Aero-engine near-stall condition acoustic monitoring method, system, medium and equipment

Abstract

An aero-engine compressor near stall condition acoustic monitoring method, system, medium and equipment, in the method, the multi-channel sound pressure time domain signal of the aero compression system is synchronously collected; the multi-channel sound pressure time domain signal is added with a rectangular window, and the acoustic time domain signal segment is constructed to monitor the current aero compression system running state; the multi-channel acoustic time domain signal segment in the current time domain window is subjected to fast Fourier transform to form multiple sound pressure spectra, whether multiple current rotation frequency non-integer multiple single tone characteristic frequencies exist in the sound pressure spectrum is judged, based on the installation position and the highest circumferential modal order, the orthogonal Fourier transfer matrix is constructed, whether the order difference of the characteristic acoustic mode under each characteristic frequency is the rotation frequency multiple difference of the corresponding characteristic frequency is judged, the corresponding acoustic mode amplitude at each wideband frequency component is calculated, the acoustic mode spectrum diagram is drawn, and whether there is a modal bright band at the cutoff frequency boundary in the acoustic mode spectrum diagram is judged.

Description

Technical Field

[0001] This invention relates to the field of aero-engine compression system condition monitoring technology, and in particular to an acoustic monitoring method, system, medium and equipment for near-stall conditions of aero-engine compressors. Background Technology

[0002] The intense pressurization process of viscous gas flow within the compression system of an aero-engine determines its aerodynamic instability characteristics, specifically manifested as rotating stall and surge in the compression system. When the engine enters an aerodynamically unstable operating state, it will cause a reduction in engine performance, an increase in vibration stress on the rotor blades of the compression components, an increase in the thermal load and thermal stress of the turbine, a reduction in the stable operating range of the combustion chamber, and may even damage the structural integrity of the engine, seriously threatening flight safety.

[0003] To ensure the compression system operates stably throughout its entire 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 the stall point, aerodynamic instability precursors often occur, such as rotationally unstable flow, flow-induced vibration, and acoustic resonance. Monitoring and diagnosing these precursory anomalies under near-stall conditions is crucial for designing with available stability margins and controlling aerodynamic stability in aero-engine compression systems.

[0004] The information disclosed in the background section is only for enhancing the understanding of the background of this invention, and therefore may contain information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0005] This invention provides a method, system, medium, and equipment for acoustic monitoring of near-stall conditions in aero-engine compressors. By arranging a ring microphone array at the compressor system inlet, and using a spectrum analysis module and a modal decomposition module for the acoustic array test signal, the acoustic signal is converted from the time domain to the wavenumber domain, acquiring the frequency and wavenumber domain modal characteristics of the acoustic test signal. This is the first time a more effective near-stall condition discrimination method has been achieved through acoustic measurement. This method uses a more sensitive, shorter transmission path, and is non-invasive acoustic monitoring approach, overcoming the difficulty of achieving dynamic and sensitive feedback in traditional hydrostatic sensors monitoring near-stall conditions.

[0006] An acoustic monitoring method for near-stall conditions of aero-engine compressors includes:

[0007] In the first step, based on the number of rotor blades in the preceding stage of the aero-compression system... With the number of stator blades Determine the highest circumferential modal order With the number of measuring points Microphone sensors are installed at predetermined circumferential positions and angles at the inlet of the aviation compression system to form a microphone array, and multi-channel sound pressure time-domain signals of the aviation compression system are synchronously acquired.

[0008] In the second step, rectangular windows are added to the multi-channel acoustic pressure time-domain signals to construct acoustic time-domain signal segments 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 within the current time-domain window to form multiple sound pressure spectra. It is then determined whether there are multiple single-tone characteristic frequencies in the sound pressure spectra that are not integer multiples of the current frequency. 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.

[0010] In the fourth step, based on the installation location 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 equal to the frequency conversion factor difference of the corresponding characteristic frequency. If the order difference is not equal to the frequency conversion factor difference, the aviation compression system is in normal working condition. Repeat the second step. If it exists, proceed to the fifth step.

[0011] In the fifth step, the amplitude of the acoustic mode corresponding to each broadband frequency component is calculated, the acoustic mode spectrum is plotted, and it is determined whether there is a bright band at the cutoff frequency boundary in the acoustic mode spectrum: if there is no bright band, the aviation compression system is in normal working condition, and the second step is repeated; if there is a bright band, the aviation compression system is in near stall condition.

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

[0013] Step S101: Calculate the highest circumferential modal order. The modal order of the circumferential acoustic mode is . , This indicates the order of pressure pulsations caused by unsteady aerodynamic forces resulting from the interference of the fan's rotation and stationary motion. Represent a non-negative integer to determine the highest circumferential modal order. The measurable number is determined to be the modal range. ;

[0014] Step S102: Calculate the required number of microphones. The installation location and number of microphones were sampled by Nyquist-Shannon. With the highest circumferential modal order The relationship is, Microphone sensors are evenly installed on the casing wall in a circumferential direction, with a spacing between the microphone sensors of [missing information]. Installation angle ,in , , And so on.

[0015] In the aforementioned acoustic monitoring method for near-stall conditions 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, with a window length of... and , For any integer, This is the sampling frequency of the microphone sensor; and every [time] during continuous sampling... Windowing of multi-channel signals, the overlap length of each window .

[0016] In the aforementioned acoustic monitoring method for 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 uniformly distributed microphones, on the th Fast Fourier Transform (FFT) of the sound pressure signals measured from each acoustic time-domain signal segment: ,in, This represents the current time-domain signal segment matrix of the sound pressure signal measured by the uniformly distributed microphone array, and the dimension of the current time-domain signal segment matrix is... , Represents the Discrete Fourier Transform. For multi-channel arrays in the first The frequency domain matrix of each time-domain signal segment has dimensions of , , means as follows:

[0018]

[0019] in ,

[0020] Step S302: Based on the obtained frequency domain matrix Plot the sound pressure spectrum obtained from sensors at different locations, and observe whether there are multiple non-integer order abnormal single-tone peak frequencies other than integer multiples of the turn rate. , If the blade frequency is not present, repeat step two; if it is present, proceed to step four.

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

[0022] Step S401: Construct the orthogonal Fourier sensing matrix ,

[0023]

[0024] in ,

[0025] Step S402: Select the abnormal single-tone peak frequency Take the frequency domain observation vector at that frequency. ,in Represents the transpose of a matrix or vector, and calculates the peak frequency of abnormal monotones. mode vector at ,

[0026]

[0027] Take the mode vector The largest component in the equation is used to determine its corresponding modal order. ,

[0028] Step S403: For the remaining abnormal single-tone peak frequencies in the frequency domain Repeat step S402 to determine its corresponding modal order. Determine whether the following numerical relationship exists between multiple abnormal single-tone peak frequencies:

[0029] If it does not exist, repeat step two; if it exists, proceed to step five.

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

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

[0032] ,

[0033] Step S502: Based on the calculated modal matrix, plot the acoustic modal spectrum. The horizontal axis of the spectrum represents the frequency analysis range, and the vertical axis represents the range of the acoustic modes of interest. The intensity of the color indicates the amplitude; the darker the color, the larger the amplitude. Observe whether there are any tilted bright band components near the cutoff frequency. If not, return to step two; if so, determine the timing of the airborne compression system. The operating state is near stall.

[0034] In the aforementioned acoustic monitoring method for near-stall conditions of an aero-engine compressor, the aero-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, which are used to measure the sound field information propagated from the compression system pipeline to the sound array installation location;

[0037] The spectrum analysis module transforms the time-domain sound field signal at the location of the acoustic array into the frequency domain to detect any abnormal frequencies other than the blade passage frequency and rotation frequency.

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

[0039] A computer storage medium including computer instructions that, when run on a computer, cause the computer to perform the method.

[0040] An electronic device, the electronic device comprising:

[0041] Memory, processor, and computer programs stored in memory and executable on the processor, wherein,

[0042] The processor implements the method when executing the program.

[0043] Compared with existing technologies, this invention has the following advantages: Compared with traditional interstage static pressure monitoring, this invention utilizes acoustic information to monitor the near-stall point of the compression system, exhibiting higher sensitivity and stronger adaptability; it obtains the near-stall point characteristics of the acoustic signal in the frequency domain through Fast Fourier Transform, resulting in clear characteristics and a simple process; it obtains the acoustic modal characteristics of the acoustic signal at the compressor near-stall point in the wavenumber domain through Spatial Fourier Transform, demonstrating high sensitivity and adaptability to different engine speeds. Defining the acoustic signal spectrum, modal spectrum, and anomalous components in the wavenumber spectrum as the acoustic modal characteristics of the near-stall point of the compression system improves monitoring accuracy. Attached Figure Description

[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 for illustrative purposes only and are not intended to limit the invention. It is obvious that the drawings described below are merely some embodiments of the invention, and those skilled in the art can obtain other drawings based on these drawings without any inventive effort. Furthermore, the same reference numerals denote the same parts throughout the drawings.

[0045] In the attached diagram:

[0046] Figure 1 This is the flowchart of this disclosure;

[0047] Figure 2 This is a schematic diagram of a device for monitoring near-stall conditions of a compression system based on acoustic modes, provided in one embodiment of this disclosure.

[0048] Figure 3 This is a spectrum diagram of the sound pressure signal at the near-stall condition provided in one embodiment of this disclosure;

[0049] Figures 4(a) to 4(c) This is one embodiment provided in the present disclosure. Figure 3 Schematic diagrams of the acoustic mode decomposition results at each characteristic frequency; wherein, Figure 4(a) is a schematic diagram of the acoustic mode decomposition results at 14.1EO, Figure 4(b) is a schematic diagram of the acoustic mode decomposition results at 15.1EO, and Figure 4(c) is a schematic diagram of the acoustic mode decomposition results at 17.1EO.

[0050] Figure 5 This is a near-stall point acoustic modal spectrum of a compression system provided in one embodiment of this disclosure.

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

[0052] Specific embodiments of the invention will now be described in more detail with reference to the accompanying drawings. While specific embodiments of the invention are shown in the drawings, it should be understood that the invention may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this invention will be thorough and complete, and will fully convey the scope of the invention to those skilled in the art.

[0053] It should be noted that certain terms are used in the specification and claims to refer to specific components. Those skilled in the art will understand that different terms may be used to refer to the same component. This specification and claims do not distinguish components based on differences in terminology, but rather on differences in function. The terms "comprising" or "including" used throughout the specification and claims are open-ended and should be interpreted as "comprising but not limited to." The following descriptions are preferred embodiments for carrying out the invention; however, these descriptions are for the purpose of understanding the general principles of the specification and are not intended to limit the scope of the invention. The scope of protection of this invention is determined by the appended claims.

[0054] To facilitate understanding of the embodiments of the present invention, further explanations and descriptions will be provided below with reference to the accompanying drawings and specific embodiments. 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 near-stall conditions of aero-engine compressors includes the following steps:

[0056] In the first step S1, based on the number of rotor blades in the preceding stage of the aero-compression system... With the number of stator blades Determine the highest circumferential modal order With the number of measuring points Microphone sensors are installed at predetermined circumferential positions and angles at the inlet of the aviation compression system to form a microphone array, and multi-channel sound pressure time-domain signals of the aviation compression system are synchronously acquired.

[0057] In the second step S2, a rectangular window is added to the multi-channel acoustic 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 within the current time-domain window to form multiple sound pressure spectra. It is determined whether there are multiple single-tone characteristic frequencies in the sound pressure spectra that are not integer multiples of the current frequency. If not, the aviation compression system is in normal working condition, and the second step S2 is repeated. If they exist, 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, determine whether the order difference of the characteristic acoustic mode at each characteristic frequency is equal to the frequency conversion factor difference of the corresponding characteristic frequency. If the order difference is not equal to the frequency conversion factor difference, the aviation compression system is in normal working condition, repeat the second step S2, if it exists, proceed to the fifth step S5.

[0060] In step S5, the amplitude of the acoustic mode corresponding to each broadband frequency component is calculated, the acoustic mode spectrum is plotted, and it is determined whether there is a bright band at the cutoff frequency boundary in the acoustic mode spectrum: if there is no bright band, the aviation compression system is in normal working condition, and step S2 is repeated; if there is a bright band, the aviation compression system is in near stall condition.

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

[0062] Step S101: Calculate the highest circumferential modal order. The modal order of the circumferential acoustic mode is . , This indicates the order of pressure pulsations caused by unsteady aerodynamic forces resulting from the interference of the fan's rotation and stationary motion. Represent a non-negative integer to determine the highest circumferential modal order. The measurable number is determined to be the modal range. ;

[0063] Step S102: Calculate the required number of microphones. The installation location and number of microphones were sampled by Nyquist-Shannon. With the highest circumferential modal order The relationship is, Microphone sensors are evenly installed on the casing wall in a circumferential direction, with a spacing between the microphone sensors of [missing information]. Installation angle ,in , , And so on.

[0064] In a preferred embodiment of the acoustic monitoring method for near-stall conditions 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, with a window length of... and , For any integer, This is the sampling frequency of the microphone sensor; and every [time] during continuous sampling... Windowing of multi-channel signals, the overlap length of each window .

[0065] In a preferred embodiment of the acoustic monitoring method for near-stall conditions 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 uniformly distributed microphones, on the th Fast Fourier Transform (FFT) of the sound pressure signals measured from each acoustic time-domain signal segment: ,in, This represents the current time-domain signal segment matrix of the sound pressure signal measured by the uniformly distributed microphone array, and the dimension of the current time-domain signal segment matrix is... , Represents the Discrete Fourier Transform. For multi-channel arrays in the first The frequency domain matrix of each time-domain signal segment has dimensions of , , means as follows:

[0067]

[0068] in ,

[0069] Step S302: Based on the obtained frequency domain matrix Plot the sound pressure spectrum obtained from sensors at different locations, and observe whether there are multiple non-integer order abnormal single-tone peak frequencies other than integer multiples of the turn rate. , If the blade frequency is not present, repeat step S2; otherwise, proceed to step S4.

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

[0071] Step S401: Construct the orthogonal Fourier sensing matrix ,

[0072]

[0073] in ,

[0074] Step S402: Select the abnormal single-tone peak frequency Take the frequency domain observation vector at that frequency. ,in Represents the transpose of a matrix or vector, and calculates the peak frequency of abnormal monotones. mode vector at ,

[0075] ,

[0076] Take the mode vector The largest component in the equation is used to determine its corresponding modal order. ,

[0077] Step S403: For the remaining abnormal single-tone peak frequencies in the frequency domain Repeat step S402 to determine its corresponding modal order. Determine whether the following numerical relationship exists between multiple abnormal single-tone peak frequencies:

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

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

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

[0081] ,

[0082] Step S502: Based on the calculated modal matrix, plot the acoustic modal spectrum. The horizontal axis of the spectrum represents the frequency analysis range, and the vertical axis represents the range of the acoustic modes of interest. The intensity of the color indicates the amplitude; the darker the color, the larger the amplitude. Observe whether a tilted bright band appears near the cutoff frequency. If not, return to step S2; if so, determine the timing of the airborne compression system. The operating state is near stall.

[0083] In a preferred embodiment of the acoustic monitoring method for near-stall conditions of an aero-engine compressor, the aero-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, which are used to measure the sound field information propagated from the compression system pipeline to the sound array installation location;

[0086] The spectrum analysis module transforms the time-domain sound field signal at the location of the acoustic array into the frequency domain to detect any abnormal frequencies other than the blade passage frequency and rotation frequency.

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

[0088] A computer storage medium including computer instructions that, when run on a computer, cause the computer to perform the method.

[0089] An electronic device, the electronic device comprising:

[0090] Memory, processor, and computer programs stored in memory and executable on the processor, wherein,

[0091] The processor implements the method when executing the program.

[0092] In one embodiment, Figure 1This is a flowchart of the near-stall condition monitoring method and system for a compression system based on acoustic modes, as completed by this invention. The method calculates the order of the transition-to-static interference modes in the compressor's single-tone noise using a compressor model of an aero-engine. Based on the maximum order of the mode of interest, it determines the acoustic mode monitoring range, the number of microphones, the axial mounting position, and the circumferential mounting angle. It then windows the multi-channel continuously measured acoustic array signal based on the sampling frequency, selecting the rectangular window signal at the current moment to achieve continuous-time monitoring of the compression system. Finally, it performs a fast Fourier transform on the acoustic array signal to obtain the frequency domain signal matrix. Output the spectrum and observe whether any abnormal peaks appear other than integer multiples of the rotational frequency. Based on the constructed transfer matrix, obtain the dominant acoustic mode order corresponding to each abnormal single-tone frequency using the acoustic mode decomposition method, and calculate whether the difference in acoustic mode order at each characteristic frequency is the rotational frequency multiple difference of the corresponding abnormal single-tone frequency. Obtain the spectrum of the array signal through continuous broadband acoustic mode decomposition, and observe whether there are rotating stall abnormal sound sources and their harmonics that are not integer multiples of the rotational frequency, as well as the oblique bright band components of the acoustic modes starting from mode order 1 for the corresponding rotating stall characteristic frequencies and their harmonics. The specific steps are as follows:

[0093] The schematic diagram of the aircraft engine fan structure used in the test is shown below. Figure 2 As shown, the number of first-stage rotor blades of the aero-engine fan Number of guide vanes According to the formula for calculating the modal order of fan single-tone noise... , usually take The order of the pressure pulsation caused by the unsteady aerodynamic forces resulting from the fan's rotation and stationary interference is 1. In this case, we take... Focus on the highest modal order The measurable number is determined to be the modal range. Number of measurable modes ;

[0094] Microphones were randomly selected at a small number of circumferential locations at the pipe inlet. The number of microphones... The Nyquist-Shannon sampling theorem must be satisfied, i.e. In this example, a number of microphone sensors are evenly installed on the casing wall in a circumferential direction. The spacing between the sensors is Installation angle ,in , , And so on;

[0095] The acoustic pressure signal of an aero-engine compressor is measured using a circular acoustic array, and the sampling frequency of each sensor is... The acoustic time-domain signal segment window length is determined based on the sampling frequency of 20000Hz. Data points, and during continuous sampling, the multi-channel signal is windowed every 1024 sampling points, i.e., the overlap length of each window. ;

[0096] A fast Fourier transform is performed on the sound pressure signals measured by 32 evenly distributed microphones in the current time domain signal segment to obtain the frequency domain matrix. Frequency domain matrix The size is Plot the spectrum of the signals measured by each sensor, with the installation location as the reference point. Taking the microphone signal as an example, at this time the compressor speed is 8600 r / min and the frequency is 143.33 Hz. Its spectrum near the stall point is as follows: Figure 3 As shown, the horizontal axis EO represents the frequency multiple, the vertical axis represents the sound pressure level, the black markings represent single-tone frequencies that are integer multiples of the frequency, and the red markings represent single-tone frequencies that are not integer multiples of the frequency, i.e., anomalous single-tone characteristic frequencies.

[0097] Constructing a compressed sensing matrix ,in The installation angle for the k-th sensor is... Let j be the modal order of the j-th circumferential modal wave, with magnitude . .

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

[0099] For frequency domain matrix Performing continuous broadband acoustic mode decomposition yields a value of mode matrix Draw a spectrum, such as Figure 5 As shown, the spectral diagram shows a slanted bright band at the cutoff boundary, which satisfies the characteristics of a near-stall point, indicating that the current compression system is under near-stall conditions.

[0100] Although embodiments of the present invention have been described above in conjunction with the accompanying drawings, the present invention is not limited to the specific embodiments and application fields described above. The specific embodiments described above are merely illustrative and instructive, and not restrictive. Those skilled in the art can make many other forms based on the guidance of this specification and without departing from the scope of protection of the claims of the present invention, and all of these are within the scope of protection of the present invention.

Claims

1. An acoustic monitoring method for near-stall conditions of an aero-engine compressor, characterized in that, Includes the following steps: In the first step (S1), based on the number of rotor blades in the preceding stage of the aero-compression system... With the number of stator blades Determine the highest circumferential modal order With the number of measuring points Microphone sensors are installed at predetermined circumferential positions and angles at the inlet of the aviation compression system to form a microphone array, and multi-channel sound pressure time-domain signals of the aviation compression system are synchronously acquired. In the second step (S2), a rectangular window is added to the multi-channel acoustic 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 within the current time-domain window to form multiple sound pressure spectra. It is determined whether there are multiple single-tone characteristic frequencies that are not 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 they exist, the process proceeds to the fourth step (S4). In the fourth step (S4), based on the installation location 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, determine whether the order difference of the characteristic acoustic mode at each characteristic frequency is equal to the frequency conversion factor difference of the corresponding characteristic frequency. If the order difference is not equal to the frequency conversion factor difference, the aviation compression system is in normal working condition, repeat the second step (S2), if it exists, proceed to the fifth step (S5). In the fifth step (S5), the amplitude of the acoustic mode corresponding to each broadband frequency component is calculated, the acoustic mode spectrum is plotted, and it is determined whether there is a bright band at the cutoff frequency boundary in the acoustic mode spectrum: if there is no bright band, the aviation compression system is in normal working condition, and the second step (S2) is repeated; if there is a bright band, the aviation compression system is in near stall condition. The first step (S1) includes, Step S101: Calculate the highest circumferential modal order. The modal order of the circumferential acoustic mode is . , This indicates the order of pressure pulsations caused by unsteady aerodynamic forces resulting from the interference of the fan's rotation and stationary motion. Represent a non-negative integer to determine the highest circumferential modal order. The measurable number is determined to be the modal range. ; Step S102: Calculate the required number of microphones. The installation location and number of microphones were sampled by Nyquist-Shannon. With the highest circumferential modal order The relationship is, Microphone sensors are evenly installed on the casing wall in a circumferential direction, with a spacing of [missing information]. Installation angle ,in , , And so on; 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, with a window length of... and , For any integer, This is the sampling frequency of the microphone sensor; and every [time] during continuous sampling... Windowing of multi-channel signals, the overlap length of each window ; The third step (S3) includes, Step S301: Let the current acoustic time-domain signal segment number be... For N uniformly distributed microphones, on the th Fast Fourier Transform (FFT) of the sound pressure signals measured from each acoustic time-domain signal segment: ,in, This represents the current time-domain signal segment matrix of the sound pressure signal measured by the uniformly distributed microphone array, and the dimension of the current time-domain signal segment matrix is... , Represents the Discrete Fourier Transform. For multi-channel arrays in the first The frequency domain matrix of each time-domain signal segment has dimensions of , , means as follows: ， in , Step S302: Based on the obtained frequency domain matrix Plot the sound pressure spectrum obtained from sensors at different locations, and observe whether there are multiple non-integer order abnormal single-tone peak frequencies other than integer multiples of the turn rate. , If the blade frequency does not exist, repeat step 2 (S2); if it does exist, proceed to step 4 (S4). The fourth step (S4) includes, Step S401: Construct the orthogonal Fourier sensing matrix , ， in , Step S402: Select the abnormal single-tone peak frequency Take the frequency domain observation vector at that frequency. ,in Represents the transpose of a matrix or vector, and calculates the peak frequency of abnormal monotones. mode vector at , ， Take the mode vector The largest component in the equation is used to determine its corresponding modal order. , Step S403: For the remaining abnormal single-tone peak frequencies in the frequency domain Repeat step S402 to determine its corresponding modal order. Determine whether the following numerical relationship exists between multiple abnormal single-tone peak frequencies: If it does not exist, repeat step 2 (S2); if it exists, proceed to step 5 (S5).

2. The acoustic monitoring method for near-stall conditions of an aero-engine compressor according to claim 1, characterized in that, The fifth step (S5) includes, Step S501: Calculate the mode matrix ,in ， Step S502: Based on the calculated modal matrix, plot the acoustic modal spectrum. The horizontal axis of the spectrum represents the frequency analysis range, and the vertical axis represents the range of the acoustic modes of interest. The intensity of the color represents the amplitude; the darker the color, the larger the amplitude. Observe whether there are any tilted bright band components near the cutoff frequency. If not, return to step two (S2); if so, determine the timing of the airborne compression system. The operating state is near stall.

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

4. A monitoring system implementing the method of any one of claims 1-3, characterized in that, It includes: The sound field measurement module includes a sound array measurement submodule and a data acquisition system submodule, which are used to measure the sound field information propagated from the compression system pipeline to the sound array installation location; The spectrum analysis module transforms the time-domain sound field signal at the location of the acoustic array into the frequency domain to detect any abnormal frequencies other than the blade passage frequency and rotation frequency. The acoustic mode decomposition module is used to perform single-tone acoustic mode decomposition and continuous broadband acoustic mode decomposition, transforming the sound field information from the frequency domain to the wavenumber domain, and determining whether the compression system is operating near the stall point based on the acoustic mode spectrum.

5. A computer storage medium, characterized in that, The storage medium includes computer instructions that, when executed on a computer, cause the computer to perform the method as described in any one of claims 1-3.

6. An electronic device, characterized in that, The electronic device includes: Memory, processor, and computer programs stored in memory and executable on the processor, wherein, When the processor executes the program, it implements the method as described in any one of claims 1-3.

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