall stiffness matrix and the unit stiffness matrix of the rotor blade finite element reference model:
wherein, K (t)s) Representing the rotor blade finite element model tsGlobal stiffness matrix, n, corresponding to time of dayeleRepresenting the number of elements in the finite element model, i representing the ith element, θi(ts) Denotes the t-thsMoment, damage factor, Q, of the ith unit of the rotor bladeiIs a relation matrix between an element stiffness matrix and an overall stiffness matrix in a finite element reference model,
is the element stiffness matrix of the ith element in the finite element reference model,
establishing a digital twin real-time updating model in a service state based on the sensitivity matrix: Δ f ═ S θ +, in which,
representing the modal frequency variation before and after damage of the rotor blade; f. ofdAnd fuRespectively representing the actual blade modal frequency measured by the sensor before and after the damage of the rotor blade, S is a sensitivity matrix,
is the unit stiffness impairment factor vector to be solved, which is the noise vector, nfIs the actual blade modal frequency number, n, measured by the sensoreleIs the number of elements in the finite element model;
in the fourth step (S4), the establishment is based on lp(p is more than or equal to 0 and less than or equal to 1) a sparse optimization model of norm:
wherein,
representing the square of two norms, | ·| non-woven phosphorpP norm is expressed, lambda represents regularization parameter, and a convex optimization method is utilized to solve the problem based on lpObtaining a uniquely determined unit stiffness damage factor vector by a sparse optimization model of norm
And according to the position of the non-zero element in the theta, corresponding to the position of the damaged unit in the finite element model of the rotor blade, wherein the size of the non-zero element corresponds to the damage severity of the damaged unit.
In the method, the first step comprises:
s101, carrying out isometric three-dimensional modeling according to the shape of the rotor blade to obtain a three-dimensional model of the rotor blade, establishing a finite element model of the rotor blade based on finite element calculation,
s102, determining the highest rotating speed Rm reached in the actual operation process of the rotor blade, calculating the modal natural frequency of each order of the three-dimensional model of the rotor blade at the rotating speed of 0-Rm by utilizing a finite element,
s103, detecting the rotor blade before the rotor blade runs to ensure that no fault exists before the actual blade runs,
s104, mounting sensors on the rotor blade casing and the surrounding operating environment, enabling the rotor blade to run at a speed increasing speed from 0 to Rm and then at a speed decreasing speed to 0, obtaining data measured by all the sensors,
and S105, after the operation of the rotor blade is finished, checking the blade, and if the actual blade is checked to have a fault after operation, replacing the blade and repeating the steps S103, S104 and S105 until the actual blade does not have the fault after operation.
In the method, in step S104, the sensor for measuring the blade vibration parameter is a blade tip timing sensor, and the step of measuring the blade vibration frequency includes the following steps:
s1041, installing the blade end timing sensor on an engine casing, measuring the time when the blade reaches the sensor, and calculating the vibration displacement of the blade end by taking a time signal measured by the rotating speed sensor as a reference standard:
y＝2πfrRtipΔ t, wherein Δ t ═ texpected-tactual，frIs the blade frequency rotation; rtipIs the distance from the rotor axis of rotation to the blade tip; t is texpectedThe time when the blade reaches the sensor under the condition that the blade does not vibrate; t is tactualIs the time that the tip timing system measures when the blade actually reaches the sensor,
s1042, constructing a compressed sensing reconstruction model according to the measured blade vibration displacement y:
s1043, calculating actual blade vibration frequency f according to the non-undersampled reconstructed signal Ym:
fmFFT (y), where FFT (·) denotes a discrete fourier transform.
In the method, when thetaiWhen the value is 0, the i-th unit of the rotor blade is not damaged, and when theta is equal toiWhen the value is 1, the ith unit of the rotor blade is completely damaged.
In the method, in the third step, the noise vector includes a modal frequency measurement error and a model numerical calculation error.
According to another aspect of the invention, a monitoring system implementing the method comprises:
a physical measurement module comprising, in combination,
the blade of the rotor to be measured is,
a drive device which drives the rotor blade to rotate,
a sensor measuring a vibration parameter of the rotor blade,
a digital twinning module receiving the blade vibration parameters obtained in the physical measurement module, the digital twinning module including a finite element reference model calculation unit generating a finite element reference model for digital twinning based on the vibration parameters measured by the sensor in an initial crack-free state of the rotor blade,
a data association module connecting the digital twin module and the entity measurement module, the data association module comprising,
a sensitivity matrix calculation unit that generates a sensitivity matrix based on the finite element reference model,
a digital twin real-time update model generation unit that establishes a digital twin real-time update model in a service state based on the sensitivity matrix,
sparse optimization calculation unit solving l-based on convex optimization methodpAnd obtaining a uniquely determined unit stiffness damage factor vector by the sparse optimization model of the norm, wherein the position of a nonzero element in the unit stiffness damage factor vector corresponds to the position of a damaged unit in the finite element model of the rotor blade, and the size of the nonzero element corresponds to the damage severity of the damaged unit.
And corresponding the position of a damage unit in the finite element model to the measured rotor blade in the entity measurement module, and determining the damage position of the measured rotor blade.
Advantageous effects
The method provided by the invention modifies the finite element model through an optimization algorithm to obtain a digital twin model corresponding to a physical entity, constructs a model updating sensitivity matrix, thereby establishing a digital twin real-time updating model in a service state, and utilizes a model based on lpCompared with the traditional manual detection, the method provided by the invention can realize the real-time monitoring of the health condition of the blade, reduce the shutdown maintenance time, reduce the maintenance cost and provide guarantee for the flight safety of the aeroengine.
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Various other advantages and benefits of the present invention will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments. The drawings are only for purposes of illustrating the preferred embodiments and are not to be construed as limiting the invention. It is obvious that the drawings described below are only some embodiments of the invention, and that for a person skilled in the art, other drawings can be derived from them without inventive effort. Also, like parts are designated by like reference numerals throughout the drawings.
In the drawings:
FIG. 1 is a flow chart of a digital twinning based rotor blade health monitoring method;
FIG. 2 is a schematic view of a digital twin based rotor blade health monitoring system.
The invention is further explained below with reference to the figures and examples.
Detailed Description
Specific embodiments of the present invention will be described in more detail below with reference to fig. 1 to 2. While specific embodiments of the invention are shown in the drawings, it should be understood that the invention may be embodied in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the invention to those skilled in the art.
It should be noted that certain terms are used throughout the description and claims to refer to particular components. As one skilled in the art will appreciate, various names may be used to refer to a component. This specification and claims do not intend to distinguish between components that differ in name but not function. In the following description and in the claims, the terms "include" and "comprise" are used in an open-ended fashion, and thus should be interpreted to mean "include, but not limited to. The description which follows is a preferred embodiment of the invention, but is made for the purpose of illustrating the general principles of the invention and not for the purpose of limiting the scope of the invention. The scope of the present invention is defined by the appended claims.
For the purpose of facilitating understanding of the embodiments of the present invention, the following description will be made by taking specific embodiments as examples with reference to the accompanying drawings, and the drawings are not to be construed as limiting the embodiments of the present invention.
For a better understanding, fig. 1 is a flow chart of a digital twin based rotor blade health monitoring method, as shown in fig. 1, comprising the steps of:
in the first step, a three-dimensional finite element model of the rotor blade is established, modal natural frequencies of various orders of the blade at different rotating speeds are calculated through finite element software, and the finite element model is corrected according to modal information measured in the initial crack-free state of the rotor blade;
in the second step, a model is constructed to update a sensitivity matrix;
in the third step, a digital twin real-time updating model in a service state is established;
in a fourth step, the establishment is based onp(p is more than or equal to 0 and less than or equal to 1) solving the sparse optimization model of norm by using a convex optimization method;
in the method, in the first step, establishing a rotor blade model, and correcting the model comprises the following steps:
and S101, carrying out equal-proportion three-dimensional modeling according to the shape of the rotor blade in actual use. And scanning the actual blade by using the contact type aspheric surface measuring instrument to obtain a more accurate three-dimensional model of the rotor blade, and establishing a finite element model of the blade in ANSYS.
S102, the highest rotating speed Rm which can be reached in the actual operation process of the rotor blade is determined, and finite element analysis software is used for calculating the modal natural frequency of each order of the three-dimensional model of the rotor blade at the rotating speed of 0-Rm.
S103, detecting the rotor blade before the rotor blade runs to ensure that no fault exists before the actual blade runs.
S104, installing a blade tip timing sensor around the actual rotor blade, and detecting the resonance frequency of the rotor blade by using a non-contact measuring means. The rotating speed of the rotor blade is increased from 0-Rm and then decreased to 0. And a temperature sensor is arranged near the rotor blade to measure the working temperature of the rotor blade and store various data measured by the blade end timing sensor and the temperature sensor.
And S105, after the operation of the rotor blade is finished, the blade is inspected. If the fault is generated after the actual blade is checked to operate, the steps S103, S104 and S105 are repeated until the actual blade does not contain the fault after the actual blade operates.
S106, substituting the rotating speed of the blade in operation and the temperature measured by the temperature sensor into finite element software to calculate the modal natural frequency f of each step of the rotor bladeFEActual blade vibration frequency f measured by blade tip timing sensormAs an objective function, with the material parameter M ═ E ρ μ of the rotor blade]And the geometric parameter G ═ l w h α]For designing variables, establishing a finite element model correction equation by taking the supremum VHB and the infimum VLB of the material parameters and the geometric parameters as constraint conditions:
subjected to VLB≤{M,G}≤VHB
wherein E is the elastic modulus of the material, rho is the density, mu is the Poisson's ratio, l is the blade length, w is the blade width, h is the blade thickness, and alpha is the blade attack angle. And continuously adjusting the material parameters and the geometric parameters in the finite element model correction equation by using an evolutionary algorithm to minimize the value of the target function, thereby obtaining the finite element reference model for the digital twin.
In the method, in step S104, the sensor for measuring the blade vibration parameter is a blade tip timing sensor, and the step of measuring the blade vibration frequency includes the following steps:
s1041, installing the blade end timing sensor on an engine casing, measuring the time when the blade reaches the sensor, and calculating the vibration displacement of the blade end by taking a time signal measured by the rotating speed sensor as a reference standard:
y＝2πfrRtipΔt
where, t isexpected-tactual，frIs the blade frequency rotation; rtipIs the distance from the rotor axis of rotation to the blade tip; t is texpectedIs the time that the blade reaches the sensor under ideal conditions (i.e., the blade does not vibrate); t is tactualIs the time that the blade actually reaches the sensor as measured by the tip timing system.
S1042, constructing a compressed sensing reconstruction model according to the measured blade vibration displacement y:
the non-undersampled reconstructed signal is obtained as follows:
Y＝Dα
d is a discrete cosine dictionary, alpha is sparse representation of the non-undersampled reconstructed signal Y under the discrete cosine dictionary D, and phi is the allowable error due to the correlation of the observation matrix and the installation position of the leaf-end timing sensor.
S1043, calculating actual blade vibration frequency f according to the non-undersampled reconstructed signal Ym:
fm＝FFT(Y)
Where FFT (.) represents a discrete fourier transform.
In the method, in the second step, the model update sensitivity matrix is constructed as follows:
wherein psijIs the j-th order mass normalized mode shape of the finite element model of the rotor blade,
element stiffness matrix, Q, for the ith element in the finite element reference model described in step S106iFor the finite element reference model, the model is,and a relation matrix between the unit stiffness matrix and the overall stiffness matrix, wherein the superscript T represents the transpose of the matrix or the vector.
In the method, in the third step, a digital twin real-time updating model in a service state is established, and the method mainly comprises the following steps:
s301, reflecting the damage condition of the blade by using the change of the overall stiffness matrix K in the finite element reference model. Establishing a parameterized stiffness damage model based on the overall stiffness matrix and the unit stiffness matrix of the rotor blade finite element reference model:
wherein, K (t)s) Representing the rotor blade finite element model tsGlobal stiffness matrix, n, corresponding to time of dayeleRepresenting the number of elements in the finite element model, i representing the ith element, θi(ts) Denotes the t-thsAt the moment, the damage factor of the ith unit of the rotor blade is thetaiWhen the value is 0, the i-th unit of the rotor blade is not damaged, and when theta is equal toiWhen 1, the i-th unit of the rotor blade is completely damaged, QiIs a relation matrix between an element stiffness matrix and an overall stiffness matrix in a finite element reference model,
the element stiffness matrix of the ith element in the finite element reference model.
S302, establishing a sensitivity matrix-based model updating equation:
Δf＝Sθ+
wherein,
the modal frequency variation before and after the damage of the rotor blade is represented, and the modal frequency variation can be used for judging whether the rotor blade is damaged or not; f. ofdAnd fuRespectively representing the actual blade modal frequency measured by the sensor before and after the damage of the rotor blade, S is a sensitivity matrix,
is a unit stiffness damage factor vector to be solved, can represent the unit damage position and degree, a noise vector comprises a modal frequency measurement error and a model numerical calculation error, nfIs the actual blade modal frequency number, n, measured by the sensoreleIs the number of elements in the finite element model.
In the fourth step, the establishment is based on lp(p is more than or equal to 0 and less than or equal to 1) a sparse optimization model of norm:
wherein,
representing the square of two norms, | ·| non-woven phosphorpRepresenting the p-norm and λ the regularization parameter. Solving the above equation based on l by convex optimization methodpThe sparse optimization model of the norm can obtain the uniquely determined unit stiffness damage factor vector
And according to the position of the nonzero element in the theta, the position of the damage unit in the finite element model of the rotor blade can be corresponded, and the size of the nonzero element corresponds to the damage severity of the damage unit.
In another aspect, a monitoring system implementing the method includes:
a physical measurement module comprising, in combination,
the blade of the rotor to be measured is,
a drive device which drives the rotor blade to rotate,
a sensor measuring a vibration parameter of the rotor blade,
a digital twinning module receiving the blade vibration parameters obtained in the physical measurement module, the digital twinning module including a finite element reference model calculation unit generating a finite element reference model for digital twinning based on the vibration parameters measured by the sensor in an initial crack-free state of the rotor blade,
a data association module connecting the digital twin module and the entity measurement module, the data association module comprising,
a sensitivity matrix calculation unit that generates a sensitivity matrix based on the finite element reference model,
a digital twin real-time update model generation unit that establishes a digital twin real-time update model in a service state based on the sensitivity matrix,
sparse optimization calculation unit solving l-based on convex optimization methodpAnd obtaining a uniquely determined unit stiffness damage factor vector by the sparse optimization model of the norm, wherein the position of a nonzero element in the unit stiffness damage factor vector corresponds to the position of a damaged unit in the finite element model of the rotor blade, and the size of the nonzero element corresponds to the damage severity of the damaged unit.
Further, in one embodiment, as shown in fig. 2, a monitoring system implementing the method includes:
and the physical entity module mainly comprises a real rotor blade, a driving device for driving the blade to rotate, a sensor for measuring the running state of the blade, and a signal measured by the sensor is used for identifying the vibration parameter of the blade and providing data for the digital twin module.
And the digital twin module mainly comprises a three-dimensional finite element model constructed based on a physical entity, and corrects the three-dimensional finite element model by utilizing an optimization method through the fault-free rotor blade data measured by the physical entity module to obtain a finite element reference model.
The data association module is used for constructing a sensitivity matrix and a rigidity damage model by using a unit rigidity matrix, a total rigidity matrix and a modal shape of a finite element reference model, comparing real-time data measured by a physical entity module sensor with the finite element reference model in the service process of the rotor blade to obtain the change condition of vibration parameters, and using a model based on lp(p is more than or equal to 0 and less than or equal to 1) norm sparse optimization model solving modelAnd updating the finite element model of the digital twin module by using the solved result, and monitoring the health condition of the rotor blade in the physical entity module.
Although the embodiments of the present invention have been described above with reference to the accompanying drawings, the present invention is not limited to the above-described embodiments and application fields, and the above-described embodiments are illustrative, instructive, and not restrictive. Those skilled in the art, having the benefit of this disclosure, may effect numerous modifications thereto without departing from the scope of the invention as defined by the appended claims.
Claims (6)
1. A digital twinning based rotor blade health monitoring method, the method comprising the steps of:
in the first step, a three-dimensional model of the rotor blade is established, and the modal natural frequency f of each order of the blade at different rotating speeds is calculated through finite elementsFECorrecting the finite element model according to the modal information measured in the initial crack-free state of the rotor blade to obtain a finite element reference model for digital twinning, wherein the modal natural frequency f of each order calculated by finite elementsFEWith actual blade vibration frequency f measured by the sensormAs an objective function, with the material parameter M ═ E ρ μ of the rotor blade]And the geometric parameter G ═ l w h α]For designing variables, establishing a finite element model correction equation by taking the supremum VHB and the infimum VLB of the material parameters and the geometric parameters as constraint conditions:
e is the elastic modulus of the material, rho is the density, mu is the Poisson ratio, l is the blade length, w is the blade width, h is the blade thickness, and alpha is the blade attack angle, and the material parameters and the geometric parameters in the finite element model correction equation are continuously adjusted based on the evolutionary algorithm so as to ensure that the value of the objective function reaches the minimum value, thereby obtaining a finite element reference model for digital twinning;
in a second step, a sensitivity matrix is constructed:
wherein psijIs the j-th order mass normalized mode shape of the finite element model of the rotor blade,
is the element stiffness matrix, Q, of the ith element in the finite element reference modeliA relation matrix between a unit stiffness matrix and an overall stiffness matrix in a finite element reference model is shown, and superscript T represents the transposition of a matrix or a vector;
in the third step, a digital twin real-time updating model in a service state is established, wherein a parameterized stiffness damage model is established based on the overall stiffness matrix and the unit stiffness matrix of the rotor blade finite element reference model:
wherein, K (t)s) Representing the rotor blade finite element model tsGlobal stiffness matrix, n, corresponding to time of dayeleRepresenting the number of elements in the finite element model, i representing the ith element, θi(ts) Denotes the t-thsMoment, damage factor, Q, of the ith unit of the rotor bladeiIs a relation matrix between an element stiffness matrix and an overall stiffness matrix in a finite element reference model,
is the element stiffness matrix of the ith element in the finite element reference model,
establishing a digital twin real-time updating model in a service state based on the sensitivity matrix: Δ f ═ S θ +, in which,
representing the modal frequency variation before and after damage of the rotor blade; f. ofdAnd fuRespectively representThe actual blade modal frequency measured by the sensor before and after the damage of the rotor blade, S is a sensitivity matrix,
is the unit stiffness impairment factor vector to be solved, which is the noise vector, nfIs the actual blade modal frequency number, n, measured by the sensoreleIs the number of elements in the finite element model;
in a fourth step, the establishment is based onp(p is more than or equal to 0 and less than or equal to 1) a sparse optimization model of norm:
wherein,
representing the square of two norms, | ·| non-woven phosphorpP norm is expressed, lambda represents regularization parameter, and a convex optimization method is utilized to solve the problem based on lpObtaining a uniquely determined unit stiffness damage factor vector by a sparse optimization model of norm
And according to the position of the non-zero element in the theta, corresponding to the position of the damaged unit in the finite element model of the rotor blade, wherein the size of the non-zero element corresponds to the damage severity of the damaged unit.
2. The method according to claim 1, wherein preferably the first step comprises:
s101, carrying out isometric three-dimensional modeling according to the shape of the rotor blade to obtain a three-dimensional model of the rotor blade, establishing a finite element model of the rotor blade based on finite element calculation,
s102, determining the highest rotating speed Rm reached in the actual operation process of the rotor blade, calculating the modal natural frequency of each order of the three-dimensional model of the rotor blade at the rotating speed of 0-Rm by utilizing a finite element,
s103, detecting the rotor blade before the rotor blade runs to ensure that no fault exists before the actual blade runs,
s104, mounting sensors on the rotor blade casing and the surrounding operating environment, enabling the rotor blade to run at a speed increasing speed from 0 to Rm and then at a speed decreasing speed to 0, obtaining data measured by all the sensors,
and S105, after the operation of the rotor blade is finished, checking the blade, and if the actual blade is checked to have a fault after operation, replacing the blade and repeating the steps S103, S104 and S105 until the actual blade does not have the fault after operation.
3. The method according to claim 2, wherein in step S104, the sensor for measuring the blade vibration parameter is an end-of-blade timing sensor, and measuring the blade vibration frequency comprises the steps of:
s1041, installing the blade end timing sensor on an engine casing, measuring the time when the blade reaches the sensor, and calculating the vibration displacement of the blade end by taking a time signal measured by the rotating speed sensor as a reference standard:
y＝2πfrRtipΔ t, wherein Δ t ═ texpected-tactual，frIs the blade frequency rotation; rtipIs the distance from the rotor axis of rotation to the blade tip; t is texpectedThe time when the blade reaches the sensor under the condition that the blade does not vibrate; t is tactualIs the time that the tip timing system measures when the blade actually reaches the sensor,
s1042, constructing a compressed sensing reconstruction model according to the measured blade vibration displacement y:
s1043, calculating actual blade vibration frequency f according to the non-undersampled reconstructed signal Ym:
fmFFT (y), where FFT (.) represents a discrete fourier transformAnd (6) transforming.
4. The method of claim 1, wherein θ is measured asiWhen the value is 0, the i-th unit of the rotor blade is not damaged, and when theta is equal toiWhen the value is 1, the ith unit of the rotor blade is completely damaged.
5. The method according to claim 1, wherein in the third step, the noise vector includes a modal frequency measurement error and a model numerical calculation error.
6. A monitoring system for carrying out the method of any one of claims 1 to 5, the monitoring system comprising:
a physical measurement module comprising, in combination,
the blade of the rotor to be measured is,
a drive device which drives the rotor blade to rotate,
a sensor measuring a vibration parameter of the rotor blade,
a digital twinning module receiving the blade vibration parameters obtained in the physical measurement module, the digital twinning module including a finite element reference model calculation unit generating a finite element reference model for digital twinning based on the vibration parameters measured by the sensor in an initial crack-free state of the rotor blade,
a data association module connecting the digital twin module and the entity measurement module, the data association module comprising,
a sensitivity matrix calculation unit that generates a sensitivity matrix based on the finite element reference model,
a digital twin real-time update model generation unit that establishes a digital twin real-time update model in a service state based on the sensitivity matrix,
sparse optimization calculation unit solving l-based on convex optimization methodpThe sparse optimization model of the norm obtains a uniquely determined unit stiffness damage factor vector, and the corresponding rotor blade has a corresponding position according to the position of a nonzero element in the unit stiffness damage factor vectorAnd the position of the damage unit in the finite element model, and the size of the nonzero element corresponds to the damage severity of the damage unit.
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