Aircraft adaptive airflow disturbance attitude correction method and system

Abstract

The invention discloses an aircraft adaptive airflow disturbance attitude correction method and system, and relates to the technical field of aircrafts. The method comprises the following steps: collecting surface fluid-structure interaction state sensing data of an aircraft through a flow field electron microscope sensing net film, generating a real-time updated airflow pressure dynamic topology hologram and a flow field vortex evolution vector flow spectrum, detecting a flow field abnormal electric signal precursor wave, dynamically anchoring an aerodynamic disturbance early warning area, generating a disturbance anchoring signal with priority, and carrying out dynamic disturbance early warning on the aerodynamic disturbance early warning area. And calling a preset bionic stress action instruction rule set to carry out local energy buffer control, extracting flow field disturbance global features based on the airflow pressure dynamic topology hologram and the flow field vortex evolution vector flow spectrum, constructing a disturbance attitude correction dynamic regulation and control network, issuing attitude correction action instructions to control units of all areas, and controlling the attitude correction action instructions to control the flow field vortex evolution vector flow spectrum. And continuous pneumatic surface traveling waves are formed. The adaptive capacity and flight stability of the aircraft in a complex airflow environment can be remarkably improved, and the influence of airflow disturbance on flight safety is reduced.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of aircraft, and particularly relates to an aircraft adaptive airflow disturbance attitude correction method and system. BACKGROUND

[0002] When the aircraft flies in a complex airflow environment, it is easily affected by turbulence, gust, vortex and other airflow disturbances, resulting in unstable flight attitude, and even causing structural vibration, aerodynamic efficiency decline and other problems. The existing attitude correction technology mostly relies on preset models or single sensor data, and has defects such as insufficient sensing accuracy, response lag, limited adaptability, etc.: traditional flow field sensing methods are difficult to capture global subtle airflow changes, and are not timely in identifying early disturbance characteristics such as vortex generation and pressure mutation; the disturbance response mostly adopts a passive adjustment strategy triggered by a fixed threshold, which cannot dynamically optimize the control logic according to the disturbance intensity and regional sensitivity; and local buffering and global correction lack coordination, making it difficult to achieve rapid and stable attitude adjustment under strong disturbance. Therefore, an adaptive attitude correction method and system that can realize real-time sensing of global flow field, intelligent identification of disturbance characteristics and dynamic collaborative regulation is urgently needed to improve the safety and stability of the aircraft in a complex airflow environment. SUMMARY

[0003] The present application provides an aircraft adaptive airflow disturbance attitude correction method, comprising:

[0004] Step S1, acquiring the fluid-structure coupling state sensing data of the surface of the aircraft in real time through a flow field electron microscope sensing retina, generating a real-time updated airflow pressure dynamic topology hologram and a flow field vortex evolution vector flow spectrum;

[0005] Step S2, detecting the abnormal electric signal precursor wave of the flow field based on the airflow pressure dynamic topology hologram and the flow field vortex evolution vector flow spectrum, dynamically anchoring the aerodynamic disturbance warning area, and generating a disturbance anchoring signal with priority;

[0006] Step S3, calling the conditional action instruction in the preset bionic stress action instruction rule set based on the disturbance anchoring signal, and performing local energy buffering control;

[0007] Step S4, extracting the global disturbance feature of the flow field based on the airflow pressure dynamic topology hologram and the flow field vortex evolution vector flow spectrum, and constructing a disturbance attitude correction dynamic regulation network;

[0008] Step S5, issuing an attitude correction action instruction to the control unit of each region based on the disturbance attitude correction dynamic regulation network, and forming a continuous aerodynamic surface traveling wave.

[0009] The aircraft adaptive airflow disturbance attitude correction method as described above, wherein the flow field electron microscope perception retina synchronously collects the fluid-solid coupling state perception data of the aircraft surface in real time during flight, and generates real-time updated airflow pressure dynamic topology hologram and flow field vortex evolution vector flow spectrum includes the following sub-steps:

[0010] Step S11, the flow field electron microscope perception retina synchronously collects the fluid-solid coupling state perception data of the aircraft surface in real time during flight;

[0011] Step S12, based on the fluid-solid coupling state perception data, generate real-time updated airflow pressure dynamic topology hologram and flow field vortex evolution vector flow spectrum.

[0012] The aircraft adaptive airflow disturbance attitude correction method as described above, wherein, based on the airflow pressure dynamic topology hologram and the flow field vortex evolution vector flow spectrum, the flow field abnormal electric signal precursor wave is detected, the aerodynamic disturbance early warning area is dynamically anchored, and the disturbance anchoring signal with priority is generated including the following sub-steps:

[0013] Step S21, based on the airflow pressure dynamic topology hologram and the flow field vortex evolution vector flow spectrum, the flow field abnormal electric signal precursor wave is detected by flow field abnormal feature intelligent comparison tracing;

[0014] Step S22, based on the flow field abnormal electric signal precursor wave and the aircraft aerodynamic sensitive area data, dynamically anchor the aerodynamic disturbance early warning area;

[0015] Step S23, based on the disturbance influence information and the regional sensitivity classification mark, the priority of each aerodynamic disturbance early warning area is generated, and the disturbance anchoring signal with priority is generated.

[0016] The aircraft adaptive airflow disturbance attitude correction method as described above, wherein, based on the disturbance anchoring signal, the conditional action instruction in the preset bionic stress action instruction rule set is called, and local energy buffer control is carried out, including the following sub-steps:

[0017] Step S31, based on the disturbance anchoring signal, the disturbance anchoring signal and the preset bionic stress action instruction rule set are matched with the conditional action instruction;

[0018] Step S32, based on the matched conditional action instruction, the intelligent attitude correction unit of the aerodynamic disturbance early warning area is micro-deformed to carry out local energy buffer control.

[0019] The aircraft adaptive airflow disturbance attitude correction method as described above, wherein, based on the airflow pressure dynamic topology hologram and the flow field vortex evolution vector flow spectrum, the flow field disturbance global feature is extracted, and the disturbance attitude correction dynamic regulation network is constructed including the following sub-steps:

[0020] Step S41, based on the airflow pressure dynamic topology hologram and the flow field vortex evolution vector flow spectrum, generate the flow field disturbance global feature vector;

[0021] Step S42, based on the flow field disturbance global feature vector, through the dynamic global attitude correction regulation algorithm, construct the disturbance attitude correction dynamic regulation network.

[0022] The aircraft adaptive airflow disturbance attitude correction method as described above, wherein the disturbance attitude correction dynamic regulation network issues attitude correction action instructions to the control units of each region to form a continuous aerodynamic surface traveling wave, including the following sub-steps:

[0023] Step S51, based on the disturbance attitude correction dynamic regulation network, the attitude correction action instructions are synchronously issued to the intelligent attitude correction units of each region;

[0024] Step S52, the intelligent attitude correction unit diffuses from the aerodynamic disturbance early warning area to the surrounding area based on the received attitude correction action instructions, forming a continuous aerodynamic surface traveling wave;

[0025] Step S53, real-time monitoring of the attitude correction effect, when the attitude error exceeds the error threshold, the disturbance attitude correction dynamic regulation network updates the parameters in real time.

[0026] The present application also provides an aircraft adaptive airflow disturbance attitude correction system, comprising:

[0027] The data acquisition and atlas generation module acquires the fluid-solid coupling state sensing data of the aircraft surface in real time through the flow field electron microscope perception retina, generates the real-time updated airflow pressure dynamic topology hologram and flow field vortex evolution vector flow spectrum;

[0028] The aerodynamic disturbance early warning area generation module detects the flow field abnormal electric signal precursor wave based on the airflow pressure dynamic topology hologram and the flow field vortex evolution vector flow spectrum, performs dynamic anchoring of the aerodynamic disturbance early warning area, and generates a disturbance anchoring signal with priority;

[0029] The local buffer control module calls the conditional action instruction in the preset bionic stress action instruction rule set based on the disturbance anchoring signal, and performs local energy buffer control;

[0030] The dynamic regulation network construction module extracts the flow field disturbance global feature based on the airflow pressure dynamic topology hologram and the flow field vortex evolution vector flow spectrum, and constructs the disturbance attitude correction dynamic regulation network.

[0031] The attitude correction module issues attitude correction action instructions to the control units of each region based on the disturbance attitude correction dynamic regulation network to form a continuous aerodynamic surface traveling wave.

[0032] The aircraft adaptive airflow disturbance attitude correction system as described above, wherein the data acquisition and atlas generation module specifically comprises:

[0033] The data acquisition submodule synchronously and in real time acquires the fluid-solid coupling state sensing data of the aircraft surface during flight through the flow field electron microscope sensing network retina;

[0034] The atlas generation submodule generates real-time updated airflow pressure dynamic topology hologram and flow field vortex evolution vector flow spectrum based on the fluid-solid coupling state sensing data.

[0035] The aircraft adaptive airflow disturbance attitude correction system as described above, wherein the aerodynamic disturbance early warning area generation module specifically comprises:

[0036] The flow field anomaly electric signal precursor wave detection submodule detects the flow field anomaly electric signal precursor wave through flow field anomaly feature intelligent comparison and tracing based on the airflow pressure dynamic topology hologram and the flow field vortex evolution vector flow spectrum;

[0037] The aerodynamic disturbance early warning area anchoring submodule dynamically anchors the aerodynamic disturbance early warning area based on the flow field anomaly electric signal precursor wave and the aircraft aerodynamic sensitive area data;

[0038] The disturbance anchoring signal generation submodule generates the disturbance anchoring signal with priority based on the disturbance influence information and the regional sensitivity classification mark of the priority of each aerodynamic disturbance early warning area.

[0039] The aircraft adaptive airflow disturbance attitude correction system as described above, wherein the local buffer control module specifically comprises:

[0040] The conditional action instruction matching submodule sequentially matches the conditional action instruction based on the disturbance anchoring signal and the preset set of bionic stress action instruction rules by matching the disturbance anchoring signal and the preset set of bionic stress action instruction rules;

[0041] The local energy buffer control submodule performs local energy buffer control based on the matched conditional action instruction and the intelligent attitude correction unit micro-deformation of the aerodynamic disturbance early warning area.

[0042] The aircraft adaptive airflow disturbance attitude correction system as described above, wherein the dynamic regulation and control network construction module specifically comprises:

[0043] The flow field disturbance global feature vector generation submodule generates the flow field disturbance global feature vector based on the airflow pressure dynamic topology hologram and the flow field vortex evolution vector flow spectrum;

[0044] The disturbance attitude correction dynamic regulation and control network construction submodule constructs the disturbance attitude correction dynamic regulation and control network through the dynamic global attitude correction regulation and control algorithm based on the flow field disturbance global feature vector.

[0045] The aircraft adaptive airflow disturbance attitude correction system as described above, wherein the attitude correction module specifically comprises:

[0046] The attitude correction action instruction issuing submodule synchronously issues attitude correction action instructions to the intelligent attitude correction units of each region based on the disturbance attitude correction dynamic regulation network.

[0047] The aerodynamic surface traveling wave forming submodule diffuses from the aerodynamic disturbance early warning zone to the surrounding region based on the received attitude correction action instructions to form a continuous aerodynamic surface traveling wave.

[0048] The dynamic regulation network updating submodule monitors the attitude correction effect in real time, and updates the parameters of the disturbance attitude correction dynamic regulation network in real time when the attitude error exceeds the error threshold.

[0049] The present application has the following beneficial effects: The present application can realize the full-domain, high-precision and real-time perception of the fluid-structure coupling state by the flow field electron microscope perception retinal and dynamic atlas generation technology, and provide comprehensive basic data for disturbance identification; in combination with the flow field abnormal feature intelligent comparison tracing and dynamic anchoring algorithm, the early disturbance signal can be accurately captured and the early warning zone can be marked in stages, so that the pertinence and timeliness of the disturbance response are improved; the hierarchical control strategy of "local energy buffer + global dynamic regulation" is adopted, the disturbance diffusion is quickly inhibited through the bionic stress action, the attitude is accurately corrected by relying on the full-domain feature extraction and dynamic regulation network, and the response speed and regulation accuracy are considered; through the cooperative execution and closed-loop feedback optimization of the aerodynamic surface traveling wave, the airflow path is actively guided, the aerodynamic characteristics are dynamically optimized, the adaptive ability and flight stability of the aircraft in the complex airflow environment are significantly improved, and the influence of the airflow disturbance on the flight safety is reduced. BRIEF DESCRIPTION OF DRAWINGS

[0050] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the drawings needed to be used in the embodiments or prior art description will be briefly introduced as follows. Obviously, the drawings in the following description are only some embodiments described in the present application, and other drawings can also be obtained by those skilled in the art according to these drawings.

[0051] Figure 1 is a flow chart of an aircraft adaptive airflow disturbance attitude correction method provided by the first embodiment of the present application;

[0052] Figure 2 is a schematic diagram of an aircraft adaptive airflow disturbance attitude correction system provided by the second embodiment of the present application. DETAILED DESCRIPTION

[0053] With reference to the accompanying drawings, the technical solutions in the embodiments of the present application will be described clearly and completely. Obviously, the described embodiments are only some of the embodiments of the present application, but not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative efforts are within the scope of the present application.

[0054] Embodiment one

[0055] As shown in the embodiment one of the present application, a method for correcting the attitude of an aircraft under adaptive air flow disturbance is provided, and the method comprises the following steps: Figure 1 Step S1, collecting the fluid-structure coupling state sensing data of the surface of the aircraft in real time through the flow field electron microscope sensing retina, and generating the real-time updated air flow pressure dynamic topology hologram and the flow field vortex evolution vector flow spectrum;

[0056] Further, the collecting the fluid-structure coupling state sensing data of the surface of the aircraft in real time through the flow field electron microscope sensing retina, and generating the real-time updated air flow pressure dynamic topology hologram and the flow field vortex evolution vector flow spectrum comprises the following sub-steps:

[0057] Step S11, synchronously collecting the fluid-structure coupling state sensing data of the surface of the aircraft in flight in real time through the flow field electron microscope sensing retina;

[0058] Specifically, the flow field electron microscope sensing retina is a high-density distributed flexible sensor network embedded under the skin of the aircraft, and the core sensing units include a differential pressure sensor array for measuring tens of thousands of points of static pressure and dynamic pressure on the surface at a millimeter level spacing, a flow speed sensor for measuring local air flow speed and vortex rotation vector, a micro-pulsation pressure sensor for capturing high-frequency pressure fluctuation, a flexible strain gauge sensor array for monitoring the micro-deformation of the skin, and a temperature sensor array for assisting in judging the flow state.

[0059] When the aircraft is in flight, the flow field electron microscope sensing retina is started, and each sensing unit synchronously and continuously collects the fluid-structure coupling state sensing data in flight at a preset sampling frequency. The fluid-structure coupling state sensing data includes pressure, flow speed and deformation data of the surface of the whole machine body.

[0060] Step S12, generating the real-time updated air flow pressure dynamic topology hologram and the flow field vortex evolution vector flow spectrum based on the fluid-structure coupling state sensing data;

[0061]

[0062] ​Specifically, by real-time interpolation, Gaussian process regression and three-dimensional space interpolation technology, the discrete fluid-structure coupling state perception data is fused into a spatial resolution fine airflow pressure dynamic topology hologram, the pressure gradient change is presented in the form of pseudo color coding, the high pressure impact area and the low pressure vortex area boundary are marked; at the same time, by analyzing the correlation between the pressure gradient and the time sequence of adjacent sensors, the direction of the surface streamline is calculated, the vortex core position, intensity and rotation direction are identified through the flow velocity vector synthesis and the vorticity algorithm, and the flow field vortex evolution vector spectrum which depicts the vortex core position, rotation direction and intensity attenuation evolution in real time is generated; the airflow pressure dynamic topology hologram and the flow field vortex evolution vector spectrum are dynamically updated at a preset frequency.

[0063] Step S2, based on the airflow pressure dynamic topology hologram and the flow field vortex evolution vector spectrum, detecting the flow field abnormal electric signal precursor wave, performing dynamic anchoring of the aerodynamic disturbance early warning area, and generating a disturbance anchoring signal with priority;

[0064] Further, based on the airflow pressure dynamic topology hologram and the flow field vortex evolution vector spectrum, detecting the flow field abnormal electric signal precursor wave, performing dynamic anchoring of the aerodynamic disturbance early warning area, and generating a disturbance anchoring signal with priority includes the following sub-steps:

[0065] Step S21, based on the airflow pressure dynamic topology hologram and the flow field vortex evolution vector spectrum, detecting the flow field abnormal electric signal precursor wave through flow field anomaly feature intelligent comparison and tracing;

[0066] Specifically, based on the airflow pressure dynamic topology hologram and the flow field vortex evolution vector spectrum, the airflow disturbance is monitored in real time, the spatial global pressure distribution data and the vortex evolution parameters are obtained, the data integration and de-dimensioning are performed, the real-time feature components are generated, and the flow field anomaly feature intelligent comparison and tracing formula is calculated, wherein LCY(sj) is the flow field anomaly value at time sj, kz is a spatial coordinate point, jc is a flow field monitoring area, Q is the number of real-time feature components, q is in the range of [1, Q], a q is the feature weight of the qth real-time feature component, tz q (kz,sj) is the qth real-time feature component at spatial coordinate point kz at time sj, tz 0q (kz) is the reference feature value of the normal flow field at spatial coordinate point kz, β is a minimum value to avoid zero denominator, yh qis the evolution time from normal to abnormal for the qth real-time feature component, and is the time scale constant. When the flow field anomaly value is greater than the flow field anomaly threshold value, the abnormal characteristics such as the mutation of the pressure gradient in the atlas and the sudden increase of the vortex intensity are captured, and the flow field anomaly electrical signal precursor wave is identified, which is the high-frequency oscillation of the local pressure information signal or the disordered jump of the vortex vector.

[0067] Step S22, based on the flow field anomaly electrical signal precursor wave and the aerodynamic sensitive region data of the aircraft, the aerodynamic disturbance early warning area is dynamically anchored;

[0068] Specifically, based on the flow field anomaly electrical signal precursor wave to locate the physical position of the sensor generating the abnormal signal, the aerodynamic sensitive region data of the aircraft at this position is obtained according to the physical position of the sensor, and based on the flow field anomaly electrical signal precursor wave and the aerodynamic sensitive region data, the coordinate range and geometric shape of the disturbance influence range are determined to dynamically anchor the aerodynamic disturbance early warning area.

[0069] Step S23, based on the disturbance influence information and the region sensitivity classification, the priority of each aerodynamic disturbance early warning area is marked, and a disturbance anchoring signal with priority is generated;

[0070] Specifically, according to the disturbance intensity, the disturbance development trend, the region sensitivity and the flight state, the threat evaluation marking formula is The threat evaluation value of the aerodynamic disturbance early warning area is calculated, wherein WXP w is the threat evaluation value of the wth aerodynamic disturbance early warning area, rq w is the instantaneous disturbance intensity of the wth aerodynamic disturbance early warning area, rq max is the maximum reference value of the disturbance intensity, rf is the amplification index of the disturbance intensity, drq w is the time change rate of the disturbance intensity of the wth aerodynamic disturbance early warning area, |drq / dt| max is the maximum reference value of the disturbance intensity change rate, qf is the amplification index of the disturbance development trend factor, mg w is the region sensitivity value of the wth aerodynamic disturbance early warning area, R is the number of flight state parameters, and the value range of r is [1, R], χ wr is the threat degree of the rth flight state to the wth aerodynamic disturbance early warning area, fz r is the rth flight state parameter. Based on the threat evaluation value, the priority of each aerodynamic disturbance early warning area is marked, and a disturbance anchoring signal including the three-dimensional coordinates of the aerodynamic disturbance early warning area, the region range, the disturbance type and the priority label is generated.

[0071] Step S3, based on the disturbance anchoring signal, the conditional action instruction in the preset bionic stress action instruction rule set is called to perform local energy buffer control;

[0072] Further, based on the disturbance anchoring signal, the preset conditional action instruction in the bionic stress action instruction rule set is called to perform local energy buffer control, including the following sub-steps:

[0073] Step S31, based on the disturbance anchoring signal, the disturbance anchoring signal and the preset bionic stress action instruction rule set are matched with the conditional action instruction in sequence;

[0074] Specifically, the disturbance anchoring signal of the pneumatic disturbance early warning area is compared with the preset bionic stress action instruction rule set in real time, and the corresponding conditional action instruction is matched therefrom, wherein hundreds of conditional-action mapping relationships are pre-stored in the rule set.

[0075] Step S32, based on the matched conditional action instruction, the intelligent posture correction unit of the pneumatic disturbance early warning area is micro-deformed to perform local energy buffer control;

[0076] Specifically, according to the priority of each pneumatic disturbance early warning area, the matched conditional action instruction is sequentially issued to the intelligent posture correction unit of the pneumatic disturbance early warning area, and the pneumatic disturbance early warning area is driven based on the conditional action instruction to perform micro-deformation, quickly disperse airflow impact energy, perform local energy buffer control, and inhibit disturbance conduction to the core structure of the aircraft body.

[0077] Step S4, based on the airflow pressure dynamic topology hologram and the flow field vortex evolution vector flow spectrum, the flow field disturbance global feature is extracted to construct a disturbance posture correction dynamic regulation network;

[0078] Further, based on the airflow pressure dynamic topology hologram and the flow field vortex evolution vector flow spectrum, the flow field disturbance global feature is extracted to construct a disturbance posture correction dynamic regulation network, including the following sub-steps:

[0079] Step S41, based on the airflow pressure dynamic topology hologram and the flow field vortex evolution vector flow spectrum, a flow field disturbance global feature vector is generated;

[0080] Specifically, while the local energy buffer control is executed, based on the airflow pressure dynamic topology hologram and the flow field vortex evolution vector flow spectrum, the flow field disturbance global feature is extracted by the flow field disturbance global feature extraction formula to generate the flow field disturbance global feature vector, wherein QTX(t) is the flow field disturbance global feature vector at time t, Y is the number of feature components, the value range of y is [1, Y], qy is the whole-machine flow field monitoring area of the aircraft, kl y (zb) is the spatial weight of the yth feature component at the spatial coordinate zb, jb y (zb, t) is the local feature of the yth feature component at the spatial coordinate zb at time t, jz y is the feature reference value of the yth feature component.

[0081] Step S42, based on the flow field disturbance global feature vector, a disturbance attitude correction dynamic regulation network is constructed through a dynamic global attitude correction regulation algorithm.

[0082] Specifically, the specific implementation of the dynamic global attitude correction regulation algorithm is that, based on the flow field disturbance global feature vector, the attitude correction value is calculated through a dynamic global attitude correction regulation formula ZTJ=dg(fz,t)·tanh(MX·QTX+pz), wherein ZTJ is a global attitude correction value vector, dg(fz,t) is a dynamic correlation weight matrix, fz is a current flight state, t is a current time, tanh(·) is an output constraint function, MX is a sensitivity and response mode coding matrix of the global feature mode, QTX is a flow field disturbance global feature vector, and pz is a bias vector. Based on the disturbance influence correlation of each region and the global attitude correction value vector ZTJ, an attitude correction parameter library is constructed, the mapping relationship of each parameter set in the attitude correction parameter library is dynamically optimized through a real-time learning algorithm, a network decision correlation interference regulation index is generated, the flow field change is dynamically adapted, a disturbance attitude correction dynamic regulation network is constructed, and the disturbance attitude correction dynamic regulation network includes specific attitude correction action instructions of each region.

[0083] Step S5, based on the disturbance attitude correction dynamic regulation network, attitude correction action instructions are issued to the control units of each region to form a continuous aerodynamic surface traveling wave.

[0084] Further, based on the disturbance attitude correction dynamic regulation network, attitude correction action instructions are issued to the control units of each region to form a continuous aerodynamic surface traveling wave, including the following sub-steps:

[0085] Step S51, based on the disturbance attitude correction dynamic regulation network, attitude correction action instructions are issued to the intelligent attitude correction units of each region synchronously;

[0086] Specifically, the attitude correction action instructions in the disturbance attitude correction dynamic regulation network are synchronously issued to the intelligent attitude correction units of each region of the aircraft through a wireless network, and the attitude correction action instructions include attitude correction parameters such as deformation amplitude, action timing, and stiffness parameters of each intelligent attitude correction unit.

[0087] Step S52, based on the received attitude correction action instructions, the intelligent attitude correction units diffuse from the aerodynamic disturbance early warning area to the surrounding areas to form a continuous aerodynamic surface traveling wave.

[0088] Specifically, each intelligent attitude correction unit receives an attitude correction action instruction, starts a cooperative action, spreads from the disturbance early warning area to the surrounding area, forms a continuous aerodynamic surface traveling wave, the traveling wave spreads along the aircraft surface at the speed of adaptive airflow disturbance, the wavelength is matched with the vortex, the amplitude is dynamically adjusted according to the airflow intensity, the traveling wave changes the local skin curvature, guides the airflow around the flow path, and dynamically optimizes the airflow interference characteristics.

[0089] Step S53, the attitude correction effect is monitored in real time, and when the attitude error exceeds the error threshold, the disturbance attitude correction dynamic regulation network updates the parameters in real time.

[0090] Specifically, the attitude correction effect is monitored in real time through the flow field electron microscope perception retina, and when the monitored attitude error exceeds the error threshold, the disturbance attitude correction dynamic regulation network updates the correction parameters of the attitude correction action instruction in real time.

[0091] Embodiment two

[0092] As shown in Figure 2 Embodiment two of the present application provides an aircraft adaptive airflow disturbance attitude correction system, comprising:

[0093] The data acquisition and atlas generation module 21 acquires the fluid-solid coupling state sensing data of the surface of the aircraft in real time through the flow field electron microscope perception retina, and generates real-time updated airflow pressure dynamic topology hologram and flow field vortex evolution vector spectrum;

[0094] Further, the data acquisition and atlas generation module 21 comprises the following sub-modules:

[0095] The data acquisition sub-module 211 synchronously acquires the fluid-solid coupling state sensing data of the surface of the aircraft during flight in real time through the flow field electron microscope perception retina;

[0096] The atlas generation sub-module 212 generates real-time updated airflow pressure dynamic topology hologram and flow field vortex evolution vector spectrum based on the fluid-solid coupling state sensing data;

[0097] The aerodynamic disturbance early warning area generation module 22 detects the flow field abnormal electric signal precursor wave based on the airflow pressure dynamic topology hologram and the flow field vortex evolution vector spectrum, dynamically anchors the aerodynamic disturbance early warning area, and generates a disturbance anchor signal with priority;

[0098] Further, the aerodynamic disturbance early warning area generation module 22 comprises the following sub-modules:

[0099] The flow field abnormal electric signal precursor wave detection sub-module 221 detects the flow field abnormal electric signal precursor wave based on the airflow pressure dynamic topology hologram and the flow field vortex evolution vector spectrum through flow field abnormal feature intelligent comparison and tracing;

[0100] The aerodynamic disturbance early warning area anchoring sub-module 222 dynamically anchors the aerodynamic disturbance early warning area based on the flow field anomaly electrical signal precursor wave and the aerodynamic sensitive area data of the aircraft;

[0101] The disturbance anchoring signal generation sub-module 223 generates a disturbance anchoring signal with priority based on the disturbance influence information and the priority of each aerodynamic disturbance early warning area marked by the area sensitivity;

[0102] The local energy buffer control module 23 calls the conditional action instruction in the preset set of bionic stress action instruction rules based on the disturbance anchoring signal, and performs local energy buffer control;

[0103] Further, the local energy buffer control module 23 includes the following sub-modules:

[0104] The conditional action instruction matching sub-module 231 matches the conditional action instruction by sequentially matching the disturbance anchoring signal and the preset set of bionic stress action instruction rules based on the disturbance anchoring signal;

[0105] The local energy buffer control sub-module 232 performs local energy buffer control by deforming the intelligent attitude correction unit of the aerodynamic disturbance early warning area based on the matched conditional action instruction;

[0106] The dynamic regulation network construction module 24 extracts the global disturbance feature of the flow field based on the airflow pressure dynamic topology hologram and the flow field vortex evolution vector flow spectrum, and constructs a disturbance attitude correction dynamic regulation network;

[0107] Further, the dynamic regulation network construction module 24 includes the following sub-modules:

[0108] The flow field disturbance global feature vector generation sub-module 241 generates a flow field disturbance global feature vector based on the airflow pressure dynamic topology hologram and the flow field vortex evolution vector flow spectrum;

[0109] The disturbance attitude correction dynamic regulation network construction sub-module 242 constructs a disturbance attitude correction dynamic regulation network based on the flow field disturbance global feature vector by using a dynamic global attitude correction regulation algorithm;

[0110] The attitude correction module 25 issues attitude correction action instructions to the control units of each region based on the disturbance attitude correction dynamic regulation network, forming a continuous aerodynamic surface traveling wave;

[0111] Further, the attitude correction module 25 includes the following sub-modules:

[0112] The attitude correction action instruction issuing sub-module 251 synchronously issues attitude correction action instructions to the intelligent attitude correction units of each region based on the disturbance attitude correction dynamic regulation network;

[0113] The aerodynamic surface traveling wave forming sub-module 252, the intelligent attitude correction unit diffuses from the aerodynamic disturbance early warning area to the surrounding area based on the received attitude correction action instruction, and forms a continuous aerodynamic surface traveling wave;

[0114] The dynamic regulation network updating sub-module 253 monitors the attitude correction effect in real time, and updates the parameters of the disturbance attitude correction dynamic regulation network in real time when the attitude error exceeds the error threshold value.

[0115] Corresponding to the above-mentioned embodiments, the embodiments of the present application provide a computer storage medium, comprising at least one memory and at least one processor.

[0116] The memory is used for storing one or more program instructions.

[0117] The processor is used for running one or more program instructions to execute the aircraft adaptive airflow disturbance attitude correction method.

[0118] Corresponding to the above-mentioned embodiments, the embodiments of the present application provide a computer readable storage medium, and the computer storage medium contains one or more program instructions, and the one or more program instructions are used for being processed by the processor to execute the aircraft adaptive airflow disturbance attitude correction method.

[0119] The embodiments disclosed in the present application provide a computer readable storage medium, and the computer readable storage medium stores computer program instructions, and when the computer program instructions run on the computer, the computer executes the above-mentioned aircraft adaptive airflow disturbance attitude correction method.

[0120] In the embodiments of the present application, the processor can be an integrated circuit chip with signal processing capability. The processor can be a general processor, a digital signal processor (Digital Signal Processor, DSP for short), an application specific integrated circuit (Application Specific Integrated Circuit, ASIC for short), a field programmable gate array (Field Programmable Gate Array, FPGA for short) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components.

[0121] The disclosed methods, steps, and logic block diagrams in the embodiments of the present application can be implemented or performed with a general- purpose processor, a special purpose processor, or any other processor. The steps of the methods disclosed in the embodiments of the present application can be directly embodied to a hardware code, a processor, or a combination of software modules and hardware modules in the processor. The software modules can reside in memories, such as random access memory (RAM), flash memory, read only memory (ROM), programmable ROM (PROM), erasable PROM (EPROM), electrically EPROM (EEPROM), a register, or other forms of storage. The processor reads information in the memories and completes the steps of the above methods with the aid of hardware.

[0122] The storage medium can be a memory, such as a volatile memory or a non-volatile memory, or can include both volatile and non-volatile memories.

[0123] The non-volatile memory can be a read only memory (ROM), a programmable ROM (PROM), an erasable PROM (EPROM), an electrically EPROM (EEPROM), or a flash memory.

[0124] The volatile memory can be a random access memory (RAM) used as an external cache. By way of example, and not limitation, many forms of RAM are available, such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDR SDRAM), Enhanced SDRAM (ESDRAM), Synchlink DRAM (SLDRAM), and Direct Rambus RAM (DRRAM).

[0125] The storage medium described in the embodiments of the present application is intended to include, but not limited to, these and any other suitable types of memory.

[0126] Those skilled in the art should be aware that, in one or more examples described above, functions described by the present application can be implemented in combination of hardware and software. When the software is applied, the corresponding functions can be stored in a computer readable medium or transmitted as one or more instructions or codes on the computer readable medium. The computer readable medium includes computer storage medium and communication medium, wherein the communication medium includes any medium that facilitates transfer of computer program from one place to another. The storage medium can be any available medium accessible by a general or special purpose computer.

[0127] The above detailed description further describes the purpose, technical solutions and beneficial effects of the present application. It should be understood that the above description is only a specific embodiment of the present application and is not used to limit the protection scope of the present application. Any modification, equivalent replacement, improvement, etc. made on the basis of the technical solutions of the present application should be included in the protection scope of the present application.

Claims

1. An aircraft adaptive airflow disturbance attitude correction method, characterized in that, Comprising: Step S1, collecting the fluid-solid coupling state sensing data of the surface of the aircraft in real time through the flow field electron microscope sensing retina, generating real-time updated airflow pressure dynamic topology hologram and flow field vortex evolution vector flow spectrum; Step S2, based on the airflow pressure dynamic topology hologram and the flow field vortex evolution vector flow spectrum, detecting the flow field abnormal electric signal precursor wave, dynamically anchoring the aerodynamic disturbance early warning area, and generating a disturbance anchoring signal with priority; Step S3, based on the disturbance anchoring signal, calling the conditional action instruction in the preset bionic stress action instruction rule set, and performing local energy buffer control; Step S4, based on the airflow pressure dynamic topology hologram and the flow field vortex evolution vector flow spectrum, extracting the global feature of the flow field disturbance, and constructing a disturbance attitude correction dynamic regulation network; Step S5, based on the disturbance attitude correction dynamic regulation network, issuing attitude correction action instructions to the control units of each region to form a continuous aerodynamic surface traveling wave.

2. The method of claim 1, wherein, Collecting the fluid-solid coupling state sensing data of the surface of the aircraft in real time through the flow field electron microscope sensing retina, generating real-time updated airflow pressure dynamic topology hologram and flow field vortex evolution vector flow spectrum includes the following sub-steps: Step S11, synchronously collecting the fluid-solid coupling state sensing data of the surface of the aircraft in real time through the flow field electron microscope sensing retina; Step S12, based on the fluid-solid coupling state sensing data, generating real-time updated airflow pressure dynamic topology hologram and flow field vortex evolution vector flow spectrum.

3. The method of claim 1, wherein, Based on the airflow pressure dynamic topology hologram and the flow field vortex evolution vector flow spectrum, detecting the flow field abnormal electric signal precursor wave, dynamically anchoring the aerodynamic disturbance early warning area, and generating a disturbance anchoring signal with priority includes the following sub-steps: Step S21, based on the airflow pressure dynamic topology hologram and the flow field vortex evolution vector flow spectrum, detecting the flow field abnormal electric signal precursor wave through flow field abnormal feature intelligent comparison and tracing; Step S22, based on the flow field abnormal electric signal precursor wave and the aircraft aerodynamic sensitive area data, dynamically anchoring the aerodynamic disturbance early warning area; Step S23, based on the disturbance influence information and the regional sensitivity classification, marking the priority of each aerodynamic disturbance early warning area, and generating a disturbance anchoring signal with priority.

4. The method of claim 1, wherein, Based on the disturbance anchoring signal, calling the conditional action instruction in the preset bionic stress action instruction rule set, and performing local energy buffer control includes the following sub-steps: Step S31, based on the disturbance anchoring signal, matching the disturbance anchoring signal and the preset bionic stress action instruction rule set with the conditional action instruction in sequence; Step S32, based on the matched conditional action instruction, the intelligent attitude correction unit of the aerodynamic disturbance early warning area is micro-deformed to perform local energy buffer control.

5. The method of claim 1, wherein, Based on the airflow pressure dynamic topology hologram and the flow field vortex evolution vector flow spectrum, extracting the global feature of the flow field disturbance, and constructing a disturbance attitude correction dynamic regulation network includes the following sub-steps: Step S41, based on the airflow pressure dynamic topology hologram and the flow field vortex evolution vector flow spectrum, generating a flow field disturbance global feature vector; Step S42, based on the flow field disturbance global feature vector, constructing a disturbance attitude correction dynamic regulation network through a dynamic global attitude correction regulation algorithm.

6. An aircraft adaptive airflow disturbance attitude correction system, characterized by, Comprising: The data acquisition and atlas generation module acquires the fluid-solid coupling state sensing data of the surface of the aircraft in real time through the flow field electron microscope sensing retina, generates real-time updated airflow pressure dynamic topology hologram and flow field vortex evolution vector spectrum; The aerodynamic disturbance early warning area generation module detects the flow field abnormal electric signal precursor wave based on the airflow pressure dynamic topology hologram and the flow field vortex evolution vector spectrum, performs dynamic anchoring of the aerodynamic disturbance early warning area, and generates a disturbance anchoring signal with priority; The local buffer control module calls the conditional action instruction in the preset set of bionic stress action instruction rules based on the disturbance anchoring signal, and performs local energy buffer control. The dynamic regulation network construction module extracts the flow field disturbance global feature based on the airflow pressure dynamic topology hologram and the flow field vortex evolution vector spectrum, and constructs a disturbance posture correction dynamic regulation network. The posture correction module issues posture correction action instructions to the control units of each region based on the disturbance posture correction dynamic regulation network, forming a continuous aerodynamic surface traveling wave.

7. An aircraft adaptive airflow disturbance attitude correction system as described in claim 6, wherein, The data acquisition and atlas generation module specifically comprises: The data acquisition sub-module synchronously and in real time acquires the fluid-solid coupling state sensing data of the surface of the aircraft during flight through the flow field electron microscope sensing retina; The atlas generation sub-module generates real-time updated airflow pressure dynamic topology hologram and flow field vortex evolution vector spectrum based on the fluid-solid coupling state sensing data.

8. An aircraft adaptive airflow disturbance attitude correction system as described in claim 6, wherein, The aerodynamic disturbance early warning area generation module specifically comprises: The flow field abnormal electric signal precursor wave detection sub-module detects the flow field abnormal electric signal precursor wave through flow field abnormal feature intelligent comparison and tracing based on the airflow pressure dynamic topology hologram and the flow field vortex evolution vector spectrum; The aerodynamic disturbance early warning area anchoring sub-module dynamically anchors the aerodynamic disturbance early warning area based on the flow field abnormal electric signal precursor wave and the aircraft aerodynamic sensitive region data; The disturbance anchoring signal generation sub-module generates a disturbance anchoring signal with priority based on the disturbance influence information and the regional sensitivity classification mark of each aerodynamic disturbance early warning area.

9. An aircraft adaptive airflow disturbance attitude correction system as described in claim 6, wherein, The local buffer control module specifically comprises: The conditional action instruction matching sub-module sequentially matches the disturbance anchoring signal and the preset set of bionic stress action instruction rules based on the disturbance anchoring signal to match the conditional action instruction; The local energy buffer control sub-module performs local energy buffer control based on the matched conditional action instruction, with the intelligent posture correction unit of the aerodynamic disturbance early warning area micro-deforming.

10. An aircraft adaptive airflow disturbance attitude correction system as described in claim 6, wherein, The dynamic regulation network construction module specifically comprises: The flow field disturbance global feature vector generation sub-module generates a flow field disturbance global feature vector based on the airflow pressure dynamic topology hologram and the flow field vortex evolution vector spectrum; The disturbance posture correction dynamic regulation network construction sub-module constructs a disturbance posture correction dynamic regulation network based on the flow field disturbance global feature vector through a dynamic global posture correction regulation algorithm.

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