Blade inherent frequency dynamic extraction method, system, medium and equipment

Abstract

The invention discloses a blade inherent frequency dynamic extraction method, system, medium and equipment for a single-sensing blade tip timing undersampled signal, and the method comprises the steps: employing a single blade tip timing sensor to obtain a blade vibration signal; selecting a blade resonance area measurement signal X according to the blade vibration signal and prior information; generating two groups of virtual signals Ym and Yn according to a blade resonance area measurement signal X and a specified virtual frequency fm; the virtual signals Ym and Yn are subjected to point multiplication with a blade resonance area measurement signal X to obtain point multiplication signals Sxym and Sxyn, and the point multiplication signals Sxym and Sxyn are processed to obtain corresponding frequency spectrums Pxym and Pxyn; the frequency spectrum Pxym and the frequency spectrum Pxyn are subtracted to obtain a frequency spectrum Pmn, and the highest frequency component fa in the frequency spectrum Pmn is extracted; according to the highest frequency component fa and the blade resonance area measurement signal X, the real inherent frequency fn is calculated in combination with prior information.

Description

Technical Field

[0001] The present invention relates to the technical field of rotating machinery vibration testing, and in particular to a method, system, medium and equipment for dynamically extracting blade natural frequency of a single-sensor blade tip timing under-sampling signal. Background Art

[0002] Rotor blades are one of the core components of rotating machinery. They are subjected to high temperature, high pressure and complex loads. They work in harsh conditions and are prone to cracks, friction and other faults, which in turn have a direct impact on the operating safety and work efficiency of rotating machinery. Therefore, it is of great significance to carry out structural health monitoring of rotor blades.

[0003] The blade tip timing measurement technology has been widely valued because of its non-contact, low-intervention and online monitoring characteristics. The blade natural frequency information contained in the blade tip timing measurement signal can accurately reflect the health status of the blade itself. Therefore, how to extract the natural frequency information has become the focus of research. However, due to the characteristics of highly under-sampling of the blade tip timing measurement signal, the signal spectrum is aliased, and how to recover the correct natural frequency from the aliased signal becomes a problem. In addition, due to the limitations of the actual installation position, the blade tip timing sensor cannot be arranged without restrictions and constraints, and the blade tip timing measurement signal itself is non-uniform. Although the blade tip timing signal natural frequency extraction scheme in the prior art can extract the natural frequency of the blade, the frequency range of the virtual signal to be constructed is close to the natural frequency of the blade. When extracting the characteristic frequency components, it only relies on the amplitude, which cannot overcome the limitation of few samples under highly under-sampling and is greatly affected by noise. Therefore, how to solve the problems of non-uniformity and under-sampling of blade tip timing signals, while meeting the limitations of the actual installation position and facilitating the construction of virtual signals to avoid noise influence is a problem that needs to be solved.

[0004] 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 to a person of ordinary skill in the art. Summary of the invention

[0005] The present invention provides a method, system, medium and equipment for dynamically extracting the blade natural frequency of a single-sensor blade tip timing under-sampling signal. The method meets the requirements of the actual installation position by arranging a single sensor, while overcoming the non-uniformity and under-sampling problems of the blade tip timing signal. A virtual signal is constructed using the characteristics of the blade tip timing signal, thereby achieving accurate extraction of the blade natural frequency.

[0006] A method for dynamically extracting blade natural frequency of a single-sensor blade tip timing undersampling signal comprises:

[0007] Step 1: Use a single blade tip timing sensor to obtain blade vibration signals;

[0008] Step 2: Select the blade resonance region measurement signal X={x(t1), x(t2),…, x(t n )};

[0009] Step 3: Measure the signal X and assign a virtual frequency f based on the blade resonance region m , generate two sets of virtual signals Y m and Y n ;

[0010] Step 4: Set the virtual signal Y m and Y n The dot product signal S is obtained by multiplying the measured signal X in the blade resonance area respectively. xym and S xyn , the point product signal S xym and S xyn Process them separately to get the corresponding spectrum P xym and P xyn ;

[0011] Step 5: Convert the spectrum P xym With P xyn The spectrum P is obtained by subtracting mn , extract the spectrum P mn The highest frequency component f a ;

[0012] Step 6: According to the highest frequency component f a and the blade resonance region measurement signal X, combined with prior information to calculate the true natural frequency f n .

[0013] In the method for dynamically extracting the blade natural frequency of a single-sensor blade tip timing undersampling signal, in step 2, the prior information is the critical speed of the blade, that is, the blade natural frequency range, which is denoted as f prior =[f p1 , f p2 ], where f p1 and f p2 Represent the upper and lower limits of the blade’s natural frequency range, f p1 Less than f p2 .

[0014] In the method for dynamically extracting blade natural frequency of a single-sensor blade tip timing under-sampling signal, step 3 comprises:

[0015] Step 3.1: Choose an arbitrary virtual frequency f 1m Determine the amplitude A of the natural frequency component 1m and phase φ 1m , frequency conversion component amplitude A rm and phase φ rmAccording to the following formula and the time series of the blade resonance region measurement signal X, t={t1, t2, ..., t n}Generate a set of virtual signals Y m ;

[0016]

[0017] Among them, f rm represents the frequency of the rotational component, which is determined according to the time series t of the measured signal X in the blade resonance region;

[0018] Step 3.2: According to the virtual signal Y m , construct another set of virtual signals Y n , the expression is as follows:

[0019]

[0020] Among them A 1n =A 1m ,f 1n =f 1m ,φ 1m =φ 1n .

[0021] In the blade natural frequency dynamic extraction method of a single-sensor blade tip timing under-sampling signal, in step 4, the dot product signal S xym and S xyn Perform discrete Fourier transform to obtain the spectrum P xym and P xyn .

[0022] In the method for dynamically extracting blade natural frequency of a single-sensor blade tip timing under-sampling signal, step 6 includes:

[0023] Step 6.1: Calculate possible blade natural frequencies f n temp :

[0024] ,

[0025] Where K is a coefficient, which takes values ​​in the range of positive integers, and f rm is the frequency of the conversion component;

[0026] Step 6.2: Based on the possible blade natural frequency f n temp and the virtual frequency f m , the folding frequency f of the difference between the two is calculated according to the following formula mnc

[0027] ,

[0028] Step 6.3: Determine the folding frequency f mnc Is it spectrum P? xym The five frequency components with the largest amplitudes determine the time f calculated in step 6.1. n temp The correct formula to use is Still ,

[0029] Step 6.4: Based on the prior information f prior =[f p1 ,f p2 ], select f n temp The frequency in this frequency range is the real natural frequency component f a .

[0030] In the method for dynamically extracting the blade natural frequency of a single-sensor blade tip timing under-sampling signal, the blade is a rotor blade of a rotating machine.

[0031] In the method for dynamically extracting blade natural frequency from a single-sensor blade tip timing under-sampling signal, the rotating machinery includes a turbine.

[0032] A blade natural frequency dynamic extraction system includes:

[0033] A blade tip timing sensor, which is used to obtain blade vibration signals;

[0034] The blade resonance region measurement unit is used to select a blade resonance region measurement signal X={x(t1), x(t2),…, x(t n )};

[0035] A virtual signal generating unit is used to measure the signal X in the blade resonance region and specify a virtual frequency f m , generate two sets of virtual signals Y m and Y n ;

[0036] The spectrum calculation unit is used to convert the virtual signal Y m and Y n The dot product signal S is obtained by multiplying the measured signal X in the blade resonance area respectively. xym and S xyn , the point product signal S xym and S xyn Process them separately to get the corresponding spectrum P xym and P xyn ;

[0037] The frequency component generating unit is used to convert the spectrum P xym With P xynThe spectrum P is obtained by subtracting mn , extract the spectrum P mn The highest frequency component f a ;

[0038] The natural frequency calculation unit is used to calculate the maximum frequency component f a and the blade resonance region measurement signal X, combined with prior information to calculate the true natural frequency f n .

[0039] A computer storage medium includes computer instructions, which, when executed on a computer, cause the computer to execute the method described.

[0040] An electronic device, comprising:

[0041] A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein:

[0042] When the processor executes the program, the method described is implemented.

[0043] Compared with the prior art, the present invention has the following advantages: the present invention uses a single blade tip timing sensor, overcomes the limitations of the actual installation position and layout, utilizes the characteristics of the blade tip timing measurement signal to construct different virtual signals, solves the non-uniform and highly undersampling problems of the blade tip timing measurement signal, and can quickly and accurately extract the natural frequency of the rotating blade from the aliased spectrum. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] By reading the detailed description of the preferred specific embodiments below, various other advantages and benefits of the present invention will become clear to those of ordinary skill in the art. The drawings in the specification are only for the purpose of illustrating the preferred embodiments and are not considered to be limitations of the present invention. Obviously, the drawings described below are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can also be obtained based on these drawings without creative work. Moreover, the same reference numerals are used to represent the same components throughout the drawings.

[0045] In the attached picture:

[0046] Figure 1 It is a flowchart of a method for dynamically extracting blade natural frequency of a single-sensor blade tip timing under-sampling signal provided by an embodiment of the present disclosure;

[0047] Figure 2 It is a schematic diagram of a measurement signal of a selected blade resonance region based on a single sensor blade tip timing measurement provided by an embodiment of the present disclosure;

[0048] Figure 3It is a schematic diagram of a blade resonance region measurement signal, a virtual signal, and a dot product signal based on a single sensor blade tip timing measurement provided by an embodiment of the present disclosure;

[0049] Figure 4 A schematic diagram of two dot product signal spectra and corresponding difference frequencies based on single sensor blade tip timing measurement provided by an embodiment of the present disclosure.

[0050] The present invention is further explained below in conjunction with the accompanying drawings and embodiments. DETAILED DESCRIPTION

[0051] The specific embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. Although the specific embodiments of the present invention are shown in the accompanying drawings, it should be understood that the present invention can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided in order to enable a more thorough understanding of the present invention and to fully convey the scope of the present invention to those skilled in the art.

[0052] It should be noted that certain words are used in the specification and claims to refer to specific components. Those skilled in the art should understand that technicians may use different nouns to refer to the same component. This specification and claims do not use the difference in nouns as a way to distinguish components, but use the difference in the functions of the components as the criterion for distinction. As mentioned throughout the specification and claims, "including" or "comprising" is an open term, so it should be interpreted as "including but not limited to". The subsequent description of the specification is a preferred embodiment of the present invention, but the description is based on the general principles of the specification and is not intended to limit the scope of the present invention. The scope of protection of the present invention shall be determined by the attached claims.

[0053] To facilitate understanding of the embodiments of the present invention, further explanation will be given below by taking specific embodiments as examples in conjunction with the accompanying drawings, and each of the accompanying drawings does not constitute a limitation on the embodiments of the present invention.

[0054] like Figures 1 to 4 As shown, the blade natural frequency dynamic extraction method of the single-sensor blade tip timing under-sampling signal includes the following steps:

[0055] Step 1: Use a single blade tip timing sensor to obtain blade vibration signals;

[0056] Step 2: Select the blade resonance region measurement signal X={x(t1), x(t2),…, x(t n )};

[0057] Step 3: Measure the signal X and assign a virtual frequency f based on the blade resonance region m , generate two sets of virtual signals Ym and Y n ;

[0058] Step 4: Set the virtual signal Y m and Y n The dot product signal S is obtained by multiplying the measured signal X in the blade resonance area respectively. xym and S xyn , the point product signal S xym and S xyn Process them separately to get the corresponding spectrum P xym and P xyn ;

[0059] Step 5: Convert the spectrum P xym With P xyn The spectrum P is obtained by subtracting mn , extract the spectrum P mn The highest frequency component f a ;

[0060] Step 6: According to the highest frequency component f a and the blade resonance region measurement signal X, combined with prior information to calculate the true natural frequency f n .

[0061] In a preferred embodiment of the method for dynamically extracting the blade natural frequency of a single-sensor blade tip timing undersampling signal, in step 2, the prior information is the critical speed of the blade, that is, the blade natural frequency range, which is denoted by f prior =[f p1 ,f p2 ], where f p1 and f p2 They represent the prior information, namely the upper and lower bounds of the blade’s natural frequency range, f p1 Less than f p2 .

[0062] In a preferred embodiment of the method for dynamically extracting blade natural frequency of a single-sensor blade tip timing under-sampling signal, step 3 comprises:

[0063] Step 3.1: Choose an arbitrary virtual frequency f m Determine the amplitude A of the natural frequency component 1m and phase φ 1m , frequency conversion component amplitude A rm and phase φ rm According to the following formula and the time series of the blade resonance region measurement signal X, t={t1, t2, ..., t n}Generate a set of virtual signals Y m ;

[0064]

[0065] Among them, f rm represents the frequency of the rotational component, which is determined according to the time series t of the measured signal X in the blade resonance region;

[0066] Step 3.2: According to the virtual signal Y m , construct another set of virtual signals Y n , the expression is as follows:

[0067]

[0068] Among them A 1n =A 1m ,f 1n =f 1m ,φ 1m =φ 1n .

[0069] In a preferred embodiment of the blade natural frequency dynamic extraction method of a single-sensor blade tip timing undersampling signal, in step 4, the dot product signal S xym and S xyn Perform discrete Fourier transform to obtain the spectrum P xym and P xyn .

[0070] In a preferred embodiment of the method for dynamically extracting blade natural frequency of a single-sensor blade tip timing under-sampling signal, step 6 includes:

[0071] Step 6.1: Calculate possible blade natural frequencies f n temp :

[0072] ,

[0073] Where K is a coefficient, which takes values ​​in the range of positive integers, and f rm is the frequency of the conversion component;

[0074] Step 6.2: Based on the possible blade natural frequency f n temp and the virtual frequency f m , the folding frequency f of the difference between the two is calculated according to the following formula mnc

[0075] ,

[0076] Step 6.3: Determine the folding frequency f mnc Is it spectrum P? xym The five frequency components with the largest amplitudes determine the time f calculated in step 6.1. n temp The correct formula to use is still ,

[0077] Step 6.4: Based on the prior information f prior =[f p1 ,f p2 ], select f n temp The frequency in this frequency range is the real natural frequency component f a .

[0078] In a preferred implementation of the method for dynamically extracting the blade natural frequency of a single-sensor blade tip timing under-sampling signal, the blade is a rotor blade of a rotating machine.

[0079] In a preferred implementation of the method for dynamically extracting blade natural frequency from a single-sensor blade tip timing under-sampling signal, the rotating machinery includes a turbine.

[0080] A blade natural frequency dynamic extraction system includes:

[0081] A blade tip timing sensor, which is used to obtain blade vibration signals;

[0082] The blade resonance region measurement unit is used to select a blade resonance region measurement signal X={x(t1), x(t2),…, x(t n )};

[0083] A virtual signal generating unit is used to measure the signal X in the blade resonance region and specify a virtual frequency f m , generate two sets of virtual signals Y m and Y n ;

[0084] The spectrum calculation unit is used to convert the virtual signal Y m and Y n The dot product signal S is obtained by multiplying the measured signal X in the blade resonance area respectively. xym and S xyn , the point product signal S xym and S xyn Process them separately to get the corresponding spectrum P xym and P xyn ;

[0085] The frequency component generating unit is used to convert the spectrum P xym With P xyn The spectrum P is obtained by subtracting mn , extract the spectrum P mn The highest frequency component f a ;

[0086] The natural frequency calculation unit is used to calculate the maximum frequency component fa and the blade resonance region measurement signal X, combined with prior information to calculate the true natural frequency f n .

[0087] A computer storage medium includes computer instructions, which, when executed on a computer, cause the computer to execute the method described.

[0088] An electronic device, comprising:

[0089] A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein:

[0090] When the processor executes the program, the method described is implemented.

[0091] In one embodiment, a method for dynamically extracting blade natural frequency from a single-sensor blade tip timing undersampling signal comprises the following steps:

[0092] Step 1: Use a single sensor to obtain blade vibration signals;

[0093] Step 2: Select the blade resonance region measurement signal X={x(t1), x(t2),…, x(t n )},like Figure 2 As shown. Given the prior information f prior =[300,350] Hz;

[0094] Step 3: According to the measured signal of the blade resonance area, select the virtual frequency 214Hz to generate virtual signal Y1 and virtual signal Y2, where the virtual signal Y1 is generated using the following formula:

[0095]

[0096] The virtual signal Y2 is generated using the following formula

[0097]

[0098] where f rm According to the measured signal X, it can be known that it is 79.3441Hz, and t is consistent with the sampling time of the measured signal X. The generated virtual signal is as follows Figure 3 shown.

[0099] Step 4: Obtain the dot product signal S based on the virtual signals Y1 and Y2 and the blade resonance region measurement signal X xy1 and S xy2 ,like Figure 3 As shown; the point product signal S xy1 and S xy2Perform discrete Fourier transform respectively to obtain the corresponding spectrum P xy1 and P xy2 ,like Figure 4 shown.

[0100] Step 5: Convert the spectrum P xy1 and P xy2 Do the difference and get the difference frequency spectrum P 12 ,like Figure 4 Extract P 12 The highest frequency component 0Hz is denoted as f a ;

[0101] Step 6: Solve the virtual blade natural frequency f according to the following n temp :

[0102]

[0103] The value of K is 4 according to the prior information, and two f are calculated. n temp : 317.3765Hz and 396.7206Hz, and 317.3765Hz is retained as the true blade natural frequency based on prior information.

[0104] The above method can be used to restore the aliased true natural frequency component. The true blade natural frequency is used to determine whether the blade has a fault and to monitor the blade status. For example, if the blade natural frequency increases, there may be a blade failure such as falling off.

[0105] The present invention reduces the number of sensors to a minimum by using a blade tip timing sensor, overcomes the signal non-uniformity problem and the limitations of sensor layout and installation, can directly use discrete Fourier transform to process the signal, and at the same time solves the frequency aliasing problem caused by undersampling and extracts the natural frequency of the blade.

[0106] Although the embodiments of the present invention are described above in conjunction with the accompanying drawings, the present invention is not limited to the above specific embodiments and application fields, and the above specific embodiments are only illustrative and instructive, rather than restrictive. A person of ordinary skill in the art can also make many forms under the guidance of this specification and without departing from the scope of protection of the claims of the present invention, all of which belong to the protection of the present invention.

Claims

1. A method for dynamically extracting blade natural frequency from a single-sensor blade tip timing undersampling signal, characterized in that: The steps include: Step 1: Use a single blade tip timing sensor to obtain blade vibration signals; Step 2: Select the blade resonance region measurement signal X={x(t1), x(t2),…, x(t n )}; Step 3: Measure the signal X and assign a virtual frequency f based on the blade resonance region m , generate two sets of virtual signals Y m and Y n ; Step 4: Set the virtual signal Y m and Y n The dot product signal S is obtained by multiplying the measured signal X in the blade resonance area respectively. xym and S xyn , the point product signal S xym and S xyn Process them separately to get the corresponding spectrum P xym and P xyn ; Step 5: Convert the spectrum P xym With P xyn The spectrum P is obtained by subtracting mn , extract the spectrum P mn The highest frequency component f a ; Step 6: According to the highest frequency component f a and the blade resonance region measurement signal X, combined with prior information to calculate the true natural frequency f n .

2. The method for dynamically extracting blade natural frequency from a single-sensor blade tip timing undersampling signal according to claim 1 is characterized in that: Preferably, in step 2, the prior information is the critical speed of the blade, that is, the natural frequency range of the blade, which is denoted as f prior =[f p1 ,f p2 ], where f p1 and f p2 Represent the upper and lower limits of the blade’s natural frequency range, f p1 Less than f p2 .

3. The method for dynamically extracting blade natural frequency from a single-sensor blade tip timing undersampling signal according to claim 1 is characterized in that: Step 3 includes: Step 3.1: Choose an arbitrary virtual frequency f 1m Determine the amplitude A of the natural frequency component 1m and phase φ 1m , frequency conversion component amplitude A rm and phase φ rm According to the following formula and the time series of the blade resonance region measurement signal X, t={t1, t2, ..., t n }Generate a set of virtual signals Y m ; , Among them, f rm represents the frequency of the rotational component, which is determined according to the time series t of the measured signal X in the blade resonance region; Step 3.2: According to the virtual signal Y m , construct another set of virtual signals Y n , the expression is as follows: , among them A 1n =A 1m ,f 1n =f 1m ,f 1m =φ 1n 。 4. The method for dynamically extracting blade natural frequency from a single-sensor blade tip timing undersampling signal according to claim 1 is characterized in that: In step 4, the point product signal S xym and S xyn Perform discrete Fourier transform to obtain the spectrum P xym and P xyn .

5. The method for dynamically extracting blade natural frequency from a single-sensor blade tip timing undersampling signal according to claim 1, characterized in that: Step 6 includes, Step 6.1: Calculate possible blade natural frequencies f n temp : ， Where K is a coefficient, which takes values ​​in the range of positive integers, and f rm is the frequency of the conversion component; Step 6.2: Based on the possible blade natural frequency f n temp and the virtual frequency f m , the folding frequency f of the difference between the two is calculated according to the following formula mnc ， Step 6.3: Determine the folding frequency f mnc Is it spectrum P? xym The five frequency components with the largest amplitudes determine the time f calculated in step 6.

1. n temp The correct formula to use is still , Step 6.4: Based on the prior information f prior =[f p1 ,f p2 ], select f n temp The frequency in this frequency range is the real natural frequency component f a .

6. The method for dynamically extracting blade natural frequency from a single-sensor blade tip timing undersampling signal according to claim 1, characterized in that: The blades are rotor blades of a rotating machine.

7. The method for dynamically extracting blade natural frequency from a single-sensor blade tip timing under-sampling signal according to claim 6 is characterized in that: Rotating machines include turbines.

8. A blade natural frequency dynamic extraction system, characterized in that: These include, A blade tip timing sensor, which is used to obtain blade vibration signals; The blade resonance region measurement unit is used to select a blade resonance region measurement signal X={x(t1), x(t2),…, x(t n )}; A virtual signal generating unit is used to measure the signal X in the blade resonance region and specify a virtual frequency f m , generate two sets of virtual signals Y m and Y n ; The spectrum calculation unit is used to convert the virtual signal Y m and Y n The dot product signal S is obtained by multiplying the measured signal X in the blade resonance area respectively. xym and S xyn , the point product signal S xym and S xyn Process them separately to get the corresponding spectrum P xym and P xyn ; The frequency component generating unit is used to convert the spectrum P xym With P xyn The spectrum P is obtained by subtracting mn , extract the spectrum P mn The highest frequency component f a ; The natural frequency calculation unit is used to calculate the maximum frequency component f a and the blade resonance region measurement signal X, combined with prior information to calculate the true natural frequency f n .

9. A computer storage medium, characterized in that: The storage medium includes computer instructions, which, when executed on a computer, enable the computer to execute the method according to any one of claims 1 to 7.

10. An electronic device, characterized in that: The electronic device comprises: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the method according to any one of claims 1 to 7 is implemented.

Images