Undersampling fractal dimension reconstruction method and system for three-dimensional blade tip clearance signal of aero-engine

Abstract

The invention discloses an aero-engine three-dimensional blade tip gap signal undersampling fractal dimension reconstruction method and system, and belongs to the field of blade non-contact testing, and the method comprises the steps: building a sampling model of a measurement signal for a three-dimensional blade tip gap undersampling signal; the method comprises the following steps: constructing a Fourier sparse matrix, performing sparse representation on an original signal in a frequency domain, deducing an observation matrix, and establishing a three-dimensional blade tip gap signal compressed sensing model; selecting the number of three-dimensional blade tip clearance sensors through a correlation coefficient minimization theory, and optimizing the mounting positions of the sensors; the method provides theoretical guidance for quantitative diagnosis of the blade crack of the aero-engine based on the three-dimensional blade tip gap.

Description

Technical Field

[0001] The invention belongs to the technical field of non-contact blade testing, and in particular relates to an under-sampling fractal reconstruction method and system for a three-dimensional blade tip clearance signal of an aero-engine. Background Art

[0002] Aircraft engines are called the "heart" of aircraft, and turbine blades are key parts of aircraft engines. Their health directly affects the safety and stability of the engine. Due to the huge workload during operation, the rotating blades are prone to fatigue cracks or even breakage, which seriously endangers the safety of engine operation.

[0003] At present, in the research on monitoring blade vibration by non-contact measurement methods, most of the measurement process usually only focuses on the circumferential vibration of the blade, which does not fully reflect the characteristics of blade cracks. In the actual operation of aircraft engines, blade failure will cause the blade to deform in three-dimensional space and present three-dimensional characteristics. However, in the actual measurement of three-dimensional tip clearance, due to the limitation of the number and installation position of sensors on the casing, the sampling of the three-dimensional tip signal does not meet the Shannon sampling theorem, resulting in the collected signal being a serious under-sampled signal, resulting in spectrum aliasing and distortion. It is impossible to analyze it through spectrum analysis methods such as Fourier transform to diagnose blade fault information, so it is necessary to reconstruct the three-dimensional tip clearance under-sampled signal and restore its spectrum characteristics.

[0004] A lot of research has been conducted at home and abroad on the processing of under-sampled signals, and some reconstruction methods have been proposed. Most reconstruction methods rely on prior information of blade vibration and cannot reconstruct the multi-frequency characteristics of the signal. In recent years, compressed sensing, which has been developed on the basis of sparse representation theory, has provided a new idea for solving the above problems. The compressed sensing theory represents the signal through the sparse characteristics of the signal, samples the signal at a rate much lower than the Shannon sampling frequency, and uses the signal reconstruction algorithm at the back end to restore the complete original signal, reducing the hardware cost. Using the compressed sensing characteristics, the spectrum aliasing phenomenon caused by the under-sampled signal of the three-dimensional blade tip clearance can be well eliminated under non-uniform sampling; however, the reconstruction of the under-sampled signal of the three-dimensional blade tip clearance is still blank. Therefore, it is urgent to use the compressed sensing method to reconstruct the three-dimensional blade tip clearance signal in a dimensional manner to extract the fault information of the blade crack in an all-round way. Summary of the invention

[0005] The technical problem to be solved by the present invention is to provide a method and system for undersampling dimensional reconstruction of three-dimensional blade tip clearance signals of aircraft engines in view of the deficiencies in the above-mentioned prior art, so as to solve the technical problem of aliasing and distortion of signal spectrum caused by undersampling characteristics in the sampling process of three-dimensional blade tip clearance signals.

[0006] The present invention adopts the following technical solutions: The method for undersampling fractal reconstruction of three-dimensional blade tip clearance signals of an aero-engine comprises the following steps: S1. Calculate the theoretical arrival time of the blade passing the sensor for the three-dimensional blade tip clearance under-sampling signal and establish a sampling model for the measurement signal; S2, by constructing a Fourier sparse matrix, the three-dimensional blade tip clearance original signal is represented as a superposition of multiple harmonics, and a sparse representation is performed in the frequency domain, and the observation matrix is ​​derived according to the sampling model obtained in step S1, and a three-dimensional blade tip clearance signal compression sensing model is established; S3. The number of three-dimensional blade tip clearance sensors is selected through correlation coefficient minimization theory, and the installation position of the sensors is optimized to obtain the optimal sampling model of the three-dimensional blade tip clearance signal. The optimal observation matrix is ​​constructed according to the obtained optimal sampling model and input into the compressed sensing model obtained in step S2 to solve and obtain the three-dimensional blade tip clearance original signal.

[0007] Preferably, in step S1, establishing a sampling model for the measurement signal is specifically as follows: According to the sampling process of three-dimensional blade tip clearance of aircraft engines, the under-sampling characteristics of the three-dimensional blade tip clearance measurement signal are derived; the sampling model of the three-dimensional blade tip clearance signal is established through the sampling sequence of the three-dimensional blade tip clearance virtual sensor, the actually installed sensor and the sensor installation position, and then the theoretical arrival time of the blade passing through one of the sensors is derived; the mathematical model of sampling the three-dimensional blade tip clearance observation signal vector from the original signal vector is obtained.

[0008] Preferably, from J Select from the following locations where you can install a 3D tip clearance sensor K Sensors are installed at positions, and the number of sensors installed is K Assume that the sampling sequence of the sensor installation position is , a k For the k The installation position of each sensor meets the following requirements: , then the sampling model of the three-dimensional blade tip clearance signal is expressed as: ( J , K , A ).

[0009] Preferably, the signal sampling process is expressed as:

[0010] in, is the observed signal vector, is the original signal vector, For the i The rotation frequency of each blade, For thei The number of revolutions of each blade.

[0011] Preferably, in step S2, the three-dimensional tip clearance signal compression sensing model is:

[0012] in, is a sparse vector, To observe the signal, is the sensing matrix, and the equations are solved by l The minimum value of the 0 norm restores the three-dimensional original signal.

[0013] Preferably, a sparse representation in the frequency domain is performed:

[0014] Among them, T is the Fourier transform basis.

[0015] Preferably, the observation signal for:

[0016] in, is the observation matrix.

[0017] Preferably, the observation matrix for:

[0018] in, M is the number of rows, N is the number of columns and rows M Much smaller than the number of columns N , each row contains only one 1, and the rest are 0.

[0019] Preferably, in step S3, the correlation coefficient is specifically:

[0020] Where D is the sensor matrix, and are two different columns of the sensing matrix, and The number of columns for the two different columns.

[0021] In a second aspect, an embodiment of the present invention provides an under-sampling fractal reconstruction system for a three-dimensional blade tip clearance signal of an aircraft engine, comprising: The signal module calculates the theoretical arrival time of the blade passing the sensor for the under-sampled signal of the three-dimensional blade tip clearance and establishes a sampling model for the measurement signal; The derivation module constructs a Fourier sparse matrix to represent the original signal of the three-dimensional blade tip clearance as a superposition of multiple harmonics, performs sparse representation in the frequency domain, and derives the observation matrix according to the sampling model to establish a compressed sensing model of the three-dimensional blade tip clearance signal; The reconstruction module selects the number of three-dimensional tip clearance sensors through the correlation coefficient minimization theory and optimizes the installation position of the sensors to obtain the optimal sampling model of the three-dimensional tip clearance signal. The optimal observation matrix is ​​constructed according to the obtained optimal sampling model and input into the compressed sensing model to solve the three-dimensional tip clearance original signal.

[0022] In a third aspect, a computer device comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the above-mentioned method for undersampling fractal reconstruction of three-dimensional tip clearance signals of aircraft engines when executing the computer program.

[0023] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, comprising a computer program, which, when executed by a processor, implements the steps of the above-mentioned method for undersampling fractal reconstruction of three-dimensional tip clearance signals of an aircraft engine.

[0024] In a fifth aspect, a chip comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the above-mentioned method for undersampling fractal reconstruction of three-dimensional tip clearance signals of aircraft engines when executing the computer program.

[0025] In a sixth aspect, an embodiment of the present invention provides an electronic device, including a computer program, which, when executed by the electronic device, implements the steps of the above-mentioned method for undersampling fractal reconstruction of three-dimensional tip clearance signals of an aircraft engine.

[0026] Compared with the prior art, the present invention has at least the following beneficial effects: The method of under-sampling fractal reconstruction of three-dimensional blade tip clearance signal of aero-engine is used. A three-dimensional blade tip clearance signal compression sensing model is established for the under-sampling signal of three-dimensional blade tip clearance. By solving and reconstructing the original signal of three-dimensional blade tip clearance, the blade tip characteristics are described from three dimensions of radial clearance, axial deflection angle and circumferential slip angle, and the blade omnidirectional fault information is extracted. Furthermore, according to the sampling model of the three-dimensional blade tip clearance measurement signal, it is helpful to analyze the sampling process of the three-dimensional blade tip clearance and obtain the under-sampling characteristics of the signal during the measurement process.

[0027] Furthermore, by establishing a sampling process of the three-dimensional blade tip clearance measurement signal, it is convenient to construct an observation matrix.

[0028] Furthermore, a compressed sensing model of the three-dimensional blade tip clearance signal is established by solving the sparse vectorl The original signal of the three-dimensional tip clearance is reconstructed by taking the minimum value of the 0 norm.

[0029] Furthermore, the number of three-dimensional tip clearance sensors is selected through correlation coefficient minimization theory, and the installation positions of the sensors are optimized.

[0030] It can be understood that the beneficial effects of the second to sixth aspects mentioned above can be found in the relevant description of the first aspect mentioned above, and will not be repeated here.

[0031] In summary, the present invention obtains a three-dimensional original signal by performing fractal reconstruction on the three-dimensional tip clearance under-sampling signal, thereby restoring the three-dimensional tip clearance dynamic response characteristics, which is beneficial to the all-round extraction of blade crack fault characteristics of the three-dimensional tip clearance, and provides theoretical guidance for the quantitative diagnosis of aircraft engine blade cracks based on three-dimensional tip clearance.

[0032] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 is a flow chart of the method of the present invention; Figure 2 Schematic diagram of the sampling model of the three-dimensional blade tip clearance measurement signal in the present invention; Figure 3 It is a schematic diagram of the compressed sensing model of three-dimensional blade tip clearance signal in the present invention; Figure 4 A schematic diagram showing the comparison of the simulation optimization of the installation position of the three-dimensional blade tip clearance sensor in the present invention; Figure 5 It is a schematic diagram of the overall design of the three-dimensional blade tip clearance signal precision measurement system in the present invention; Figure 6 It is a schematic diagram of the static calibration module of the upper computer software system for the accurate measurement of the three-dimensional blade tip clearance signal in the present invention; Figure 7 Schematic diagram of the sensor signal acquisition and display module of the upper computer software system for accurate measurement of three-dimensional blade tip clearance signals in the present invention; Figure 8 It is a schematic diagram of the measurement signal decoupling module of the upper computer software system for accurate measurement of three-dimensional blade tip clearance signals in the present invention; Fig. 9 It is a schematic diagram of the measurement signal processing and fractal reconstruction module of the host computer software system for accurate measurement of three-dimensional blade tip clearance signals in the present invention; Fig.10 A schematic diagram of a computer device provided by an embodiment of the present invention; Fig.11 A block diagram of a chip provided according to an embodiment of the present invention; Fig.12 Reconstruct the result graph for time domain; Fig.13 This is the frequency domain reconstruction result diagram. DETAILED DESCRIPTION

[0034] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0035] In the description of the present invention, it should be understood that the terms “include” and “comprises” indicate the presence of described features, wholes, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or collections thereof.

[0036] It should also be understood that the terms used in the present specification are only for the purpose of describing specific embodiments and are not intended to limit the present invention. As used in the present specification and the appended claims, unless the context clearly indicates otherwise, the singular forms "a", "an" and "the" are intended to include plural forms.

[0037] It should be further understood that the term "and / or" used in the present specification and the appended claims refers to any combination of one or more of the associated listed items and all possible combinations, and includes these combinations. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in the present invention generally indicates that the associated objects are in an "or" relationship.

[0038] It should be understood that, although the terms first, second, third, etc. may be used to describe preset ranges, etc. in the embodiments of the present invention, these preset ranges should not be limited to these terms. These terms are only used to distinguish preset ranges from each other. For example, without departing from the scope of the embodiments of the present invention, the first preset range may also be referred to as the second preset range, and similarly, the second preset range may also be referred to as the first preset range.

[0039] The word "if" as used herein may be interpreted as "at the time of" or "when" or "in response to determining" or "in response to detecting", depending on the context. Similarly, the phrases "if it is determined" or "if (stated condition or event) is detected" may be interpreted as "when it is determined" or "in response to determining" or "when detecting (stated condition or event)" or "in response to detecting (stated condition or event)", depending on the context.

[0040] Various structural schematic diagrams of the embodiments disclosed in the present invention are shown in the accompanying drawings. These figures are not drawn to scale, and some details are magnified and some details may be omitted for the purpose of clear expression. The shapes of various regions and layers shown in the figures and the relative sizes and positional relationships therebetween are only exemplary, and may deviate in practice due to manufacturing tolerances or technical limitations, and those skilled in the art may additionally design regions / layers with different shapes, sizes, and relative positions according to actual needs.

[0041] The invention provides a method for reconstructing under-sampling fractal dimensions of a three-dimensional blade tip clearance signal of an aero-engine. A sampling model of a measurement signal is established for the three-dimensional blade tip clearance under-sampling signal. A sparse representation of the original signal in the frequency domain is performed by constructing a Fourier sparse matrix, and an observation matrix is ​​derived to establish a three-dimensional blade tip clearance signal compression sensing model. The number of three-dimensional blade tip clearance sensors is selected through the correlation coefficient minimization theory, and the sensor installation positions are optimized. Theoretical guidance is provided for quantitative diagnosis of aero-engine blade cracks based on three-dimensional blade tip clearance.

[0042] See also Figure 1 The present invention provides an under-sampling fractal reconstruction method for a three-dimensional blade tip clearance signal of an aero-engine, comprising the following steps: S1. Calculate the theoretical arrival time of the blade passing the sensor for the three-dimensional blade tip clearance under-sampling signal and establish a sampling model for the measurement signal; See also Figure 2 , the theoretical arrival time of the blade passing the sensor, and establish the sampling model of the measurement signal.

[0043] from J Select from the following locations where you can install a 3D tip clearance sensor K Sensors are installed at positions, and the number of sensors installed is K Assume that the sampling sequence of the sensor installation position is ,in a k For the k The installation position of each sensor meets the following requirements: , then the sampling model of the three-dimensional blade tip clearance signal is expressed as: ( J , K , A ); The rotation frequency of the blade is f r , according to the sampling model ( J , K , A ),blade i Rotate n When the circle passes kThe theoretical arrival time of a sensor is expressed as: (1) No. k The installation angle of each sensor is α k , the theoretical arrival time is expressed as: (2) The signal sampling process is expressed as: (3) in, is the original signal vector, h x ( t ), α x ( t ), β x ( t ) are the original signals of radial clearance, axial deflection angle and circumferential slip angle respectively; is the observed signal vector, h y ( n ), α y ( n ), β y ( n ) are the radial clearance, axial deflection angle and circumferential slip angle measurement signals respectively.

[0044] S2. By constructing a Fourier sparse matrix, the original signal of the three-dimensional blade tip clearance is represented as a superposition of multiple harmonics, thereby performing a sparse representation in the frequency domain, and deriving an observation matrix based on a sampling model to establish a compressed sensing model of the three-dimensional blade tip clearance signal; See also Figure 3 According to the characteristics of multi-frequency combination of the dynamic response of the three-dimensional blade tip clearance signal, the signal is expressed as a superposition of multiple harmonics: (4) in, is the amplitude vector of the dynamic response of the three-dimensional tip clearance signal, is the frequency vector, is the phase vector, M is the harmonic superposition number.

[0045] Using the sparse characteristics of the signal in the frequency domain, Fourier transform is performed on equation (4), and then the signal is sparsely represented in the frequency domain: (5) Among them, Tis the Fourier transform basis, i.e., a sparse matrix, is a sparse vector, h θ ( f ), α θ ( f ), β θ ( f ) are the frequency domain sparse values ​​of radial clearance, axial deflection angle and circumferential slip angle, respectively. Each row contains only a small number of non-zero elements, and the number of non-zero elements is the sparsity.

[0046] According to formula (3), the observed signal is obtained by regularly sampling the original signal according to the sampling mode, which can be expressed as: (6) in, is the observation matrix, whose number of rows M Much smaller than the number of columns N , each row contains only one 1, and the rest are 0.

[0047] The observed signal is further expressed as: (7) in, is the sensor matrix.

[0048] Therefore, the following three-dimensional blade tip clearance signal compressed sensing model is established: (8) This system of equations is solved by l The minimum value of the 0 norm restores the original signal.

[0049] S3. Select the number of three-dimensional tip clearance sensors through correlation coefficient minimization theory and optimize the installation position of the sensors.

[0050] See also Figure 4 For the sampling of three-dimensional blade tip clearance signals, the constructed observation matrix is ​​a specific matrix constructed according to a certain rule, and its rule is related to the number and arrangement of sensors. For a general matrix, determining whether it satisfies the RIP characteristic is an NP-hard problem and cannot be solved.

[0051] The correlation coefficient is used to describe the correlation between matrix columns and is defined as follows: (9) Where D is the sensor matrix. By optimizing the arrangement of sensors, the correlation between columns of D is reduced, thereby increasing the probability of accurate signal reconstruction.

[0052] The finite element model of the rotor system is established using Ansys finite element analysis software to obtain the three-dimensional tip clearance simulation signal. The reconstruction success rate of the three-dimensional tip clearance signal of the reconstruction algorithm under different numbers of sensors is compared through simulation. The number of three-dimensional tip clearance sensors is preliminarily selected, and the sensor installation position is optimized according to the correlation coefficient minimization theory to obtain the optimal sampling model of the three-dimensional tip clearance signal.

[0053] See also Figure 5 , a three-dimensional blade tip clearance signal precise measurement hardware system, including a three-dimensional blade tip clearance fiber optic sensor, a light source driving circuit and a signal conditioning circuit; firstly, a three-dimensional blade tip clearance fiber optic sensor is selected, which is a double-circle coaxial fiber optic sensor, and multiple sensors are installed on the casing at a certain angle according to the optimal sampling model to obtain measurement signals; secondly, a light source driving circuit is designed to provide light sources for multiple incident optical fibers of the sensor probe, and a circuit model simulation of the light source circuit is established in the Multisim software to ensure the optical power and stability of the multiple light sources; then a signal conditioning circuit is designed, which is mainly a photoelectric conversion module, which is used to convert the light intensity signal output by the optical fiber into a voltage signal output, and the output consistency of the multi-channel conditioning circuit is made good through simulation; finally, the printed circuit board wiring is performed using the Altium Designer software according to the circuit schematic.

[0054] The upper computer software system for accurate measurement of three-dimensional tip clearance signals includes a sensor static calibration module, a sensor signal acquisition and display module, a measurement signal decoupling module, and a measurement signal processing and dimensional reconstruction module.

[0055] See also Figure 6 , which is the software design diagram of the sensor static calibration module, is used to calibrate the optical fiber sensor and store the pre-trained network.

[0056] See also Figure 7 , which is the design diagram of the sensor signal acquisition and display module, is used to record and display the voltage signals output by multiple optical fiber sensors and phase detection sensors.

[0057] See also Figure 8 , which is the design diagram of the measurement signal decoupling module, is used to decouple the voltage output values ​​of multiple optical fiber sensors to obtain the three-dimensional blade tip clearance measurement signal.

[0058] See also Fig. 9 , which is the design diagram of the measurement signal processing and fractal reconstruction module, is used for processing and fractal reconstruction of three-dimensional blade tip clearance measurement signals.

[0059] The host computer software system for accurate measurement of three-dimensional blade tip clearance signal is designed by LabVIEW. Firstly, the sensor static calibration module is designed for the calibration of the optical fiber sensor. By calling the MatLab script, the voltage output value of the sensor and the three-dimensional blade tip clearance value are input into the neural network for training, and the pre-trained network is stored. Secondly, design the sensor signal acquisition and display module, collect and display the voltage signals output by multiple optical fiber sensors and phase detectors, set the sampling rate and number of samples, turn on the recording mode, record the output of multiple sensors at the same time and store the data, and display the data length; Then, a measurement signal decoupling module is designed. By calling the MatLab script, the voltage output values ​​of multiple fiber optic sensors are decoupled through the pre-trained neural network, the three-dimensional blade tip clearance measurement values ​​are obtained and displayed, the required signal length is set, and the data is stored; Finally, a measurement signal processing and dimensional reconstruction module is designed. By calling the MatLab script, the three-dimensional tip clearance measurement values ​​of multiple sensors are segmented and processed, the three-dimensional tip clearance measurement value of a certain blade is obtained and the data is stored. At the same time, dimensional reconstruction is performed to obtain the three-dimensional tip clearance original signal of a certain blade and store the data.

[0060] In another embodiment of the present invention, a system for under-sampling fractal reconstruction of three-dimensional blade tip clearance signals of an aircraft engine is provided. The system can be used to implement the above-mentioned under-sampling fractal reconstruction method of three-dimensional blade tip clearance signals of an aircraft engine. Specifically, the system for under-sampling fractal reconstruction of three-dimensional blade tip clearance signals of an aircraft engine includes a signal module, a derivation module and a reconstruction module.

[0061] Among them, the signal module calculates the theoretical arrival time of the blade passing the sensor for the three-dimensional blade tip clearance under-sampling signal and establishes a sampling model for the measurement signal; The derivation module constructs a Fourier sparse matrix to represent the original signal of the three-dimensional blade tip clearance as a superposition of multiple harmonics, performs sparse representation in the frequency domain, and derives the observation matrix according to the sampling model to establish a compressed sensing model of the three-dimensional blade tip clearance signal; The reconstruction module selects the number of three-dimensional tip clearance sensors through the correlation coefficient minimization theory and optimizes the installation position of the sensors to obtain the optimal sampling model of the three-dimensional tip clearance signal. The optimal observation matrix is ​​constructed according to the obtained optimal sampling model and input into the compressed sensing model to solve the three-dimensional tip clearance original signal.

[0062] In another embodiment of the present invention, a terminal device is provided, which includes a processor and a memory, wherein the memory is used to store a computer program, the computer program includes program instructions, and the processor is used to execute the program instructions stored in the computer storage medium. The processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. It is the computing core and control core of the terminal, which is suitable for implementing one or more instructions, and is specifically suitable for loading and executing one or more instructions to implement corresponding method processes or corresponding functions; the processor described in the embodiment of the present invention can be used for the operation of the undersampling fractal reconstruction method of the three-dimensional blade tip clearance signal of an aircraft engine, including: For the under-sampling signal of three-dimensional tip clearance, the theoretical arrival time of the blade passing the sensor is calculated, and the sampling model of the measurement signal is established; by constructing a Fourier sparse matrix, the three-dimensional tip clearance original signal is represented as a superposition of multiple harmonics, and a sparse representation is performed in the frequency domain. The observation matrix is ​​derived according to the sampling model, and a compressed sensing model of the three-dimensional tip clearance signal is established; the number of three-dimensional tip clearance sensors is selected through the correlation coefficient minimization theory, and the installation position of the sensor is optimized to obtain the optimal sampling model of the three-dimensional tip clearance signal. The optimal observation matrix is ​​constructed according to the obtained optimal sampling model and input into the compressed sensing model to solve the three-dimensional tip clearance original signal.

[0063] See also Fig.10 , the terminal device is a computer device. The computer device 60 of this embodiment includes: a processor 61, a memory 62, and a computer program 63 stored in the memory 62 and executable on the processor 61. When the computer program 63 is executed by the processor 61, the method for calculating the fluid composition in the reservoir transformation wellbore in the embodiment is implemented. To avoid repetition, it is not described one by one here. Alternatively, when the computer program 63 is executed by the processor 61, the functions of each model / unit in the undersampling fractal reconstruction system of the three-dimensional blade tip clearance signal of the aircraft engine in the embodiment are implemented. To avoid repetition, it is not described one by one here.

[0064] The computer device 60 may be a computing device such as a desktop computer, a notebook, a PDA, or a cloud server. The computer device 60 may include, but is not limited to, a processor 61 and a memory 62. Those skilled in the art will appreciate that Figure 8 This is only an example of the computer device 60 and does not constitute a limitation of the computer device 60. It may include more or fewer components than shown in the figure, or a combination of certain components, or different components. For example, the computer device may also include input and output devices, network access devices, buses, etc.

[0065] The processor 61 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc.

[0066] The memory 62 may be an internal storage unit of the computer device 60, such as a hard disk or memory of the computer device 60. The memory 62 may also be an external storage device of the computer device 60, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc., equipped on the computer device 60.

[0067] Furthermore, the memory 62 may include both an internal storage unit of the computer device 60 and an external storage device. The memory 62 is used to store computer programs and other programs and data required by the computer device. The memory 62 may also be used to temporarily store data that has been output or is to be output.

[0068] See also Fig.11 , the terminal device is a chip, and the chip 600 of this embodiment includes a processor 622, which may be one or more, and a memory 632 for storing a computer program executable by the processor 622. The computer program stored in the memory 632 may include one or more modules, each corresponding to a set of instructions. In addition, the processor 622 may be configured to execute the computer program to execute the above-mentioned aircraft engine three-dimensional blade tip clearance signal undersampling fractal reconstruction method.

[0069] In addition, the chip 600 may further include a power supply component 626 and a communication component 650, wherein the power supply component 626 may be configured to perform power management of the chip 600, and the communication component 650 may be configured to implement communication, for example, wired or wireless communication, of the chip 600. In addition, the chip 600 may further include an input / output interface 658. The chip 600 may operate based on an operating system stored in the memory 632.

[0070] In another embodiment of the present invention, the present invention also provides a storage medium, specifically a computer-readable storage medium, which is a memory device in a terminal device for storing programs and data. It can be understood that the computer-readable storage medium here can include both the built-in storage medium in the terminal device and the extended storage medium supported by the terminal device. The computer-readable storage medium provides a storage space, which stores the operating system of the terminal. In addition, one or more instructions suitable for being loaded and executed by the processor are also stored in the storage space, and these instructions can be one or more computer programs. It should be noted that the computer-readable storage medium here can be a high-speed RAM memory, or a non-volatile memory (Non-VolatileMemory), such as at least one disk memory.

[0071] The processor may load and execute one or more instructions stored in a computer-readable storage medium to implement the corresponding steps of the method for undersampling fractal reconstruction of a three-dimensional blade tip clearance signal of an aircraft engine in the above embodiment; the processor may load and execute the following steps: For the three-dimensional blade tip clearance under-sampling signal, the theoretical arrival time of the blade passing the sensor is calculated, and a sampling model of the measurement signal is established; by constructing a Fourier sparse matrix, the three-dimensional blade tip clearance original signal is represented as a superposition of multiple harmonics, and a sparse representation is performed in the frequency domain, and the observation matrix is ​​derived according to the sampling model to establish a three-dimensional blade tip clearance signal compression sensing model; the number of three-dimensional blade tip clearance sensors is selected by correlation coefficient minimization theory, and the installation position of the sensor is optimized to obtain the optimal sampling model of the three-dimensional blade tip clearance signal, and the optimal observation matrix is ​​constructed according to the obtained optimal sampling model, and input into the compression sensing model to solve and obtain the three-dimensional blade tip clearance original signal. In order to make the purpose, technical solution and advantages of the embodiment of the present invention clearer, the technical solution in the embodiment of the present invention will be clearly and completely described in conjunction with the drawings in the embodiment of the present invention. Obviously, the described embodiment is a part of the embodiment of the present invention, not all of the embodiments. Generally, the components of the embodiment of the present invention described and shown in the drawings here can be arranged and designed by various different configurations. Therefore, the following detailed description of the embodiment of the present invention provided in the drawings is not intended to limit the scope of the claimed invention, but only represents the selected embodiment of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in the field without making any creative work shall fall within the scope of protection of the present invention.

[0072] The three-dimensional blade tip clearance simulation signal is reconstructed by fractal dimension, and the normal signal and the fault signal of the cracked blade are reconstructed respectively. The time domain reconstruction results are as follows: Fig.12 As shown, the frequency domain reconstruction result is Fig.13 As shown in the figure, the simulation results show that the absolute error and relative error of the reconstruction of the 3D-BTC signal are less than 1e-15. The radial clearance signal, axial deflection angle signal and circumferential slip angle signal are accurately reconstructed and their respective spectra are accurately restored, verifying the reconstruction performance.

[0073] In summary, the invention provides a method and system for reconstructing the three-dimensional blade tip clearance signal undersampling fractal dimension of an aircraft engine. By reconstructing the three-dimensional blade tip clearance undersampling signal undersampling dimension, a three-dimensional original signal is obtained, thereby restoring the three-dimensional blade tip clearance dynamic response characteristics, which is conducive to extracting the blade crack fault characteristics of the three-dimensional blade tip clearance in all directions and realizing non-contact rapid quantitative diagnosis of blade cracks. It is of great significance for timely discovering early weak cracks in turbine blades and ensuring flight safety.

[0074] The technicians in the relevant field can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In practical applications, the above-mentioned function allocation can be completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiment can be integrated in a processing unit, or each unit can exist physically separately, or two or more units can be integrated in one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application. The specific working process of the units and modules in the above-mentioned system can refer to the corresponding process in the aforementioned method embodiment, which will not be repeated here.

[0075] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0076] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed in the present invention can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0077] In the embodiments provided by the present invention, it should be understood that the disclosed devices / terminals and methods can be implemented in other ways. For example, the device / terminal embodiments described above are only schematic. For example, the division of the modules or units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0078] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0079] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0080] If the integrated module / unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present invention implements all or part of the processes in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and the computer program can implement the steps of the above-mentioned various method embodiments when executed by the processor. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, U disk, mobile hard disk, disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electric carrier signal, telecommunication signal and software distribution medium, etc. It should be noted that the content contained in the computer-readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable media do not include electric carrier signals and telecommunication signals.

[0081] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices, and computer program products according to the embodiments of the present application. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of the processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0082] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0083] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0084] The above contents are only for explaining the technical idea of ​​the present invention and cannot be used to limit the protection scope of the present invention. Any changes made on the basis of the technical solution in accordance with the technical idea proposed by the present invention shall fall within the protection scope of the claims of the present invention.

Claims

1. An under-sampling fractal reconstruction method for three-dimensional tip clearance signals of aircraft engines, characterized in that: The following steps are involved: S1. Calculate the theoretical arrival time of the blade passing the sensor for the three-dimensional blade tip clearance under-sampling signal and establish a sampling model for the measurement signal; S2, by constructing a Fourier sparse matrix, the three-dimensional blade tip clearance original signal is represented as a superposition of multiple harmonics, and a sparse representation is performed in the frequency domain, and the observation matrix is ​​derived according to the sampling model obtained in step S1, and a three-dimensional blade tip clearance signal compression sensing model is established; S3. The number of three-dimensional blade tip clearance sensors is selected through correlation coefficient minimization theory, and the installation position of the sensors is optimized to obtain the optimal sampling model of the three-dimensional blade tip clearance signal. The optimal observation matrix is ​​constructed according to the obtained optimal sampling model and input into the compressed sensing model obtained in step S2 to solve and obtain the three-dimensional blade tip clearance original signal.

2. The method for undersampling fractal reconstruction of three-dimensional tip clearance signals of an aircraft engine according to claim 1, characterized in that: In step S1, the sampling model of the measurement signal is established as follows: According to the sampling process of three-dimensional blade tip clearance of aircraft engines, the under-sampling characteristics of the three-dimensional blade tip clearance measurement signal are derived; the sampling model of the three-dimensional blade tip clearance signal is established through the sampling sequence of the three-dimensional blade tip clearance virtual sensor, the actually installed sensor and the sensor installation position, and then the theoretical arrival time of the blade passing through one of the sensors is derived; the mathematical model of sampling the three-dimensional blade tip clearance observation signal vector from the original signal vector is obtained.

3. The method for undersampling fractal reconstruction of three-dimensional tip clearance signals of an aircraft engine according to claim 2, characterized in that: from J Select from the following locations where you can install a 3D tip clearance sensor K Sensors are installed at positions, and the number of sensors installed is K Assume that the sampling sequence of the sensor installation position is , a k For the k The installation position of each sensor meets the following requirements: , then the sampling model of the three-dimensional blade tip clearance signal is expressed as: ( J , K , A ).

4. The method for undersampling fractal reconstruction of three-dimensional tip clearance signals of an aircraft engine according to claim 2, characterized in that: The signal sampling process is expressed as: in, is the observed signal vector, is the original signal vector, For the i The rotation frequency of each blade, For the i The number of revolutions of each blade.

5. The method for undersampling fractal reconstruction of three-dimensional tip clearance signals of an aircraft engine according to claim 1, characterized in that: In step S2, the three-dimensional tip clearance signal compression sensing model is: in, is a sparse vector, To observe the signal, is the sensor matrix.

6. The method for undersampling fractal reconstruction of three-dimensional tip clearance signals of an aircraft engine according to claim 5, characterized in that: Perform sparse representation in the frequency domain: Among them, T is the Fourier transform basis.

7. The method for undersampling fractal reconstruction of three-dimensional tip clearance signals of an aircraft engine according to claim 5, characterized in that: Observation signal for: in, is the observation matrix.

8. The method for undersampling fractal reconstruction of three-dimensional tip clearance signals of an aircraft engine according to claim 7, characterized in that: Observation Matrix for: in, M is the number of rows, N is the number of columns and rows M Much smaller than the number of columns N , each row contains only one 1, and the rest are 0.

9. The method for undersampling fractal reconstruction of three-dimensional tip clearance signals of an aircraft engine according to claim 1, characterized in that: In step S3, the correlation coefficient is specifically: Where D is the sensor matrix, and are two different columns of the sensing matrix, and The number of columns for the two different columns.

10. An under-sampling fractal reconstruction system for three-dimensional tip clearance signals of an aircraft engine, characterized in that: include: The signal module calculates the theoretical arrival time of the blade passing the sensor for the under-sampled signal of the three-dimensional blade tip clearance and establishes a sampling model for the measurement signal; The derivation module constructs a Fourier sparse matrix to represent the original signal of the three-dimensional blade tip clearance as a superposition of multiple harmonics, performs sparse representation in the frequency domain, and derives the observation matrix according to the sampling model to establish a compressed sensing model of the three-dimensional blade tip clearance signal; The reconstruction module selects the number of three-dimensional tip clearance sensors through the correlation coefficient minimization theory and optimizes the installation position of the sensors to obtain the optimal sampling model of the three-dimensional tip clearance signal. The optimal observation matrix is ​​constructed according to the obtained optimal sampling model and input into the compressed sensing model to solve the three-dimensional tip clearance original signal.

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