Instability prediction method and instability prediction device under distorted intake conditions

Abstract

The present invention provides an instability prediction method and instability prediction device under distorted intake conditions. The method includes measuring multiple dynamic pressure signals at different circumferential positions of the casing wall surface during the compressor throttling process when the compressor is in a distorted intake condition, wherein the dynamic pressure signal represents the dynamic pressure data of the compressor running from a stable condition to an unstable condition; performing correlation calculation on the dynamic pressure signal for each circumferential position of the casing wall surface to obtain a target characteristic quantity, wherein the target characteristic quantity represents the irregularity of the dynamic pressure signal; adjusting a reference threshold value according to the target characteristic quantity to obtain a target threshold value; generating an instability prediction result according to the target characteristic quantity and the target threshold value measured in real time, wherein the instability prediction result represents whether flow instability occurs in the compressor.

Description

Technical Field

[0001] The present invention relates to the field of compressors and aerodynamic thermodynamics, and more specifically, to an instability prediction method, an instability prediction device, an electronic device, a computer-readable storage medium and a computer program product under distorted intake conditions. Background Art

[0002] Rotating stall and surge are the two most serious flow instability phenomena in the field of turbomachinery, which seriously threaten the safe and stable operation of aircraft engines. In order to avoid the occurrence of instability, active control is an important stabilization measure. The core idea is to perceive the compressor status in real time by monitoring the disturbance information of the flow field. When the working point of the compressor is close to the instability boundary, the monitoring system will promptly issue an alarm signal and transmit it to the actuator, such as the jet valve or the guide vane adjustment mechanism, so that the working point can be restored to a stable state. It can be seen that one of the key factors that determine the success or failure of active control is timely and reliable forecast signals.

[0003] The current prediction method is based on the detection of two types of precursor signals: modal waves and spike waves. However, since the appearance of the spike-type stall precursor is only a few or ten turns away from the compressor instability, it is difficult for the control system to complete the adjustment in such a short time. Another type of prediction method is to capture the irregularity of the wall dynamic pressure signal and output the characteristic quantity that characterizes the irregular shape of the signal in real time to achieve prediction. Under uniform intake conditions, if the circumferential propagation time of the disturbance is ignored, the disturbance can be detected almost simultaneously at different circumferential positions. Therefore, only one sensor is needed to achieve prediction under uniform intake conditions; however, under distorted intake conditions, the disturbance may be generated in the distorted area and disappear in the non-distorted area. When the sensor is arranged in the non-distorted area, the prediction method may fail, thereby reducing the safety of the aircraft engine. Summary of the invention

[0004] In view of this, embodiments of the present invention provide an instability prediction method under distorted intake conditions, an instability prediction device, an electronic device, a computer-readable storage medium, and a computer program product.

[0005] An aspect of an embodiment of the present invention provides a method for predicting instability under distorted intake conditions, the method comprising:

[0006] When the compressor is in the above-mentioned distorted intake condition, measuring a plurality of dynamic pressure signals at different circumferential positions of the casing wall during the throttling process of the above-mentioned compressor, wherein the above-mentioned dynamic pressure signals represent the dynamic pressure data of the above-mentioned compressor when it operates from a stable condition to an unstable condition;

[0007] For each circumferential position of the casing wall, a correlation calculation is performed on the dynamic pressure signal to obtain a target characteristic quantity, wherein the target characteristic quantity characterizes the irregularity of the dynamic pressure signal;

[0008] The reference threshold is adjusted according to the above target feature quantity to obtain the target threshold;

[0009] An instability prediction result is generated based on the target characteristic quantity measured in real time and the target threshold, wherein the instability prediction result indicates whether flow instability occurs in the compressor.

[0010] According to an embodiment of the present invention, the above-mentioned dynamic pressure signal is a dynamic pressure signal at different circumferential positions on the casing wall near the leading edge of the blade.

[0011] According to an embodiment of the present invention, correlation calculation is performed on the above dynamic pressure signal to obtain a target feature quantity, including:

[0012] The dynamic pressure signal is processed by a preset processing algorithm to obtain the target characteristic quantity, wherein the preset processing algorithm includes an autocorrelation analysis method, a fast wavelet analysis method, a fuzzy entropy analysis method or an approximate entropy analysis method.

[0013] According to an embodiment of the present invention, the dynamic pressure signal is processed by a preset processing algorithm to obtain the target characteristic quantity, including:

[0014] Based on a preset step length, the dynamic pressure signal is processed using a preset window to obtain a plurality of pressure signals;

[0015] The plurality of pressure signals are processed using the preset processing algorithm to obtain the target characteristic quantity characterizing the irregularity.

[0016] According to an embodiment of the present invention, the above target feature quantity is calculated by the following formula:

[0017]

[0018] Among them, P is the pressure signal, wnd is the length of the fixed window, that is, the preset step size, and N wnd is the data length of the dynamic pressure signal in a fixed window, and the autocorrelation coefficient Characterize the above target characteristics, autocorrelation coefficient It describes the correlation between the pressure signal in the current fixed window and the pressure signal in the fixed window at the next moment. The size of the autocorrelation coefficient is related to the irregularity.

[0019] According to an embodiment of the present invention, the above-mentioned instability prediction method further includes:

[0020] In the case where the instability prediction result indicates that there is a flow instability phenomenon, generating a regulation instruction according to the instability prediction result;

[0021] The above-mentioned adjustment instruction is transmitted to the adjustment mechanism, so that the above-mentioned adjustment mechanism adjusts the above-mentioned compressor in response to the above-mentioned adjustment instruction, so that the above-mentioned compressor recovers the stable working condition, wherein the above-mentioned adjustment mechanism includes adjustable guide vanes and / or bleed valves.

[0022] According to an embodiment of the present invention, adjusting the reference threshold according to the above target feature quantity to obtain the target threshold includes:

[0023] Based on a preset correction formula, the target threshold is generated according to the target feature quantity and the reference threshold.

[0024] According to an embodiment of the present invention, the above preset correction formula is as follows:

[0025]

[0026] in, is the reference threshold, is the autocorrelation coefficient of stable working conditions at different circumferential positions, i.e., the target characteristic quantity, is the target threshold.

[0027] According to an embodiment of the present invention, generating an instability prediction result based on the target feature quantity measured in real time and the above target threshold includes:

[0028] When the target characteristic quantity is less than the target threshold, generating an instability prediction result representing the occurrence of flow instability;

[0029] When the target characteristic quantity is not less than the target threshold, an instability prediction result indicating that no flow instability phenomenon occurs is generated.

[0030] Another aspect of an embodiment of the present invention provides an instability prediction device under distorted intake conditions, the device comprising:

[0031] A measuring module, for measuring a plurality of dynamic pressure signals at different circumferential positions of the casing wall surface during the throttling process of the compressor when the compressor is in the distorted intake condition, wherein the dynamic pressure signals represent the dynamic pressure data of the compressor when the compressor is operated from a stable condition to an unstable condition;

[0032] A calculation module, for performing correlation calculation on the dynamic pressure signal for each circumferential position of the casing wall to obtain a target characteristic quantity, wherein the target characteristic quantity characterizes the irregularity of the dynamic pressure signal;

[0033] An adjustment module, used to adjust the reference threshold according to the target feature quantity to obtain a target threshold;

[0034] A generation module is used to generate an instability prediction result based on the target characteristic quantity measured in real time and the above-mentioned target threshold, wherein the above-mentioned instability prediction result indicates whether the above-mentioned compressor has flow instability phenomenon.

[0035] Another aspect of an embodiment of the present invention provides an electronic device, comprising: one or more processors; and a memory for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the method as described above.

[0036] Another aspect of an embodiment of the present invention provides a computer-readable storage medium storing computer-executable instructions, which are used to implement the method described above when executed.

[0037] Another aspect of an embodiment of the present invention provides a computer program product, wherein the computer program product includes computer executable instructions, and the instructions are used to implement the method described above when executed.

[0038] According to an embodiment of the present invention, by measuring the dynamic pressure signal on the wall near the leading edge of the compressor in real time, the threshold is corrected in real time so as to timely capture the disturbance signal before the stall. At the same time, time-varying thresholds are set at different circumferential positions to achieve instability prediction under distorted intake conditions. It has high robustness and helps to ensure the safe and stable operation of the aircraft engine. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] The above and other objects, features and advantages of the present invention will become more apparent through the following description of the embodiments of the present invention with reference to the accompanying drawings, in which:

[0040] Figure 1 An exemplary system architecture to which the instability prediction method can be applied according to an embodiment of the present invention is schematically shown;

[0041] Figure 2 A flow chart of a method for predicting instability under distorted intake conditions according to an embodiment of the present invention is schematically shown;

[0042] Figure 3 A schematic diagram showing the position of a dynamic pressure sensor near the leading edge of a rotor according to an embodiment of the present invention;

[0043] Figure 4 A schematic diagram of dynamic pressure signals near the leading edge of a rotor at different circumferential positions during a throttling process according to an embodiment of the present invention is shown;

[0044] Figure 5A schematic diagram of dynamic pressure signals near the leading edge of a rotor at different circumferential positions under an unstable working condition according to an embodiment of the present invention is shown;

[0045] Figure 6 A schematic diagram showing the variation of characteristic quantities along with the rotor speed obtained by autocorrelation analysis of dynamic pressure signals near the leading edge of the rotor at different circumferential positions during the throttling process according to an embodiment of the present invention;

[0046] Figure 7 A block diagram of a device for predicting instability under distorted intake conditions according to an embodiment of the present invention is schematically shown;

[0047] Figure 8 A block diagram of an electronic device suitable for implementing the method described above according to an embodiment of the present invention is schematically shown.

[0048] In the above drawings, the meanings of the reference numerals are as follows:

[0049] 1—rotor; 2—leading edge; 3—trailing edge; 4—dynamic pressure sensor; 5—distortion plate. DETAILED DESCRIPTION

[0050] Below, embodiments of the present invention will be described with reference to the accompanying drawings. However, it should be understood that these descriptions are exemplary only and are not intended to limit the scope of the present invention. In the following detailed description, for ease of explanation, many specific details are set forth to provide a comprehensive understanding of embodiments of the present invention. However, it is apparent that one or more embodiments may also be implemented without these specific details. In addition, in the following description, descriptions of known structures and technologies are omitted to avoid unnecessary confusion of concepts of the present invention.

[0051] The terms used herein are only for describing specific embodiments and are not intended to limit the present invention. The terms "comprise", "include", etc. used herein indicate the existence of the features, steps, operations and / or components, but do not exclude the existence or addition of one or more other features, steps, operations or components.

[0052] All terms (including technical and scientific terms) used herein have the meanings commonly understood by those skilled in the art unless otherwise defined. It should be noted that the terms used herein should be interpreted as having a meaning consistent with the context of this specification and should not be interpreted in an idealized or overly rigid manner.

[0053] When using expressions such as "at least one of A, B, and C, etc.", they should generally be interpreted according to the meaning of the expression commonly understood by those skilled in the art (for example, "a system having at least one of A, B, and C" should include but is not limited to a system having A alone, B alone, C alone, A and B, A and C, B and C, and / or A, B, C, etc.).

[0054] An embodiment of the present invention provides an instability prediction method and an instability prediction device under distorted intake conditions. The method includes measuring multiple dynamic pressure signals at different circumferential positions of the casing wall during the compressor throttling process when the compressor is in a distorted intake condition, wherein the dynamic pressure signal represents the dynamic pressure data of the compressor from a stable operating condition to an unstable operating condition; performing correlation calculation on the dynamic pressure signal for each circumferential position of the casing wall to obtain a target characteristic quantity, wherein the target characteristic quantity represents the irregularity of the dynamic pressure signal; adjusting the reference threshold according to the target characteristic quantity to obtain a target threshold; generating an instability prediction result according to the target characteristic quantity and the target threshold measured in real time, wherein the instability prediction result represents whether flow instability occurs in the compressor.

[0055] Figure 1 The exemplary system architecture 100 to which the instability prediction method according to an embodiment of the present invention can be applied is schematically shown. It should be noted that: Figure 1 The examples shown are merely examples of system architectures to which the embodiments of the present invention may be applied, to help those skilled in the art understand the technical content of the present invention, but do not mean that the embodiments of the present invention may not be used in other devices, systems, environments or scenarios.

[0056] like Figure 1 As shown, the system architecture 100 according to this embodiment may include terminal devices 101, 102, 103, a network 104 and a server 105. The network 104 is used to provide a medium for communication links between the terminal devices 101, 102, 103 and the server 105. The network 104 may include various connection types, such as wired and / or wireless communication links, etc.

[0057] Users can use terminal devices 101, 102, 103 to interact with server 105 through network 104 to receive or send messages, etc. Various communication client applications can be installed on terminal devices 101, 102, 103, such as shopping applications, web browser applications, search applications, instant messaging tools, email clients and / or social platform software, etc. (only for example).

[0058] The terminal devices 101 , 102 , and 103 may be various electronic devices having a display screen and supporting web browsing, including but not limited to smart phones, tablet computers, laptop computers, and desktop computers.

[0059] The server 105 may be a server that provides various services, such as a background management server (only as an example) that provides support for websites browsed by users using the terminal devices 101, 102, and 103. The background management server may analyze and process the received data such as user requests, and feed back the processing results (such as web pages, information, or data obtained or generated according to user requests) to the terminal device.

[0060] It should be noted that the instability prediction method provided in the embodiment of the present invention can generally be executed by the server 105. Accordingly, the instability prediction device provided in the embodiment of the present invention can generally be set in the server 105. The instability prediction method provided in the embodiment of the present invention can also be executed by a server or server cluster that is different from the server 105 and can communicate with the terminal devices 101, 102, 103 and / or the server 105. Accordingly, the instability prediction device provided in the embodiment of the present invention can also be set in a server or server cluster that is different from the server 105 and can communicate with the terminal devices 101, 102, 103 and / or the server 105. Alternatively, the instability prediction method provided in the embodiment of the present invention can also be executed by the terminal devices 101, 102, or 103, or can also be executed by other terminal devices different from the terminal devices 101, 102, or 103. Accordingly, the instability prediction device provided in the embodiment of the present invention can also be set in the terminal devices 101, 102, or 103, or can be set in other terminal devices different from the terminal devices 101, 102, or 103.

[0061] It should be understood that Figure 1 The number of terminal devices, networks and servers in the embodiment is only for illustration. Any number of terminal devices, networks and servers may be provided according to implementation requirements.

[0062] Figure 2 A flow chart of a method for predicting instability under distorted intake conditions according to an embodiment of the present invention is schematically shown.

[0063] like Figure 2 As shown, the instability prediction method under distorted intake conditions includes operations S201 to S204.

[0064] In operation S201, when the compressor is in a distorted intake condition, a plurality of dynamic pressure signals at different circumferential positions of the casing wall surface during the compressor throttling process are measured, wherein the dynamic pressure signals represent dynamic pressure data of the compressor when the compressor operates from a stable condition to an unstable condition;

[0065] In operation S202, for each circumferential position of the casing wall, correlation calculation is performed on the dynamic pressure signal to obtain a target characteristic quantity, wherein the target characteristic quantity represents the irregularity of the dynamic pressure signal;

[0066] In operation S203, the reference threshold is adjusted according to the target feature quantity to obtain a target threshold;

[0067] In operation S204, an instability prediction result is generated according to the target characteristic quantity and the target threshold measured in real time, wherein the instability prediction result indicates whether flow instability occurs in the compressor.

[0068] According to an embodiment of the present invention, the distorted intake condition may refer to the airflow non-uniformity that changes with time at the inlet outlet flow field of the compressor. The dynamic pressure signal is a dynamic pressure signal at different circumferential positions on the casing wall near the leading edge of the blade. The compressor may be a centrifugal, diagonal flow or axial flow compressor of a single-stage or multi-stage configuration.

[0069] According to an embodiment of the present invention, a compressor of a high-speed two-stage fan is selected as a research object, and the dynamic pressure signals at different circumferential positions near the leading edge of the compressor rotor are measured to predict instability under distorted intake conditions.

[0070] According to an embodiment of the present invention, for each circumferential position, a correlation calculation can be performed on the dynamic pressure signal of the circumferential position to obtain a target characteristic quantity characterizing the irregularity of the dynamic pressure signal. Based on the target characteristic quantity, a pre-set reference threshold can be adjusted to obtain a target threshold corresponding to the circumferential position.

[0071] It should be noted that the target threshold is adjusted in real time according to the operation of the compressor. The reference threshold can be obtained through the distribution of the characteristic quantity at a certain circumferential position, or can be set according to prior knowledge, such as 0.82.

[0072] According to an embodiment of the present invention, during the operation of the compressor, if the target characteristic quantity measured in real time at the circumferential position meets the target threshold at the circumferential position, an instability prediction result corresponding to the circumferential position can be generated, and the instability prediction result shows that the compressor has flow instability.

[0073] According to an embodiment of the present invention, by measuring the dynamic pressure signal on the wall near the leading edge of the compressor in real time, the threshold is corrected in real time so as to timely capture the disturbance signal before the stall. At the same time, time-varying thresholds are set at different circumferential positions to achieve instability prediction under distorted intake conditions. It has high robustness and helps to ensure the safe and stable operation of the aircraft engine.

[0074] According to an embodiment of the present invention, correlation calculation is performed on the dynamic pressure signal to obtain a target feature quantity, including:

[0075] The dynamic pressure signal is processed by a preset processing algorithm to obtain a target characteristic quantity, wherein the preset processing algorithm includes an autocorrelation analysis method, a fast wavelet analysis method, a fuzzy entropy analysis method or an approximate entropy analysis method.

[0076] According to the embodiments of the present invention, the autocorrelation analysis method, the fast wavelet analysis method, the fuzzy entropy analysis method or the approximate entropy analysis method can analyze the irregularity of the dynamic pressure signal, thereby obtaining the target feature quantity related to the irregularity.

[0077] According to an embodiment of the present invention, a dynamic pressure signal is processed using a preset processing algorithm to obtain a target characteristic quantity, including:

[0078] Based on a preset step size, the dynamic pressure signal is processed using a preset window to obtain a plurality of pressure signals;

[0079] A plurality of pressure signals are processed using a preset processing algorithm to obtain target feature quantities characterizing irregularities.

[0080] According to an embodiment of the present invention, the length of the window (i.e., the preset step length) can be several blade channels or several rotor cycles. The selection of the length mainly depends on the compressor speed and the sampling rate. If the window length is too small, the autocorrelation coefficient is too sensitive to the irregularity of the signal. If the window length is too long, the autocorrelation coefficient (i.e., the target characteristic quantity) will ignore local detail information. In an embodiment of the present invention, the window length is the data collected when the rotor rotates one circle.

[0081] According to an embodiment of the present invention, the target feature quantity is calculated by formula (1):

[0082] (1)

[0083] Among them, P is the pressure signal, wnd is the length of the fixed window, that is, the preset step size, and N wnd is the data length of the dynamic pressure signal in a fixed window, and the autocorrelation coefficient Characterize the target feature quantity, autocorrelation coefficient Describes the correlation between the pressure signal in the current fixed window and the pressure signal in the fixed window at the next moment.

[0084] According to an embodiment of the present invention, the magnitude of the autocorrelation coefficient is related to irregularity. For example, the closer the autocorrelation coefficient is to 1, the lower the irregularity of the dynamic pressure signal is; and the closer the autocorrelation coefficient is to 0, the higher the irregularity of the dynamic pressure signal is.

[0085] According to an embodiment of the present invention, the instability prediction method further includes:

[0086] When the instability prediction result indicates that there is flow instability, a regulation instruction is generated according to the instability prediction result;

[0087] The regulating instruction is transmitted to the regulating mechanism, so that the regulating mechanism regulates the compressor in response to the regulating instruction, so that the compressor recovers to a stable operating condition, wherein the regulating mechanism includes adjustable guide vanes and / or bleed valves.

[0088] According to an embodiment of the present invention, during the compressor throttling process, when the target characteristic quantity at any circumferential position is lower than the target threshold value of the circumferential position, it indicates that the compressor operating point is close to the instability boundary, and the forecasting system issues an adjustment instruction to act on the adjustment mechanism to restore the compressor to a stable working state.

[0089] According to an embodiment of the present invention, adjusting the reference threshold according to the target feature quantity to obtain the target threshold includes:

[0090] Based on the preset correction formula, the target threshold is generated according to the target feature quantity and the reference threshold.

[0091] According to an embodiment of the present invention, the preset correction formula is shown in formula (2):

[0092] (2)

[0093] in, is the reference threshold, is the autocorrelation coefficient of stable working conditions at different circumferential positions, i.e., the target characteristic quantity, is the target threshold.

[0094] According to an embodiment of the present invention, since the numerical value of the autocorrelation coefficient can measure the strength of the overall disturbance of the compressor flow field, formula (2) can be understood as a reference threshold value corrected by disturbances at different circumferential positions. The larger the amplitude of the autocorrelation coefficient change in the place where the disturbance is severe, the smaller the reference threshold value is; the smaller the amplitude of the autocorrelation coefficient change in the place where the disturbance is weak, the larger the reference threshold value is. Therefore, the formula for correcting the threshold value can achieve timely prediction of instability at different circumferential positions.

[0095] According to an embodiment of the present invention, generating an instability prediction result based on a target feature quantity and a target threshold measured in real time includes:

[0096] When the target characteristic quantity is less than the target threshold, an instability prediction result representing the occurrence of flow instability is generated;

[0097] When the target characteristic quantity is not less than the target threshold, an instability prediction result indicating that no flow instability phenomenon occurs is generated.

[0098] Figure 3A schematic diagram showing the location of a dynamic pressure sensor near the leading edge of a rotor according to an embodiment of the present invention is shown.

[0099] In one embodiment, during the compressor test, the irregularity of the dynamic pressure signal of the compressor wall is mainly related to the unsteady fluctuation of the tip clearance leakage flow. The more violent the leakage flow fluctuation is, the better the instability prediction effect is. When approaching the instability boundary, the compressor inlet angle of attack increases, the blade leading edge load increases, and the tip clearance leakage flow has a strong fluctuation near the leading edge. Therefore, in the embodiment of the present invention, the sensor used to analyze the instability prediction under the distorted intake condition is arranged near the leading edge of the rotor. Figure 3 As shown, a row of dynamic pressure sensors are arranged circumferentially at a position 24.47% of the blade tip axial chord length away from the rotor leading edge.

[0100] According to an embodiment of the present invention, in order to simulate the distorted intake condition, a distortion plate is provided at the compressor inlet section, such as Figure 3 As shown in the middle shaded area, when the airflow flows through the distortion plate, due to the obstruction of the distortion plate to the airflow, a vortex will be formed behind the distortion plate, resulting in a low-pressure area. Figure 3 The middle arrow represents the compressor rotation direction. A total of 6 dynamic pressure sensors are arranged along the circumference near the leading edge of the rotor, covering the distortion zone 1#, the distortion exit zones 2# and 3#, the non-distortion zone 4#, and the distortion entry zones 5# and 6#.

[0101] According to an embodiment of the present invention, the dynamic pressure sensor is arranged at a position 24.47% of the axial chord length of the blade tip in front of the leading edge of the rotor. The throttling characteristics of the compressor are obtained by closing the outlet throttle valve. During the throttling process of the compressor, the wall dynamic pressure signals at 6 different circumferential positions are recorded at a sampling rate of 50K. The dynamic pressure signals cover information from stable conditions to unstable conditions.

[0102] Figure 4 A schematic diagram of dynamic pressure signals near the leading edge of the rotor at different circumferential positions during a throttling process according to an embodiment of the present invention is shown. Figure 5 A schematic diagram of dynamic pressure signals near the leading edge of a rotor at different circumferential positions under an unstable operating condition according to an embodiment of the present invention is shown.

[0103] According to an embodiment of the present invention, Figure 4 It can be seen that the fluctuation amplitude of the pressure signal gradually increases from the stable working condition to the unstable working condition. Figure 4 The dashed box shows the characteristics of the flow field after instability. Figure 5 It can be seen that when instability occurs, the flow field disturbance gradually increases and the irregularity of the pressure signal gradually increases.

[0104] Figure 6A schematic diagram showing the variation of characteristic quantities with rotor speed obtained through autocorrelation analysis of dynamic pressure signals near the leading edge of the rotor at different circumferential positions during the throttling process according to an embodiment of the present invention.

[0105] According to an embodiment of the present invention, Figure 6 It can be seen that as the throttling progresses, from stable conditions to unstable conditions, the autocorrelation coefficients at different circumferential positions decrease to varying degrees. At position 3#, which is out of the distortion zone, the decrease in the autocorrelation coefficient is felt first, and the decrease in the autocorrelation coefficient is the largest. At position 5#, which is entering the distortion zone, the decrease in the autocorrelation coefficient is felt last, and the decrease in the autocorrelation coefficient is the smallest.

[0106] According to an embodiment of the present invention, when the same preset threshold is used at different circumferential positions, underreporting or premature forecasting may occur. Taking the dynamic pressure signals monitored by sensors 3# and 5# as an example, if the preset threshold is fixed to the position 3# out of the distortion zone as the standard, such as Figure 6 As shown by the black line in the middle, the prediction can be achieved at the position of the transition out of the distortion zone, but at the 5# position of the transition into the distortion zone, the threshold line and the change curve of the autocorrelation coefficient did not intersect before instability, so the prediction cannot be achieved at the position of the transition into the distortion zone; if the fixed threshold is based on the 5# position of the transition into the distortion zone, an early prediction will occur at the 3# position of the transition out of the distortion zone, and the compressor is still in a stable working state.

[0107] According to the embodiment of the present invention, timely forecasting can be achieved at different circumferential positions by using formula (2), such as Figure 6 As shown by the middle dotted line, the prediction was successfully achieved both when entering the distortion zone 5# and when exiting the distortion zone 3#.

[0108] According to an embodiment of the present invention, the above-mentioned instability prediction method realizes instability prediction at different circumferential positions by adopting a variable threshold, which effectively improves the robustness of instability prediction and has broad application prospects.

[0109] Figure 7 A block diagram of a device for predicting instability under distorted intake conditions according to an embodiment of the present invention is schematically shown.

[0110] like Figure 7 As shown, the instability prediction device 700 under distorted intake conditions includes a measurement module 710 , a calculation module 720 , an adjustment module 730 , and a generation module 740 .

[0111] The measuring module 710 is used to measure a plurality of dynamic pressure signals at different circumferential positions of the casing wall surface during the throttling process of the compressor when the compressor is in a distorted intake condition, wherein the dynamic pressure signal represents the dynamic pressure data of the compressor when the compressor is operated from a stable condition to an unstable condition;

[0112] A calculation module 720 is used to perform correlation calculation on the dynamic pressure signal for each circumferential position of the casing wall to obtain a target characteristic quantity, wherein the target characteristic quantity represents the irregularity of the dynamic pressure signal;

[0113] An adjustment module 730, configured to adjust the reference threshold according to the target feature quantity to obtain a target threshold;

[0114] The generation module 740 is used to generate an instability prediction result according to the target characteristic quantity and the target threshold measured in real time, wherein the instability prediction result indicates whether flow instability occurs in the compressor.

[0115] According to an embodiment of the present invention, by measuring the dynamic pressure signal on the wall near the leading edge of the compressor in real time, the threshold is corrected in real time so as to timely capture the disturbance signal before the stall. At the same time, time-varying thresholds are set at different circumferential positions to achieve instability prediction under distorted intake conditions. It has high robustness and helps to ensure the safe and stable operation of the aircraft engine.

[0116] According to an embodiment of the present invention, the dynamic pressure signal is a dynamic pressure signal at different circumferential positions on the casing wall near the leading edge of the blade.

[0117] According to an embodiment of the present invention, the calculation module 720 includes a calculation unit.

[0118] The calculation unit is used to process the dynamic pressure signal using a preset processing algorithm to obtain a target characteristic quantity, wherein the preset processing algorithm includes an autocorrelation analysis method, a fast wavelet analysis method, a fuzzy entropy analysis method or an approximate entropy analysis method.

[0119] According to an embodiment of the present invention, the calculation unit includes a processing subunit and an obtaining subunit.

[0120] A processing subunit, used for processing the dynamic pressure signal based on a preset step size and using a preset window to obtain a plurality of pressure signals;

[0121] A subunit is obtained, which is used to process a plurality of pressure signals using a preset processing algorithm to obtain a target characteristic quantity characterizing the irregularity.

[0122] According to an embodiment of the present invention, the instability prediction device 700 further includes a second generation module and a transmission module.

[0123] The second generation module is used to generate a regulation instruction according to the instability prediction result when the instability prediction result indicates the existence of flow instability phenomenon;

[0124] The transmission module is used to transmit the adjustment instruction to the adjustment mechanism, so that the adjustment mechanism adjusts the compressor in response to the adjustment instruction so that the compressor recovers to a stable operating condition, wherein the adjustment mechanism includes adjustable guide vanes and / or bleed valves.

[0125] According to an embodiment of the present invention, the adjustment module 730 includes a first generating unit.

[0126] The first generating unit is used to generate a target threshold value based on a preset correction formula according to the target feature quantity and the reference threshold value.

[0127] According to the embodiment of the present invention, the generation module 740 includes a second generation unit and a third generation unit.

[0128] The second generating unit is used to generate an instability prediction result representing the occurrence of flow instability phenomenon when the target characteristic quantity is less than the target threshold value;

[0129] The third generating unit is used to generate an instability prediction result indicating that no flow instability phenomenon occurs when the target characteristic quantity is not less than the target threshold value.

[0130] According to the embodiments of the present invention, any one or more of the modules, submodules, units, and subunits, or at least part of the functions of any one of them can be implemented in one module. According to the embodiments of the present invention, any one or more of the modules, submodules, units, and subunits can be split into multiple modules for implementation. According to the embodiments of the present invention, any one or more of the modules, submodules, units, and subunits can be at least partially implemented as hardware circuits, such as field programmable gate arrays (Field Programmable Gate Array, FPGA), programmable logic arrays (Programmable Logic Arrays, PLA), systems on chips, systems on substrates, systems on packages, application specific integrated circuits (Application Specific Integrated Circuit, ASIC), or can be implemented by hardware or firmware in any other reasonable way of integrating or packaging the circuit, or by any one of the three implementation methods of software, hardware, and firmware, or by a proper combination of any of them. Alternatively, according to the embodiments of the present invention, one or more of the modules, submodules, units, and subunits can be at least partially implemented as computer program modules, and when the computer program module is run, the corresponding functions can be performed.

[0131] For example, any multiple of the measurement module 710, the calculation module 720, the adjustment module 730, and the generation module 740 can be combined in one module / unit / sub-unit for implementation, or any one of the modules / units / sub-units can be split into multiple modules / units / sub-units. Alternatively, at least part of the functions of one or more of these modules / units / sub-units can be combined with at least part of the functions of other modules / units / sub-units and implemented in one module / unit / sub-unit. According to an embodiment of the present invention, at least one of the measurement module 710, the calculation module 720, the adjustment module 730, and the generation module 740 can be at least partially implemented as a hardware circuit, such as a field programmable gate array (FPGA), a programmable logic array (PLA), a system on a chip, a system on a substrate, a system on a package, an application specific integrated circuit (ASIC), or can be implemented by hardware or firmware such as any other reasonable way of integrating or packaging the circuit, or implemented in any one of the three implementation methods of software, hardware, and firmware, or in any appropriate combination of any of them. Alternatively, at least one of the measuring module 710 , the calculating module 720 , the adjusting module 730 , and the generating module 740 may be at least partially implemented as a computer program module, and when the computer program module is executed, a corresponding function may be performed.

[0132] It should be noted that the instability prediction device part in the embodiment of the present invention corresponds to the instability prediction method part in the embodiment of the present invention. The description of the instability prediction device part specifically refers to the instability prediction method part, which will not be repeated here.

[0133] Figure 8 A block diagram of an electronic device suitable for implementing the method described above according to an embodiment of the present invention is schematically shown. Figure 8 The electronic device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention.

[0134] like Figure 8As shown, the electronic device 800 according to an embodiment of the present invention includes a processor 801, which can perform various appropriate actions and processes according to the program stored in the read-only memory (ROM) 802 or the program loaded from the storage part 808 to the random access memory (RAM) 803. The processor 801 may include, for example, a general-purpose microprocessor (such as a CPU), an instruction set processor and / or a related chipset and / or a special-purpose microprocessor (for example, an application-specific integrated circuit (ASIC)), etc. The processor 801 may also include an onboard memory for caching purposes. The processor 801 may include a single processing unit or multiple processing units for performing different actions of the method flow according to an embodiment of the present invention.

[0135] In RAM 803, various programs and data required for the operation of electronic device 800 are stored. Processor 801, ROM 802 and RAM 803 are connected to each other via bus 804. Processor 801 performs various operations of the method flow according to the embodiment of the present invention by executing the programs in ROM 802 and / or RAM 803. It should be noted that the program can also be stored in one or more memories other than ROM 802 and RAM 803. Processor 801 can also perform various operations of the method flow according to the embodiment of the present invention by executing the programs stored in the one or more memories.

[0136] According to an embodiment of the present invention, the electronic device 800 may further include an input / output (I / O) interface 805, which is also connected to the bus 804. The electronic device 800 may further include one or more of the following components connected to the I / O interface 805: an input portion 806 including a keyboard, a mouse, etc.; an output portion 807 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage portion 808 including a hard disk, etc.; and a communication portion 809 including a network interface card such as a LAN card, a modem, etc. The communication portion 809 performs communication processing via a network such as the Internet. A drive 810 is also connected to the I / O interface 805 as needed. A removable medium 811, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 810 as needed, so that a computer program read therefrom is installed into the storage portion 808 as needed.

[0137] According to an embodiment of the present invention, the method flow according to an embodiment of the present invention can be implemented as a computer software program. For example, an embodiment of the present invention includes a computer program product, which includes a computer program carried on a computer-readable storage medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from the network through the communication part 809, and / or installed from the removable medium 811. When the computer program is executed by the processor 801, the above-mentioned functions defined in the system of the embodiment of the present invention are executed. According to an embodiment of the present invention, the system, equipment, device, module, unit, etc. described above can be implemented by a computer program module.

[0138] The present invention also provides a computer-readable storage medium, which may be included in the device / apparatus / system described in the above embodiment; or may exist independently without being assembled into the device / apparatus / system. The above computer-readable storage medium carries one or more programs, and when the above one or more programs are executed, the method according to the embodiment of the present invention is implemented.

[0139] According to an embodiment of the present invention, the computer-readable storage medium may be a non-volatile computer-readable storage medium. For example, it may include, but is not limited to: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM (Erasable Programmable Read Only Memory, EPROM) or flash memory), a portable compact disk read-only memory (Computer Disc Read-Only Memory, CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present invention, the computer-readable storage medium may be any tangible medium containing or storing a program, which may be used by or in combination with an instruction execution system, apparatus or device.

[0140] For example, according to an embodiment of the present invention, the computer-readable storage medium may include the ROM 802 and / or the RAM 803 described above and / or one or more memories other than the ROM 802 and the RAM 803 .

[0141] An embodiment of the present invention also includes a computer program product, which includes a computer program, and the computer program contains program code for executing the method provided by the embodiment of the present invention. When the computer program product runs on an electronic device, the program code is used to enable the electronic device to implement the instability prediction method provided by the embodiment of the present invention.

[0142] When the computer program is executed by the processor 801, the above functions defined in the system / device of the embodiment of the present invention are executed. According to the embodiment of the present invention, the system, device, module, unit, etc. described above can be implemented by a computer program module.

[0143] In one embodiment, the computer program may rely on tangible storage media such as optical storage devices, magnetic storage devices, etc. In another embodiment, the computer program may also be transmitted and distributed in the form of signals on a network medium, and downloaded and installed through the communication part 809, and / or installed from a removable medium 811. The program code contained in the computer program may be transmitted using any appropriate network medium, including but not limited to: wireless, wired, etc., or any suitable combination of the above.

[0144] According to an embodiment of the present invention, the program code for executing the computer program provided by the embodiment of the present invention can be written in any combination of one or more programming languages. Specifically, these computing programs can be implemented using high-level process and / or object-oriented programming languages, and / or assembly / machine languages. Programming languages ​​include, but are not limited to, Java, C++, python, "C" language or similar programming languages. The program code can be executed entirely on the user computing device, partially on the user device, partially on the remote computing device, or entirely on the remote computing device or server. In the case of a remote computing device, the remote computing device can be connected to the user computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computing device (e.g., using an Internet service provider to connect through the Internet).

[0145] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present invention. In this regard, each box in the flowchart or block diagram may represent a module, a program segment, or a part of a code, and the above-mentioned module, program segment, or a part of the code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box may also occur in a different order from the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flowchart, and the combination of boxes in the block diagram or flowchart, can be implemented with a dedicated hardware-based system that performs the specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions. It can be understood by those skilled in the art that the features recorded in the various embodiments and / or claims of the present invention can be combined and / or combined in various ways, even if such a combination or combination is not explicitly recorded in the present invention. In particular, without departing from the spirit and teachings of the present invention, the features described in the various embodiments and / or claims of the present invention may be combined and / or combined in a variety of ways. All of these combinations and / or combinations fall within the scope of the present invention.

[0146] The embodiments of the present invention are described above. However, these embodiments are only for the purpose of illustration, and are not intended to limit the scope of the present invention. Although each embodiment is described above, it does not mean that the measures in each embodiment cannot be used in combination. The scope of the present invention is defined by the attached claims and their equivalents. Without departing from the scope of the present invention, those skilled in the art may make various substitutions and modifications, which should all fall within the scope of the present invention.

Claims

1. A method for predicting instability under distorted intake conditions, characterized in that: The method comprises: When the compressor is in the distorted intake condition, measuring a plurality of dynamic pressure signals at different circumferential positions of the casing wall during the throttling process of the compressor, wherein the dynamic pressure signals represent the dynamic pressure data of the compressor when it operates from a stable condition to an unstable condition; For each circumferential position of the casing wall, based on a preset step length, the dynamic pressure signal is processed using a preset window to obtain a plurality of pressure signals; The plurality of pressure signals are processed by a preset processing algorithm to obtain a target feature quantity characterizing irregularity, wherein the preset processing algorithm includes an autocorrelation analysis method, wherein the target feature quantity characterizes the irregularity of the dynamic pressure signal, and the target feature quantity is calculated by formula (1): （1） Among them, P is the pressure signal, wnd is the length of the fixed window, that is, the preset step size, and N wnd is the data length of the dynamic pressure signal in a fixed window, and the autocorrelation coefficient Characterize the target feature quantity, autocorrelation coefficient It describes the correlation between the pressure signal in the current fixed window and the pressure signal in the fixed window at the next moment. The size of the autocorrelation coefficient is related to the irregularity. Based on a preset correction formula, a target threshold is generated according to the target feature quantity and the reference threshold, wherein the preset correction formula is shown in formula (2): （2） in, is the reference threshold, is the autocorrelation coefficient of stable working conditions at different circumferential positions, i.e., the target characteristic quantity, is the target threshold; An instability prediction result is generated according to the target characteristic quantity measured in real time and the target threshold, wherein the instability prediction result indicates whether flow instability occurs in the compressor.

2. The method according to claim 1, characterized in that The dynamic pressure signals are dynamic pressure signals at different circumferential positions on the casing wall near the leading edge of the blade.

3. The method according to claim 1, characterized in that The method further comprises: In the case where the instability prediction result indicates the existence of flow instability, generating a regulation instruction according to the instability prediction result; The regulating instruction is transmitted to the regulating mechanism, so that the regulating mechanism regulates the compressor in response to the regulating instruction, so that the compressor recovers to a stable operating condition, wherein the regulating mechanism includes adjustable guide vanes and / or bleed valves.

4. The method according to claim 1, characterized in that: According to the target characteristic quantity measured in real time and the target threshold, an instability prediction result is generated, including: When the target characteristic value is less than the target threshold, generating an instability prediction result representing the occurrence of flow instability; When the target characteristic quantity is not less than the target threshold, an instability prediction result indicating that no flow instability phenomenon occurs is generated.

5. A device for predicting instability under distorted intake conditions, characterized in that: The device comprises: A measuring module, configured to measure, when the compressor is in the distorted intake condition, a plurality of dynamic pressure signals at different circumferential positions of the casing wall during the throttling process of the compressor, wherein the dynamic pressure signals represent the dynamic pressure data of the compressor when the compressor is operated from a stable condition to an unstable condition; A calculation module, for performing correlation calculation on the dynamic pressure signal for each circumferential position of the casing wall to obtain a target characteristic quantity, wherein the target characteristic quantity characterizes the irregularity of the dynamic pressure signal; An adjustment module, used for adjusting the reference threshold according to the target feature quantity to obtain a target threshold; A generating module, configured to generate an instability prediction result according to the target characteristic quantity measured in real time and the target threshold, wherein the instability prediction result indicates whether flow instability occurs in the compressor; The calculation module includes: A calculation unit, used to process the dynamic pressure signal using a preset processing algorithm to obtain a target characteristic quantity, wherein the preset processing algorithm includes an autocorrelation analysis method; Wherein, the computing unit comprises: A processing subunit, used for processing the dynamic pressure signal based on a preset step size and using a preset window to obtain a plurality of pressure signals; The subunit is used to process multiple pressure signals using a preset processing algorithm to obtain a target feature quantity that characterizes the irregularity. The target feature quantity is calculated using formula (3): （3） Among them, P is the pressure signal, wnd is the length of the fixed window, that is, the preset step size, and N wnd is the data length of the dynamic pressure signal in a fixed window, and the autocorrelation coefficient Characterize the target feature quantity, autocorrelation coefficient It describes the correlation between the pressure signal in the current fixed window and the pressure signal in the fixed window at the next moment. The size of the autocorrelation coefficient is related to the irregularity. Wherein, the adjustment module includes: The first generating unit is used to generate a target threshold value based on a preset correction formula according to the target feature quantity and the reference threshold value. The preset correction formula is shown in formula (4): （4） in, is the reference threshold, is the autocorrelation coefficient of stable working conditions at different circumferential positions, i.e., the target characteristic quantity, is the target threshold.

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