Method, system, medium and equipment for dynamic extraction of blade natural frequency

Abstract

A method, system, medium and device for dynamically extracting blade natural frequency from a single-sensor blade tip timing undersampling signal. In the method, a single blade tip timing sensor is used to obtain a blade vibration signal; a blade resonance region measurement signal X is selected based on the blade vibration signal and prior information; a virtual frequency f is specified based on the blade resonance region measurement signal X and a virtual frequency f is specified based on the blade resonance region measurement signal X and a virtual frequency f is specified based on the blade tip timing undersampling signal. m , generate two sets of virtual signals Y m and Y n ; 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 spectrum P xym With P xyn Do the difference to get the spectrum P mn , extract the spectrum P mn The highest frequency component f in a ; According to the highest frequency component f a The true natural frequency f is calculated by combining the measured signal X in the blade resonance region with the prior information n .

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 the natural frequency of a blade using a single-sensor blade tip timing undersampling 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 have a direct impact on the operating safety and work efficiency of rotating machinery. Therefore, structural health monitoring of rotor blades is of great significance.

[0003] Blade tip timing measurement technology has attracted widespread attention due to its non-contact, minimally invasive, and online monitoring capabilities. The blade natural frequency information contained in the blade tip timing measurement signal can accurately reflect the blade's health, making the extraction of this natural frequency information a key research topic. However, due to the highly undersampled nature of the blade tip timing measurement signal, the signal spectrum is aliased, making it challenging to recover the correct natural frequency from the aliased signal. Furthermore, due to practical installation location limitations, blade tip timing sensors cannot be deployed in an unlimited and unconstrained manner, and the blade tip timing measurement signal itself is non-uniform. While existing blade tip timing signal natural frequency extraction schemes can extract the blade's natural frequency, they require constructing a virtual signal with a frequency range close to the blade's natural frequency. Relying solely on amplitude to extract characteristic frequency components, they cannot overcome the limitations of the highly undersampling, low sample count, and are significantly affected by noise. Therefore, addressing the non-uniformity and undersampling of the blade tip timing signal while simultaneously meeting practical installation location limitations and facilitating the construction of a virtual signal to avoid noise influences remains a pressing issue.

[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 undersampling signal. By arranging a single sensor, the requirements of the actual installation position are met, while overcoming the non-uniformity and undersampling problems of the blade tip timing signal. A virtual signal is constructed by utilizing 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 from a single-sensor blade tip timing undersampling signal includes:

[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 based on the blade resonance region and specify a virtual frequency f m , generate two sets of virtual signals Y m and Y n ;

[0010] Step 4: 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 ;

[0011] Step 5: Convert the spectrum P xym With P xyn Do the difference to get the spectrum P mn , extract the spectrum P mn The highest frequency component f in a ;

[0012] Step 6: According to the highest frequency component f a The true natural frequency f is calculated by combining the measured signal X in the blade resonance region with the prior information n .

[0013] In the method for extracting the blade natural frequency dynamically from the single-sensor blade tip under-sampling 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 from a single-sensor blade tip timing undersampling signal, step 3 includes:

[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 frequency component, which is determined according to the time series t of the measurement 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 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 .

[0022] In the method for dynamically extracting blade natural frequency from a single-sensor blade tip timing undersampling 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 virtual frequency f m , calculate the folding frequency f of the difference between the two 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 f 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 within this frequency range is the real natural frequency component f n .

[0030] In the method for dynamically extracting the blade natural frequency from 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 undersampling 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 the 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 xynDo the difference to get the spectrum P mn , extract the spectrum P mn The highest frequency component f in a ;

[0038] The natural frequency calculation unit is used to calculate the natural frequency according to the highest frequency component f a The true natural frequency f is calculated by combining the measured signal X in the blade resonance region with the prior information n .

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

[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 existing technology, the present invention has the following advantages: the present invention uses a single blade tip timing sensor, overcomes the limitations of actual installation position and layout, utilizes the characteristics of the blade tip timing measurement signal to construct different virtual signals, solves the non-uniformity and high 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] Various other advantages and benefits of the present invention will become apparent to those skilled in the art upon reading the detailed description of the preferred embodiments below. The accompanying drawings are intended only to illustrate preferred embodiments and are not to be construed as limiting the present invention. It should be understood that the drawings described below are merely examples of the present invention, and that those skilled in the art will be able to derive other drawings from these drawings without inventive effort. Throughout the drawings, identical reference numerals are used to denote identical components.

[0045] In the attached figure:

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

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

[0048] Figure 3This is a schematic diagram of a blade resonance region measurement signal, a virtual signal, and a dot product signal based on single-sensor blade tip timing measurement provided by one 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 will be further explained below with reference to the accompanying drawings and embodiments. DETAILED DESCRIPTION

[0051] Specific embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. Although 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. Rather, these embodiments are provided 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 invention. The scope of protection of the present invention shall be as defined in the attached claims.

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

[0054] like Figures 1 to 4 As shown in FIG, the method for dynamically extracting the blade natural frequency from the single-sensor blade tip timing undersampling 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 based on the blade resonance region and specify a virtual frequency f m , generate two sets of virtual signals Ym and Y n ;

[0058] Step 4: 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 ;

[0059] Step 5: Convert the spectrum P xym With P xyn Do the difference to get the spectrum P mn , extract the spectrum P mn The highest frequency component f in a ;

[0060] Step 6: According to the highest frequency component f a The true natural frequency f is calculated by combining the measured signal X in the blade resonance region with the prior information n .

[0061] In a preferred embodiment of the method for dynamically extracting blade natural frequency from 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 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 from a single-sensor blade tip timing undersampling signal, step 3 includes:

[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 frequency component, which is determined according to the time series t of the measurement 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 from a single-sensor blade tip timing undersampling 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 virtual frequency f m , calculate the folding frequency f of the difference between the two 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 f 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 within this frequency range is the real natural frequency component f n .

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

[0079] In a preferred embodiment of the method for dynamically extracting blade natural frequency from a single-sensor blade tip timing undersampling 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 the 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 Do the difference to get the spectrum P mn , extract the spectrum P mn The highest frequency component f in a ;

[0086] The natural frequency calculation unit is used to calculate the natural frequency according to the highest frequency component fa The true natural frequency f is calculated by combining the measured signal X in the blade resonance region with the prior information n .

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

[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: Based on the measured signal in the blade resonance region, select a virtual frequency of 214 Hz to generate virtual signals Y1 and Y2. 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 found to be 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 As shown. 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 n temp : 317.3765Hz and 396.7206Hz, 317.3765Hz is retained as the true blade natural frequency based on prior information.

[0104] The above method can restore the true natural frequency components of the aliased blades. The true blade natural frequency is used to determine whether there are blade faults and implement blade condition monitoring. For example, if the blade natural frequency increases, it may indicate a blade failure such as a broken blade.

[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 have been described above with reference to the accompanying drawings, the present invention is not limited to the above-mentioned specific embodiments and application fields. The above-mentioned specific embodiments are merely illustrative and instructive, and are not restrictive. A person skilled in the art, guided by this specification and without departing from the scope of protection of the claims of the present invention, may also devise various forms, all of which fall within the scope of 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 based on the blade resonance region and specify a virtual frequency f m , generate two sets of virtual signals Y m and Y n ; Step 4: 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 ; Step 5: Convert the spectrum P xym With P xyn Do the difference to get the spectrum P mn , extract the spectrum P mn The highest frequency component f in a ; Step 6: According to the highest frequency component f a The true natural frequency f is calculated by combining the measured signal X in the blade resonance region with the prior information n ; Wherein, 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 frequency component, which is determined according to the time series t of the measurement 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 ; 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 virtual frequency f m , calculate the folding frequency f of the difference between the two 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 f 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 within this frequency range is 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: In step 2, the prior information is the critical speed of the blade, that is, the natural frequency range of the blade, which is recorded 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, characterized in that: 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 .

4. 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.

5. The method for dynamically extracting blade natural frequency from a single-sensor blade tip timing undersampling signal according to claim 4, characterized in that: Rotating machines include turbines.

6. A blade natural frequency dynamic extraction system, the system is used to execute the method according to any one of claims 1 to 5, 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 the 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 Do the difference to get the spectrum P mn , extract the spectrum P mn The highest frequency component f in a ; The natural frequency calculation unit is used to calculate the natural frequency according to the highest frequency component f a The true natural frequency f is calculated by combining the measured signal X in the blade resonance region with the prior information n .

7. A computer storage medium, characterized in that The storage medium includes computer instructions, which, when executed on a computer, enable the computer to perform the method according to any one of claims 1 to 5.

8. 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 5 is implemented.

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