Evaluation and Prediction Method for Landing Gear Shock Strut by Integrating Data-Driven and Physical Modeling

Abstract

The embodiment of this specification provides an evaluation and prediction method for the landing gear shock strut that integrates data-driven and physical modeling. The method includes: obtaining the angle of attack value corresponding to the current touchdown moment of the aircraft, and determining the initial lift coefficient corresponding to the current touchdown moment of the aircraft based on the angle of attack value; determining a first objective function corresponding to the lift value of the aircraft based on the initial lift coefficient and the decay duration of the lift coefficient; determining second objective functions corresponding to at least two force parameters in the vertical direction at the current touchdown moment of the aircraft, and determining the delay time corresponding to the landing gear wheel load signal of the aircraft according to the first objective function and the second objective function; inputting the delay time into a prediction model for processing to obtain the target delay time corresponding to the landing gear wheel load signal at the target moment, and determining the fault prediction result corresponding to the landing gear shock strut of the aircraft based on the target delay time.

Description

Technical Field

[0001] The embodiments of this specification relate to the technical field of fault prediction, and particularly to an evaluation and prediction method for landing gear shock struts that combines data-driven and physical modeling. Background Art

[0002] The wheel load signal delay of the landing gear of an aircraft is the most important fault type of the landing gear shock strut, which is related to the safety of the aircraft. During actual flight, there may be a situation where the aircraft taxis after landing until the nose landing gear touches the ground, and the ground spoiler function has not been activated yet. The reason for this situation is that after the aircraft touches the ground, the main landing gear does not generate a wheel load signal in time, and the ground spoiler operation requires this wheel load signal. That is, after the aircraft lands and taxis for a period of time, and after the wheel load signal of the main landing gear appears, the ground spoiler function is immediately activated and operates normally.

[0003] During the flight of the aircraft, if the ground spoiler function is not activated in time after landing, it may be caused by the fact that after the landing main landing gear touches the ground, it does not generate a wheel load signal in time. Since after the aircraft lands and taxis for a period of time, the ground spoiler function is activated when the wheel load signal appears. If the wheel load signal is delayed, it will affect functions such as the ground spoiler function, reverse thrust, and braking, resulting in an increase in the landing distance, and thus affecting flight safety. It can be seen that how to determine the delay time of the wheel load signal and perform fault prediction on the landing gear shock strut of the aircraft based on the delay time has become an urgent problem to be solved. Summary of the Invention

[0004] In view of this, the embodiments of this specification provide an evaluation and prediction method for landing gear shock struts that combines data-driven and physical modeling. One or more embodiments of this specification also relate to an evaluation and prediction device for landing gear shock struts that combines data-driven and physical modeling, a computing device, a computer-readable storage medium, and a computer program to solve the technical defects existing in the prior art.

[0005] According to the first aspect of the embodiments of this specification, an evaluation and prediction method for landing gear shock struts that combines data-driven and physical modeling is provided, including:

[0006] Obtain the angle of attack value corresponding to the current touchdown moment of the aircraft, and determine the initial lift coefficient corresponding to the current touchdown moment of the aircraft based on the angle of attack value;

[0007] Determine a first objective function corresponding to the lift value of the aircraft based on the initial lift coefficient and the decay duration of the lift coefficient;

[0008] Determine the second objective functions corresponding to at least two force parameters in the vertical direction of the aircraft at the current touchdown moment, and determine the delay time corresponding to the landing gear wheel load signal of the aircraft according to the first objective function and the second objective function;

[0009] Input the delay time into a prediction model for processing to obtain the target delay time corresponding to the landing gear wheel load signal at the target moment, and determine the fault prediction result corresponding to the landing gear shock strut of the aircraft based on the target delay time.

[0010] Optionally, the at least two force parameters include: load, air chamber support force of the landing gear shock strut, and oil hole damping force of the landing gear shock strut;

[0011] Correspondingly, the method further includes:

[0012] Determine the second objective function corresponding to the air chamber support force of the landing gear shock strut based on the initial inflation pressure of the landing gear shock strut, the cross-sectional area of the air chamber, and the stroke of the landing gear shock strut;

[0013] Determine the second objective function corresponding to the oil hole damping force of the landing gear shock strut based on the oil hole damping coefficient and the compression speed of the landing gear shock strut.

[0014] Optionally, the determining the initial lift coefficient corresponding to the aircraft at the current touchdown moment based on the angle of attack value includes:

[0015] Obtain the functional relationship between the lift coefficient and the angle of attack value;

[0016] Determine the initial lift coefficient corresponding to the aircraft at the current touchdown moment based on the angle of attack value and the functional relationship.

[0017] Optionally, the determining the delay time corresponding to the landing gear wheel load signal of the aircraft according to the first objective function and the second objective function includes:

[0018] Construct a third objective function based on the first objective function and the second objective function;

[0019] Obtain the delay time corresponding to the landing gear wheel load signal of the aircraft by solving the third objective function.

[0020] Optionally, the determining the first objective function corresponding to the lift value of the aircraft based on the initial lift coefficient and the decay duration of the lift coefficient includes:

[0021] Taking the decay duration of the lift coefficient as the independent variable, taking the lift values of the aircraft at different times within the decay duration as the dependent variable, and constructing a first objective function corresponding to the lift value of the aircraft based on the initial lift coefficient and the decay coefficient.

[0022] Optionally, the data-driven and physical modeling fusion-based landing gear shock strut evaluation and prediction method further includes:

[0023] When it is determined that the delay time belongs to the parameter value interval corresponding to the pre-generated landing gear wheel load signal, updating the parameter value interval to generate a target parameter value interval.

[0024] Optionally, the data-driven and physical modeling fusion-based landing gear shock strut evaluation and prediction method further includes:

[0025] Obtaining a plurality of historical delay times corresponding to the landing gear wheel load signal of the aircraft;

[0026] Calculating the mean and standard deviation corresponding to the plurality of historical delay times;

[0027] Based on the mean, the standard deviation, and the target confidence level, constructing a parameter value interval corresponding to the landing gear wheel load signal.

[0028] Optionally, the data-driven and physical modeling fusion-based landing gear shock strut evaluation and prediction method further includes:

[0029] When it is determined that the delay time belongs to the parameter value interval corresponding to the pre-generated landing gear wheel load signal, constructing the health state corresponding to the delay time.

[0030] Optionally, the constructing the health state corresponding to the delay time includes:

[0031] Obtaining a plurality of historical delay times corresponding to the landing gear wheel load signal of the aircraft, and calculating the mean corresponding to the plurality of historical delay times;

[0032] Determining the absolute value of the difference between the delay time and the mean;

[0033] Mapping the absolute value to a target interval, and determining the mapping result as the health state corresponding to the delay time, where the upper limit value and the lower limit value of the target interval are 1 and 0 respectively.

[0034] According to the second aspect of the embodiments of the present specification, there is provided a data-driven and physical modeling fusion-based landing gear shock strut evaluation and prediction device, including:

[0035] An acquisition module, configured to acquire the angle of attack value corresponding to the current touchdown moment of the aircraft, and determine the initial lift coefficient corresponding to the current touchdown moment of the aircraft based on the angle of attack value;

[0036] A first determination module, configured to determine a first objective function corresponding to the lift value of the aircraft based on the initial lift coefficient and the decay duration of the lift coefficient;

[0037] A second determination module, configured to determine second objective functions corresponding to at least two force parameters in the vertical direction at the current touchdown moment of the aircraft, and determine the delay time corresponding to the landing gear wheel load signal of the aircraft according to the first objective function and the second objective function;

[0038] A third determination module, configured to input the delay time into a prediction model for processing, obtain the target delay time corresponding to the landing gear wheel load signal at the target moment, and determine the fault prediction result corresponding to the landing gear shock strut of the aircraft based on the target delay time.

[0039] According to a third aspect of the embodiments of the present specification, a computing device is provided, including:

[0040] A memory and a processor;

[0041] The memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions to implement the steps of any one of the above-mentioned landing gear shock strut evaluation and prediction methods that integrate data driving and physical modeling.

[0042] According to a fourth aspect of the embodiments of the present specification, a computer-readable storage medium is provided, which stores computer-executable instructions, and when the instructions are executed by a processor, the steps of any one of the above-mentioned landing gear shock strut evaluation and prediction methods that integrate data driving and physical modeling are implemented.

[0043] According to a fifth aspect of the embodiments of the present specification, a computer program is provided, wherein when the computer program is executed on a computer, the computer is made to execute the steps of the above-mentioned landing gear shock strut evaluation and prediction method that integrates data driving and physical modeling.

[0044] The landing gear shock strut evaluation and prediction method integrating data-driven and physical modeling provided by the embodiments of this specification obtains the angle of attack value corresponding to the current touchdown moment of the aircraft, and determines the initial lift coefficient corresponding to the current touchdown moment of the aircraft based on the angle of attack value; determines the first objective function corresponding to the lift value of the aircraft based on the initial lift coefficient and the decay duration of the lift coefficient; determines the second objective functions corresponding to at least two acting force parameters in the vertical direction of the aircraft at the current touchdown moment, and determines the delay time corresponding to the landing gear wheel load signal of the aircraft according to the first objective function and the second objective functions; inputs the delay time into the prediction model for processing to obtain the target delay time corresponding to the landing gear wheel load signal at the target moment, and determines the fault prediction result corresponding to the landing gear shock strut of the aircraft based on the target delay time. In this way, the delay time corresponding to the landing gear wheel load signal of the aircraft is determined, and the landing gear shock strut is fault predicted based on this delay time, and a fault warning can be given when a fault is determined to exist, which is beneficial to avoiding the situation where the ground breaking and lifting function cannot be opened in time due to the delay of the landing gear wheel load signal, and further beneficial to avoiding or reducing the flight faults of the aircraft and improving flight safety. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 is a flowchart of a landing gear shock strut evaluation and prediction method integrating data-driven and physical modeling provided by an embodiment of this specification;

[0046] Figure 2a is a schematic diagram of the relationship between the radio altitude and the braking time corresponding to the braking stage of the aircraft provided by an embodiment of this specification;

[0047] Figure 2b is a schematic diagram of the stable section of the radio altitude provided by an embodiment of this specification;

[0048] Figure 3 is a schematic diagram of the relationship between the ground speed and the braking time corresponding to the braking stage of the aircraft provided by an embodiment of this specification;

[0049] Figure 4 is a schematic diagram of the change of the displacement of the landing gear shock strut with time provided by an embodiment of this specification;

[0050] Figure 5 is a schematic diagram of the structure of a prediction model provided by an embodiment of this specification;

[0051] Figure 6 is a schematic diagram of the trend prediction result corresponding to the delay time of the wheel load signal provided by an embodiment of this specification;

[0052] Figure 7aIt is a schematic diagram of the fitting result corresponding to the mean value of the historical delay time provided by an embodiment of this specification;

[0053] Figure 7b It is a schematic diagram of the fitting update result corresponding to the mean value of the historical delay time provided by an embodiment of this specification;

[0054] Figure 7c It is a schematic diagram of the fitting result corresponding to the standard deviation of the historical delay time provided by an embodiment of this specification;

[0055] Figure 7d It is a schematic diagram of the fitting update result corresponding to the standard deviation of the historical delay time provided by an embodiment of this specification;

[0056] Figure 8 It is a schematic diagram of the structure of a landing gear shock strut evaluation and prediction device that integrates data-driven and physical modeling provided by an embodiment of this specification;

[0057] Figure 9 It is a structural block diagram of a computing device provided by an embodiment of this specification. Detailed implementation manners

[0058] In the following description, many specific details are set forth in order to provide a thorough understanding of this specification. However, this specification can be implemented in many other ways different from those described herein, and those skilled in the art can make similar generalizations without departing from the connotation of this specification. Therefore, this specification is not limited by the specific implementations disclosed below.

[0059] The terms used in one or more embodiments of this specification are for the purpose of describing specific embodiments only and are not intended to limit one or more embodiments of this specification. The singular forms "a", "the", and "said" used in one or more embodiments of this specification and the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the term "and / or" used in one or more embodiments of this specification refers to and includes any or all possible combinations of one or more of the associated listed items.

[0060] It should be understood that although the terms first, second, etc. may be used in one or more embodiments of this specification to describe various information, such information should not be limited to these terms. These terms are only used to distinguish the same type of information from each other. For example, without departing from the scope of one or more embodiments of this specification, the first may also be referred to as the second, and similarly, the second may also be referred to as the first. Depending on the context, the word "if" as used herein can be interpreted as "when" or "while" or "in response to determining".

[0061] First, the noun terms involved in one or more embodiments of this specification are explained.

[0062] By considering the physical mechanism of the compression process of the shock strut when the aircraft touches down, the kinematic and dynamic models of the compression process of the shock strut are established in the embodiments of this specification to obtain the delay time of the wheel load signal of the landing gear, which is used as a characteristic value for monitoring the health status of the shock strut of the landing gear. Subsequently, data-driven algorithms such as Bayesian theory and deep recurrent network are combined to realize the health assessment and fault trend prediction of the shock strut of the landing gear.

[0063] In this specification, a method for evaluating and predicting the shock strut of the landing gear that combines data-driven and physical modeling is provided. This specification also relates to a device for evaluating and predicting the shock strut of the landing gear that combines data-driven and physical modeling, a computing device, a computer-readable storage medium, and a computer program, which will be described in detail one by one in the following embodiments.

[0064] Figure 1 The flowchart of a method for evaluating and predicting the shock strut of the landing gear that combines data-driven and physical modeling provided by an embodiment of this specification is shown, which specifically includes the following steps.

[0065] Step 102: Obtain the angle of attack value corresponding to the current touchdown moment of the aircraft, and determine the initial lift coefficient corresponding to the current touchdown moment of the aircraft based on the angle of attack value.

[0066] In an alternative embodiment, the determining the initial lift coefficient corresponding to the current touchdown moment of the aircraft based on the angle of attack value includes:

[0067] Obtain the functional relationship between the lift coefficient and the angle of attack value;

[0068] Based on the angle of attack value and the functional relationship, determine the initial lift coefficient corresponding to the current touchdown moment of the aircraft.

[0069] Specifically, the current touchdown moment is the instantaneous moment corresponding to the moment when the aircraft touches down. For an aircraft, the angle of attack refers to the angle between the lift direction vector of the aircraft and the longitudinal axis of the aircraft.

[0070] The schematic diagram of the relationship between the radio altitude and the braking time corresponding to the braking stage of the aircraft provided by the embodiments of this specification is as Figure 2a shown. The schematic diagram of the stable section of the radio altitude provided by the embodiments of this specification is as Figure 2b shown.

[0071] In the embodiments of this specification, according to the radio altitude signal 'RADIO_GEIGHT_L', the parameter stationary segment capture algorithm can be used to capture the stationary segments of the radio altitude in each flight segment. Each flight segment contains multiple stationary segments of the radio altitude, including the pre-takeoff stage, the cruise stage, and the post-landing stage. The last stationary segment of each flight segment should be the stage when the radio altitude of the aircraft is 0 after landing. Furthermore, the timestamp of the moment when the aircraft lands can be found, and this moment is recorded as the current touchdown moment of the aircraft.

[0072] In addition, there is a correlation between the lift coefficient during the aircraft touchdown process and the angle of attack value during the aircraft touchdown process. When the angle of attack value is between -5 and 10 degrees, the two approximately satisfy a linear relationship. And in the embodiments of this specification, considering the influence of the landing configuration and the ground effect near the ground on the lift coefficient at the same time, according to the python data fitting function, the function relationship with the angle of attack AOA can be fitted, as follows:

[0073] Formula (1)

[0074] Where, is the angle of attack value; is the correction value, K and are both constants, and K can be obtained through fitting.

[0075] In practical applications, multiple angle of attack values and the corresponding lift coefficients can be obtained from the information included in the flight manual of the aircraft, and the correction value corresponding to each angle of attack value can be obtained. Then, through the corresponding relationship between each angle of attack value and the respective lift coefficients , the value of K can be obtained through fitting, that is, the function relationship between and is obtained as ; in addition, the function relationship between and can also be obtained through the corresponding relationship between each angle of attack value and the respective correction values , and then the two are summed to obtain the lift coefficient shown in formula (1) and the function relationship between the angle of attack .

[0076] When the function relationship between the lift coefficient and the angle of attack value, that is, the above formula (1), is determined, the angle of attack value corresponding to the aircraft at the current touchdown moment can be input into formula (1) to obtain the initial lift coefficient corresponding to the aircraft at the current touchdown moment.

[0077] Step 104: Determine a first objective function corresponding to the lift value of the aircraft based on the initial lift coefficient and the decay duration of the lift coefficient.

[0078] In an alternative embodiment, the determining a first objective function corresponding to the lift value of the aircraft based on the initial lift coefficient and the decay duration of the lift coefficient includes:

[0079] Taking the decay duration of the lift coefficient as the independent variable, taking the lift values of the aircraft at different times during the decay duration as the dependent variable, and constructing a first objective function corresponding to the lift value of the aircraft based on the initial lift coefficient and the decay coefficient.

[0080] Specifically, since the lift coefficient also changes in real time during the landing phase of the aircraft, another calculation method in the embodiments of this specification is as follows: First, find the angle of attack value at the moment of aircraft landing, and use the fitting algorithm to obtain the initial lift coefficient at the moment of landing. Then, the lift coefficient rapidly decays to 0, and the decay method is linear decay. Taking the decay duration t of the lift coefficient as the independent variable, the expression of can be obtained as follows: The expression of

[0081] Formula (2)

[0082] where k is the decay coefficient, T is the total decay duration, and both k and T are constants.

[0083] Taking the decay duration of the lift coefficient as the independent variable and taking the lift coefficient as the dependent variable, after determining the functional relationship between the lift coefficient and the decay duration t, taking the decay duration of the lift coefficient as the independent variable and taking the lift values L of the aircraft at different times during the decay duration as the dependent variable, and constructing the first objective function corresponding to the lift value of the aircraft based on the initial lift coefficient and the decay coefficient is:

[0084] Formula (3)

[0085] where is the air density; is the wing reference area; v1 is the ground speed, and its value can be obtained by detecting the ground speed at different times through a sensor; and are both constants.

[0086] The schematic diagram of the relationship between the ground speed and the braking time corresponding to the braking phase of the aircraft provided in the embodiments of this specification is as shown in Figure 3 as follows.

[0087] Substitute the expression in formula (2) into formula (3), and the first objective function corresponding to the lift value of the aircraft can be obtained.

[0088] In practical applications, the reference wing area can be taken as 79.86 m 2 .

[0089] Step 106: Determine the second objective functions corresponding to at least two force parameters in the vertical direction of the aircraft at the current touchdown moment, and determine the delay time corresponding to the landing gear wheel load signal of the aircraft according to the first objective function and the second objective function.

[0090] In an alternative embodiment, the at least two force parameters include: load, air chamber support force of the landing gear shock strut, and oil hole damping force of the landing gear shock strut;

[0091] Correspondingly, the method further includes:

[0092] Determine the second objective function corresponding to the air chamber support force of the landing gear shock strut based on the initial inflation pressure of the landing gear shock strut, the cross-sectional area of the air chamber, and the stroke of the landing gear shock strut;

[0093] Determine the second objective function corresponding to the oil hole damping force of the landing gear shock strut based on the oil hole damping coefficient and the compression speed of the landing gear shock strut.

[0094] Further, the determining the delay time corresponding to the landing gear wheel load signal of the aircraft according to the first objective function and the second objective function includes:

[0095] Construct a third objective function based on the first objective function and the second objective function;

[0096] Obtain the delay time corresponding to the landing gear wheel load signal of the aircraft by solving the third objective function.

[0097] In the embodiments of this specification, the process of the aircraft touching down and generating a landing gear wheel load signal is actually a process of compression of the landing gear shock strut, accompanied by the compression of the tire. The energy of these two compressions comes from the impact kinetic energy of the aircraft sinking and touching down, as well as the work done by the resultant force of lift and gravity during this process. Its characteristics are:

[0098] 1) The energy of the aircraft sinking is absorbed by the landing gear shock strut and the tire, and the energy conversion is conserved;

[0099] 2) When the landing gear shock strut is compressed, part of the energy is stored in the compressed gas, and the other part is dissipated through damping effects such as oil and friction.

[0100] 3) When the tire is compressed, it absorbs energy, and this energy is basically not dissipated.

[0101] Furthermore, considering the most severe situation for the generation of the landing gear wheel load signal, that is, considering the case of floating descent (sinking speed is 0) when the aircraft touches down, taking the part of the aircraft above the air chamber of the main landing gear shock strut as the research object, the bouncing process, that is, the compression process of the landing gear shock strut, is analyzed.

[0102] In the embodiments of this specification, the vertical force when the aircraft touches down includes the lift force L, and also includes the load G when the aircraft touches down, the support force f1 of the air chamber of the landing gear shock strut, and the damping force f2 of the oil hole of the landing gear shock strut.

[0103] Among them, the load G when the aircraft touches down is actually related to multiple factors such as the attitude and pitch angle of the aircraft when it touches down, and the actual load calculation is relatively complex. Therefore, in the embodiments of this specification, the load G is calculated according to the total gravity of the aircraft.

[0104] In addition, the second objective function corresponding to the support force of the air chamber of the landing gear shock strut determined based on the initial inflation pressure, the cross-sectional area of the air chamber, and the stroke of the landing gear shock strut is:

[0105] Formula (4)

[0106] Among them, is the initial inflation pressure of the landing gear shock strut; is the cross-sectional area of the air chamber; is the displacement of the landing gear shock strut in the vertical direction; P and are both constants.

[0107] The schematic diagram of the displacement of the landing gear shock strut changing with time provided by the embodiments of this specification is as Figure 4 shown.

[0108] In practical applications, the value of the initial inflation pressure P can be 21 / 23 bar; the cross-sectional area of the air chamber can be 0.017471749 m 2 .

[0109] In addition, the second objective function corresponding to the damping force of the oil hole of the landing gear shock strut determined based on the oil hole damping coefficient and the compression speed of the landing gear shock strut is:

[0110] Formula (5)

[0111] where j is the damping coefficient of the oil hole; is the compression speed of the shock strut, and j is a constant.

[0112] In the embodiments of this specification, after determining the first objective function or the second objective function corresponding to the force parameters in the vertical direction of the aircraft at the current touchdown moment, the delay time corresponding to the wheel load signal of the aircraft landing gear can be determined according to the first objective function and the second objective function.

[0113] Specifically, since the force parameters in the vertical direction of the aircraft satisfy a certain dynamic relationship, therefore, a third objective function can be constructed based on the first objective function and the second objective function, and by solving the third objective function, the delay time corresponding to the wheel load signal of the aircraft landing gear can be obtained.

[0114] Among them, the third objective function constructed based on the first objective function and the second objective function is:

[0115] a Formula (6)

[0116] Formula (6) includes the stroke of the landing gear shock strut, that is, the displacement s of the landing gear shock strut in the vertical direction, the compression speed v2 of the shock strut, and the acceleration a, and it is a second-order differential equation. The embodiments of this specification can use python programming to solve it, and the specific algorithm is as follows:

[0117] Step 1: Determine the initial values and boundary conditions.

[0118] Initial value setting: s = 0, v2 = 0, , L0 is calculated according to calculate;

[0119] Boundary condition: threshold_s = 0.0254 (m)

[0120] Step 2: Set the time step t = 0.0001s.

[0121] Step 3: For each advancement of a time step, the program updates the displacement s, the real-time acceleration a, and the speed v2 once. When s > threshold_s, stop the calculation and record the total number of time steps, that is, obtain the delay time corresponding to the wheel load signal of the aircraft landing gear.

[0122] It should be noted that even though the landing gear shock strut of the aircraft compresses, and at the same time the tire compresses, when constructing the third objective function based on the dynamic relationship between the force parameters in the vertical direction of the aircraft in the embodiments of this specification, the force generated by the tire compression is not considered.

[0123] Step 108: Input the delay time into the prediction model for processing to obtain the target delay time corresponding to the landing gear wheel load signal at the target moment, and determine the fault prediction result corresponding to the landing gear shock strut of the aircraft based on the target delay time.

[0124] Specifically, after obtaining the delay time corresponding to the landing gear wheel load signal at the current grounding moment of the aircraft, the delay time can be input into the pre-trained prediction model, so as to predict through the prediction model to obtain the target delay time corresponding to the landing gear wheel load signal at the target moment, and perform fault prediction on the landing gear shock strut of the aircraft based on the target delay time to obtain the corresponding fault prediction result.

[0125] The prediction model in the embodiments of this specification adopts an end-to-end time series prediction model architecture, and uses a Bayesian neural network to quantify the prediction uncertainty. Specifically, a long short-term memory network (LSTM) is introduced to perform end-to-end modeling on the time series to extract the long-term dependence features existing in the time series. Uncertainty is introduced into the deep learning model from a Bayesian perspective, and dropout is applied after each hidden layer. The model output can be approximately regarded as a random sample generated by the posterior predictive distribution. Therefore, the uncertainty of the model can be estimated by the sample variance of several repeated model predictions.

[0126] A schematic structural diagram of a prediction model provided by the embodiments of this specification is as Figure 5 shown. This model includes two main components:

[0127] (1) An encoder-decoder framework, which captures the inherent patterns in the time series and is learned during the pre-training process. In the embodiments of this specification, an encoder-decoder framework with two layers of long short-term memory network (LSTM) units is used.

[0128] (2) A prediction network, which obtains the input from the learned embedding of the encoder-decoder, as well as any potential external features to guide the prediction. In the embodiments of this specification, a multi-layer perceptron is used as the prediction network.

[0129] The pre-training process of the prediction model is specifically as follows: First, filter and smooth the multiple historical delay times of the landing gear wheel load signal. Then, set the prediction time step of the model to 1 and the historical time step to 5. The prediction time step and the historical time step can be adjusted according to the actual data characteristics. Next, the constructed samples are first input into the encoder-decoder (AE) for pre-training, and then the features output by the AE are sent into the prediction network to obtain the trained prediction model.

[0130] After the complete model training process is completed, the trend of the delay time of the landing gear wheel load signal can be predicted by the prediction model obtained through training. Specifically, all the historical delay times and the delay time corresponding to the landing gear wheel load signal at the current grounding moment of the aircraft can be used to predict the target delay time at the next moment, that is, the target time.

[0131] A schematic diagram of the trend prediction result corresponding to the delay time of the wheel load signal provided by an embodiment of this specification is as Figure 6 shown.

[0132] In addition, it is also possible to determine whether there is a fault in the landing gear shock strut at the target time by judging whether the target delay time is within the parameter value range corresponding to the preset landing gear wheel load signal. Among them, if it is determined that the target delay time is within the parameter value range corresponding to the preset landing gear wheel load signal, it is determined that there is no fault in the landing gear shock strut at the target time; otherwise, it is determined that there is a fault in the landing gear shock strut at the target time. In this case, measures such as fault warning can be taken.

[0133] In practical applications, the real flight segment data of 46 flights can be used. The flight segment data belongs to time series data, the sampling frequency is 1Hz, the sampling length is about 3600 to 10800 points, and the flight parameters used include radio altitude (RADIO_GEIGHT), left inner wheel speed (WHL_SPD_BCU1(IN)_L), left outer wheel speed (WHL_SPD_BCU2(OUT)_L), right inner wheel speed (WHL_SPD_BCU1(IN)_R), right outer wheel speed (WHL_SPD_BCU2(OUT)_R), aircraft weight (GROSS_WEIGHT), ground speed (GRD_SPD). Other data includes wing reference area, initial inflation pressure of the shock strut, cross-sectional area of the air chamber, damping coefficient of the oil hole, shock strut compression speed parameter, etc.

[0134] In an alternative embodiment, the method for evaluating and predicting the landing gear shock strut by fusing data-driven and physical modeling further includes:

[0135] When it is determined that the delay time belongs to the parameter value interval corresponding to the pre-generated landing gear wheel load signal, update the parameter value interval to generate a target parameter value interval.

[0136] Further, the method for evaluating and predicting the landing gear shock strut by fusing data-driven and physical modeling further includes:

[0137] Obtain multiple historical delay times corresponding to the landing gear wheel load signal of the aircraft;

[0138] Calculate the mean and standard deviation corresponding to the multiple historical delay times;

[0139] Based on the mean, the standard deviation, and the target confidence level, construct a parameter value interval corresponding to the landing gear wheel load signal.

[0140] Specifically, after determining the delay time corresponding to the landing gear wheel load signal of the aircraft, it is also possible to first determine whether the delay time belongs to the parameter value interval corresponding to the pre-generated landing gear wheel load signal; if so, step 108 can be executed, and the parameter value interval can be updated based on the delay time to generate a target parameter value interval. Specifically, when it is determined that the delay time belongs to the parameter value interval corresponding to the pre-generated landing gear wheel load signal, the delay time is incorporated into the historical delay times, and the upper and lower threshold values of the parameter value interval are updated according to all the historical delay times to adapt to the changing trend of the health state of the aircraft hydraulic system.

[0141] In the embodiments of this specification, since the delay time of the landing gear wheel load signal approximately follows a normal distribution, the normal distribution is used to describe the delay time. Among them, the distribution parameters of the normal distribution are obtained by the Bayesian method. After obtaining the distribution parameters using the historical delay times, the upper and lower threshold values of the pre-constructed parameter value interval are updated based on the Bayesian theory using the new flight segment data.

[0142] The construction process of the upper and lower threshold values of the specific parameter value interval is as follows:

[0143] 1) First, based on experience, give a set of approximate distribution parameters for the distribution of the mean and variance of the delay time of the landing gear wheel load signal; then, based on the Bayesian method, use the historical delay times to adjust the prior distribution of the mean and variance to make it approximate the true distribution.

[0144] 2) Calculate the mean of the distribution of the mean and variance, and use its mean as the mean and variance of the distribution of the delay time of the landing gear wheel load signal. Select a reasonable confidence level, and use the confidence interval of the delay time of the landing gear wheel load signal as the upper and lower threshold values. The calculation method of the confidence interval is as follows:

[0145] Formula (7)

[0146] where up is the upper threshold and down is the lower threshold, is the average delay time, is the standard deviation of the delay time. is the quantile of the standard normal distribution, is the quantile.

[0147] In practical applications, first, the delay time of the landing gear wheel load signal can be fitted based on the single normal distribution with Bayesian optimization. The preset prior distribution follows a normal distribution, whose mean is the mean of the historical delay times of the historical flight segments and the variance is 1. Considering that has no negative values, it is set that in the prior distribution follows a half-normal distribution with a standard deviation of 1. Based on the above characteristic data, the fitting result of the posterior distribution is obtained; further, based on the obtained posterior distribution, the upper and lower threshold values of the parameter value interval are determined based on the 3 principle.

[0148] After the upper and lower threshold values of the parameter value interval are constructed, the parameter value interval can be used to detect faults and discriminate the health status of the delay time of the landing gear wheel load signal. When new flight segment data enters, first, the delay time of the landing gear wheel load signal is extracted based on the foregoing steps, and then it is judged whether the delay time is within the constructed upper and lower threshold values. If it is within the upper and lower threshold values, it is considered that the new flight segment data is in a normal state. If it exceeds the upper and lower threshold values, it is considered that the new flight segment data is in an abnormal state.

[0149] In addition, when the new flight segment data is in a normal state, the delay time of the landing gear wheel load signal in the new flight segment data needs to be incorporated into the historical data, and the upper and lower threshold values are updated using the extracted delay time of the landing gear wheel load signal. To avoid cumbersome calculations caused by excessive historical data, Bayesian theory is used to update the upper and lower threshold values and distribution parameters. Specifically, when the new flight segment data is determined to be in a normal state, the extracted delay time of the landing gear wheel load signal and a small part of the later historical delay times are used to update the distribution parameters and the upper and lower threshold values, rather than using all the historical delay times to update the upper and lower threshold values.

[0150] The schematic diagram of the fitting result corresponding to the mean of the historical delay times provided by an embodiment of this specification is as Figure 7a shown; the schematic diagram of the fitting update result corresponding to the mean of the historical delay times provided by an embodiment of this specification is as Figure 7bAs shown, where HDI represents the confidence level, mu_norm represents the normal distribution of the mean, and mean represents the mean; The schematic diagram of the fitting result corresponding to the standard deviation of the historical delay time provided by an embodiment of this specification is as Figure 7c shown; The schematic diagram of the fitting update result corresponding to the standard deviation of the historical delay time provided by an embodiment of this specification is as Figure 7d shown, where sigma_norm represents the normal distribution of the standard deviation.

[0151] In an alternative implementation, the data-driven and physical-modeling integrated landing gear shock strut evaluation and prediction method further includes:

[0152] When it is determined that the delay time belongs to the parameter value interval corresponding to the pre-generated landing gear wheel load signal, construct the health state corresponding to the delay time.

[0153] Further, constructing the health state corresponding to the delay time includes:

[0154] Obtain multiple historical delay times corresponding to the landing gear wheel load signal of the aircraft, and calculate the mean value corresponding to the multiple historical delay times;

[0155] Determine the absolute value of the difference between the delay time and the mean value;

[0156] Map the absolute value to the target interval, and determine the mapping result as the health state corresponding to the delay time, where the upper limit value and the lower limit value of the target interval are 1 and 0 respectively.

[0157] Specifically, when it is determined that the delay time belongs to the parameter value interval corresponding to the pre-generated landing gear wheel load signal, the health state corresponding to the delay time can also be constructed. Among them, this health state represents the degree of deviation of the delay time from the statistical mean.

[0158] In the embodiment of this specification, the construction process of the health state corresponding to the delay time is as follows:

[0159] 1) First, obtain the absolute value of the difference between the delay time and its mean value:

[0160] Formula (8)

[0161] Among them, e is the difference, x is the delay time, is the mean value of the delay time.

[0162] 2) Since the difference values of different delay times are different, it is necessary to map this difference to the interval (0, 1).

[0163] The mapping method can be a linear mapping:

[0164] Formula (9)

[0165] Wherein, is the health degree, e is the difference, is the standard deviation of e. J is the health degree truncation coefficient, and its value range is (0, 1), indicating that a warning is required when the health degree is 1 - J.

[0166] In practical applications, the health degree truncation coefficient J can be 0.4, that is, it is considered that a warning is required when the health degree is 0.6.

[0167] The mapping method can also be a non - linear mapping:

[0168] Formula (10)

[0169] Wherein, is the health degree, e is the difference, and J is the health degree truncation coefficient, and its value range is , indicating that a warning is required when the health degree is 1 - , is the standard deviation of e.

[0170] The landing gear shock strut evaluation and prediction method provided by the embodiments of this specification, which combines data - driven and physical modeling, obtains the angle of attack value corresponding to the current touchdown moment of the aircraft, and determines the initial lift coefficient corresponding to the current touchdown moment of the aircraft based on the angle of attack value; determines the first objective function corresponding to the lift value of the aircraft based on the initial lift coefficient and the decay duration of the lift coefficient; determines the second objective functions corresponding to at least two acting force parameters in the vertical direction at the current touchdown moment of the aircraft, and determines the delay time corresponding to the landing gear wheel load signal of the aircraft according to the first objective function and the second objective functions; inputs the delay time into the prediction model for processing to obtain the target delay time corresponding to the landing gear wheel load signal at the target moment, and determines the fault prediction result corresponding to the landing gear shock strut of the aircraft based on the target delay time. By this means, the delay time corresponding to the landing gear wheel load signal of the aircraft is determined, and the fault of the landing gear shock strut is predicted based on this delay time, and a fault warning can be given when a fault is determined, which is beneficial to avoiding the situation that the ground breaking - lift function cannot be opened in time due to the delay of the landing gear wheel load signal, and further beneficial to avoiding or reducing the flight faults of the aircraft and improving flight safety.

[0171] Corresponding to the above - mentioned method embodiments, this specification also provides embodiments of a landing gear shock strut evaluation and prediction device that combines data - driven and physical modeling, Figure 8The structural schematic diagram of a landing gear shock strut evaluation and prediction device that fuses data-driven and physical modeling provided by an embodiment of this specification is shown. As Figure 8 shown, the device includes:

[0172] An acquisition module 802, configured to acquire the angle of attack value corresponding to the current ground contact moment of the aircraft, and determine the initial lift coefficient corresponding to the aircraft at the current ground contact moment based on the angle of attack value;

[0173] A first determination module 804, configured to determine a first objective function corresponding to the lift value of the aircraft based on the initial lift coefficient and the decay duration of the lift coefficient;

[0174] A second determination module 806, configured to determine second objective functions corresponding to at least two acting force parameters in the vertical direction of the aircraft at the current ground contact moment, and determine the delay time corresponding to the landing gear wheel load signal of the aircraft according to the first objective function and the second objective functions;

[0175] A third determination module 808, configured to input the delay time into a prediction model for processing, obtain the target delay time corresponding to the landing gear wheel load signal at the target moment, and determine the fault prediction result corresponding to the landing gear shock strut of the aircraft based on the target delay time.

[0176] Optionally, the at least two acting force parameters include: load, air chamber support force of the landing gear shock strut, and oil hole damping force of the landing gear shock strut;

[0177] Correspondingly, the device further includes a processing module, configured to:

[0178] Determine the second objective function corresponding to the air chamber support force of the landing gear shock strut based on the initial inflation pressure of the landing gear shock strut, the cross-sectional area of the air chamber, and the stroke of the landing gear shock strut;

[0179] Determine the second objective function corresponding to the oil hole damping force of the landing gear shock strut based on the oil hole damping coefficient and the compression speed of the landing gear shock strut.

[0180] Optionally, the acquisition module 802 is further configured to:

[0181] Acquire the functional relationship between the lift coefficient and the angle of attack value;

[0182] Determine the initial lift coefficient corresponding to the aircraft at the current ground contact moment based on the angle of attack value and the functional relationship.

[0183] Optionally, the second determination module 806 is further configured to:

[0184] Construct a third objective function based on the first objective function and the second objective function;

[0185] By solving the third objective function, obtain the delay time corresponding to the landing gear wheel load signal of the aircraft.

[0186] Optionally, the first determination module 804 is further configured to:

[0187] Take the decay duration of the lift coefficient as the independent variable, take the lift values of the aircraft at different moments during the decay duration as the dependent variable, and construct a first objective function corresponding to the lift value of the aircraft based on the initial lift coefficient and the decay coefficient.

[0188] Optionally, the processing module is further configured to:

[0189] In the case where it is determined that the delay time belongs to a pre-generated parameter value interval corresponding to the landing gear wheel load signal, update the parameter value interval to generate a target parameter value interval.

[0190] Optionally, the processing module is further configured to:

[0191] Obtain multiple historical delay times corresponding to the landing gear wheel load signal of the aircraft;

[0192] Calculate the mean value and the standard deviation corresponding to the multiple historical delay times;

[0193] Based on the mean value, the standard deviation, and the target confidence level, construct a parameter value interval corresponding to the landing gear wheel load signal.

[0194] Optionally, the processing module is further configured to:

[0195] In the case where it is determined that the delay time belongs to a pre-generated parameter value interval corresponding to the landing gear wheel load signal, construct the health state corresponding to the delay time.

[0196] Optionally, the processing module is further configured to:

[0197] Obtain multiple historical delay times corresponding to the landing gear wheel load signal of the aircraft, and calculate the mean value corresponding to the multiple historical delay times;

[0198] Determine the absolute value of the difference between the delay time and the mean value;

[0199] Map the absolute value to a target interval, and determine the mapping result as the health state corresponding to the delay time, where the upper limit value and the lower limit value of the target interval are 1 and 0 respectively.

[0200] The above is a schematic solution of an evaluation and prediction device for a landing gear shock strut that integrates data-driven and physical modeling. It should be noted that the technical solution of the evaluation and prediction device for the landing gear shock strut that integrates data-driven and physical modeling belongs to the same concept as the technical solution of the above-mentioned evaluation and prediction method for the landing gear shock strut that integrates data-driven and physical modeling. For the details not described in the technical solution of the evaluation and prediction device for the landing gear shock strut that integrates data-driven and physical modeling, reference can be made to the description of the technical solution of the above-mentioned evaluation and prediction method for the landing gear shock strut that integrates data-driven and physical modeling.

[0201] Figure 9 FIG. shows a structural block diagram of a computing device 900 provided according to an embodiment of the present specification. The components of the computing device 900 include, but are not limited to, a memory 910 and a processor 920. The processor 920 is connected to the memory 910 via a bus 930, and a database 950 is used to store data.

[0202] The computing device 900 further includes an access device 940, and the access device 940 enables the computing device 900 to communicate via one or more networks 960. Examples of these networks include the Public Switched Telephone Network (PSTN), Local Area Network (LAN), Wide Area Network (WAN), Personal Area Network (PAN), or a combination of communication networks such as the Internet. The access device 940 may include one or more of any type of wired or wireless network interfaces (e.g., Network Interface Card (NIC)), such as an IEEE802.11 Wireless Local Area Network (WLAN) wireless interface, a Worldwide Interoperability for Microwave Access (Wi-MAX) interface, an Ethernet interface, a Universal Serial Bus (USB) interface, a cellular network interface, a Bluetooth interface, a Near Field Communication (NFC) interface, and so on.

[0203] In an embodiment of the present specification, the above components of the computing device 900 and Figure 9 other components not shown in Figure 9 may also be connected to each other, for example, via a bus. It should be understood that

[0204] the structural block diagram of the computing device shown is only for illustrative purposes and is not a limitation on the scope of the present specification. Those skilled in the art can add or replace other components as needed.

[0205] Among them, the processor 920 is used to execute the following computer-executable instructions, and when the computer-executable instructions are executed by the processor, the steps of the above-mentioned landing gear shock strut evaluation and prediction method that combines data driving and physical modeling are implemented.

[0206] The above is a schematic solution of a computing device according to this embodiment. It should be noted that the technical solution of this computing device and the technical solution of the above-mentioned landing gear shock strut evaluation and prediction method that combines data driving and physical modeling belong to the same concept. For the details not described in detail in the technical solution of the computing device, reference can be made to the description of the technical solution of the above-mentioned landing gear shock strut evaluation and prediction method that combines data driving and physical modeling.

[0207] An embodiment of this specification also provides a computer-readable storage medium, which stores computer-executable instructions, and when the computer-executable instructions are executed by the processor, the steps of the above-mentioned landing gear shock strut evaluation and prediction method that combines data driving and physical modeling are implemented.

[0208] The above is a schematic solution of a computer-readable storage medium according to this embodiment. It should be noted that the technical solution of this storage medium and the technical solution of the above-mentioned landing gear shock strut evaluation and prediction method that combines data driving and physical modeling belong to the same concept. For the details not described in detail in the technical solution of the storage medium, reference can be made to the description of the technical solution of the above-mentioned landing gear shock strut evaluation and prediction method that combines data driving and physical modeling.

[0209] An embodiment of this specification also provides a computer program. Among them, when the computer program is executed on a computer, the computer is made to execute the steps of the above-mentioned landing gear shock strut evaluation and prediction method that combines data driving and physical modeling.

[0210] The above is a schematic solution of a computer program according to this embodiment. It should be noted that the technical solution of this computer program and the technical solution of the above-mentioned landing gear shock strut evaluation and prediction method that combines data driving and physical modeling belong to the same concept. For the details not described in detail in the technical solution of the computer program, reference can be made to the description of the technical solution of the above-mentioned landing gear shock strut evaluation and prediction method that combines data driving and physical modeling.

[0211] The above describes specific embodiments of this specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims can be performed in a different order than in the embodiments and still achieve the desired results. Additionally, the processes depicted in the figures do not necessarily require the particular order or sequential order shown to achieve the desired results. In certain implementations, multitasking and parallel processing are also possible or may be advantageous.

[0212] The computer instructions include computer program code, which may be in the form of source code, object code, executable files, or some intermediate forms, etc. The computer-readable medium may include: any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium, etc. It should be noted that the content included in the computer-readable medium may be appropriately increased or decreased according to the requirements of legislation and patent practice within the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, the computer-readable medium does not include electrical carrier signals and telecommunication signals.

[0213] It should be noted that for the foregoing method embodiments, for the sake of simplicity of description, they are all expressed as a series of action combinations. However, those skilled in the art should know that the embodiments of this specification are not limited by the described action sequence, because according to the embodiments of this specification, certain steps can be performed in other sequences or simultaneously. Secondly, those skilled in the art should also know that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily essential to the embodiments of this specification.

[0214] In the above embodiments, the descriptions of the respective embodiments have their own emphases. For parts not detailed in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0215] The preferred embodiments of this specification disclosed above are only used to help explain this specification. The optional embodiments do not elaborate on all the details and do not limit the invention to the specific embodiments described. Obviously, many modifications and changes can be made according to the content of the embodiments of this specification. This specification selects and specifically describes these embodiments to better explain the principles and practical applications of the embodiments of this specification, so that those skilled in the art can well understand and utilize this specification. This specification is only limited by the claims and their full scope and equivalents.

Claims

1. A method for evaluating and predicting the landing gear shock strut by integrating data-driven and physical modeling, comprising: Obtaining the angle of attack value corresponding to the current touchdown moment of the aircraft, and determining the initial lift coefficient corresponding to the aircraft at the current touchdown moment based on the angle of attack value; Determining a first objective function corresponding to the lift value of the aircraft based on the initial lift coefficient and the decay duration of the lift coefficient; Determining a second objective function corresponding to the gas chamber support force of the landing gear shock strut based on the initial inflation pressure of the landing gear shock strut, the cross-sectional area of the gas chamber, and the stroke of the landing gear shock strut; Determining a second objective function corresponding to the oil hole damping force of the landing gear shock strut based on the oil hole damping coefficient and the compression speed of the landing gear shock strut; Constructing a third objective function based on the first objective function and the second objective function; Obtaining the delay time corresponding to the landing gear wheel load signal of the aircraft by solving the third objective function; Inputting the delay time into a prediction model for processing to obtain the target delay time corresponding to the landing gear wheel load signal at the target moment, and determining the fault prediction result corresponding to the landing gear shock strut of the aircraft based on the target delay time.

2. The method for evaluating and predicting the landing gear shock strut by integrating data-driven and physical modeling according to claim 1, wherein the determining the initial lift coefficient corresponding to the aircraft at the current touchdown moment based on the angle of attack value comprises: Obtaining the functional relationship between the lift coefficient and the angle of attack value; Determining the initial lift coefficient corresponding to the aircraft at the current touchdown moment based on the angle of attack value and the functional relationship.

3. The method for evaluating and predicting the landing gear shock strut by integrating data-driven and physical modeling according to claim 1 or 2, wherein the determining a first objective function corresponding to the lift value of the aircraft based on the initial lift coefficient and the decay duration of the lift coefficient comprises: Taking the decay duration of the lift coefficient as an independent variable, taking the lift values of the aircraft at different moments within the decay duration as dependent variables, and constructing a first objective function corresponding to the lift value of the aircraft based on the initial lift coefficient and the decay coefficient.

4. The method for evaluating and predicting the landing gear shock strut by integrating data-driven and physical modeling according to claim 1 further comprises: Updating the parameter value interval to generate a target parameter value interval when it is determined that the delay time belongs to the parameter value interval corresponding to the pre-generated landing gear wheel load signal.

5. The method for evaluating and predicting the landing gear shock strut by integrating data-driven and physical modeling according to claim 1 or 4 further comprises: Obtaining a plurality of historical delay times corresponding to the landing gear wheel load signal of the aircraft; Calculating the mean and standard deviation corresponding to the plurality of historical delay times; Constructing a parameter value interval corresponding to the landing gear wheel load signal based on the mean, the standard deviation, and the target confidence level.

6. The method for evaluating and predicting the landing gear shock strut by integrating data-driven and physical modeling according to claim 1 further comprises: When it is determined that the delay time belongs to the parameter value range corresponding to the pre-generated landing gear wheel load signal, a health state corresponding to the delay time is constructed.

7. The data-driven and physical modeling fusion-based landing gear shock strut evaluation and prediction method according to claim 6, wherein constructing the health state corresponding to the delay time includes: Obtaining a plurality of historical delay times corresponding to the landing gear wheel load signal of the aircraft, and calculating the mean value corresponding to the plurality of historical delay times; Determining the absolute value of the difference between the delay time and the mean value; Mapping the absolute value to a target range, and determining the mapping result as the health state corresponding to the delay time, wherein the upper limit value and the lower limit value of the target range are 1 and 0 respectively.

8. A data-driven and physical modeling fusion-based landing gear shock strut evaluation and prediction device, comprising: An acquisition module, configured to acquire the angle of attack value corresponding to the current touchdown moment of the aircraft, and determine the initial lift coefficient corresponding to the current touchdown moment of the aircraft based on the angle of attack value; A first determination module, configured to determine a first objective function corresponding to the lift value of the aircraft based on the initial lift coefficient and the decay duration of the lift coefficient; A second determination module, configured to determine a second objective function corresponding to the air chamber support force of the landing gear shock strut based on the initial inflation pressure of the landing gear shock strut, the cross-sectional area of the air chamber, and the stroke of the landing gear shock strut, determine a second objective function corresponding to the oil hole damping force of the landing gear shock strut based on the oil hole damping coefficient and the compression speed of the landing gear shock strut, construct a third objective function based on the first objective function and the second objective function, and obtain the delay time corresponding to the landing gear wheel load signal of the aircraft by solving the third objective function; A third determination module, configured to input the delay time into a prediction model for processing, obtain a target delay time corresponding to the landing gear wheel load signal at a target moment, and determine a fault prediction result corresponding to the landing gear shock strut of the aircraft based on the target delay time.

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