Method and device for determining vibration frequency through gradient sampling, medium and product

Abstract

The invention discloses a method and device for determining vibration frequency through gradient sampling, a medium and a product, and relates to the field of data processing, and the method comprises the steps: obtaining a plurality of sampling frequencies according to gradient setting; carrying out undersampling on the object vibration signal by adopting a plurality of sampling frequencies to obtain undersampled data; performing frequency estimation on the under-sampling data to obtain an acquisition waveform frequency; constructing a plurality of object vibration frequency equations based on the acquired waveform frequency and the plurality of sampling frequencies; the original frequency equations of the objects are calculated through the Chinese remainder theorem, and the vibration frequency is obtained. According to the method, the calculation process can be simplified on the basis that complicated installation of measurement equipment is not needed, and the purpose of efficiently obtaining the frequency range of the high-frequency vibration object is achieved.

Description

Technical Field

[0001] The present application relates to the field of data processing, and in particular to a method, device, medium and product for determining vibration frequency by gradient sampling. Background Art

[0002] During the service of aircraft engines, high-speed rotating objects such as blades will generate high-frequency vibrations under the action of complex centrifugal aerodynamic loads. This vibration will not only affect the performance of the engine, but may also cause fatigue failure of the blades, posing a threat to flight safety. Therefore, it is particularly important to accurately measure the vibration frequency of high-frequency vibrating objects. Accurately measuring the frequency and amplitude of high-frequency vibrating objects in aircraft engines is of great significance to ensure the safe operation of the engine and extend its service life.

[0003] Traditional measurement methods may not be able to accurately capture these high-frequency vibrations, so advanced measurement technologies are needed. These technologies include, but are not limited to, laser vibrometers, accelerometers, and fiber optic sensors, which can measure the vibration of objects with high precision in a non-contact manner. The above methods all need to comply with the Nyquist sampling theorem, which is an important basic theory in digital signal processing and describes the relationship between the frequency at which an analog signal is sampled and the signal spectrum. Specifically, if f(t) is a frequency band limited to (0, f h ), if the sampled signal is to be able to restore the original signal without distortion, the sampling frequency f must be s Greater than or equal to the highest frequency component f of the signal h twice, that is, f s ≥2f h In other words, the highest frequency of the signal must not be greater than the folding frequency f s / 2. Undersampling refers to the situation where the sampling frequency is less than twice the highest frequency of the signal. In the case of undersampling, the sampled signal will be aliased, that is, the high-frequency signal will affect the performance of the low-frequency signal. The commonly used vibration frequency measurement method is a blade synchronous resonance frequency recovery method based on the characteristics of the blade tip timing undersampling signal, which includes: randomly installing blade tip timing sensors, obtaining the vibration displacement of the blade tip timing signal, and performing discrete Fourier transform on each channel to form a low-dimensional matrix. Measure the relative angle between the blade tip timing sensors, set the number of sensors that need to be installed to meet the Nyquist sampling theorem, and calculate the position parameters corresponding to each blade tip timing sensor. Calculate the compensation matrix of the low-dimensional matrix and the parameterized compression matrix to form an underdetermined equation group of multiple column vectors. In the iterative solution process, select multiple atoms to calculate the sparse estimate of the least squares solution to obtain the reconstructed high-dimensional matrix. Connect the row vectors of the high-dimensional matrix end to end in order to obtain the recovered spectrum value, and obtain the recovered frequency of blade vibration.

[0004] In addition to the above methods, there is also a frequency recovery method for undersampled signals based on intrinsic time scale decomposition. Intrinsic Time Scale Decomposition (ITD) is a signal processing method that aims to solve the frequency recovery problem of undersampled signals. Based on the nonlinear, instability and nonlinear characteristics of the signal, this method decomposes a signal into several intrinsic rotation frequencies and trend terms. The intrinsic rotation frequency is a periodic component existing in the signal, while the trend term represents the non-periodic component in the signal. Through intrinsic time scale decomposition, the frequency value of each intrinsic rotation frequency can be accurately obtained, thereby obtaining the frequency of the undersampled signal. Compared with traditional signal processing methods, intrinsic time scale decomposition has better adaptability and can process various complex signals. In addition, this method can also be used in other fields, such as seismic signal processing, speech processing, etc. This method first performs intrinsic time scale decomposition on the undersampled signal to obtain several intrinsic rotation frequencies and trend terms, then performs frequency tracking on the intrinsic rotation frequency to obtain the frequency value of each intrinsic rotation frequency, and finally adds up the frequency values ​​of all intrinsic rotation frequencies to obtain the frequency of the undersampled signal. Specifically, intrinsic time scale decomposition decomposes the signal into multiple intrinsic rotation frequencies and trend terms through filtering, prediction and reconstruction of the signal. Each intrinsic rotation frequency represents a periodic component in the signal, while the trend term represents the non-periodic component in the signal. By accurately obtaining the frequency value of each intrinsic rotation frequency, the frequency of the undersampled signal can be restored.

[0005] The basic principle of the above-mentioned blade synchronous resonance frequency recovery method based on the characteristics of the blade tip timing undersampling signal is to install the vibration sensor on the engine casing, measure the pulse time signal of the blade arrival through the vibration sensor, use different analysis algorithms to process the time signal, and obtain the vibration characteristic parameters of the blade. The main limitation of the blade synchronous resonance frequency recovery method based on the characteristics of the blade tip timing undersampling signal is that it is necessary to drill holes on the casing to install sensors, which causes certain damage to the engine structure, and multiple sensors need to be installed to obtain the vibration signals of all blades, which increases the difficulty and cost of installation.

[0006] The frequency recovery method of undersampled signals based on intrinsic time scale decomposition is mainly used to analyze nonlinear and non-stationary signals. Although the intrinsic time scale characteristics in the signal can be extracted, the calculation process is relatively complicated, requiring higher computing resources and time, and has high computational complexity. Summary of the invention

[0007] The purpose of this application is to provide a method, device, medium and product for determining vibration frequency by gradient sampling, which can simplify the calculation process without the need for complex installation of measurement equipment and achieve the purpose of efficiently obtaining the frequency range of high-frequency vibrating objects.

[0008] To achieve the above objectives, this application provides the following solutions:

[0009] In a first aspect, the present application provides a method for determining vibration frequency by gradient sampling, comprising:

[0010] Multiple sampling frequencies are obtained according to the gradient setting;

[0011] Under-sampling the vibration signal of the object using a plurality of the sampling frequencies to obtain under-sampling data;

[0012] Performing frequency estimation on the under-sampled data to obtain a collection waveform frequency;

[0013] Constructing multiple object vibration frequency equations based on the acquisition waveform frequency and the multiple sampling frequencies;

[0014] The Chinese remainder theorem is used to calculate the original frequency equations of multiple objects and obtain the vibration frequency.

[0015] Optionally, the multiple sampling frequencies obtained according to the gradient setting are frequencies between 2 Hz and 10 Hz.

[0016] Optionally, performing frequency estimation on the under-sampled data to obtain the acquisition waveform frequency includes:

[0017] Determining a periodicity regularity of each data point in the undersampled data;

[0018] Based on the periodic law, the under-sampled data is subjected to discrete Fourier transform to obtain the acquisition waveform frequency.

[0019] Optionally, a formula for performing discrete Fourier transform on the under-sampled data is:

[0020]

[0021] In the formula, x[n] is the undersampled data, e is the natural logarithm, k is the discrete sampling position, j is the imaginary unit, n is the nth data point in the undersampled data, and N is the length of the undersampled data.

[0022] Optionally, constructing multiple object vibration frequency equations based on the acquisition waveform frequency and the multiple sampling frequencies includes:

[0023] Taking the collected waveform frequency as the remainder and taking the plurality of sampling frequencies as the dividends respectively, a plurality of object vibration frequency equations are constructed.

[0024] Optionally, the object vibration frequency equation is expressed as:

[0025] f=n i *f si +f i ;

[0026] Where F is the vibration frequency, n i is an unknown number, f si is the i-th sampling frequency, f i is the frequency of the acquired waveform.

[0027] Optionally, the Chinese remainder theorem is used to calculate the original frequency equations of multiple objects to obtain the vibration frequencies, including:

[0028] determining a product of the sampling frequencies;

[0029] Obtaining an intermediate quantity based on the product of the sampling frequencies and the sampling frequency, and determining an inverse element of the intermediate quantity;

[0030] The vibration frequency is determined based on the acquired waveform frequency, the intermediate quantity, and an inverse element of the intermediate quantity.

[0031] In a second aspect, the present application provides a computer device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of any one of the above-described methods for determining vibration frequency by gradient sampling.

[0032] In a third aspect, the present application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of any of the above-mentioned methods for determining vibration frequency by gradient sampling.

[0033] In a fourth aspect, the present application provides a computer program product, including a computer program, which, when executed by a processor, implements the steps of any of the above-mentioned methods for determining vibration frequency by gradient sampling.

[0034] According to the specific embodiments provided in this application, this application has the following technical effects:

[0035] The present application provides a method, device, medium and product for determining vibration frequency by gradient sampling. By obtaining multiple sampling frequencies according to the gradient setting, undersampling of low-frequency gradients can be achieved. By estimating the frequency of the undersampled data and obtaining the frequency of the acquired waveform, the calculation process can be simplified, thereby reducing computing resources and shortening the calculation time. The Chinese remainder theorem is used to calculate the original frequency equations of multiple objects to obtain the vibration frequency, which can achieve the purpose of efficiently obtaining the frequency range of high-frequency vibration objects. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0037] Figure 1 A schematic flow chart of a method for determining vibration frequency by gradient sampling provided in one embodiment of the present application;

[0038] Figure 2 A waveform diagram of a 50 Hz vibration waveform provided in an embodiment of the present application that is undersampled by 2 Hz;

[0039] Figure 3 A spectrum diagram of a 2Hz under-sampling waveform of a 50Hz vibration waveform provided in an embodiment of the present application;

[0040] Figure 4 A waveform diagram of a 50 Hz vibration waveform provided in an embodiment of the present application that is undersampled by 3 Hz;

[0041] Figure 5 A spectrum diagram of a 3Hz under-sampling waveform of a 50Hz vibration waveform provided in an embodiment of the present application;

[0042] Figure 6 A waveform diagram of a 50 Hz vibration waveform provided in an embodiment of the present application that is undersampled by 4 Hz;

[0043] Figure 7 A spectrum diagram of a 4Hz under-sampling waveform of a 50Hz vibration waveform provided in an embodiment of the present application;

[0044] Figure 8 A waveform diagram of a 50 Hz vibration waveform provided in an embodiment of the present application that is undersampled by 5 Hz;

[0045] Fig. 9 A spectrum diagram of a 5 Hz under-sampling waveform of a 50 Hz vibration waveform provided in an embodiment of the present application;

[0046] Fig.10 A waveform diagram of a 50 Hz vibration waveform provided in an embodiment of the present application that is undersampled by 6 Hz;

[0047] Fig.11 A spectrum diagram of a 6Hz under-sampling waveform of a 50Hz vibration waveform provided in an embodiment of the present application;

[0048] Fig.12A waveform diagram of a 50 Hz vibration waveform provided in an embodiment of the present application that is undersampled by 7 Hz;

[0049] Fig.13 A spectrum diagram of a 7Hz under-sampling waveform of a 50Hz vibration waveform provided in an embodiment of the present application;

[0050] Fig.14 A waveform diagram of a 50 Hz vibration waveform provided in an embodiment of the present application that is undersampled by 8 Hz;

[0051] Fig.15 A spectrum diagram of an 8Hz under-sampling waveform of a 50Hz vibration waveform provided in an embodiment of the present application;

[0052] Fig.16 A waveform diagram of a 50 Hz vibration waveform provided in an embodiment of the present application that is undersampled by 9 Hz;

[0053] Fig.17 A spectrum diagram of a 9Hz under-sampling waveform of a 50Hz vibration waveform provided in an embodiment of the present application;

[0054] Fig.18 A waveform diagram of a 50 Hz vibration waveform provided in an embodiment of the present application that is undersampled by 10 Hz;

[0055] Fig.19 A spectrum diagram of a 10 Hz under-sampling waveform of a 50 Hz vibration waveform provided in an embodiment of the present application;

[0056] Fig. 20 A schematic diagram of the structure of a computer device provided in one embodiment of the present application. DETAILED DESCRIPTION

[0057] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0058] In order to make the above-mentioned objects, features and advantages of the present application more obvious and easy to understand, the present application is further described in detail below in conjunction with the accompanying drawings and specific implementation methods.

[0059] In an exemplary embodiment, Figure 1As shown, a method for determining vibration frequency by gradient sampling is provided, and the method is executed by a computer device, and can be executed by a computer device such as a terminal or a server alone, or by a terminal and a server together. In the embodiment of the present application, the method is applied to a server as an example for explanation, and includes the following steps 101 to 108. Among them:

[0060] Step 100: Obtain multiple sampling frequencies according to the gradient setting.

[0061] Step 101: Under-sampling the vibration signal of the object using multiple sampling frequencies to obtain under-sampling data.

[0062] Step 102: Perform frequency estimation on the under-sampled data to obtain the collected waveform frequency.

[0063] Step 103: construct multiple object vibration frequency equations based on the collected waveform frequency and multiple sampling frequencies.

[0064] Step 104: Use the Chinese remainder theorem to calculate the original frequency equations of multiple objects to obtain the vibration frequency.

[0065] In another exemplary embodiment of the present application, in order to achieve low-frequency gradient sampling, in this embodiment, the sampling frequency can be set to a value between 2 Hz and 10 Hz according to the gradient. A plurality of (e.g., 200) data points are collected at each sampling frequency to obtain under-sampled data.

[0066] In another exemplary embodiment of the present application, after obtaining the under-sampled data, the period of the sampling waveform will be periodic. Based on this, in order to further simplify the calculation process, in this embodiment, the periodic law of each data point in the under-sampled data is calculated, and the acquisition waveform frequency is obtained by discrete Fourier transform (DFT). For example, for under-sampled data x[n] with a length of N, the formula for its discrete Fourier transform is:

[0067]

[0068] Where x[n] is the undersampled data, e is the natural logarithm, k is the discrete sampling position, j is the imaginary unit, n is the nth data point in the undersampled data, and N is the length of the undersampled data.

[0069] Based on the above description, the waveform and frequency of the 50Hz vibration waveform undersampled by 2Hz-10Hz are as follows Figures 2 to 19 As shown in the figure, the absolute value of the horizontal axis corresponding to the highest peak value in the spectrum waveform is taken as the frequency of the collected waveform, that is, the collected waveform frequency.

[0070] In another exemplary embodiment of the present application, in order to increase the accuracy of vibration frequency determination, in the test, multiple object vibration frequency equations can be constructed with the collected waveform frequency as the remainder and multiple sampling frequencies as the dividends. The object vibration frequency equation is expressed as:

[0071] F=n i *f si +f i .

[0072] Where F is the vibration frequency. i is an unknown number, and its purpose is to be the minimum coefficient that makes the equation of the object's vibration frequency valid. si is the i-th sampling frequency, f i is the frequency of the collected waveform, i=1,...,10.

[0073] The 2-, 3-, 4-, 5-, 6-, 7-, 8- and 9-equations corresponding to the sampling frequencies that are mutually prime are respectively established and the results are calculated. Invalid results are recorded as 0. The above result information is counted, and the one with the largest number is the estimated vibration frequency (i.e., F value).

[0074] Among them, taking the two-variable equation as an example, if (f si , f i ) respectively take (3, 2) and (5, 4), that is, the system of equations is written as F = 3n i +2 and F = 5n i +4,n i There is no solution at this time, so it is marked as invalid, and the result F is counted as 0.

[0075] In another exemplary embodiment of the present application, the implementation process of step 104 can be described as follows:

[0076] (1) Determine the product of the sampling frequencies. The product of the sampling frequencies is expressed as M = f s1 *f s2 *...*f sg . g is the number of remainders, and M is the product of the sampling frequencies.

[0077] (2) Obtain an intermediate quantity based on the product of the sampling frequencies and the sampling frequency, and determine the inverse element of the intermediate quantity. si , the intermediate quantity is represented by M i =M / f si The inverse element of the intermediate quantity is expressed as The inverse element of the intermediate quantity satisfies Mod is the remainder function.

[0078] (3) Determine the vibration frequency based on the collected waveform frequency, the intermediate quantity, and the inverse element of the intermediate quantity. The determined vibration frequency is expressed as:

[0079]

[0080] In an exemplary embodiment, a computer device is provided. The computer device may be a server or a terminal. The internal structure diagram thereof may be as follows: Fig. 20 As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, referred to as I / O) and a communication interface. Among them, the processor, the memory and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store gradient sampling estimated vibration frequency data. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a method for determining vibration frequency by gradient sampling is implemented.

[0081] Those skilled in the art will understand that Fig. 20 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components. In an exemplary embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the steps in the above-mentioned method embodiments when executing the computer program.

[0082] In an exemplary embodiment, a computer-readable storage medium is provided, storing a computer program, and when the computer program is executed by a processor, the steps in the above method embodiments are implemented.

[0083] In an exemplary embodiment, a computer program product is provided, including a computer program, and when the computer program is executed by a processor, the steps in the above method embodiments are implemented.

[0084] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0085] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM may be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

[0086] The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. The non-relational database may include a distributed database based on blockchain, etc., but is not limited thereto. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but is not limited thereto.

[0087] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0088] This article uses specific examples to illustrate the principles and implementation methods of this application. The description of the above embodiments is only used to help understand the method and core ideas of this application. At the same time, for those skilled in the art, according to the ideas of this application, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting this application.

Claims

1. A method for determining vibration frequency by gradient sampling, characterized in that: The method for determining the vibration frequency by gradient sampling comprises: Multiple sampling frequencies are obtained according to the gradient setting; Under-sampling the vibration signal of the object using a plurality of the sampling frequencies to obtain under-sampling data; Performing frequency estimation on the under-sampled data to obtain a collection waveform frequency; Constructing multiple object vibration frequency equations based on the acquisition waveform frequency and the multiple sampling frequencies; The Chinese remainder theorem is used to calculate the original frequency equations of multiple objects and obtain the vibration frequency.

2. The method for determining vibration frequency by gradient sampling according to claim 1, characterized in that: The multiple sampling frequencies obtained according to the gradient setting are frequencies between 2 Hz and 10 Hz.

3. The method for determining vibration frequency by gradient sampling according to claim 1, characterized in that: Performing frequency estimation on the under-sampled data to obtain the acquisition waveform frequency includes: Determining a periodicity regularity of each data point in the undersampled data; Based on the periodic law, the under-sampled data is subjected to discrete Fourier transform to obtain the acquisition waveform frequency.

4. The method for determining vibration frequency by gradient sampling according to claim 3, characterized in that: The formula for performing discrete Fourier transform on the under-sampled data is: In the formula, x[n] is the undersampled data, e is the natural logarithm, k is the discrete sampling position, j is the imaginary unit, n is the nth data point in the undersampled data, and N is the length of the undersampled data.

5. The method for determining vibration frequency by gradient sampling according to claim 1, characterized in that: Constructing multiple object vibration frequency equations based on the acquisition waveform frequency and the multiple sampling frequencies, including: Taking the collected waveform frequency as the remainder and taking the plurality of sampling frequencies as the dividends respectively, a plurality of object vibration frequency equations are constructed.

6. The method for determining vibration frequency by gradient sampling according to claim 5, characterized in that: The object vibration frequency equation is expressed as: F=n i *f si +f i ; Where F is the vibration frequency, n i is an unknown number, f si is the i-th sampling frequency, f i is the frequency of the acquired waveform.

7. The method for determining vibration frequency by gradient sampling according to claim 6, characterized in that: The Chinese remainder theorem is used to calculate the original frequency equations of multiple objects to obtain the vibration frequencies, including: determining a product of the sampling frequencies; Obtaining an intermediate quantity based on the product of the sampling frequencies and the sampling frequency, and determining an inverse element of the intermediate quantity; The vibration frequency is determined based on the acquired waveform frequency, the intermediate quantity, and an inverse element of the intermediate quantity.

8. A computer device comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the method for determining vibration frequency by gradient sampling according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method for determining vibration frequency by gradient sampling according to any one of claims 1 to 6 is implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the method for determining vibration frequency by gradient sampling according to any one of claims 1 to 6 is implemented.

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