Aerodynamic gas compressor near-stall condition acoustic monitoring method, system, medium and equipment

Abstract

The invention discloses an acoustic monitoring method, system, medium and equipment for the near stall condition of an aircraft compressor, and the method comprises the steps: carrying out the synchronous collection of sound pressure time domain signals of multiple channels of an aviation compression system; adding a rectangular window to the multi-channel sound pressure time-domain signal, and constructing an acoustic time-domain signal segment to monitor the current operation state of the aviation compression system; performing fast Fourier transform on the multichannel acoustic time domain signal segment in the current time domain window to form a plurality of sound pressure frequency spectrums, judging whether a plurality of single-tone characteristic frequencies which are non-integer multiples of the current rotation frequency exist in the sound pressure frequency spectrums or not, and constructing an orthogonal Fourier transfer matrix based on the installation position and the highest circumferential modal order, and judging whether the order difference of the characteristic acoustic mode under each characteristic frequency is the rotation frequency multiple difference of the corresponding characteristic frequency, calculating the acoustic mode amplitude corresponding to each broadband frequency component, drawing an acoustic mode spectrogram, and judging whether a mode bright band exists at the cut-off frequency boundary in the acoustic mode spectrogram.

Description

Technical Field

[0001] The present invention relates to the technical field of aircraft engine compression system state monitoring, and in particular to an aircraft engine compressor near-stall condition acoustic monitoring method, system, medium and equipment. Background Art

[0002] The intense pressurization of viscous gas flows within aircraft engine compression systems creates aerodynamic instability, manifesting as rotating stall and compression system surge. When an engine enters an aerodynamically unstable operating state, it can degrade performance, increase vibration stress on the compression component's rotor blades, increase thermal loads and stresses on the turbine, reduce the stable operating range of the combustion chamber, and even damage the engine's structural integrity, posing a serious threat to flight safety.

[0003] To ensure that the compression system's operating point remains within the stable operating range throughout the full flight envelope, engine design and operation typically require a stability margin between the compressor operating point and the stability boundary, balancing compressor efficiency and stability. When the compression system operates near stall, precursor anomalies often occur, such as rotational instability, flow-induced vibration, and acoustic resonance. Monitoring and diagnosing the precursor anomalies exhibited during near-stall conditions is crucial for designing the available stability margin and controlling aerodynamic stability in aircraft engine compression systems.

[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 acoustic monitoring of near-stall conditions on an aero-engine compressor. By placing a circular microphone array at the compression system's air inlet, and employing a spectrum analysis module and acoustic modal decomposition module to measure the acoustic array's test signal, the method transforms the acoustic signal from the time domain to the wavenumber domain, acquiring the acoustic modal characteristics of the acoustic test signal in both the frequency and wavenumber domains. This method, for the first time, achieves a more effective method for identifying near-stall conditions through acoustic measurement. This method utilizes a more responsive, non-invasive acoustic monitoring method, addressing the difficulty of achieving dynamic, sensitive feedback when monitoring near-stall conditions using traditional static pressure sensors.

[0006] An acoustic monitoring method for an aero-engine compressor near-stall condition includes:

[0007] In the first step, according to the number of rotor blades in the first stage of the aviation compression system Number of stator blades Determine the highest circumferential modal order and the number of measuring points , evenly select a predetermined number of circumferential installation positions and angles to install microphone sensors at the entrance of the aviation compression system to form a microphone array, and synchronously collect multi-channel sound pressure time domain signals of the aviation compression system;

[0008] In the second step, a rectangular window is added to the multi-channel sound pressure time domain signal to construct an acoustic time domain signal segment to monitor the current operating status of the aviation compression system;

[0009] In the third step, a fast Fourier transform is performed on the multi-channel acoustic time domain signal segment in the current time domain window to form multiple sound pressure spectra, and it is determined whether there are multiple single-tone characteristic frequencies that are non-integer multiples of the current frequency shift in the sound pressure spectrum. If not, the aviation compression system is in a normal working state, and the second step (S2) is repeated. If so, the fourth step is entered;

[0010] In the fourth step, based on the installation position and the highest circumferential modal order Construct an orthogonal Fourier transfer matrix, perform spatial Fourier transform on each eigenfrequency, obtain the order of the eigenmode corresponding to each eigenfrequency, and determine whether the order difference of the eigenmode at each eigenfrequency is the frequency multiple difference of the corresponding eigenfrequency. If the order difference is not equal to the frequency multiple difference, the aviation compression system is in normal working condition, and repeat the second step. If so, proceed to the fifth step.

[0011] In the fifth step, the acoustic modal amplitude corresponding to each broadband frequency component is calculated, and the acoustic modal spectrum is plotted to determine whether a modal bright band exists at the cutoff frequency boundary in the acoustic modal spectrum. If not, the aviation compression system is in normal working condition, and the second step is repeated. If present, the aviation compression system is in a near-stall condition.

[0012] In the acoustic monitoring method for near-stall conditions of an aero-engine compressor, the first step includes:

[0013] Step S101, calculate the highest circumferential modal order , where the modal order of the circumferential acoustic mode is , represents the pressure pulsation order caused by the unsteady aerodynamic force caused by the fan's rotation-stationary interference. Represents a non-negative integer, determining the highest circumferential modal order , determine the measurable number as the modal range is ;

[0014] Step S102: Calculate the number of microphones required and installation location, Nyquist-Shannon sampling, number of microphones and the highest circumferential modal order The relationship is, , microphone sensors are evenly installed on the casing wall in the circumferential direction, and the spacing between the microphone sensors is , installation angle ,in 、 、 , and so on.

[0015] In the acoustic monitoring method for near-stall condition of an aero-engine compressor, in the second step, the window length of the acoustic time domain signal segment is determined based on the sampling frequency, and a rectangular window is added to the multi-channel sound pressure time domain signal, and the window length is and , is any integer, is the sampling frequency of the microphone sensor; and every Add windows to multi-channel signals, and the overlap length of each window .

[0016] In the method for acoustic monitoring of near-stall conditions of an aero-engine compressor, the third step includes:

[0017] Step S301: Let the current acoustic time domain signal segment number be , for N evenly distributed microphones in the first The sound pressure signal measured by each acoustic time domain signal segment is subjected to fast Fourier transform: ,in, It represents the current time domain signal fragment matrix of the sound pressure signal measured by the uniformly distributed microphone array. The dimension of the current time domain signal fragment matrix is , represents the discrete Fourier transform, For multi-channel arrays The frequency domain matrix of the time domain signal segments has the dimension , , which is expressed as follows:

[0018]

[0019] in ,

[0020] Step S302: Based on the obtained frequency domain matrix , draw the sound pressure spectrum measured by sensors at different positions, and observe whether there are multiple non-integer order abnormal single-tone peak frequencies other than integer multiples of the rotation frequency. , The blade rotation frequency, if it does not exist, repeat the second step, if it exists, go to the fourth step.

[0021] In the method for acoustic monitoring of an aero-engine compressor near-stall condition, the fourth step includes:

[0022] Step S401: Construct an orthogonal Fourier perception matrix ,

[0023]

[0024] in ,

[0025] Step S402: Select abnormal single-tone peak frequency , take the frequency domain observation vector at this frequency ,in Represents the transpose of a matrix or vector and calculates the peak frequency of an abnormal single tone The modal vector at ,

[0026]

[0027] Take the modal vector The maximum component in the equation determines its corresponding modal order. ,

[0028] Step S403: The remaining abnormal single-tone peak frequencies in the frequency domain are Repeat step S402 to determine the corresponding modal order , determine whether the peak frequencies of multiple abnormal single tones have the following numerical relationship:

[0029] If it does not exist, repeat the second step. If it does exist, go to the fifth step.

[0030] In the method for acoustic monitoring of an aero-engine compressor near-stall condition, the fifth step includes:

[0031] Step S501: Calculate the modal matrix ,in

[0032] ,

[0033] Step S502: Draw an acoustic modal spectrum diagram based on the calculated modal matrix, where the horizontal axis of the spectrum diagram represents the frequency analysis range, the vertical axis represents the range of the acoustic mode of interest, and the depth of the color represents the amplitude. The darker the color, the larger the amplitude. Observe whether there is a tilted bright band component near the cutoff frequency. If not, return to the second step; if so, determine whether the aviation compression system is at time The working state point is near stall.

[0034] In the acoustic monitoring method for near-stall conditions of an aero-engine compressor, the aviation compression system includes rotor blades and a turbine.

[0035] A monitoring system for implementing the method includes:

[0036] The sound field measurement module includes a sound array measurement submodule and a data acquisition system submodule, and is used to measure the sound field information transmitted from the compression system pipeline to the sound array installation location;

[0037] The spectrum analysis module is used to transform the time domain sound field signal at the acoustic array position into the frequency domain to detect whether there are abnormal frequencies other than the blade passing frequency and rotation frequency.

[0038] The acoustic modal decomposition module is used to perform single-tone acoustic mode decomposition and continuous broadband acoustic mode decomposition, transform the sound field information from the frequency domain to the wavenumber domain, and determine whether the compression system is operating near the stall point based on the acoustic modal spectrogram.

[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 utilizes acoustic information to monitor the near-stall point of the compression system, which is more sensitive and adaptable than traditional interstage static pressure monitoring. The acoustic signal's near-stall point characteristics in the frequency domain are obtained through fast Fourier transform, with distinct characteristics and a simple process. The acoustic modal characteristics of the compressor near-stall point in the wavenumber domain are obtained through spatial Fourier transform, with high sensitivity and adaptability to different speeds. Abnormal components in the acoustic signal's spectrum, acoustic modal spectrogram, and wave spectrogram are defined as the acoustic modal characteristics of the compression system near-stall point, thereby improving monitoring accuracy. 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 is a flow chart of the present disclosure;

[0047] Figure 2 1 is a schematic diagram of a method and device for monitoring a near-stall condition of a compression system based on acoustic modes, provided by one embodiment of the present disclosure;

[0048] Figure 3 This is a spectrum diagram of a sound pressure signal at a near-stall operating condition provided by an embodiment of the present disclosure;

[0049] Figure 4(a) to Figure 4(c) An embodiment of the present disclosure provides Figure 3 Schematic diagram of the results of acoustic modal decomposition at each characteristic frequency; among them, Figure 4(a) is a schematic diagram of the results of acoustic modal decomposition at 14.1EO, Figure 4(b) is a schematic diagram of the results of acoustic modal decomposition at 15.1EO, and Figure 4(c) is a schematic diagram of the results of acoustic modal decomposition at 17.1EO;

[0050] Figure 5 This is a near-stall point acoustic modal spectrum diagram of a compression system provided by an embodiment of the present disclosure.

[0051] The present invention will be further explained below with reference to the accompanying drawings and embodiments. DETAILED DESCRIPTION

[0052] 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.

[0053] 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.

[0054] 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.

[0055] like Figures 1 to 5 As shown, the acoustic monitoring method for an aero-engine compressor near-stall condition includes the following steps:

[0056] In the first step S1, according to the number of rotor blades of the previous stage of the aviation compression system Number of stator blades Determine the highest circumferential modal order and the number of measuring points , evenly select a predetermined number of circumferential installation positions and angles to install microphone sensors at the entrance of the aviation compression system to form a microphone array, and synchronously collect multi-channel sound pressure time domain signals of the aviation compression system;

[0057] In the second step S2, a rectangular window is added to the multi-channel sound pressure time domain signal to construct an acoustic time domain signal segment to monitor the current operating status of the aviation compression system;

[0058] In the third step S3, a fast Fourier transform is performed on the multi-channel acoustic time domain signal segment in the current time domain window to form multiple sound pressure spectra, and it is determined whether there are multiple single-tone characteristic frequencies that are non-integer multiples of the current frequency in the sound pressure spectrum. If not, the aviation compression system is in normal working condition, and the second step S2 is repeated. If so, the process proceeds to the fourth step S4.

[0059] In the fourth step S4, based on the installation position and the highest circumferential modal order Construct an orthogonal Fourier transfer matrix, perform spatial Fourier transform on each characteristic frequency, obtain the order of the characteristic acoustic mode corresponding to each characteristic frequency, and determine whether the order difference of the characteristic acoustic mode at each characteristic frequency is the frequency multiple difference of the corresponding characteristic frequency. If the order difference is not equal to the frequency multiple difference, the aviation compression system is in normal working condition, and repeat the second step S2. If so, proceed to the fifth step S5.

[0060] In the fifth step S5, the acoustic modal amplitude corresponding to each broadband frequency component is calculated, and an acoustic modal spectrum is plotted to determine whether a modal bright band exists at the cutoff frequency boundary in the acoustic modal spectrum. If not, the aviation compression system is in normal working condition, and the second step S2 is repeated. If present, the aviation compression system is in a near-stall condition.

[0061] In a preferred embodiment of the acoustic monitoring method for near-stall condition of an aero-engine compressor, the first step S1 includes:

[0062] Step S101, calculate the highest circumferential modal order , where the modal order of the circumferential acoustic mode is , represents the pressure pulsation order caused by the unsteady aerodynamic force caused by the fan's rotation-stationary interference. Represents a non-negative integer, determining the highest circumferential modal order , determine the measurable number as the modal range is ;

[0063] Step S102: Calculate the number of microphones required and installation location, Nyquist-Shannon sampling, number of microphones and the highest circumferential modal order The relationship is, , microphone sensors are evenly installed on the casing wall in the circumferential direction, and the spacing between the microphone sensors is , installation angle ,in 、 、 , and so on.

[0064] In a preferred embodiment of the acoustic monitoring method for near-stall condition of an aero-engine compressor, in the second step S2, the window length of the acoustic time domain signal segment is determined based on the sampling frequency, and a rectangular window is added to the multi-channel sound pressure time domain signal, and the window length is and , is any integer, is the sampling frequency of the microphone sensor; and every Add windows to multi-channel signals, and the overlap length of each window .

[0065] In a preferred embodiment of the acoustic monitoring method for near-stall condition of an aero-engine compressor, the third step S3 includes:

[0066] Step S301: Let the current acoustic time domain signal segment number be , for N evenly distributed microphones in the first The sound pressure signal measured by each acoustic time domain signal segment is subjected to fast Fourier transform: ,in, It represents the current time domain signal fragment matrix of the sound pressure signal measured by the uniformly distributed microphone array. The dimension of the current time domain signal fragment matrix is , represents the discrete Fourier transform, For multi-channel arrays The frequency domain matrix of the time domain signal segments has the dimension , , which is expressed as follows:

[0067]

[0068] in ,

[0069] Step S302: Based on the obtained frequency domain matrix , draw the sound pressure spectrum measured by sensors at different positions, and observe whether there are multiple non-integer order abnormal single-tone peak frequencies other than integer multiples of the rotation frequency. , The blade rotation frequency is, if it does not exist, repeat the second step S2, if it exists, go to the fourth step S4.

[0070] In a preferred embodiment of the method for acoustically monitoring an aero-engine compressor near-stall condition, the fourth step S4 includes:

[0071] Step S401: Construct an orthogonal Fourier perception matrix ,

[0072]

[0073] in ,

[0074] Step S402: Select abnormal single-tone peak frequency , take the frequency domain observation vector at this frequency ,in Represents the transpose of a matrix or vector and calculates the peak frequency of an abnormal single tone The modal vector at ,

[0075] ,

[0076] Take the modal vector The maximum component in the equation determines its corresponding modal order. ,

[0077] Step S403: The remaining abnormal single-tone peak frequencies in the frequency domain are Repeat step S402 to determine the corresponding modal order , determine whether the peak frequencies of multiple abnormal single tones have the following numerical relationship:

[0078] If it does not exist, repeat the second step S2; if it does exist, proceed to the fifth step S5.

[0079] In a preferred embodiment of the method for acoustic monitoring of an aero-engine compressor near-stall condition, the fifth step S5 includes:

[0080] Step S501: Calculate the modal matrix ,in

[0081] ,

[0082] Step S502: Draw an acoustic modal spectrum diagram based on the calculated modal matrix, where the horizontal axis of the spectrum diagram represents the frequency analysis range, the vertical axis represents the range of the acoustic mode of interest, and the depth of the color represents the amplitude. The darker the color, the larger the amplitude. Observe whether there is a tilted bright band component near the cutoff frequency. If not, return to the second step S2; if so, determine whether the aviation compression system is at time The working state point is near stall.

[0083] In a preferred embodiment of the acoustic monitoring method for near-stall conditions of an aero-engine compressor, the aviation compression system includes rotor blades and a turbine.

[0084] A monitoring system for implementing the method includes:

[0085] The sound field measurement module includes a sound array measurement submodule and a data acquisition system submodule, and is used to measure the sound field information transmitted from the compression system pipeline to the sound array installation location;

[0086] The spectrum analysis module is used to transform the time domain sound field signal at the acoustic array position into the frequency domain to detect whether there are abnormal frequencies other than the blade passing frequency and rotation frequency.

[0087] The acoustic modal decomposition module is used to perform single-tone acoustic mode decomposition and continuous broadband acoustic mode decomposition, transform the sound field information from the frequency domain to the wavenumber domain, and determine whether the compression system is operating near the stall point based on the acoustic modal spectrogram.

[0088] A computer storage medium includes computer instructions, which, when executed on a computer, cause the computer to execute the method described above.

[0089] An electronic device, comprising:

[0090] A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein:

[0091] When the processor executes the program, the method described is implemented.

[0092] In one embodiment, Figure 1This is a flowchart of the method and system for monitoring the near-stall condition of a compression system based on acoustic modes completed by the present invention. The method calculates the rotational-static interference mode order in the compressor single-tone noise through the compressor model of the aircraft engine, and determines the acoustic mode monitoring range, the number of microphones, the axial installation position and the circumferential installation angle according to the maximum modal order of interest; based on the sampling frequency, the multi-channel continuously measured acoustic array signal is windowed, and the rectangular window signal at the current moment is selected to realize continuous time monitoring of the compression system; the acoustic array signal is fast Fourier transformed to obtain a frequency domain signal matrix and Output the spectrum diagram to observe whether there are abnormal peaks other than integer multiples of the rotation frequency; based on the constructed transfer matrix, obtain the dominant acoustic mode order corresponding to each abnormal single-tone frequency through the acoustic mode decomposition method, and calculate whether the acoustic mode order difference at each characteristic frequency is the rotation frequency multiple difference of the corresponding characteristic abnormal single-tone frequency; obtain the spectrum diagram of the array signal through continuous broadband acoustic mode decomposition, and observe whether there are abnormal rotating stall sound sources and their multiples that are non-integer multiples of the rotation frequency, as well as the acoustic mode oblique bright band components starting from the modal order of 1 corresponding to the rotating stall characteristic frequency and its multiples. The specific steps are as follows:

[0093] The schematic diagram of the aircraft engine fan structure used in the test is as follows Figure 2 As shown, the number of first-stage rotor blades of the aircraft engine fan , number of guide blades , according to the calculation formula of the fan single-tone noise mode order , usually take The pressure pulsation order caused by the unsteady aerodynamic force caused by the fan's static interference is 1. Focus on the highest modal order ; Determine the measurable number as the modal range is , the number of measurable modes ;

[0094] A few circumferential positions are randomly selected to install microphones at the entrance of the pipe. The Nyquist-Shannon sampling theorem must be satisfied, that is, In this example, the number of microphone sensors installed uniformly on the casing wall in the circumferential direction is , the spacing between sensors is , installation angle ,in 、 、 , and so on;

[0095] The sound pressure signal of the aircraft engine compressor is measured using a circular acoustic array. The sampling frequency of each sensor is The window length of the acoustic time domain signal segment is determined based on the sampling frequency. Data points, and in the continuous sampling process, the multi-channel signal is windowed every 1024 sampling points, that is, the overlapping length of each window ;

[0096] Perform fast Fourier transform on the sound pressure signal measured by 32 evenly distributed microphones in the current time domain signal segment to obtain the frequency domain matrix , the frequency domain matrix The size is . Draw the spectrum of the signal measured by each sensor, taking the installation position as Take the microphone signal as an example. At this time, the compressor speed is 8600r / min and the rotation frequency is 143.33Hz. The spectrum diagram near the stall point is as follows Figure 3 As shown, the horizontal axis EO is the multiple of the rotation frequency, the vertical axis is the sound pressure level, the black mark is the single tone frequency that is an integer multiple of the rotation frequency, and the red mark is the single tone frequency that is a non-integer multiple of the rotation frequency, that is, the abnormal single tone characteristic frequency.

[0097] Constructing a compressed sensing matrix ,in is the kth sensor installation angle, is the modal order of the jth circumferential modal wave, and its magnitude is .

[0098] right Figure 3 The acoustic modal decomposition is performed at the abnormal peak frequency, and the acoustic modal spectra at each characteristic frequency are plotted. The acoustic modal spectrum at 13.1EO is shown in Figure 4(a), where the acoustic modal order is observed to be +8; the acoustic modal spectrum at 14.1EO is shown in Figure 4(b), where the acoustic modal order is observed to be +9; and the acoustic modal spectrum at 16.1EO is shown in Figure 4(c), where the acoustic modal order is observed to be +11. This satisfies the characteristic that the difference in the order of each acoustic mode is equal to the difference in the frequency multiples of the characteristic frequency.

[0099] Frequency domain matrix Continuous broadband acoustic modal decomposition is performed to obtain a magnitude of The modal matrix , draw the spectrum, such as Figure 5 As shown in the figure, there is an oblique bright band at the cutoff boundary of the spectrum, which meets the characteristics of the near-stall point. It can be judged that the current compression system is in a near-stall condition.

[0100] 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 acoustic monitoring of an aero-engine compressor near-stall condition, characterized in that: The steps include: In the first step (S1), according to the number of rotor blades of the previous stage of the aviation compression system Number of stator blades Determine the highest circumferential modal order and the number of measuring points , evenly select a predetermined number of circumferential installation positions and angles to install microphone sensors at the entrance of the aviation compression system to form a microphone array, and synchronously collect multi-channel sound pressure time domain signals of the aviation compression system; In the second step (S2), a rectangular window is added to the multi-channel sound pressure time domain signal to construct an acoustic time domain signal segment to monitor the current operating status of the aviation compression system; In the third step (S3), a fast Fourier transform is performed on the multi-channel acoustic time domain signal segment in the current time domain window to form multiple sound pressure spectra, and it is determined whether there are multiple single-tone characteristic frequencies that are non-integer multiples of the current frequency shift in the sound pressure spectrum. If not, the aviation compression system is in a normal working state, and the second step (S2) is repeated. If so, the process proceeds to the fourth step (S4). In the fourth step (S4), based on the installation position and the highest circumferential modal order Construct an orthogonal Fourier transfer matrix, perform spatial Fourier transform on each characteristic frequency, obtain the order of the characteristic acoustic mode corresponding to each characteristic frequency, and judge whether the order difference of the characteristic acoustic mode at each characteristic frequency is the frequency multiple difference of the corresponding characteristic frequency. If the order difference is not equal to the frequency multiple difference, the aviation compression system is in a normal working state, and repeat the second step (S2). If so, proceed to the fifth step (S5); In the fifth step (S5), the acoustic modal amplitude corresponding to each broadband frequency component is calculated, and an acoustic modal spectrum is plotted to determine whether a modal bright band exists at the cutoff frequency boundary in the acoustic modal spectrum. If not, the aviation compression system is in normal working condition, and the second step (S2) is repeated. If so, the aviation compression system is in a near-stall condition.

2. The method for acoustic monitoring of an aero-engine compressor near-stall condition according to claim 1, characterized in that: Preferably, the first step (S1) comprises, Step S101, calculate the highest circumferential modal order , where the modal order of the circumferential acoustic mode is , represents the pressure pulsation order caused by the unsteady aerodynamic force caused by the fan's rotation-stationary interference. Represents a non-negative integer, determining the highest circumferential modal order , determine the measurable number as the modal range is ; Step S102: Calculate the number of microphones required and installation location, Nyquist-Shannon sampling, number of microphones and the highest circumferential modal order The relationship is, , microphone sensors are evenly installed on the casing wall in the circumferential direction, and the spacing between the microphone sensors is , installation angle ,in 、 、 , and so on.

3. The method for acoustic monitoring of an aero-engine compressor near-stall condition according to claim 1, characterized in that: In the second step (S2), the acoustic time domain signal segment window length is determined based on the sampling frequency, and a rectangular window is added to the multi-channel sound pressure time domain signal. The window length is and , is any integer, is the sampling frequency of the microphone sensor; and every Add windows to multi-channel signals, and the overlap length of each window .

4. The method for acoustic monitoring of an aero-engine compressor near-stall condition according to claim 3, characterized in that: The third step (S3) includes, Step S301: Let the current acoustic time domain signal segment number be , for N evenly distributed microphones in the first The sound pressure signal measured by each acoustic time domain signal segment is subjected to fast Fourier transform: ,in, It represents the current time domain signal fragment matrix of the sound pressure signal measured by the uniformly distributed microphone array. The dimension of the current time domain signal fragment matrix is , represents the discrete Fourier transform, For multi-channel arrays The frequency domain matrix of the time domain signal segments has the dimension , , which is expressed as follows: ， in , Step S302: Based on the obtained frequency domain matrix , draw the sound pressure spectrum measured by sensors at different positions, and observe whether there are multiple non-integer order abnormal single-tone peak frequencies other than integer multiples of the rotation frequency. , The blade rotation frequency is, if it does not exist, repeat the second step (S2), if it exists, go to the fourth step (S4).

5. The method for acoustic monitoring of an aero-engine compressor near-stall condition according to claim 4, characterized in that: The fourth step (S4) comprises, Step S401: Construct an orthogonal Fourier perception matrix , ， in , Step S402: Select abnormal single-tone peak frequency , take the frequency domain observation vector at this frequency ,in Represents the transpose of a matrix or vector and calculates the peak frequency of an abnormal single tone The modal vector at , ， Take the modal vector The maximum component in the equation determines its corresponding modal order. , Step S403: The remaining abnormal single-tone peak frequencies in the frequency domain are Repeat step S402 to determine the corresponding modal order , determine whether the peak frequencies of multiple abnormal single tones have the following numerical relationship: If it does not exist, repeat the second step (S2); if it does exist, go to the fifth step (S5).

6. The method for acoustic monitoring of an aero-engine compressor near-stall condition according to claim 5, characterized in that: The fifth step (S5) comprises, Step S501: Calculate the modal matrix ,in ， Step S502: Draw an acoustic modal spectrum diagram based on the calculated modal matrix, where the horizontal axis of the spectrum diagram represents the frequency analysis range, the vertical axis represents the range of the acoustic mode of interest, and the depth of the color represents the amplitude. The darker the color, the larger the amplitude. Observe whether a tilted bright band component appears near the cutoff frequency. If not, return to the second step (S2); if so, determine whether the aviation compression system is at time The working state point is near stall.

7. The method for acoustic monitoring of an aero-engine compressor near-stall condition according to claim 1, characterized in that: The aviation compression system includes rotor blades and a turbine.

8. A monitoring system for implementing the method according to any one of claims 1 to 7, characterized in that: It includes: The sound field measurement module includes a sound array measurement submodule and a data acquisition system submodule, and is used to measure the sound field information transmitted from the compression system pipeline to the sound array installation location; The spectrum analysis module is used to transform the time domain sound field signal at the acoustic array position into the frequency domain to detect whether there are abnormal frequencies other than the blade passing frequency and rotation frequency. The acoustic modal decomposition module is used to perform single-tone acoustic mode decomposition and continuous broadband acoustic mode decomposition, transform the sound field information from the frequency domain to the wavenumber domain, and determine whether the compression system is operating near the stall point based on the acoustic modal spectrogram.

9. 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 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.

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