A method and device for constructing an aircraft performance monitoring model and an electronic device

Abstract

The application discloses a kind of construction methods, device and electronic equipment of aircraft performance monitoring model, wherein the method comprises: determining at least one flight phase of target aircraft in flight process;For each flight phase, determine the performance index to be monitored corresponding to the current flight phase, and integrate the performance monitoring function corresponding to the performance index to be monitored in the performance monitoring submodel corresponding to the current flight phase;According to the performance monitoring submodel of corresponding connection between at least one flight phase, the aircraft performance monitoring model corresponding to target aircraft is obtained. By determining at least one flight phase of target aircraft in flight process, and setting the performance monitoring submodel corresponding to each flight phase, then based on at least one performance monitoring submodel, the aircraft performance monitoring model is obtained, the aircraft performance of target aircraft in different flight phases is monitored quickly and accurately, and the effect of more accurate performance monitoring result is obtained.

Description

Technical Field

[0001] This invention relates to the field of aircraft performance monitoring technology, and in particular to a method, apparatus and electronic equipment for constructing an aircraft performance monitoring model. Background Technology

[0002] To ensure flight quality, improve flight stability, and guarantee safe flight, it is necessary to assess the aircraft's operational status in a timely manner.

[0003] Currently, most aircraft performance monitoring during flight is based on the performance monitoring of specific aircraft components, and traditional aircraft performance monitoring mainly relies on the analysis of collected and transmitted data through airframe sensors and communication methods. However, the data collection and transmission process generates a large amount of invalid data, erroneous data, and data loss, which in turn makes it impossible to accurately monitor and analyze aircraft performance at different stages of flight.

[0004] To address the aforementioned issues, it is necessary to construct a corresponding aircraft performance monitoring model to monitor aircraft performance indicators based on this model. Summary of the Invention

[0005] This invention provides a method, apparatus, and electronic device for constructing an aircraft performance monitoring model, in order to solve the problem that existing technologies based on sensor-based aircraft flight data contain a large amount of invalid data, erroneous data, and data loss, which leads to the inability to accurately monitor aircraft performance at various flight stages.

[0006] In a first aspect, embodiments of the present invention provide a method for constructing an aircraft performance monitoring model, comprising: Identify at least one flight phase of the target aircraft during its flight; wherein the flight phase includes the aircraft takeoff phase, aircraft climb phase, aircraft cruise phase, aircraft descent phase, aircraft approach phase, and aircraft landing phase; For each flight phase, determine the performance indicators to be monitored corresponding to the current flight phase, and integrate the performance monitoring functions corresponding to the performance indicators to be monitored into the performance monitoring sub-model corresponding to the current flight phase; By connecting the corresponding performance monitoring sub-models according to the continuity relationship between the at least one flight phase, an aircraft performance monitoring model corresponding to the target aircraft is obtained.

[0007] Secondly, embodiments of the present invention also provide an apparatus for constructing an aircraft performance monitoring model, comprising: The flight phase determination module is used to determine at least one flight phase of the target aircraft during flight; wherein, the flight phase includes the aircraft takeoff phase, aircraft climb phase, aircraft cruise phase, aircraft descent phase, aircraft approach phase, and aircraft landing phase. The function integration module is used to determine the performance indicators to be monitored corresponding to the current flight stage for each flight stage, and to integrate the performance monitoring functions corresponding to the performance indicators to be monitored into the performance monitoring sub-model corresponding to the current flight stage. The monitoring model determination module is used to connect the corresponding performance monitoring sub-models according to the continuity relationship between the at least one flight phase, so as to obtain the aircraft performance monitoring model corresponding to the target aircraft.

[0008] Thirdly, embodiments of the present invention also provide an electronic device, comprising: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, which enables the at least one processor to perform the method for constructing an aircraft performance monitoring model according to any embodiment of the present invention.

[0009] Fourthly, embodiments of the present invention also provide a computer-readable storage medium storing computer instructions, which are used to cause a processor to execute and implement the method for constructing an aircraft performance monitoring model according to any embodiment of the present invention.

[0010] The technical solution of this invention determines at least one flight phase of the target aircraft during flight; for each flight phase, it determines the performance indicators to be monitored corresponding to the current flight phase, and integrates the performance monitoring functions corresponding to the performance indicators into the performance monitoring sub-model corresponding to the current flight phase; and connects the corresponding performance monitoring sub-models according to the relationship between at least one flight phase to obtain an aircraft performance monitoring model corresponding to the target aircraft. This solves the problem in the prior art where sensor-based aircraft flight data contains a large amount of invalid data, erroneous data, and data loss, leading to the inability to accurately monitor aircraft performance at each flight phase. By determining at least one flight phase of the target aircraft during flight and setting performance monitoring sub-models corresponding to each flight phase, and then obtaining an aircraft performance monitoring model based on at least one performance monitoring sub-model, the invention achieves rapid and accurate monitoring of the target aircraft's performance at different flight phases, resulting in more accurate performance monitoring results.

[0011] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0012] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0013] Figure 1 This is a flowchart of a method for constructing an aircraft performance monitoring model according to Embodiment 1 of the present invention; Figure 2 This is a schematic diagram of a flight phase according to Embodiment 1 of the present invention; Figure 3 This is a flowchart of a method for constructing an aircraft performance monitoring model according to Embodiment 2 of the present invention; Figure 4 This is a flowchart of an aircraft takeoff type determination method provided in Embodiment 2 of the present invention; Figure 5 This is a flowchart of an aircraft go-around determination method provided in Embodiment 2 of the present invention; Figure 6 This is a schematic diagram of an aircraft performance monitoring method according to Embodiment 2 of the present invention; Figure 7 This is a schematic diagram of the structure of a device for constructing an aircraft performance monitoring model according to Embodiment 3 of the present invention; Figure 8 This is a schematic diagram of the structure of an electronic device that implements the method for constructing an aircraft performance monitoring model according to an embodiment of the present invention. Detailed Implementation

[0014] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0015] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in sequences other than those illustrated or described herein.

[0016] Before elaborating on this technical solution, a brief introduction to its application scenarios will be provided to facilitate a clearer understanding. To ensure aircraft flight quality, improve flight stability, and guarantee safe flight, it is necessary to promptly assess the aircraft's operational status to reduce costs and improve flight efficiency. Therefore, the development of aircraft performance monitoring methods and software is of profound significance to the entire aircraft design and operation process. Traditional aircraft performance monitoring research mainly relies on data collected and transmitted through fuselage sensors and communication methods for calculation and analysis. However, the data acquisition and communication transmission process generates a large amount of invalid data, erroneous data, and data loss, affecting the quality of the overall aircraft performance analysis. Secondly, in the early stages of aircraft development, obtaining flight parameters is difficult, and the overall performance monitoring provides little assistance to aircraft design. Finally, regardless of the aircraft design or operation phases, obtaining aircraft fault data is difficult, and testing costs are too high.

[0017] This invention primarily focuses on developing an aircraft performance analysis system based on the Modelica language. It concentrates on monitoring the performance of aircraft during different flight phases and evaluating the aircraft's condition at each stage. The advantage of this approach is that Modelica is a secondary development language that supports non-causal modeling. It can automatically solve linear differential equations, ordinary differential equations, and partial differential equations to achieve model simulation. It is particularly suitable for system modeling and multidisciplinary, multi-domain collaborative simulation calculations. Using Modelica, the construction of large-scale, complex, heterogeneous models in modern engineering can be effectively addressed. Specifically for the aviation field, it allows for the design of reasonable flight scenarios and the performance calculation of related parameters.

[0018] Example 1 Figure 1This is a flowchart of a method for constructing an aircraft performance monitoring model according to Embodiment 1 of the present invention. This embodiment is applicable to dividing the flight process into at least one flight stage based on the flight process of the aircraft, determining the performance indicators to be monitored for each flight stage, setting corresponding performance monitoring functions for each performance indicator to be monitored, and integrating at least one performance monitoring function associated with the same flight stage into the corresponding performance monitoring sub-model of the flight stage. Then, the corresponding performance monitoring sub-models are connected according to the relationship between at least one flight stage to obtain the final aircraft performance monitoring model. The aircraft performance indicators of each flight stage during the flight process are monitored based on the aircraft performance monitoring model to obtain the indicator analysis results. This method can be executed by an aircraft performance monitoring model construction device, which can be implemented in hardware and / or software. The aircraft performance monitoring model construction device can be configured in a computing device that can execute the method for constructing an aircraft performance monitoring model.

[0019] like Figure 1 As shown, the method includes: S110. Determine at least one flight phase of the target aircraft during its flight.

[0020] The target aircraft can be understood as the aircraft whose performance indicators need to be monitored. The flight phase includes the takeoff phase, climb phase, cruise phase, descent phase, approach phase, and landing phase.

[0021] In practical applications, the performance indicators that need to be monitored differ depending on the flight stage of the target aircraft. Therefore, to ensure the flight quality and stability of the target aircraft, the flight process needs to be divided into at least one flight stage based on the flight status of the target aircraft. Furthermore, the performance indicators to be monitored corresponding to each flight stage need to be determined in order to monitor the aircraft performance of the target aircraft.

[0022] Optionally, determining at least one flight phase of the target aircraft during flight includes: obtaining the aircraft takeoff position and aircraft landing position corresponding to the target aircraft, and determining the unprocessed route between the aircraft takeoff position and aircraft landing position; dividing the unprocessed route according to the flight status information of the target aircraft in the unprocessed route to obtain at least one flight phase corresponding to the target aircraft in the unprocessed route.

[0023] The flight path to be processed can be understood as the route the target aircraft will take during flight. It is understood that the flight path to be processed is set before takeoff, and the target aircraft needs to fly according to this path during actual flight. Flight status information includes at least one of the following: flight position, flight speed, flight altitude, rate of change of speed, and rate of change of altitude.

[0024] In practical applications, before taking flight, the target aircraft needs to obtain the required flight path and then fly according to it. Specifically, the aircraft's takeoff and landing positions must first be determined. Between these two positions, there may be one or more available flight paths. Further, based on flight requirements, the required flight path can be selected from these available paths. For example, the shortest available flight path or the path with the shortest flight time can be chosen as the required flight path.

[0025] Furthermore, after determining the flight path to be processed used by the target aircraft, it is necessary to divide the flight path into different flight phases based on the target aircraft's flight status information. For example, during the takeoff phase, the target aircraft's speed is generally between a standstill and a first speed threshold, while its altitude is below a first altitude threshold. If the target aircraft's flight status information simultaneously meets both the speed and altitude detection conditions, then the takeoff phase of the target aircraft within the flight path to be processed can be determined. In other words, the requirements for the target aircraft's flight status differ in different flight phases. Based on this, flight status detection conditions corresponding to each flight phase can be pre-set to detect the target aircraft's flight status according to the flight status detection conditions of each flight phase, thereby dividing the flight path to be processed corresponding to the target aircraft into multiple different flight phases.

[0026] Alternatively, when dividing the flight path to be processed into flight phases, staff can customize these phases based on their aircraft flight experience. This is because the target aircraft typically uses a fixed flight path, and during its flight, it can only complete the flight when it reaches a certain flight state. To ensure the target aircraft's normal flight, it needs to reach a specific flight state at a certain location or time. Therefore, the flight path to be processed can be pre-divided into flight phases, and the target aircraft's flight state in each phase can be preset to prompt the pilot in the target aircraft to adjust the flight state in real time.

[0027] S120. For each flight phase, determine the performance indicators to be monitored corresponding to the current flight phase, and integrate the performance monitoring functions corresponding to the performance indicators to be monitored into the performance monitoring sub-model corresponding to the current flight phase.

[0028] The performance indicators to be monitored can be understood as metrics characterizing the flight performance of an aircraft, and the specific performance indicators to be monitored differ depending on the flight phase of the target aircraft. It can be understood that in different flight phases, there can be one or more performance indicators to be monitored, and each performance indicator can correspond to a performance monitoring function. The performance monitoring function can be understood as a function that detects the performance indicator and determines whether it meets the requirements. The performance monitoring sub-model can be understood as a sub-model used to monitor the performance indicators corresponding to a specific flight phase, integrating the performance monitoring functions corresponding to that flight phase.

[0029] This technical solution primarily involves constructing an aircraft performance monitoring model corresponding to the target aircraft, and then using this model to monitor the target aircraft's performance indicators during each flight phase. Furthermore, to quickly and accurately monitor the performance indicators for each flight phase, a separate performance monitoring sub-model is set up for each flight phase within the aircraft performance monitoring model. This allows for the monitoring of the corresponding performance indicators for the flight phase based on the sub-model corresponding to the target aircraft's current flight phase.

[0030] The advantage of this setup is that by setting up a corresponding performance monitoring sub-model for each flight phase, the corresponding performance monitoring sub-model can be directly invoked when it is necessary to monitor the performance indicators to be monitored in a certain flight phase. The performance monitoring sub-model has already integrated the functions for monitoring the performance indicators of that flight phase, thereby improving the efficiency and convenience of performance indicator monitoring.

[0031] S130. Connect the corresponding performance monitoring sub-models according to the connection between at least one flight phase to obtain the aircraft performance monitoring model corresponding to the target aircraft.

[0032] The "sequential relationship" refers to the sequential relationship between different flight phases. An aircraft performance monitoring model can be understood as a model used to monitor the performance of a target aircraft throughout its entire flight process. In other words, the aircraft performance monitoring model includes performance monitoring sub-models corresponding to each flight phase.

[0033] Specifically, during the entire flight, such as Figure 2As shown, the sequence of at least one flight phase is as follows: takeoff phase → climb phase → cruise phase → descent phase → approach phase → landing phase. After determining the performance monitoring sub-models corresponding to each flight phase, the corresponding performance monitoring sub-models are connected according to the sequence of at least one flight phase to obtain the aircraft performance monitoring model corresponding to the target aircraft.

[0034] Optionally, the corresponding performance monitoring sub-models are connected according to the continuity relationship between at least one flight phase to obtain the aircraft performance monitoring model corresponding to the target aircraft. This includes: determining the next flight phase associated with the end of the current flight phase for each flight phase; and performing simulation connection based on the data connection interface between the performance monitoring sub-model corresponding to the current flight phase and the performance monitoring sub-model corresponding to the next flight phase to obtain the aircraft performance monitoring model corresponding to the target aircraft.

[0035] In this technical solution, to improve the reusability of the aircraft performance monitoring model, performance monitoring sub-models corresponding to each flight phase are integrated into the model. Furthermore, each performance monitoring sub-model sets a corresponding performance monitoring function for each performance indicator to be monitored. The advantage of this approach is that when a new performance indicator is added to be monitored during a flight phase, or when a performance indicator changes or is updated, the corresponding indicator monitoring function in the relevant performance monitoring sub-model can be directly updated without needing to reconfigure the entire aircraft performance monitoring model.

[0036] Based on this, this technical solution determines the next flight stage connected to the current flight stage according to the continuity relationship between at least one flight stage, and constructs a performance monitoring sub-model corresponding to each flight stage. Furthermore, to facilitate the monitoring of performance indicators of the target aircraft throughout the entire flight process, each performance monitoring sub-model needs to be configured with a corresponding data connection interface. This interface allows for simulation connection between the performance monitoring sub-model corresponding to the current flight stage and the performance monitoring sub-model corresponding to the next flight stage, resulting in an aircraft performance monitoring model corresponding to the target aircraft.

[0037] In this technical solution, an aircraft performance monitoring model corresponding to the target aircraft is constructed based on the overall flight architecture of the target aircraft throughout the entire flight process. At the same time, for ease of use, corresponding component packages, interface packages, system performance test packages, toolboxes, and icon packages can be set in the aircraft performance monitoring model, thereby realizing the visualization of the aircraft performance monitoring model. Based on the display interface of the visualized aircraft performance monitoring model, the monitoring results of the target aircraft's performance indicators at each flight stage are displayed in a visual manner.

[0038] It should be noted that this technical solution does not specifically limit the target aircraft model or configuration information. Furthermore, during the construction process, the aircraft performance monitoring model can be tested based on flight data corresponding to different aircraft models, thereby obtaining an aircraft performance monitoring model with higher confidence. Therefore, the aircraft performance monitoring model constructed based on this technical solution has strong universality and versatility.

[0039] The technical solution of this invention determines at least one flight phase in the flight process of a target aircraft. In this solution, the flight process is divided into phases based on the aircraft's flight path and flight status information. The purpose is that the performance indicators to be monitored for the target aircraft differ in different flight phases. By dividing the flight into phases, performance indicators to be monitored corresponding to each flight phase can be set, thus establishing a performance monitoring sub-model corresponding to each flight phase. Furthermore, for each flight phase, the performance indicators to be monitored corresponding to the current flight phase are determined, and the performance monitoring functions corresponding to these indicators are integrated into the performance monitoring sub-model corresponding to the current flight phase. In this solution, a corresponding performance monitoring function is set for each performance indicator to be monitored in each flight phase, and performance monitoring functions associated with the same flight phase are integrated into the corresponding performance monitoring sub-model. This allows for the construction of an aircraft performance monitoring model corresponding to the target aircraft based on each performance monitoring sub-model. Based on this, the corresponding performance monitoring sub-models are connected according to the relationship between at least one flight stage to obtain the aircraft performance monitoring model corresponding to the target aircraft. That is to say, in the actual flight process, the order of the flight stages experienced by the target aircraft is fixed. Therefore, after obtaining the performance monitoring sub-models corresponding to each flight stage, the performance monitoring sub-models can be connected based on the relationship between at least one flight stage to obtain the aircraft performance monitoring model. When it is necessary to monitor the performance indicators of the target aircraft during the complete flight process, the flight data corresponding to the target aircraft can be directly input into the aircraft performance monitoring model for monitoring, thereby improving the convenience of aircraft performance monitoring. The flight data can be flight simulation data corresponding to the target aircraft. This invention addresses the problem in existing technologies where sensor-based aircraft flight data contains a significant amount of invalid, erroneous, and lost data, hindering accurate monitoring of aircraft performance at various flight stages. By identifying at least one flight stage of the target aircraft and establishing corresponding performance monitoring sub-models for each stage, an aircraft performance monitoring model is derived based on at least one performance monitoring sub-model. This enables rapid and accurate monitoring of the target aircraft's performance at different flight stages, resulting in more precise performance monitoring results.

[0040] Example 2 Figure 3 This is a flowchart of a method for constructing an aircraft performance monitoring model according to Embodiment 2 of the present invention. Optionally, the performance indicators to be monitored corresponding to the current flight phase can be refined.

[0041] like Figure 3 As shown, the method includes: S210. Determine at least one phase of flight of the target aircraft during its flight.

[0042] S220. For each flight phase, retrieve the performance indicator monitoring information table corresponding to the current flight phase based on the phase identifier of the current flight phase.

[0043] The performance indicator monitoring information table includes at least one performance indicator to be monitored during the current flight phase.

[0044] Specifically, the performance indicators to be monitored for the target aircraft in each flight phase are not static and can be added, modified, or deleted according to actual monitoring needs. Therefore, to ensure the completeness and accuracy of monitoring the performance indicators of the target aircraft in each flight phase, this technical solution can set up a corresponding performance indicator monitoring information table for each flight phase, recording at least one performance indicator to be monitored for each corresponding flight phase in this information table. Furthermore, a corresponding phase identifier is set for each flight phase, and a correlation is established between each phase identifier and the performance indicator monitoring information table, so that when determining the performance indicators to be monitored in the current flight phase, the corresponding performance indicator monitoring information table can be retrieved directly based on the phase identifier of the current flight phase.

[0045] S230. Based on the performance indicator monitoring information table, determine the performance indicators to be monitored corresponding to the current flight phase.

[0046] For example, at least one performance indicator to be monitored for the current flight phase can be determined based on the performance indicator monitoring information table corresponding to the current flight phase. For instance, during takeoff, the performance indicators to be monitored could include takeoff type, takeoff climb rate, takeoff altitude, taxi distance, and takeoff speed. During climb, the performance indicators to be monitored could include climb rate, climb distance, and climb speed. During cruise, the performance indicators to be monitored could include fuel consumption rate, emissions, cruise altitude fluctuations, engine performance, and aircraft speed. During descent, the performance indicators to be monitored could include current aircraft altitude, descent altitude, and rate of descent. During approach, the performance indicators to be monitored could include aircraft position and rate of descent. During landing, the performance indicators to be monitored could include touchdown speed and landing distance.

[0047] S240. Integrate the performance monitoring function corresponding to the performance index to be monitored into the performance monitoring sub-model corresponding to the current flight phase.

[0048] In this technical solution, the performance monitoring function corresponding to the performance indicator to be monitored is integrated into the performance monitoring sub-model corresponding to the current flight phase. This includes: retrieving the basic function corresponding to the performance indicator to be monitored from the basic function database, and constructing the performance monitoring function corresponding to the performance indicator to be monitored based on the basic function; determining the function call interface corresponding to the performance monitoring function; and encapsulating the performance monitoring function and the function call interface to obtain the performance indicator monitoring sub-module corresponding to the current flight phase.

[0049] The basic function database refers to a database used to store basic detection functions for performance monitoring. These basic functions can be functions for detecting the target aircraft's flight altitude, determining the target aircraft's fuel consumption rate, determining the aircraft's touchdown speed, etc. Generally, each performance indicator to be monitored corresponds to a specific basic function. However, in actual performance indicator monitoring, the basic functions may need to be modified based on the aircraft's configuration information to obtain the performance monitoring function corresponding to the monitored indicator. The function call interface can be understood as a data interface used to call the performance monitoring functions.

[0050] In practical applications, the performance monitoring function corresponding to the performance indicator to be monitored is constructed based on the basic function. This includes: determining the indicator monitoring logic corresponding to the performance indicator to be monitored, and at least one indicator parameter to be used corresponding to the performance indicator to be monitored; and modifying the basic function based on the indicator monitoring logic and at least one indicator parameter to be used to obtain the performance monitoring function corresponding to the performance indicator to be monitored.

[0051] The indicator monitoring logic can be understood as the algorithm execution logic used to monitor the performance indicators to be monitored. The indicator parameters to be used can be understood as the aircraft parameter information needed when monitoring the performance indicators to be monitored, such as aircraft operating parameters or aircraft configuration parameters.

[0052] It should be noted that in this technical solution, when constructing the aircraft performance monitoring model corresponding to the target aircraft, all performance monitoring functions integrated into the aircraft performance monitoring model are based on the Modelica language. The advantage of this approach is that performance monitoring functions generated using Modelica can extract the common information of the performance analysis system to the greatest extent. Furthermore, after generating performance monitoring sub-models corresponding to each flight phase and obtaining the aircraft performance monitoring model based on at least one of these sub-models, the coupling problem between the various performance monitoring sub-models can be resolved. This allows for direct retrieval of the corresponding performance monitoring sub-model when analyzing and processing the performance indicators to be monitored in a specific flight phase, without needing to focus excessively on the complete flight process. This minimizes the development time of the aircraft performance monitoring model and improves the efficiency and accuracy of aircraft performance analysis.

[0053] For example, taking the aircraft takeoff phase as an example, during the takeoff phase, it is necessary to determine the aircraft takeoff type, retrieve the basic function corresponding to the takeoff type, and modify the basic function according to the actual judgment logic for determining the aircraft takeoff type, thereby obtaining the performance monitoring function corresponding to the performance indicator to be monitored for the aircraft takeoff type. Specifically, such as... Figure 4 As shown, when the target aircraft is in the engine-driven state, it is necessary to determine whether the engine is operational, i.e., whether the target aircraft's engine is running normally. If the target aircraft's critical speed at the current moment is greater than the preset critical speed, and the target aircraft is in the critical position, and its takeoff speed meets the preset takeoff speed, then it can be determined that the target aircraft can take off. However, to ensure the flight stability and safety of the target aircraft, the engine operation can be checked again. If it is, the target aircraft can be controlled to take off normally; if not, it indicates that the target aircraft's engine has failed, and the target aircraft needs to return to the takeoff position for adjustment after takeoff. Conversely, if the target aircraft's engine starts operating, but the target aircraft's critical speed is less than the preset critical speed, it is necessary to check whether the target aircraft's engine is operating again. If it is, even if the target aircraft has already started takeoff, it is necessary to abort the takeoff and control the target aircraft to decelerate and stop; if not, it indicates that the target aircraft's engine has failed, the target aircraft's takeoff is aborted, and the target aircraft is controlled to decelerate and stop. Based on this, a performance monitoring function corresponding to the aircraft takeoff type is established, and a function call interface corresponding to the performance monitoring function is also established. The performance monitoring function and function call interface corresponding to the aircraft takeoff type determination are encapsulated to obtain a performance indicator monitoring submodule corresponding to the aircraft takeoff phase.

[0054] In yet another example, such as Figure 5As shown, taking the aircraft go-around determination during the approach phase as an example, determining whether a target aircraft should go around requires verifying whether it is in a normal approach state. Specifically, the vertical velocity of the target aircraft during the approach phase is obtained, and it is determined whether the vertical velocity is positive. If so, it is further determined whether the target aircraft's vertical velocity is within the normal approach fluctuation altitude. When the target aircraft's approach fluctuation altitude exceeds the set fluctuation altitude, it is determined that the target aircraft has entered the go-around climb state; conversely, if the approach fluctuation altitude is lower than the set fluctuation altitude, it is determined that the target aircraft has entered the normal approach process. Further, it is necessary to determine whether the target aircraft's current vertical altitude is negative. If so, the target aircraft begins the go-around approach; otherwise, the target aircraft enters the normal approach process. Based on this, a performance monitoring function corresponding to the aircraft go-around determination is established, along with a corresponding function call interface. The performance monitoring function and function call interface corresponding to the aircraft go-around determination are then encapsulated to obtain a performance indicator monitoring submodule corresponding to the aircraft approach phase.

[0055] S250. Connect the corresponding performance monitoring sub-models according to the connection between at least one flight phase to obtain the aircraft performance monitoring model corresponding to the target aircraft.

[0056] In practical applications, after constructing an aircraft performance monitoring model corresponding to the target aircraft, it is necessary to test and debug the model to ensure the accuracy of the monitoring. Specifically, this technical solution also includes: acquiring at least one set of flight simulation data to be tested, and inputting each set of flight simulation data to be tested into the aircraft performance monitoring model to obtain index analysis results; determining the model confidence level corresponding to the aircraft performance monitoring model based on the index analysis results corresponding to each set of flight simulation data to be tested and the preset index analysis results; adjusting the model parameters of the flight performance monitoring model based on the model confidence level until the model confidence level of the aircraft performance monitoring model is greater than the preset model confidence level.

[0057] The test flight simulation data can be understood as flight simulation data output by a flight simulation system. This system simulates the flight conditions of the test aircraft based on its configuration information, obtaining simulation data during flight. The index analysis results are the results of index analysis performed on the test flight simulation data using an aircraft performance monitoring model. These results characterize whether any abnormalities exist in the monitored performance indicators of the test aircraft during each flight phase. The preset index analysis results refer to the pre-set index results corresponding to various monitored performance indicators under normal flight conditions, serving as a reference for the index analysis results corresponding to the test flight simulation data. The model confidence level characterizes the accuracy of the aircraft performance monitoring model's index analysis. A higher model confidence level indicates higher accuracy, and vice versa.

[0058] It should be noted that traditional flight performance analysis system verification mainly utilizes sensors and communication methods to test and verify the system. However, this verification method is costly and time-consuming, making it impossible to achieve rapid iterative design of the entire flight performance analysis process. Therefore, in this technical solution, when testing and evaluating the aircraft performance monitoring model, a data interface can be used to connect the aircraft performance monitoring model to a pre-built flight simulation system. Simulation data corresponding to the test aircraft can be obtained from the simulation system, and the aircraft performance monitoring model can be tested and evaluated based on this simulation data, yielding the corresponding model confidence level. If the model confidence level is greater than the preset model confidence level, it indicates that the reliability of the aircraft performance monitoring model's indicator analysis results is high, and no further debugging is needed. Conversely, if the model confidence level is less than the preset model confidence level, it indicates that the reliability of the aircraft performance monitoring model's indicator analysis results is low, and further debugging is needed to ensure the accuracy of the aircraft performance monitoring model.

[0059] It should be noted that, to ensure the universality of the aircraft performance monitoring model, the flight simulation data to be tested obtained from the flight simulation system can be simulation data corresponding to different aircraft models. Specifically, the aircraft configuration information corresponding to different aircraft models is input into the flight simulation system to simulate the flight process of different test aircraft models based on the flight simulation system, and at least one set of flight simulation data to be tested for at least one test aircraft is obtained. At least one set of flight simulation data to be tested is then sent to the aircraft performance monitoring model for testing.

[0060] It should be noted that, in order to avoid the problem that the accuracy of the aircraft performance monitoring model is low due to the inaccuracy of the flight data collected by the target aircraft during flight, this technical solution can use simulation data corresponding to different models of aircraft to evaluate the aircraft performance monitoring model, so as to improve the accuracy of the aircraft performance monitoring model in evaluating the actual aircraft performance indicators.

[0061] The advantage of this setup is that it tests the monitoring functions of each index in the aircraft performance monitoring model based on at least one set of flight simulation data to be tested, and compares the index analysis results output by the aircraft performance analysis system model built based on Modelica language with the corresponding preset index analysis results for further debugging. This can improve the accuracy of the system simulation and the reliability of the model.

[0062] Optionally, after evaluating the aircraft performance monitoring model, it can be put into use. Specifically, in at least one editable control on the control panel of the aircraft model flight system, the aircraft configuration information corresponding to the target aircraft is entered; the target aircraft is simulated to fly according to the aircraft configuration information, and target simulation data corresponding to the target aircraft is obtained. Based on the aircraft performance monitoring model, the target simulation data is analyzed to obtain the performance index monitoring results of the target aircraft in each flight phase.

[0063] The aircraft configuration information includes aircraft configuration data, aircraft attribute information, and flight missions. The target simulation data includes at least one performance indicator to be monitored during the flight phase.

[0064] In a specific example, such as Figure 6 As shown, the entire aircraft testing system comprises an aircraft operating system, a flight simulation system, a visual display system, a performance calculation system (i.e., an aircraft performance monitoring model), and a parameter control panel. First, the corresponding aircraft configuration data and flight mission are set through at least one editable control in the parameter control panel. Then, the aircraft attitude (i.e., aircraft configuration information) is controlled through the flight simulation system, and relevant control commands are output to the flight simulation system. Simultaneously, considering the influence of environmental factors, flight control performance, control surface response, and dynamic mechanisms, target simulation data corresponding to the target aircraft is output and sent to the aircraft performance monitoring model. Based on this, the aircraft performance monitoring model automatically determines the performance indicators to be monitored during at least one flight phase in the simulated flight process.

[0065] The technical solution of this invention determines at least one flight phase of the target aircraft during flight; for each flight phase, it determines the performance indicators to be monitored corresponding to the current flight phase, and integrates the performance monitoring functions corresponding to the performance indicators into the performance monitoring sub-model corresponding to the current flight phase; and connects the corresponding performance monitoring sub-models according to the relationship between at least one flight phase to obtain an aircraft performance monitoring model corresponding to the target aircraft. This solves the problem in the prior art where sensor-based aircraft flight data contains a large amount of invalid data, erroneous data, and data loss, leading to the inability to accurately monitor aircraft performance at each flight phase. By determining at least one flight phase of the target aircraft during flight and setting performance monitoring sub-models corresponding to each flight phase, and then obtaining an aircraft performance monitoring model based on at least one performance monitoring sub-model, the invention achieves rapid and accurate monitoring of the target aircraft's performance at different flight phases, resulting in more accurate performance monitoring results.

[0066] Example 3 Figure 7 This is a schematic diagram of a device for constructing an aircraft performance monitoring model according to Embodiment 3 of the present invention. Figure 7 As shown, the device includes: a flight phase determination module 310, a function integration module 320, and a monitoring model determination module 330.

[0067] The flight phase determination module 310 is used to determine at least one flight phase of the target aircraft during flight; the flight phase includes the aircraft takeoff phase, the aircraft climb phase, the aircraft cruise phase, the aircraft descent phase, the aircraft approach phase, and the aircraft landing phase. The function integration module 320 is used to determine the performance indicators to be monitored corresponding to the current flight stage for each flight stage, and to integrate the performance monitoring functions corresponding to the performance indicators to be monitored into the performance monitoring sub-model corresponding to the current flight stage. The monitoring model determination module 330 is used to connect the corresponding performance monitoring sub-models according to the connection between at least one flight phase to obtain the aircraft performance monitoring model corresponding to the target aircraft.

[0068] The technical solution of this invention determines at least one flight phase of the target aircraft during flight; for each flight phase, it determines the performance indicators to be monitored corresponding to the current flight phase, and integrates the performance monitoring functions corresponding to the performance indicators into the performance monitoring sub-model corresponding to the current flight phase; and connects the corresponding performance monitoring sub-models according to the relationship between at least one flight phase to obtain an aircraft performance monitoring model corresponding to the target aircraft. This solves the problem in the prior art where sensor-based aircraft flight data contains a large amount of invalid data, erroneous data, and data loss, leading to the inability to accurately monitor aircraft performance at each flight phase. By determining at least one flight phase of the target aircraft during flight and setting performance monitoring sub-models corresponding to each flight phase, and then obtaining an aircraft performance monitoring model based on at least one performance monitoring sub-model, the invention achieves rapid and accurate monitoring of the target aircraft's performance at different flight phases, resulting in more accurate performance monitoring results.

[0069] Optionally, the flight phase determination module includes: a route determination unit, used to obtain the aircraft takeoff position and aircraft landing position corresponding to the target aircraft, and determine the route to be processed between the aircraft takeoff position and aircraft landing position; The flight phase determination unit is used to divide the flight path to be processed according to the flight status information of the target aircraft in the flight path to be processed, and obtain at least one flight phase corresponding to the target aircraft in the flight path to be processed; wherein, the flight status information includes at least one of flight position, flight speed, flight altitude, speed change rate and flight altitude change rate.

[0070] Optionally, the function integration module includes: an information table determination unit, used to retrieve the performance indicator monitoring information table corresponding to the current flight stage based on the stage identifier of the current flight stage; wherein, the performance indicator monitoring information table includes at least one performance indicator to be monitored in the current flight stage; The indicator determination unit is used to determine the performance indicators to be monitored corresponding to the current flight phase based on the performance indicator monitoring information table.

[0071] Optionally, the function integration module includes: a basic function retrieval unit, used to retrieve the basic functions corresponding to the performance indicators to be monitored from the basic function database, and to construct performance monitoring functions corresponding to the performance indicators to be monitored based on the basic functions; The interface determination unit is used to determine the function call interface corresponding to the performance monitoring function; The monitoring submodule determination unit is used to encapsulate the performance monitoring functions and function call interfaces to obtain the performance indicator monitoring submodule corresponding to the current flight phase.

[0072] Optionally, the basic function call unit includes: a parameter determination subunit, used to determine the indicator monitoring logic corresponding to the performance indicator to be monitored, and at least one indicator parameter to be used corresponding to the performance indicator to be monitored; The function generation subunit is used to modify the base function based on the indicator monitoring logic and at least one indicator parameter to be used, so as to obtain the performance monitoring function corresponding to the performance indicator to be monitored; wherein, the performance monitoring function is a function generated based on the Modelica language.

[0073] Optionally, the monitoring model determination module includes: a next flight phase determination unit, used to determine the next flight phase associated with the end of the current flight phase for each flight phase; The monitoring module determination unit is used to perform simulation connection based on the data connection interface between the performance monitoring sub-model corresponding to the current flight phase and the performance monitoring sub-model corresponding to the next flight phase, so as to obtain the aircraft performance monitoring model corresponding to the target aircraft.

[0074] Optionally, the aircraft performance monitoring model construction device further includes: a simulation data acquisition module, used to acquire at least one set of flight simulation data to be tested, and input each set of flight simulation data to be tested into the aircraft performance monitoring model to obtain index analysis results; The confidence level determination module is used to determine the model confidence level of the aircraft performance monitoring model based on the index analysis results and preset index analysis results of each flight simulation data to be tested. The parameter adjustment module is used to adjust the model parameters of the flight performance monitoring model according to the model confidence level until the model confidence level of the aircraft performance monitoring model is greater than the preset model confidence level.

[0075] Optionally, the aircraft performance monitoring model construction device further includes: a configuration information determination module, used to input aircraft configuration information corresponding to the target aircraft in at least one editable control on the control panel of the aircraft model flight system; The target simulation data determination module is used to simulate the flight of the target aircraft based on the aircraft configuration information to obtain target simulation data corresponding to the target aircraft; wherein, the target simulation data includes at least one performance index to be monitored in the flight phase; The monitoring result determination module is used to perform index monitoring and analysis on the target simulation data based on the aircraft performance monitoring model, and obtain the performance index monitoring results of the target aircraft in each flight phase.

[0076] The aircraft performance monitoring model construction apparatus provided in this embodiment of the invention can execute the aircraft performance monitoring model construction method provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0077] Example 4 Figure 8 A schematic diagram of the structure of an electronic device 10 according to an embodiment of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (such as helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0078] like Figure 8 As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 or a random access memory (RAM) 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer program stored in the ROM 12 or loaded from storage unit 18 into the RAM 13. The RAM 13 can also store various programs and data required for the operation of the electronic device 10. The processor 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0079] Multiple components in electronic device 10 are connected to I / O interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of displays, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows electronic device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0080] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, digital signal processors (DSPs), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as the method for constructing an aircraft performance monitoring model.

[0081] In some embodiments, the method for constructing an aircraft performance monitoring model can be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program can be loaded and / or installed on electronic device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the method for constructing an aircraft performance monitoring model described above can be performed. Alternatively, in other embodiments, processor 11 can be configured to execute the method for constructing an aircraft performance monitoring model by any other suitable means (e.g., by means of firmware).

[0082] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0083] Computer programs used for constructing the aircraft performance monitoring model of the present invention can be written in any combination of one or more programming languages. These computer programs can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the functions / operations specified in the flowcharts and / or block diagrams are performed. The computer programs can be executed entirely on the machine, partially on the machine, as a standalone software package partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0084] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0085] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0086] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or middleware components (e.g., application servers), or frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0087] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0088] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0089] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A method for constructing an aircraft performance monitoring model, characterized in that, include: Identify at least one flight phase of the target aircraft during its flight; wherein the flight phase includes the aircraft takeoff phase, aircraft climb phase, aircraft cruise phase, aircraft descent phase, aircraft approach phase, and aircraft landing phase; For each flight phase, determine the performance indicators to be monitored corresponding to the current flight phase, and integrate the performance monitoring functions corresponding to the performance indicators to be monitored into the performance monitoring sub-model corresponding to the current flight phase; Based on the connection between the at least one flight phase, the corresponding performance monitoring sub-models are connected to obtain the aircraft performance monitoring model corresponding to the target aircraft. The step of integrating the performance monitoring function corresponding to the performance indicator to be monitored into the performance monitoring sub-model corresponding to the current flight phase includes: retrieving the basic function corresponding to the performance indicator to be monitored from the basic function database, and constructing the performance monitoring function corresponding to the performance indicator to be monitored based on the basic function; determining the function call interface corresponding to the performance monitoring function; and encapsulating the performance monitoring function and the function call interface to obtain the performance indicator monitoring sub-module corresponding to the current flight phase. The step of constructing a performance monitoring function corresponding to the performance indicator to be monitored based on the basic function includes: determining the indicator monitoring logic corresponding to the performance indicator to be monitored, and at least one indicator parameter to be used corresponding to the performance indicator to be monitored; modifying the basic function based on the indicator monitoring logic and at least one indicator parameter to be used to obtain the performance monitoring function corresponding to the performance indicator to be monitored; wherein the performance monitoring function is a function generated based on the Modelica language.

2. The method according to claim 1, characterized in that, Determining at least one flight phase of the target aircraft during flight includes: Obtain the takeoff and landing positions of the target aircraft, and determine the unprocessed flight path between the takeoff and landing positions. Based on the flight status information of the target aircraft in the flight path to be processed, the flight path to be processed is divided to obtain at least one flight phase corresponding to the target aircraft in the flight path to be processed; wherein, the flight status information includes at least one of flight position, flight speed, flight altitude, speed change rate and flight altitude change rate.

3. The method according to claim 1, characterized in that, The determination of the performance indicators to be monitored corresponding to the current flight phase includes: Based on the phase identifier of the current flight phase, retrieve the performance indicator monitoring information table corresponding to the current flight phase; wherein, the performance indicator monitoring information table includes at least one performance indicator to be monitored in the current flight phase; Based on the performance indicator monitoring information table, determine the performance indicators to be monitored corresponding to the current flight phase.

4. The method according to claim 1, characterized in that, The step of connecting the corresponding performance monitoring sub-models according to the take-off and landing relationships between the at least one flight phase to obtain the aircraft performance monitoring model corresponding to the target aircraft includes: For each of the aforementioned flight phases, determine the next flight phase that is associated with the end of the current flight phase; Simulation connection is performed based on the data connection interface between the performance monitoring sub-model corresponding to the current flight phase and the performance monitoring sub-model corresponding to the next flight phase to obtain the aircraft performance monitoring model corresponding to the target aircraft.

5. The method according to claim 1, characterized in that, Also includes: Acquire at least one set of flight simulation data to be tested, and input each set of flight simulation data to be tested into the aircraft performance monitoring model to obtain the index analysis results; Based on the index analysis results and preset index analysis results corresponding to the flight simulation data to be tested, the model confidence level corresponding to the aircraft performance monitoring model is determined; The model parameters of the flight performance monitoring model are adjusted based on the model confidence level until the model confidence level of the aircraft performance monitoring model is greater than the preset model confidence level.

6. The method according to claim 1, characterized in that, Also includes: In at least one editable control on the control panel of the aircraft model flight system, input the aircraft configuration information corresponding to the target aircraft; The target aircraft is simulated to fly based on the aircraft configuration information to obtain target simulation data corresponding to the target aircraft; wherein, the target simulation data includes at least one performance indicator to be monitored in the flight phase; Based on the aircraft performance monitoring model, the target simulation data is analyzed to obtain the performance monitoring results of the target aircraft in each flight phase.

7. A device for constructing an aircraft performance monitoring model, characterized in that, include: The flight phase determination module is used to determine at least one flight phase of the target aircraft during flight; wherein, the flight phase includes the aircraft takeoff phase, aircraft climb phase, aircraft cruise phase, aircraft descent phase, aircraft approach phase, and aircraft landing phase. The function integration module is used to determine the performance indicators to be monitored corresponding to the current flight stage for each flight stage, and to integrate the performance monitoring functions corresponding to the performance indicators to be monitored into the performance monitoring sub-model corresponding to the current flight stage. The monitoring model determination module is used to connect the corresponding performance monitoring sub-models according to the continuity relationship between the at least one flight phase, so as to obtain the aircraft performance monitoring model corresponding to the target aircraft. The function integration module includes: a basic function retrieval unit, used to retrieve the basic function corresponding to the performance indicator to be monitored from the basic function database, and construct a performance monitoring function corresponding to the performance indicator to be monitored based on the basic function; an interface determination unit, used to determine the function call interface corresponding to the performance monitoring function; and a monitoring submodule determination unit, used to encapsulate the performance monitoring function and the function call interface to obtain a performance indicator monitoring submodule corresponding to the current flight phase. Optionally, the basic function retrieval unit includes: a parameter determination subunit, used to determine the indicator monitoring logic corresponding to the performance indicator to be monitored, and at least one indicator parameter to be used corresponding to the performance indicator to be monitored; and a function generation subunit, used to modify the basic function based on the indicator monitoring logic and at least one indicator parameter to be used, to obtain a performance monitoring function corresponding to the performance indicator to be monitored; wherein, the performance monitoring function is a function generated based on the Modelica language.

8. An electronic device, characterized in that, The electronic device includes: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the method for constructing the aircraft performance monitoring model according to any one of claims 1-6.

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