Aero-engine model correction method and device, storage medium and electronic equipment

Abstract

The invention relates to the field of aero-engines, in particular to an aero-engine model correction method and device, a storage medium and electronic equipment. The aero-engine model correction method comprises the steps of obtaining component characteristics of a target component of an aero-engine model, wherein the aero-engine model is used for representing performance of an aero-engine in each working state; acquiring test flight data of the aero-engine; and according to the test flight data, characteristic correction is carried out on the component characteristics, so that the aero-engine model is corrected, and the characteristic correction comprises correction of design points and correction of non-design points. Therefore, the test flight data is used for correcting the characteristics of the part, the actual working state of the part can be accurately reflected, the accuracy of the model is improved, the applicability and accuracy of the model are enhanced, the problem that the aero-engine model correction precision is not high in the prior art is solved, and the flight safety is further ensured.

Description

Technical Field

[0001] The present disclosure relates to the field of aeroengines, and particularly to a method, device, storage medium and electronic device for correcting an aeroengine model. Background Art

[0002] With the rapid development of aeroengine technology, its structure has become increasingly complex and the tasks it undertakes have become increasingly onerous. The diversification of flight environments such as large airspaces, wide speed ranges, and high maneuverability has put forward more urgent requirements for the performance analysis and observation technologies of aeroengines. As a mathematical model describing the complex change relationships among various parameters of an engine, the aeroengine model is not only the key cornerstone for the design of aeroengine control systems, state monitoring and health management research, but also an indispensable tool in fields such as performance research, analysis, monitoring, and sensor fault diagnosis and fault-tolerant control design.

[0003] However, in the actual modeling process, there are often deviations between the idealized general characteristics and the actual characteristics of engine components, which results in non-negligible errors between the output results of the established component-level engine model and the actual engine performance parameter values. In addition, changes in factors such as the installation and working environment of each component, the process level of component manufacturing, and the degradation of component performance make it extremely difficult to accurately obtain the characteristics of each component. More complexly, the components work in a coupled manner, causing error accumulation and making it difficult for the accuracy of the aeroengine model to meet the requirements of actual work. Therefore, there is an urgent need for a high-precision method for correcting an aeroengine model to correct the component characteristics of the aeroengine model, so as to better meet the actual needs of aeroengine performance research and application. Summary of the Invention

[0004] The main purpose of the present disclosure is to provide a method, device, storage medium and electronic device for correcting an aeroengine model, aiming to solve the problem of low correction accuracy of the aeroengine model in the prior art.

[0005] To achieve the above object, the present disclosure proposes a method for correcting an aeroengine model, including: Obtaining the component characteristics of a target component of the aeroengine model, where the aeroengine model is used to characterize the performance of the aeroengine in each working state; Obtaining the flight test data of the aeroengine; According to the flight test data, correcting the component characteristics so as to correct the aeroengine model, and the characteristic correction includes the correction of the design point and the correction of the off-design point.

[0006] Optionally, the correcting the component characteristics according to the flight test data includes: Extract the multi-source information features of the aero-engine according to the test flight data; Determine the steady state point of the aero-engine according to the multi-source information features, where the steady state point is the operating point at which the aero-engine enters the target operating state; Perform characteristic correction on the component characteristics according to the steady state point.

[0007] Optionally, the performing characteristic correction on the component characteristics according to the steady state point includes: Determine the design point according to the steady state point; Obtain the steady state performance parameters of the steady state point; Determine the first target performance parameter and the first component characteristic parameter to be adjusted corresponding to the design point according to the steady state performance parameters; Based on the particle swarm optimization algorithm, determine the first component characteristic target parameter corresponding to the design point according to the first target performance parameter; Correct the first component characteristic parameter to be adjusted according to the first component characteristic target parameter.

[0008] Optionally, the determining the first component characteristic target parameter corresponding to the design point based on the particle swarm optimization algorithm according to the first target performance parameter includes: Determine the gas path parameters of the thermal calculation and the measured gas path parameters corresponding to the design point according to the first target performance parameter; Determine the first optimization objective function corresponding to the design point according to the gas path parameters of the thermal calculation and the measured gas path parameters corresponding to the design point; Perform iterative calculation based on the particle swarm optimization algorithm to determine the optimal solution of the first optimization objective function; Determine the first component characteristic target parameter according to the optimal solution of the first optimization objective function.

[0009] Optionally, the performing characteristic correction on the component characteristics according to the steady state point includes: Determine the off-design point according to the steady state point and the design point; Obtain the component characteristic parameters of the corrected design point; Determine the second target performance parameter and the second component characteristic parameter to be adjusted corresponding to the off-design point according to the component characteristic parameters of the corrected design point; Based on the particle swarm optimization algorithm, determine the second component characteristic target parameter corresponding to the off-design point according to the second target performance parameter; Correct the second component characteristic parameter to be adjusted according to the second component characteristic target parameter.

[0010] Optionally, the particle swarm optimization algorithm determines the second component characteristic target parameter corresponding to the off-design point according to the second target performance parameter, including: Determine the gas path parameters of the thermal calculation and the measured gas path parameters corresponding to the off-design point according to the second target performance parameter; Determine the second optimization objective function corresponding to the off-design point according to the gas path parameters of the thermal calculation and the measured gas path parameters corresponding to the off-design point; Perform iterative calculations based on the particle swarm optimization algorithm to determine the optimal solution of the second optimization objective function; Determine the second component characteristic target parameter according to the optimal solution of the second optimization objective function.

[0011] Optionally, before obtaining the component characteristics of the target component of the aero-engine model, it further includes: Obtain the monitoring parameters of the aero-engine, the engine component module library, and the module parameters of each module in the engine component module library; Construct an initial aero-engine model according to the monitoring parameters, the engine component module library, and the module parameters of each module; Perform performance solution on the initial aero-engine model to obtain the performance parameters and state variables of the aero-engine under each working condition; Adjust the initial aero-engine model according to the performance parameters and the state variables to obtain the aero-engine model.

[0012] In addition, to achieve the above object, the present disclosure also provides an aero-engine model correction device, including: A first acquisition module, configured to acquire the component characteristics of the target component of the aero-engine model, where the aero-engine model is used to characterize the performance of the aero-engine under each working state; A second acquisition module, configured to acquire the flight test data of the aero-engine; A correction module, configured to perform characteristic correction on the component characteristics according to the flight test data, so as to correct the aero-engine model, where the characteristic correction includes the correction of the design point and the correction of the off-design point.

[0013] In addition, to achieve the above object, the present disclosure also provides a computer-readable storage medium, on which a computer program is stored, and a processor executes the computer program to implement the above method.

[0014] In addition, to achieve the above object, the present disclosure also provides an electronic device, which includes a memory and a processor, where a computer program is stored in the memory, and the processor executes the computer program to implement the above method.

[0015] In addition, to achieve the above object, the present disclosure also provides a computer program product, which, when run by a processor, implements the above method.

[0016] The beneficial effects that the present disclosure can achieve.

[0017] Through the above technical solutions, the component characteristics of the target components of the aero-engine model and the flight test data of the aero-engine are obtained. According to the flight test data, the component characteristics are corrected so as to correct the aero-engine model. The characteristic correction includes the correction of the design point and the correction of the off-design point. Since the flight test data is the direct feedback during the actual operation process and includes the true performance of the engine under various working conditions. Therefore, using the flight test data to correct the component characteristics can more accurately reflect the actual working state of the components, thereby greatly improving the accuracy of the model. Secondly, the characteristic correction process not only focuses on the performance of the engine under standard design conditions, but also fully considers various non-standard conditions that the engine may encounter during actual operation. This comprehensive correction method further enhances the applicability and accuracy of the model, enabling the model to provide reliable performance prediction and analysis under various working environments, providing a strong guarantee for the subsequent use of the model, and providing strong support for the performance research and application of aero-engines. Further, by improving the accuracy of the aero-engine model and making it closer to the actual working state of the engine, the performance changes of the engine can be predicted and analyzed more accurately, so as to timely discover potential safety hazards and take corresponding measures for prevention and treatment to ensure the safe and smooth progress of the flight. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions in the embodiments of the present disclosure or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the following drawings are only some embodiments of the present disclosure. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on the structures shown in these drawings.

[0019] Figure 1 It is a schematic diagram of the device structure of the hardware operating environment related to the solution of the embodiment of the present disclosure; Figure 2 It is a schematic flowchart of the first embodiment of the aero-engine model correction method of the present disclosure; Figure 3 It is a schematic flowchart of the first embodiment of the adaptive correction method of the present disclosure; Figure 4 It is a schematic diagram of the first embodiment of the evidence theory fusion rule of the present disclosure; Figure 5Schematic diagram for comparing characteristics before and after design point correction in the first embodiment of the aeroengine model correction method of the present disclosure; Figure 6 Flowchart of the first embodiment of the overall component correction method of the present disclosure; Figure 7 Schematic structural diagram of the first embodiment of the aeroengine of the present disclosure; Figure 8 Schematic flowchart of the first embodiment of the modular model performance solution algorithm of the present disclosure; Figure 9 Schematic flowchart of the first embodiment of the modeling calculation method of the present disclosure; Figure 10 Block diagram of the structure of the first embodiment of the aeroengine model correction device of the present disclosure.

[0020] The realization, functional features and advantages of the present disclosure will be further described with reference to the embodiments and the accompanying drawings. Detailed implementation manners

[0021] Next, the technical solutions in the embodiments of the present disclosure will be clearly and completely described with reference to the accompanying drawings in the embodiments of the present disclosure. Obviously, the described embodiments are only a part of the embodiments of the present disclosure, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present disclosure without creative efforts shall fall within the protection scope of the present disclosure.

[0022] Refer to Figure 1 , Figure 1 Schematic diagram of the device structure of the hardware operating environment involved in the solution of the embodiment of the present disclosure.

[0023] Generally, the device includes: at least one processor 301, a memory 302, and an aeroengine model correction program stored on the memory 302 and executable on the processor 301. The aeroengine model correction program is configured to implement the steps of the aeroengine model correction method as described above.

[0024] The processor 301 may include one or more processing cores, such as a 4-core processor, an 8-core processor, etc. The processor 301 may be implemented in at least one of the following hardware forms: DSP (Digital Signal Processing), FPGA (Field-Programmable Gate Array), and PLA (Programmable Logic Array). The processor 301 may also include a main processor and a coprocessor. The main processor is a processor for processing data in the wake state, also known as the CPU (Central Processing Unit); the coprocessor is a low-power processor for processing data in the standby state. In some embodiments, the processor 301 may be integrated with a GPU (Graphics Processing Unit), and the GPU is responsible for rendering and drawing the content to be displayed on the display screen. The processor 301 may also include an AI (Artificial Intelligence) processor, which is used to process operations related to the aeroengine model correction method, enabling the aeroengine model correction method model to autonomously train and learn, improving efficiency and accuracy.

[0025] The memory 302 may include one or more storage media, and the storage media may be non-transitory. The memory 302 may also include high-speed random access memory and non-volatile memory, such as one or more disk storage devices and flash storage devices. In some embodiments, the non-transitory storage media in the memory 302 is used to store at least one instruction, and the at least one instruction is to be executed by the processor 301 to implement the aeroengine model correction method provided in the method embodiments of the present disclosure.

[0026] In some embodiments, the terminal may further optionally include: a communication interface 303 and at least one peripheral device. The processor 301, the memory 302, and the communication interface 303 may be connected through a bus or signal lines. Each peripheral device may be connected to the communication interface 303 through a bus, signal lines, or a circuit board. Specifically, the peripheral devices include at least one of a radio frequency circuit 304, a display screen 305, and a power supply 306.

[0027] The communication interface 303 can be used to connect at least one peripheral device related to I / O (Input / Output) to the processor 301 and the memory 302. In some embodiments, the processor 301, the memory 302, and the communication interface 303 are integrated on the same chip or circuit board; in some other embodiments, any one or two of the processor 301, the memory 302, and the communication interface 303 can be implemented on separate chips or circuit boards, and this embodiment does not limit this.

[0028] The radio frequency circuit 304 is used to receive and transmit RF (Radio Frequency) signals, also known as electromagnetic signals. The radio frequency circuit 304 communicates with the communication network and other communication devices through electromagnetic signals. The radio frequency circuit 304 converts an electrical signal into an electromagnetic signal for transmission, or converts the received electromagnetic signal into an electrical signal. Optionally, the radio frequency circuit 304 includes: an antenna system, an RF transceiver, one or more amplifiers, a tuner, an oscillator, a digital signal processor, a codec chipset, a user identity module card, and so on. The radio frequency circuit 304 can communicate with other terminals through at least one wireless communication protocol. The wireless communication protocol includes but is not limited to: metropolitan area network, generations of mobile communication networks (2G, 3G, 4G, and 5G), wireless local area network, and / or WiFi (Wireless Fidelity) network. In some embodiments, the radio frequency circuit 304 may further include a circuit related to NFC (Near Field Communication), and the present disclosure does not limit this.

[0029] The display screen 305 is used to display the UI (User Interface). The UI may include graphics, text, icons, videos, and any combination thereof. When the display screen 305 is a touch display screen, the display screen 305 also has the ability to collect touch signals on or above the surface of the display screen 305. The touch signals can be input as control signals to the processor 301 for processing. At this time, the display screen 305 can also be used to provide virtual buttons and / or virtual keyboards, also known as soft buttons and / or soft keyboards. In some embodiments, the display screen 305 can be one, the front panel of the electronic device; in other embodiments, the display screen 305 can be at least two, respectively arranged on different surfaces of the electronic device or in a folding design; in still other embodiments, the display screen 305 can be a flexible display screen, arranged on the curved surface or folding surface of the electronic device. Even, the display screen 305 can also be set to an irregular non-rectangular shape, that is, a special-shaped screen. The display screen 305 can be prepared from materials such as LCD (Liquid Crystal Display) and OLED (Organic Light-Emitting Diode).

[0030] The power supply 306 is used to supply power to each component in the electronic device. The power supply 306 can be alternating current, direct current, a disposable battery, or a rechargeable battery. When the power supply 306 includes a rechargeable battery, the rechargeable battery can support wired charging or wireless charging. The rechargeable battery can also be used to support fast charging technology. Those skilled in the art can understand that Figure 1 the structure shown in does not constitute a limitation on the device, and may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0031] In addition, embodiments of the present disclosure also propose a storage medium, on which an aeroengine model correction program is stored. When the aeroengine model correction program is executed by a processor, the steps of the aeroengine model correction method described above are implemented. Therefore, it will not be elaborated here. In addition, the description of the beneficial effects of using the same method will not be elaborated either. For the technical details not disclosed in the storage medium embodiments of the present disclosure, please refer to the description of the method embodiments of the present disclosure. By way of example, the program instructions can be deployed to be executed on one device, or on multiple devices located at one location, or on multiple devices distributed at multiple locations and interconnected by a communication network.

[0032] Those of ordinary skill in the art can understand that all or part of the processes of implementing the methods in the above embodiments can be completed by instructing relevant hardware through a computer program. The above program can be stored in a storage medium. When the program is executed, it can include the processes of the embodiments of the above various methods. Among them, the above storage medium can be a magnetic disk, an optical disc, a read-only memory (ROM), or a random access memory (RAM), etc.

[0033] Referring to Figure 2 , Figure 2 FIG. is a schematic flow chart of the first embodiment of the method for correcting an aero-engine model according to the present disclosure, including the following steps: Step S11: Obtain the component characteristics of the target components of the aero-engine model, where the aero-engine model is used to characterize the performance of the aero-engine in each working state.

[0034] Step S12: Obtain the flight test data of the aero-engine.

[0035] Step S13: According to the flight test data, perform characteristic correction on the component characteristics so as to correct the aero-engine model. The characteristic correction includes the correction of the design point and the correction of the off-design point.

[0036] Exemplarily, the target components are typical components of the aero-engine, which may include a fan, a compressor, etc. Specifically, the baseline estimation method can be used to obtain the component characteristics of the target components.

[0037] Taking the compressor as an example, the main calculation process of the baseline estimation method for the compressor characteristic line can be as follows: First, find the highest efficiency point on each equivalent rotational speed line at each equivalent rotational speed, and use the highest efficiency point as the reference point. Connect these reference points to form a highest efficiency line, which is the baseline. The other points on the baseline except the reference points are called base points. Then determine the compressor stall limit line composed of stall limit points, and then calculate other points on each constant speed line, and then obtain the constant speed characteristics of the entire compressor and determine its characteristic curve. In this way, using the general characteristic diagram as the reference, the operating parameters of each target component of the engine can be used for correction to achieve the adjustment of the aero-engine model.

[0038] Exemplarily, the flight test data can be the flight test data of the aero-engine obtained based on the engine gas path system, flight test, and navigation system of the aero-engine. Obtaining the flight test data of the aero-engine can be obtained from data sources such as public flight test data, web crawlers, and local historical files, or can be the flight test data obtained in real time after obtaining the component characteristics of the target components of the aero-engine model. The embodiments of the present disclosure do not make specific limitations on this.

[0039] Through the above technical solution, the component characteristics of the target components of the aero-engine model and the flight test data of the aero-engine are obtained. According to the flight test data, the component characteristics are corrected to correct the aero-engine model. The characteristic correction includes the correction of the design point and the non-design point. Since the flight test data, as the direct feedback during the actual operation process, contains the true performance of the engine under various working conditions. Therefore, using the flight test data to correct the component characteristics can more accurately reflect the actual working state of the components, thereby greatly improving the accuracy of the model. Secondly, the characteristic correction process not only focuses on the performance of the engine under standard design conditions, but also fully considers various non-standard conditions that the engine may encounter during actual operation. This comprehensive correction method further enhances the applicability and accuracy of the model, enabling the model to provide reliable performance prediction and analysis in various working environments, providing a strong guarantee for the subsequent use of the model, and providing strong support for the performance research and application of aero-engines. Further, by improving the accuracy of the aero-engine model and making it closer to the actual working state of the engine, the performance changes of the engine can be predicted and analyzed more accurately, so as to timely discover potential safety hazards and take corresponding measures for prevention and treatment to ensure the safe and smooth progress of the flight.

[0040] In a possible way, according to the flight test data, the characteristic correction of the component characteristics includes: Extract the multi-source information features of the aero-engine according to the flight test data; Determine the steady-state points of the aero-engine according to the multi-source information features. The steady-state points are the operating points at which the aero-engine enters the target working state; Correct the component characteristics according to the steady-state points.

[0041] It should be understood that the multi-source information features can include various parameters and state information of the aero-engine during the flight test process, which can more comprehensively reflect the operating conditions of the engine. By extracting these features, a more accurate model can be established to more accurately predict the performance of the engine. Extracting the multi-source information features can be text feature extraction and / or image feature extraction for the flight test data. The present disclosure embodiment does not make specific limitations on the feature extraction method.

[0042] Exemplarily, after determining the multi-source information features, multiple steady-state operating points, that is, steady-state points, based on the typical mission profile can be determined according to the multi-source information features, and then the component characteristics are corrected according to the steady-state points.

[0043] In a possible way, according to the steady-state points, the characteristic correction of the component characteristics includes: Determine the design point according to the steady-state points; Obtain the steady-state performance parameters of the steady-state points; Determine the first target performance parameter and the first component characteristic parameter to be adjusted corresponding to the design point according to the steady-state performance parameters; Based on the particle swarm optimization algorithm, determine the first component characteristic target parameter corresponding to the design point according to the first target performance parameter; Correct the first component characteristic parameter to be adjusted according to the first component characteristic target parameter.

[0044] It should be understood that since the steady-state point is the operating point for the aero-engine to enter the target operating state, the steady-state point with a higher engine operating condition can be determined as the design point, and the steady-state performance parameters of the steady-state point can be obtained. Then, according to the steady-state performance parameters of the steady-state point, the first target performance parameter corresponding to the design point can be determined, and then the component characteristic parameters of the design point can be corrected.

[0045] It should also be understood that the correction of the design point is to correct the component characteristics of each rotating component in this operating state, which may include four components: the fan, the compressor, the high-pressure turbine, and the low-pressure turbine. By matching the component characteristics with the actual engine component characteristics, the target parameters of the corrected component-level model can meet the accuracy requirements.

[0046] Exemplarily, the correction of the component characteristics can be to correct the characteristic map. The process of correcting the characteristic map is based on the similarity principle under quasi-steady-state operation, that is, it is considered that the relative trends and shapes of the operating characteristic maps of the actual engine and the general characteristic map are similar, but the absolute parameter ranges of the characteristic maps are quite different. Therefore, the absolute parameters of the characteristic map can be adaptively corrected through actual data, and a characteristic map that meets the requirements in both shape and parameters can be achieved. The similarity conditions satisfy two requirements: the working efficiencies at similar operating points are equal, and the velocity triangles at similar operating points are similar. According to the similarity principle, the working characteristic function of similar operating conditions can be expressed as the n power of the speed ratio:

[0047]

[0048]

[0049] Among them, represents the mass flow rate at operating point 1; represents the mass flow rate at operating point 2; n 1 represents the rotational speed at operating point 1; n 2 represents the rotational speed at operating point 2; W 1 represents the specific work at operating point 1; W 2 represents the specific work at operating point 2; N 1 represents the power at operating point 1; N2 represents the power at operating point 2.

[0050] It should be understood that the correction of the design point can be a performance adaptation process of the design point. Figure 3 It is a schematic flow chart of the first embodiment of the adaptive correction method of the present disclosure. As Figure 3 shown, first, the range and initial values of the compressor / turbine characteristic line adaptation coefficients are defined. These values are the starting points of the optimization process and provide a basis for subsequent algorithm iterations.

[0051] Next, the PSO algorithm (Particle Swarm Optimization) starts to iterate. In this process, the PSO algorithm is used to iteratively calculate and adjust the characteristic line. In each iteration, the algorithm adjusts the characteristic lines of the compressor and the turbine according to the current adaptation coefficients. The characteristic lines describe the performance of the compressor / turbine under different conditions. Therefore, adjusting the characteristic lines can optimize their performance.

[0052] Then, according to the thermodynamic model and the given boundary conditions, the cross-sectional state parameters of the engine are calculated using the adjusted new characteristic lines. These parameters reflect the performance of the engine under different operating conditions and are important bases for evaluating the optimization effect.

[0053] After the calculation is completed, the algorithm evaluates the error between the calculated value and the sensor measurement value. The error is a key indicator for measuring the optimization effect. By comparing the calculated value with the actual measurement value, the advantages and disadvantages of the current adaptation coefficients can be judged. If the error does not reach the preset index, the algorithm will continue to iterate, adjust the adaptation coefficients and recalculate until the error meets the index.

[0054] Finally, when the error meets the requirements, the algorithm outputs the optimal adaptation coefficient parameters. These parameters represent the optimal adjustment method of the compressor / turbine characteristic line under the current conditions and can achieve the optimization of the engine performance. The entire process effectively optimizes the adaptation coefficients of the compressor / turbine characteristic line by combining the PSO algorithm and the thermodynamic model, improving the performance of the engine.

[0055] Exemplarily, in the performance adaptation process of the design point, two types of adaptation parameters can be defined: one type is the component characteristic parameter x to be adjusted, which belongs to the independent variable and can include the air mass flow rate, the compressor pressure ratio and isentropic efficiency, the turbine expansion ratio and isentropic efficiency, etc. The first component characteristic parameter to be adjusted can be determined according to the component characteristic parameter x to be adjusted. The second type is the target performance parameter z, which belongs to the dependent variable and is a measurable gas path parameter, which can include the fuel flow rate, the gas path pressures and temperatures at the inlets and outlets of each component, etc. The thermodynamic relationship between these two types of adaptation parameters can be described as:

[0056] Among them, z ∈ R is the measured gas path parameter vector, M is the number of measured gas path parameters, x ∈ R is the component characteristic parameter vector to be corrected, R is a real number, N is the number of component characteristic parameters to be corrected, v is the measurement noise vector.

[0057] Exemplarily, the design point performance adaptive process can be regarded as an optimization process and can be implemented by using a particle swarm optimization algorithm. Figure 4 is a schematic diagram of the first embodiment of the evidence theory fusion rule of the present disclosure. As Figure 4 shown, after the algorithm starts, initialization is first performed. This step includes randomly generating the positions and velocities of particles in the D-dimensional problem space. Then the algorithm enters the stage of evaluating particles, and the fitness values of each particle are obtained according to the fitness function. Subsequently, it will be judged whether the optimization goal is reached. If the goal has been reached, the algorithm ends and outputs the current optimal particle position and its fitness. If the optimization goal has not been reached yet, it will enter the stage of updating the optimal position, and the current optimal solution is updated according to the fitness value of the particle. Specifically, it can be achieved by comparing the particle fitness with its individual optimal value pbest , if it is better than pbest , then the current particle position is assigned to pbest Compare the particle fitness with the global optimal value gbest , if it is better than gbest then the current particle position is assigned to gbest . Then, it enters the iterative loop stage. In each iteration, the particle position is first updated, which usually involves updating the velocity and position of the particle to explore a better solution in the space. After updating the particle position, the algorithm evaluates the particle again and adjusts the behavior of the particle according to the fitness value. This iterative process will continue until the maximum number of generations is reached, that is, the algorithm reaches the set maximum number of iterations. At this time, whether the optimization goal is reached or not, the algorithm will end and output the current found optimal particle position and its fitness value.

[0058] In a possible way, based on the particle swarm optimization algorithm, according to the first target performance parameter, the first component characteristic target parameter corresponding to the design point is determined, including: According to the first target performance parameter, determine the gas path parameters of the thermal calculation and the measured gas path parameters corresponding to the design point; According to the gas path parameters of the thermal calculation and the measured gas path parameters corresponding to the design point, determine the first optimization objective function of the design point; Perform iterative calculations based on the particle swarm optimization algorithm to determine the optimal solution of the first optimization objective function; Determine the first component characteristic target parameters according to the optimal solution of the first optimization objective function.

[0059] Exemplarily, under the working condition environment conditions and operating conditions corresponding to the design point, the gas path parameters z of the thermal calculation can be compared with the measured gas path parameters, and the root mean square error thereof can be used as the optimization objective function Fitness , that is, the first optimization objective function, and a set of optimal component characteristic parameters can be obtained through optimization iteration. The first optimization objective function Fitness can be expressed as:

[0060] where i represents the i th item of the gas path parameters, M represents the total number of gas path parameters, z i,predicted represents: the gas path parameter value calculated by the engine model, z i,actual represents the gas path parameter value of the actual engine.

[0061] After the performance adaptation at the design point, the corrected component design point characteristic parameters can be obtained. Combining with the measured gas path parameters, the design point characteristic parameters on the component general characteristic line can be sorted out, usually in the form of relative reduced parameters. Then, by comparing with the design point characteristic parameters before adaptation, the design point performance adaptation coefficient can be obtained:

[0062]

[0063]

[0064]

[0065] where represents the adaptation speed coefficient, represents the adaptation pressure ratio coefficient, represents the adaptation flow coefficient, represents the adaptation efficiency coefficient, and the subscript n represents the speed, and the subscript π represents the pressure ratio, and the subscript g represents the flow rate, and the subscript η represents the efficiency. and are the relative reduced speeds at the design point before and after adaptation respectively, and are the relative pressure ratios (for compressors) or expansion ratios (for turbines) of the design points before and after adaptation, respectively, is the pressure ratio (for compressors) or expansion ratio (for turbines) of the design point before adaptation; and are the relative reduced flow rates of the design points before and after adaptation, respectively, and are the relative isentropic efficiencies of the design points before and after adaptation, respectively. In the subscripts, DP represents the design point, 0 represents before adaptation, cor represents the reduced parameter, rel represents the relative parameter.

[0066] Exemplarily, the obtained design point adaptation coefficients are applied to the entire component characteristic curve. Taking the compressor module as an example, the schematic comparison diagram before and after correction is as shown in Figure 5 The parameter of the corrected component characteristic curve can be expressed as:

[0067]

[0068]

[0069]

[0070] In a possible way, according to the steady state point, the characteristic correction of the component is carried out, including: Determine the off-design points according to the steady state point and the design point; Obtain the component characteristic parameters of the corrected design point; According to the component characteristic parameters of the corrected design point, determine the second target performance parameters and the second component characteristic parameters to be adjusted corresponding to the off-design points; Based on the particle swarm optimization algorithm, according to the second target performance parameters, determine the second component characteristic target parameters corresponding to the off-design points; Correct the second component characteristic parameters to be adjusted according to the second component characteristic target parameters.

[0071] It should be understood that for a turbofan engine, the off-design points can be all other operating points within the envelope excluding the design points. Therefore, the correction of the off-design points can be carried out on the basis of the correction results of the design points.

[0072] The design point correction performs an overall transformation on the component characteristic diagrams of each component according to certain rules, making the corrected component characteristic diagrams closer to the real component characteristics, which also indicates that the errors in other operating conditions (i.e., non-design points) of the engine model are relatively reduced. However, it can be found from the simulation results that when performing the steady-state model calculation of non-design points based on the design point correction results, the model accuracy is still poor, and it is necessary to further correct the component characteristics of non-design points. At this time, the design point can be used as a fixed reference point.

[0073] Refer to Figure 6 , Figure 6 which is the flowchart of the first overall embodiment of the component correction method of the present disclosure. As Figure 6 shown, first, in the image processing or data preprocessing stage, adjustment operations such as scaling, stretching, and translation are performed on the general characteristic diagram. These adjustments are aimed at making the general characteristic diagram adapt to subsequent analysis or processing requirements, ensuring the accuracy and availability of the data.

[0074] Next, in combination with the design point data, data matching and measurement point determination operations are performed on the adjusted general characteristic diagram. Among them, the design point data is determined according to the flight test data of the airborne measurement points, which represents the key performance points of the engine under different operating conditions. Through data matching and the determination of measurement points, the accuracy and consistency between the general characteristic diagram and the design point data can be ensured.

[0075] Then, based on the non-design point data, correction coefficients are established and a complete characteristic diagram is generated. Among them, the non-design point data is also determined according to the flight test data of the airborne measurement points, which provides the performance information of the engine under more operating conditions. By establishing correction coefficients, the general characteristic diagram can be further corrected and improved to more accurately reflect the actual performance of the engine. The determination of correction coefficients and the generation of a complete characteristic diagram contribute to improving the accuracy of engine performance prediction.

[0076] Finally, based on the optimization algorithm, the objective function is calculated according to the correction coefficients and the complete characteristic diagram to obtain the corrected characteristic diagram. The optimization algorithm plays a key role here. It can find the optimal correction coefficients through iterative calculation and parameter adjustment, making the error between the corrected characteristic diagram and the actual performance the smallest. Through the application of the optimization algorithm, the accuracy and reliability of engine performance prediction can be further improved.

[0077] Exemplarily, the variable operating condition adaptive coefficient can be defined as follows:

[0078]

[0079]

[0080] Among them, the superscript * represents the component characteristic parameters after off-design condition adaptation.

[0081] In order to correct the off-design part of the component characteristic curve non-linearly, the above off-design condition adaptation coefficient can be defined as an adaptation coefficient function in the quadratic form of the reduced speed. :

[0082] Among them, a , b , c are all adaptation function coefficients. is the relative reduced speed at the off-design point. Since the characteristic diagram has been processed based on the design point in the previous steps, and the performance at the design point is used as a fixed reference point during the off-design condition adaptation process, the coefficient a = 1. is the relative reduced speed at the design point, equal to 1. The subscript OD represents the off-design point.

[0083] Exemplarily, the off-design condition performance adaptation can also be regarded as an optimization problem, and its optimization process is the same as that of the design point adaptation method. Under off-design condition environmental conditions and operating conditions, the gas path parameters obtained from the thermal calculation are compared with the measured gas path parameters, and their root mean square error is used as the optimization objective function Fitness , and the values of the coefficients b and c are obtained through optimization iteration, so as to obtain the optimal off-design condition adaptation coefficient function. Therefore, in a possible way, based on the particle swarm optimization algorithm, according to the second target performance parameter, the second component characteristic target parameter corresponding to the off-design point is determined, including: Determine the gas path parameters obtained from the thermal calculation and the measured gas path parameters corresponding to the off-design point according to the second target performance parameter; Determine the second optimization objective function corresponding to the off-design point according to the gas path parameters obtained from the thermal calculation and the measured gas path parameters corresponding to the off-design point; Perform iterative calculation based on the particle swarm optimization algorithm to determine the optimal solution of the second optimization objective function; Determine the second component characteristic target parameter according to the optimal solution of the second optimization objective function.

[0084] Exemplarily, the optimization objective function Fitness , that is, the second optimization objective function can be shown as follows:

[0085] Among them, i represents a certain item in the gas path parameters of a single operating condition point; j represents a certain item among all operating condition points; mrepresents the total number of operating points to be corrected; M represents the total number of gas path parameters of a single operating point.

[0086] In a possible way, before obtaining the component characteristics of the target component of the aero-engine model, it further includes: Obtaining the monitoring parameters of the aero-engine, the engine component module library, and the module parameters of each module in the engine component module library; Constructing an initial aero-engine model according to the monitoring parameters, the engine component module library, and the module parameters of each module; Performing performance solution on the initial aero-engine model to obtain the performance parameters and state variables of the aero-engine under each operating condition; Adjusting the initial aero-engine model according to the performance parameters and state variables to obtain the aero-engine model.

[0087] Exemplarily, in order to construct the aero-engine model, model simplification and module division can be performed according to the overall gas flow path of the aero-engine and based on the existing monitoring parameters and modular modeling methods.

[0088] Referring to Figure 7 , Figure 7 is the structural schematic diagram of the first embodiment of the aero-engine of the present disclosure. As Figure 7 shown, the engine component module library can include modules such as an intake duct, a fan, a high-pressure compressor, a combustion chamber, a high-pressure turbine, a low-pressure turbine, a mixing chamber, and a tail nozzle.

[0089] Specifically, the specific ideas for modeling each component will be elaborated below.

[0090] (1) Intake duct Since when the aircraft is flying under different altitudes and Mach numbers, the working states of parameters such as the temperature and pressure at the engine inlet vary greatly. Therefore, the environmental parameters under known altitude H , Mach number Ma and other parameters can be calculated according to empirical formulas.

[0091] The static air temperature T 0 and the static pressure P 0 can be calculated according to the following calculation formulas: When km:

[0092]

[0093] When km:

[0094]

[0095] Total temperature at the inlet of the inlet duct and total pressure at the inlet can be calculated according to the following calculation formula:

[0096]

[0097] Among them, k is the adiabatic coefficient of air.

[0098] Total temperature at the outlet of the inlet duct and total pressure at the outlet can be calculated according to the following calculation formula:

[0099]

[0100] Among them, is the total pressure recovery coefficient of the inlet duct, indicating the magnitude of the total pressure loss. When there is no known inlet duct characteristic, it can be estimated according to the following calculation formula:

[0101]

[0102] It should be noted that when the ground is in a non-standard atmospheric environment, the static pressure and static temperature at high altitude can be calculated first according to the standard atmospheric environment, and then corrected.

[0103] (2) Compression component It should be understood that the compression component of a turbofan engine consists of two parts: a fan and a high-pressure compressor. Their aerodynamic and thermodynamic processes are similar, but the high-pressure compressor has the characteristic of cooling output, which makes the high-pressure compressor play a unique role in the operation of the engine.

[0104] In terms of calculation logic, the compressor module has two different calculation methods, namely the design point calculation logic and the off-design point calculation logic. The design point calculation logic depends on design parameters, while the off-design point calculation logic requires interpolation operations. This flexibility enables the compressor module to adapt to different working conditions.

[0105] In the off-design point calculation logic, first perform interpolation operations. Using the Rline curve and the relative reduced speed, find the reduced flow rate, pressure ratio, and efficiency on the characteristic diagram. Then, using the pressure ratio and efficiency obtained by interpolation, calculate the physical properties parameters at the outlet of the compressor in the actual situation. Among them, key data such as the reduced flow rate, pressure ratio, and efficiency can be obtained by looking up the characteristic diagram.

[0106] In addition, the aero-engine model also has a cold air output module, which can obtain the cold air parameters at the outlet of the high-pressure compressor by specifying the cold air output flow ratio. The compressor module calculates the torque as another output, adjusts the reduced speed line by iterating the speed value, and realizes the power balance between the compressor and the turbine. Finally, the flow residual of the compressor is calculated, and the Rline line is iterated to reduce the residual between the reduced flow at the engine inlet and the reduced flow obtained by interpolating the characteristic map. In this way, through reasonable calculation logic and parameter adjustment, it can be ensured that the engine can operate efficiently and stably under various working conditions.

[0107] Exemplarily, the compressor pressure ratio π c can be calculated by the following calculation formula:

[0108] where is the total pressure at the outlet of the compressor, is the total pressure at the inlet of the compressor.

[0109] The isentropic power of the compressor can be calculated by the following calculation formula:

[0110] The actual power of the compressor can be calculated by the following calculation formula:

[0111] where is the isentropic power of the compressor, is the actual power of the compressor, is the specific heat capacity at constant pressure, is the total temperature at the outlet of the compressor, is the total temperature at the outlet of the compressor after isentropic compression, is the total temperature at the inlet of the compressor, is the enthalpy value at the outlet of the compressor in the isentropic compression process, is the enthalpy value at the outlet of the compressor, is the enthalpy value at the inlet of the compressor.

[0112] The isentropic efficiency of the compressor η c can be calculated by the following calculation formula:

[0113] The compression process of the compressor is a polytropic process. According to the calculation method of the isentropic compression process, the total temperature at the outlet of the compressor can be calculated by using the entropy function for variable specific heat : a. First, calculate the ideal entropy function at the outlet of the isentropic compression process ; b. Iteratively calculate the ideal outlet total temperature according to ; ; c. Calculate the ideal enthalpy value at the isentropic compression outlet according to the ideal outlet total temperature and the outlet pressure ; d. Obtain the compressor efficiency from the characteristic curve by reading the pressure ratio and the reduced speed, and then calculate the actual outlet enthalpy value according to the compressor efficiency ; the compressor efficiency can be calculated according to the following calculation formula: ;

[0114] e. Finally, iteratively calculate the outlet temperature according to ;

[0115] Among them, s represents the parameter under the ideal state; t represents the total parameter; represents the inlet entropy function; in represents the inlet; out represents the outlet; ln represents taking the logarithm calculation; h represents the unit enthalpy; H represents the calculation function of the unit enthalpy.

[0116] It should be understood that when calculating the parameters at the bleed air outlet, generally one of the following three conditions is required: (1) The relative enthalpy increase of the bleed air is known, and it is assumed that the polytropic efficiency of the compression process from the inlet to the bleed air outlet is the same as that to the outlet; (2) The bleed air pressure ratio and the bleed air adiabatic efficiency (or the bleed air characteristic diagram) are known; (3) The number of stages of the bleed air, the bleed air pressure ratio and the bleed air efficiency are known, and can be expressed by the following calculation formula:

[0117]

[0118] Among them, Z is the number of stages of the axial flow compressor, X is the stage number of the bleed air at the intermediate stage, the subscript C represents the compressor, bleed represents the bleed air, pol represents the polytropic parameter.

[0119] The outlet flow rate and the total pressure can be calculated by the following calculation formula:

[0120]

[0121] Among them, is the air extraction coefficient.

[0122] Compressor work consumption can be calculated according to the following calculation formula:

[0123] When calculating at off-design points, the characteristics of the compressor are required. Its characteristics can be described as follows:

[0124]

[0125] Among them, is the inlet corrected flow rate, is the relative corrected speed, is the guide vane angle.

[0126] Usually, when performing off-design point calculations for the compressor, the inlet total temperature , total pressure , and speed are known, while the compressor pressure ratio often needs to be assumed first. The calculation steps are as follows: a. First, calculate the relative corrected speed of the compressor :

[0127] b. The guide vane angle can be determined according to the relative reduced speed , and the inlet corrected flow rate and efficiency of the compressor can be interpolated from the compressor pressure ratio , relative corrected speed and guide vane angle using the compressor characteristic diagram; c. Calculate the compressor inlet mass flow rate :

[0128] Among them, represents the inlet total pressure, represents the inlet total temperature.

[0129] (3) Combustor Exemplarily, based on the combustion model equation of mass conservation and energy conservation, the total temperature at the combustor outlet can be calculated according to the following calculation formula:

[0130] Among them, is the specific heat at constant pressure of the fuel, is the specific heat at constant pressure of the combustion gas, is the calorific value of fuel combustion, is the combustion efficiency, is the enthalpy value of the fuel, is the fuel flow rate, is the inlet flow rate of the combustion chamber, is the outlet flow rate of the combustion chamber.

[0131] Fuel - air ratio can be calculated according to the following formula:

[0132] Among them, is the specific enthalpy at the outlet of the combustion chamber, is the specific enthalpy at the inlet of the combustion chamber.

[0133] (4) Turbine unit It should be understood that the high - temperature and high - pressure gas at the outlet of the combustion chamber expands in the gas turbine to generate mechanical energy, driving the compressor and the accessories of the gas turbine to do work.

[0134] Exemplarily, the turbine expansion ratio can be calculated according to the following formula:

[0135] Among them, is the total pressure at the inlet of the turbine, is the total pressure at the outlet of the turbine.

[0136] Turbine isentropic efficiency can be calculated according to the following formula: Turbine expansion work can be calculated according to the following formula:

[0137] Among them, is the turbine expansion work; is the turbine expansion work under ideal conditions; is the total temperature at the inlet of the turbine; is the total temperature at the outlet of the turbine; is the total temperature at the outlet of the turbine under ideal conditions; is the specific enthalpy at the inlet of the turbine; is the specific enthalpy at the outlet of the turbine.

[0138] Taking the high-pressure turbine as an example, the design point calculation method is similar to that of the compressor. The compression process of the turbine is also a polytropic process. The outlet total temperature can be calculated by using the entropy function for variable specific heat according to the calculation method of the isentropic compression process. : a. First, calculate the ideal entropy function at the outlet of the isentropic compression process. ; b. According to Iteratively find the ideal outlet total temperature ; c. According to the ideal outlet total temperature and the outlet pressure Find the ideal enthalpy value at the isentropic compression outlet; d. Read the characteristic curve from the pressure ratio and reduced speed to obtain the turbine efficiency , and calculate the actual outlet enthalpy value according to the turbine efficiency . Among them, the turbine efficiency can be calculated according to the following calculation formula :

[0139] e. Finally, according to Iteratively find the outlet temperature.

[0140] When calculating off-design points, the characteristics of the turbine are required. Its characteristics can be described by the following calculation formula:

[0141]

[0142] Among them, is the inlet corrected flow rate, is the relative corrected speed, is the guide vane angle.

[0143] It should be understood that when calculating the off-design points of the turbine, the inlet total temperature , total pressure , and speed are known data, while the pressure ratio often needs to be assumed first. The assumed parameters can be optimized and solved using boundary conditions in the thermodynamic model. The calculation steps are as follows: a. First, calculate the relative corrected speed and reduced flow rate of the turbine:

[0144]

[0145] b. According to The guide vane angle can be determined (if needed), and then according to Interpolate the turbine characteristic map to obtain the turbine's inlet converted flow rate and efficiency ; c. From the assumed pressure ratio , calculate the outlet pressure :

[0146] d. From the inlet temperature , pressure calculate the inlet enthalpy value :

[0147] e. From the inlet temperature , pressure calculate the isentropic enthalpy value :

[0148] f. From the efficiency and the inlet enthalpy value , the isentropic enthalpy value calculate the outlet enthalpy value :

[0149] g. From the outlet enthalpy value and the outlet pressure iteratively calculate the outlet temperature :

[0150] (5)Mixing chamber It should be understood that the calculation of the mixing chamber can be divided into two parts: design point calculation and off-design point calculation. The purpose of the design point calculation is to design the areas of the two inlets of the mixing chamber. The off-design point calculation uses the areas obtained from the design point calculation. Its purposes are, first, to confirm whether the mixing chamber can operate in a stable state, and second, to calculate the total pressure of the gas at the outlet of the mixing chamber.

[0151] Exemplarily, first, after knowing the physical properties of the two gas streams at the engine inlet, the total enthalpy and total temperature of the outlet gas can be calculated using the energy conservation equation. For the design point calculation, the main stream of the two inlet gas streams can be determined first, and the Mach number Ma of the main stream can be specified. Then, using the Mach number Ma of the main stream gas, the static pressure is iteratively reduced to minimize the Mach number Ma residual, thereby solving for the static temperature and static pressure of the main stream gas. Then, using the Kutta condition that the static pressures of the main stream and the secondary stream should be the same, the static pressure of the secondary stream can be obtained, and thus the Mach number Ma of the secondary stream can be obtained. Next, using the ideal gas state equation, the areas of the main stream and the secondary stream can be calculated, thereby determining the areas of the two inlet gas streams of the mixing chamber.

[0152] For off-design calculations, first, the areas of the two designed inlets can be assigned. Then, since the Mach numbers Ma of the two gas streams are unknown, the Mach numbers Ma can be assumed respectively, and the calculated area of the mixing chamber can be obtained using the ideal gas state equation, thereby obtaining the residual between the calculated area and the designed area of the mixing chamber. The residual of the static pressure of the gas is iteratively reduced to obtain the static pressure values of the two gas streams at the inlet of the mixing chamber. Furthermore, the total pressure value of the gas at the outlet of the mixing chamber is calculated. By assuming the Mach number Ma and the total pressure value of the outlet gas, the calculated area and the calculated momentum of the outlet gas can be obtained.

[0153] In this way, the mixing chamber has two residual quantities: the residual between the calculated area and the designed area, and the residual between the outlet momentum and the momenta of the two inlet gas streams. By iterating the total pressure and the Mach number Ma at the outlet of the mixing chamber to reduce the residual, the total pressure at the outlet of the mixing chamber (i.e., the total pressure solved based on the momentum balance equation) is finally obtained. Finally, the residual quantity of the mixing chamber is calculated. For design point calculations, the residual is the residual between the flow rate ratios of the two inlet gas streams and the bypass ratio. For off-design calculations, the residual is the residual of the static pressures of the two inlet gas streams.

[0154] Since the outer flow and the core flow are mixed at the inlet cross-section of the mixing chamber, the thermodynamic parameters of the outlet mixed gas can be obtained through the calculation of the mixing parameters.

[0155] Specifically, the total temperature at the outlet of the mixing chamber can be calculated by the following formula:

[0156]

[0157]

[0158] where is the specific heat capacity at constant pressure of air, is the specific heat capacity at constant pressure of the fuel gas, is the specific heat capacity at constant pressure of the mixed gas, is the outer flow rate is the inner flow rate, B is the ratio of the mass flow rates of the outer and inner flows.

[0159] The total pressure at the outlet of the mixing chamber can be calculated by the following formula:

[0160] where is the total pressure recovery coefficient.

[0161] The flow rate at the outlet of the mixing chamber can be calculated by the following formula:

[0162] (6) Nozzle The nozzle calculation method includes: Total pressure at the nozzle exit , total temperature , fuel-air ratio which are respectively expressed as:

[0163]

[0164]

[0165] Among them, is the total pressure recovery coefficient of the nozzle.

[0166] Available pressure drop of the nozzle , critical pressure drop can be calculated by the following calculation formulas:

[0167]

[0168] Among them, is the adiabatic coefficient of the gas at the nozzle exit.

[0169] Nozzle state judgment and exit parameter calculation include: If , that is, the nozzle is in the subcritical working state:

[0170]

[0171]

[0172]

[0173] Among them, is the nozzle velocity coefficient, which is determined by , is the throat area of the nozzle, is the exit area of the nozzle.

[0174] If , that is, the nozzle is in the supercritical (choked) working state:

[0175]

[0176]

[0177]

[0178] Performance parameters can be calculated by the following equations:

[0179]

[0180] Among them, w f is the outlet fuel flow rate, F is the thrust, SFC is the specific fuel consumption (7) Performance solution module The performance solution module is mainly used to solve the engine's common working equations simultaneously. The flow balance equation in the common working equations is mainly reflected in the flow continuity at the inlet and outlet sections of the fan, compressor, high / low-pressure turbines. Specifically, the flow balance equations for typical components can be defined as:

[0181] Among them, represents the actual corrected flow rate calculated based on the inlet conditions, is the corrected flow rate obtained from the characteristic diagram, represents the residual of the flow balance equation.

[0182] The pressure balance equation in the common working equations is mainly reflected in the total pressure balance of the nozzle and the static pressure balance of the mixing chamber, etc. The static pressure balance of the engine's mixing chamber needs to ensure the entrainment static pressure and the mainstream static pressure are equal when the outer duct airflow mixes with the mainstream. The total pressure and static pressure balance equations for typical components can be defined as:

[0183] Among them, represents the total pressure at the component inlet, is the total pressure at the component outlet, is the residual of the total pressure balance equation. For example, the residual of the nozzle component is reflected in the total pressure of the airflow at the outlet of the afterburner and the total back pressure, represents the residual of the static pressure balance equation.

[0184] In addition, since the power balance of the high and low pressure rotors can also be solved stably to achieve the power balance between the fan and the low pressure turbine, and the power balance between the high pressure compressor and the high pressure turbine. Specifically, the modified Newton method with the same number of equations as the number of iteration quantities can be used. This method has a relatively fast calculation speed and good stability.

[0185] Reference Figure 8 , Figure 8 is a schematic flowchart of the first embodiment of the performance solving algorithm for the modular model disclosed herein. As Figure 8 shown, the modular model performance solving algorithm includes three parts: the main loop, the Jacobian matrix calculation, the modified Newton method, and the thermodynamic calculation. The main loop module provides the initial parameter x and the residual y(j) calculated according to the parameter x. The Jacobian matrix calculation module calculates the Jacobian matrix J according to the input parameters x and the residual y(j), and outputs the Jacobian matrix J to the modified Newton method iterative solution module. The modified Newton method iterative solution module receives the Jacobian matrix J and the residual y(j), calculates the parameter update amount dx, and updates the parameter x. Then, the updated parameter x is output to the thermodynamic calculation module. The thermodynamic calculation module receives the updated parameter x, performs thermodynamic calculations, obtains new performance parameters, and fine-tunes or confirms x based on these parameters. If the convergence condition is met, the entire process ends.

[0186] Reference Figure 9 , Figure 9 is a schematic flowchart of the first embodiment of the modeling calculation method disclosed herein. As Figure 9 shown, first, the flight parameter data can be preprocessed, parameters such as altitude and Mach number are selected for parameter calculation of the fan component, the high-pressure compression ratio is calculated in combination with the high-pressure compressor outlet pressure in the flight parameter data, a preliminary correction is made for the characteristic map, the power consumption of the two compression components is calculated, the high / low-pressure turbine pressure drop ratio is calculated through the power balance equation, and then it is compared and verified with the exhaust gas temperature measurement point and exhaust gas pressure measurement point in the flight parameter data, and then the bypass ratio is corrected for the pressure drop ratio. Recirculation calculations are performed again to meet the exhaust gas temperature and pressure requirements. Finally, the characteristic map is adjusted for the working state of each component to establish an engine working state model.

[0187] Reference Figure 10 , Figure 10 is a structural block diagram of the first embodiment of the aeroengine model correction device disclosed herein. Based on the same inventive concept as the foregoing embodiment, the device includes: The first acquisition module 10 is configured to acquire the component characteristics of the target component of the aeroengine model, and the aeroengine model is used to characterize the performance of the aeroengine in each working state; The second acquisition module 20 is configured to acquire the flight test data of the aeroengine; The correction module 30 is configured to perform characteristic correction on the component characteristics according to the flight test data so as to correct the aeroengine model, and the characteristic correction includes correction of the design point and correction of the off-design point.

[0188] Optionally, the correction module 30 is configured to: Extract multi-source information features of the aero-engine according to the test flight data; Determine the steady state point of the aero-engine according to the multi-source information features, where the steady state point is the operating point at which the aero-engine enters the target operating state; Perform characteristic correction on the component characteristics according to the steady state point.

[0189] Optionally, the correction module 30 is used for: Determine the design point according to the steady state point; Obtain the steady state performance parameters of the steady state point; Determine the first target performance parameter and the first component characteristic parameter to be adjusted corresponding to the design point according to the steady state performance parameters; Based on the particle swarm optimization algorithm, determine the first component characteristic target parameter corresponding to the design point according to the first target performance parameter; Correct the first component characteristic parameter to be adjusted according to the first component characteristic target parameter.

[0190] Optionally, the correction module 30 is used for: Determine the gas path parameters of the thermodynamic calculation and the measured gas path parameters corresponding to the design point according to the first target performance parameter; Determine the first optimization objective function of the design point according to the gas path parameters of the thermodynamic calculation and the measured gas path parameters corresponding to the design point; Perform iterative calculation based on the particle swarm optimization algorithm to determine the optimal solution of the first optimization objective function; Determine the first component characteristic target parameter according to the optimal solution of the first optimization objective function.

[0191] Optionally, the correction module 30 is used for: Determine the off-design point according to the steady state point and the design point; Obtain the component characteristic parameters of the corrected design point; Determine the second target performance parameter and the second component characteristic parameter to be adjusted corresponding to the off-design point according to the component characteristic parameters of the corrected design point; Based on the particle swarm optimization algorithm, determine the second component characteristic target parameter corresponding to the off-design point according to the second target performance parameter; Correct the second component characteristic parameter to be adjusted according to the second component characteristic target parameter.

[0192] Optionally, the correction module 30 is used for: Determine the gas path parameters of the thermodynamic calculation and the measured gas path parameters corresponding to the off-design point according to the second target performance parameter; Determine a second optimization objective function for the off-design point based on the gas path parameters obtained from the thermal calculation corresponding to the off-design point and the measured gas path parameters. Perform iterative calculations based on the particle swarm optimization algorithm to determine the optimal solution of the second optimization objective function. Determine the target parameters of the second component characteristics according to the optimal solution of the second optimization objective function.

[0193] Optionally, the aero-engine model correction device further includes: A third acquisition module, configured to acquire the monitoring parameters of the aero-engine, the engine component module library, and the module parameters of each module in the engine component module library. A construction module, configured to construct an initial aero-engine model according to the monitoring parameters, the engine component module library, and the module parameters of each module. A performance solution module, configured to perform performance solution on the initial aero-engine model to obtain the performance parameters and state variables of the aero-engine under each operating condition. An adjustment module, configured to adjust the initial aero-engine model according to the performance parameters and the state variables to obtain the aero-engine model.

[0194] It should be noted that since the steps executed by the device in this embodiment are the same as those in the foregoing method embodiment, the specific implementation manners and the achievable technical effects can refer to the foregoing embodiment, and will not be elaborated here.

[0195] In addition, in one embodiment, the embodiments of the present disclosure further provide an electronic device, which includes a processor, a memory, and a computer program stored in the memory. When the computer program is run by the processor, the steps of the method in the foregoing embodiment are implemented.

[0196] In addition, in one embodiment, the embodiments of the present disclosure further provide a computer storage medium, on which a computer program is stored. When the computer program is run by the processor, the steps of the method in the foregoing embodiment are implemented.

[0197] In some embodiments, the computer-readable storage medium may be a memory such as FRAM, ROM, PROM, EPROM, EEPROM, flash memory, magnetic surface memory, optical disc, or CD-ROM; or may be various devices including one or any combination of the foregoing memories. The computer may be various computing devices including smart terminals and servers.

[0198] In some embodiments, the executable instructions may be in the form of a program, software, software module, script, or code, written in any form of programming language (including compiled or interpreted languages, or declarative or procedural languages), and may be deployed in any form, including being deployed as a stand-alone program or being deployed as a module, component, subroutine, or other unit suitable for use in a computing environment.

[0199] As an example, the executable instructions may or may not correspond to a file in a file system, may be stored as part of a file that holds other programs or data, for example, in one or more scripts in a Hyper Text Markup Language (HTML) document, stored in a single file dedicated to the program being discussed, or, stored in multiple cooperating files (e.g., files that store one or more modules, subroutines, or portions of code).

[0200] As an example, the executable instructions may be deployed to execute on one computing device, or on multiple computing devices located at one site, or, on multiple computing devices distributed across multiple sites and interconnected by a communication network.

[0201] It should be noted that in this document, the term "comprising", "may comprise", or any other variation thereof is intended to cover a non-exclusive inclusion, such that a process, method, article, or system that comprises a series of elements includes not only those elements but also other elements not expressly listed, or elements that are inherent to such process, method, article, or system. Without further limitation, an element defined by the statement "comprising an..." does not exclude the presence of additional identical elements in the process, method, article, or system that comprises the element.

[0202] The serial numbers of the above-described embodiments of the present disclosure are for description only and do not represent the superiority or inferiority of the embodiments.

[0203] From the description of the above embodiments, those skilled in the art can clearly understand that the above-described embodiment methods can be implemented by means of software plus a necessary general hardware platform. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation. Based on such an understanding, the technical solution of the present disclosure, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as a read-only memory / random access memory, magnetic disk, optical disc), and includes several instructions for causing a multimedia terminal device (which may be a mobile phone, a computer, a television receiver, or a network device, etc.) to execute the methods described in the various embodiments of the present disclosure.

[0204] The above are only alternative embodiments of the present disclosure, and do not limit the patent scope of the present disclosure. Any equivalent structural transformation made by using the content of the specification and drawings of the present disclosure under the inventive concept of the present disclosure, or any direct / indirect application in other related technical fields is included in the patent protection scope of the present disclosure.

Claims

1. A method for correcting an aeroengine model, characterized in that Including: Obtaining the component characteristics of the target components of the aero-engine model, where the aero-engine model is used to characterize the performance of the aero-engine under each operating condition; Obtaining the flight test data of the aero-engine; According to the flight test data, performing characteristic correction on the component characteristics so as to correct the aero-engine model, and the characteristic correction includes correction of the design point and correction of the off-design point.

2. The method according to claim 1, wherein The performing characteristic correction on the component characteristics according to the flight test data includes: Extracting the multi-source information characteristics of the aero-engine according to the flight test data; Determining the steady state points of the aero-engine according to the multi-source information characteristics, where the steady state points are the operating points at which the aero-engine enters the target operating condition; Performing characteristic correction on the component characteristics according to the steady state points.

3. The method according to claim 2, wherein The performing characteristic correction on the component characteristics according to the steady state points includes: Determining the design point according to the steady state points; Obtaining the steady state performance parameters of the steady state points; Determining the first target performance parameters and the first component characteristic parameters to be adjusted corresponding to the design point according to the steady state performance parameters; Based on the particle swarm optimization algorithm, determining the first component characteristic target parameters corresponding to the design point according to the first target performance parameters; Correcting the first component characteristic parameters to be adjusted according to the first component characteristic target parameters.

4. The method according to claim 3, characterized in that, The determining the first component characteristic target parameters corresponding to the design point based on the particle swarm optimization algorithm according to the first target performance parameters includes: Determining the gas path parameters of the thermal calculation and the measured gas path parameters corresponding to the design point according to the first target performance parameters; Determining the first optimization objective function of the design point according to the gas path parameters of the thermal calculation and the measured gas path parameters corresponding to the design point; Performing iterative calculation based on the particle swarm optimization algorithm to determine the optimal solution of the first optimization objective function; Determining the first component characteristic target parameters according to the optimal solution of the first optimization objective function.

5. The method according to claim 2, wherein The performing characteristic correction on the component characteristics according to the steady state points includes: Determining the off-design points according to the steady state points and the design point; Obtaining the component characteristic parameters of the corrected design point; Determining the second target performance parameters and the second component characteristic parameters to be adjusted corresponding to the off-design points according to the component characteristic parameters of the corrected design point; Based on the particle swarm optimization algorithm, determining the second component characteristic target parameters corresponding to the off-design points according to the second target performance parameters; Correcting the second component characteristic parameters to be adjusted according to the second component characteristic target parameters.

6. The method according to claim 5, wherein The determining the second component characteristic target parameters corresponding to the off-design points based on the particle swarm optimization algorithm according to the second target performance parameters includes: Determining the gas path parameters of the thermal calculation and the measured gas path parameters corresponding to the off-design points according to the second target performance parameters; Determining the second optimization objective function of the off-design points according to the gas path parameters of the thermal calculation and the measured gas path parameters corresponding to the off-design points; Perform iterative calculations based on the particle swarm optimization algorithm to determine the optimal solution of the second optimization objective function; Determine the second component characteristic target parameters according to the optimal solution of the second optimization objective function.

7. The method according to claim 1, characterized in that, Before obtaining the component characteristics of the target component of the aero-engine model, it further includes: Obtain the monitoring parameters of the aero-engine, the engine component module library, and the module parameters of each module in the engine component module library; Construct an initial aero-engine model according to the monitoring parameters, the engine component module library, and the module parameters of each module; Perform performance solution on the initial aero-engine model to obtain the performance parameters and state variables of the aero-engine under each working condition; Adjust the initial aero-engine model according to the performance parameters and the state variables to obtain the aero-engine model.

8. An aero-engine model correction device, characterized in that, It includes: A first acquisition module, configured to acquire the component characteristics of the target component of the aero-engine model, where the aero-engine model is used to characterize the performance of the aero-engine under each working state; A second acquisition module, configured to acquire the flight test data of the aero-engine; A correction module, configured to perform characteristic correction on the component characteristics according to the flight test data, so as to correct the aero-engine model, and the characteristic correction includes correction of the design point and correction of the off-design point.

9. A computer-readable storage medium, characterized in that, A computer program is stored on the computer-readable storage medium, and the processor executes the computer program to implement the method according to any one of claims 1-7.

10. An electronic device, characterized in that, The electronic device includes a memory and a processor. A computer program is stored in the memory, and the processor executes the computer program to implement the method according to any one of claims 1-7.

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