Reliability evaluation method for coordinated folding and unfolding actions of aircraft landing gear hydraulic system

Abstract

The invention relates to the technical field of aircraft landing gear hydraulic systems, in particular to an aircraft landing gear hydraulic system coordinated extension and retraction function reliability evaluation method, which comprises the following steps: constructing an AMESim-MATLAB-based landing gear hydraulic system joint performance simulation model; determining uncertain parameters and interval boundaries of the uncertain parameters which influence the coordinated folding and unfolding function; on the basis of the interval boundary, constructing a performance function representing the coordinated receiving and releasing function of the system, calculating an output interval of the performance function through joint simulation, and further calculating a non-probability reliability index to evaluate the reliability of the system; and based on the output interval, identifying a key variable influencing the reliability through global sensitivity analysis. According to the method, the non-probability interval theory is adopted, evaluation can be completed only through parameter boundary information, the defect that a traditional probability method depends on mass data and expensive computing resources is overcome, the method is particularly suitable for aviation engineering scenes with scarce experimental data, weak links can be accurately recognized, and a quantitative basis is provided for system optimization and maintenance.

Description

Technical Field

[0001] This invention relates to the field of aircraft landing gear hydraulic system technology, and in particular to a reliability evaluation method for the coordinated extension and retraction function of an aircraft landing gear hydraulic system. Background Technology

[0002] The aircraft landing gear system is a critical functional system ensuring safe takeoff, landing, and ground operations; its reliability directly affects flight safety. Among its components, the coordinated retraction and extension of the left and right main landing gear is one of the core performance characteristics of the landing gear system. Its synchronicity and timeliness directly impact the aircraft's attitude stability during takeoff and landing. Failures such as delayed retraction / extension or asynchronous left and right movements can lead to loss of aircraft attitude control and even serious flight safety accidents.

[0003] The aircraft landing gear hydraulic system is a typical complex system with highly coupled mechanical, electrical, and hydraulic components. Its coordinated retraction and extension functions and performance are influenced by multiple parameters, including hydraulic oil characteristics, actuator performance, and mechanical clearances. These core parameters are not constant values ​​in actual engineering; they exhibit significant uncertainties due to manufacturing tolerances, fluctuations in assembly processes, wear and degradation during long-term service, and disturbances from the external environment. This multi-source, coupled parameter uncertainty greatly increases the complexity of reliability analysis for landing gear.

[0004] Currently, landing gear reliability analysis primarily employs traditional probabilistic reliability methods. These methods typically require pre-assuming that the system input parameters follow a specific probability distribution, constructing a limit state function to describe the system failure boundary, and relying on numerical analytical techniques such as Monte Carlo simulation and importance sampling to solve for the system's failure probability, thereby completing the reliability assessment. However, directly applying traditional probabilistic reliability methods to the evaluation of the coordinated retraction and extension function of aircraft landing gear hydraulic systems has the following limitations:

[0005] First, the computational cost is high and the efficiency is low. The evaluation accuracy of traditional probabilistic reliability methods mainly relies on massive amounts of experimental data or high-fidelity simulation samples. For complex systems with high-dimensional and strongly nonlinear characteristics, such as landing gear hydraulic systems, the required sample size increases exponentially with the increase in the number of uncertain parameters, resulting in huge computational demands and making it difficult to achieve efficient evaluation.

[0006] Second, it has poor engineering adaptability and strong data dependence. Full-scale testing of aerospace equipment is extremely costly and data is scarce. In particular, testing under extreme conditions may cause irreversible damage to the equipment, making traditional methods that rely on rich data to fit probability distributions difficult to implement in practice.

[0007] Third, the uncertainty characterization is not precise enough, easily introducing model errors. In practical engineering, for many key parameters, such as the friction coefficient and minute leakage, their approximate fluctuation range can often only be determined based on experience, tolerance range, or limited test data, making it difficult to accurately obtain their precise probability distribution type and parameters. Traditional probabilistic reliability methods forcibly assume a probability distribution, which may introduce model errors that do not conform to the actual situation, causing the final reliability assessment results to deviate from the behavior of the real system, resulting in distorted assessment conclusions.

[0008] Fourth, it lacks the ability to identify key variables. Traditional probabilistic reliability methods typically output system-level reliability indicators, which can only qualitatively determine whether a system is "reliable" or "failed" from a macroscopic perspective. They struggle to quantify the specific impact of each uncertain parameter on the system's coordinated operation. This prevents engineers from accurately identifying the weakest link in the system or the key variables with the greatest impact on reliability, thus creating difficulties for subsequent system optimization design, tolerance allocation, and the development of preventative maintenance strategies.

[0009] Therefore, there is a lack of a reliable evaluation method for the coordinated deployment and retraction of landing gear hydraulic systems that is applicable to conditions of data scarcity, computationally efficient, capable of accurately characterizing interval uncertainties, and effectively identifying key influencing parameters. Summary of the Invention

[0010] To address the shortcomings of existing technologies, this invention provides a reliability evaluation method for the coordinated retraction and extension actuation of an aircraft landing gear hydraulic system. This method combines interval-based nonprobabilistic reliability theory with AMESim-MATLAB co-simulation technology. By constructing a system performance simulation model, setting parameter interval boundaries, defining nonprobabilistic function and reliability indices, and performing global sensitivity analysis, it achieves accurate quantitative evaluation of the system's coordinated retraction and extension reliability and effective identification of key influencing variables.

[0011] To achieve the above objectives, the present invention adopts the following technical solution:

[0012] This invention proposes a reliability evaluation method for the coordinated retraction and extension of an aircraft landing gear hydraulic system, comprising the following steps:

[0013] S1. Construct a joint performance simulation model of the landing gear hydraulic system based on AMESim-MATLAB;

[0014] S2. Determine the uncertain parameters affecting the coordinated retraction and extension of the landing gear and their interval boundaries;

[0015] S3. Based on the interval boundaries of uncertain parameters, construct a functional function characterizing the coordinated retraction and extension function of the landing gear; sample and calculate the interval of uncertain parameters through the joint performance simulation model to obtain the output interval of the functional function; calculate a non-probabilistic reliability index based on the output interval; and determine the system state based on the non-probabilistic reliability index.

[0016] S4. Based on the output range, perform global sensitivity analysis to identify key variables affecting system reliability from the uncertain parameters.

[0017] Furthermore, in S1, the construction process of the joint performance simulation model specifically includes:

[0018] S11. In the AMESim environment, based on the physical composition and oil circuit logic of the landing gear hydraulic system, build an initial simulation model including hydraulic oil tank, electric pump assembly, check valve, high pressure combined oil filter, relief valve, retraction solenoid valve, front landing gear strut actuator, front landing gear retraction actuator, left / right main landing gear retraction actuator and flow limiter.

[0019] S12. Assign corresponding mathematical sub-models to each component in the initial simulation model and set initial physical parameters;

[0020] S13. Run the initial simulation model and perform dynamic simulation to obtain the displacement-time response curves of each actuator. Compare the displacement-time response curves with the measured data to verify the initial simulation model. If the verification is successful, proceed to S14. Otherwise, return to S12 to correct the initial physical parameters and re-verify until the verification is successful.

[0021] S14. Compile the main control program in the MATLAB environment and call the verified initial simulation model to obtain the joint performance simulation model.

[0022] Furthermore, in S2, the interval boundaries of the uncertain parameters are determined based on the aircraft's design specifications, manufacturing tolerances, engineering measurement data, and aircraft support manual.

[0023] Furthermore, in S2, the uncertain parameters include at least: hydraulic oil viscosity, motor speed, safety valve pressure, viscous friction coefficient of each actuator, and leakage coefficient of each actuator.

[0024] Furthermore, in S3, the functional function includes a time-sensitive functional function. and symmetric function The effectiveness function and symmetric function System function :

[0025]

[0026]

[0027]

[0028] In the formula, The maximum allowable opening and closing time. For uncertain parameter combinations Next Simulated retraction and extension time of each actuator cylinder; The maximum allowable time difference between the retraction and extension of the left and right main landing gear actuators. For uncertain parameter combinations Simulated retraction and extension time of the lower left main landing gear actuator. For uncertain parameter combinations Simulated retraction and extension time of the lower right main landing gear actuator.

[0029] Furthermore, in S3, the specific process for determining the system state is as follows:

[0030] S31. Discretize the interval boundaries of each uncertain parameter and take values;

[0031] S32. By iterating through all discretized uncertain parameter combinations, the joint simulation model is called to perform calculations to obtain the output range of the function.

[0032] S33, based on the lower bound of the output interval Upper Realm Calculate its corresponding nonprobabilistic reliability index :

[0033]

[0034]

[0035]

[0036] In the formula, The median value. For deviation;

[0037] S34. Based on non-probabilistic reliability indicators Determine system status: when When ≥1, it indicates complete reliability; when -1 < When <1, it indicates an uncertain state; when When the value is ≤-1, it indicates complete failure.

[0038] Furthermore, the global sensitivity analysis is performed through the following steps:

[0039] S41. Fix a single uncertain parameter to a certain value within its range, while other parameters fluctuate discretely within their ranges. Obtain the output range of the function function under the current state through co-simulation.

[0040] S42. Cyclicly switch different fixed values ​​within the entire value range of the single uncertain parameter, repeat S41, and obtain the set of output intervals corresponding to the uncertain parameter within its entire range;

[0041] S43. Repeat S41 and S42 for all uncertain parameters to obtain the set of output intervals corresponding to each uncertain parameter in its entire interval.

[0042] S44. Based on the set of output intervals corresponding to each uncertain parameter, calculate the sensitivity index of the uncertain parameter. The sensitivity index is used to quantify the influence of the uncertain parameter on the fluctuation of the function output.

[0043] S45. Compare the sensitivity indices of all uncertain parameters to identify the key variables that have the greatest impact on system reliability.

[0044] Furthermore, in S44, the formula for calculating the sensitivity index is:

[0045]

[0046] In the formula For the first Sensitivity index for an uncertain parameter For the first When an uncertain parameter varies within its interval, the function outputs the actual cumulative total within that interval. The baseline cumulative total of the function output interval when all uncertain parameters vary within their intervals.

[0047] The present invention also proposes a computer-readable storage medium storing a computer program, characterized in that the program, when executed by a processor, implements the aforementioned reliability evaluation method for the coordinated retraction and extension of the aircraft landing gear hydraulic system.

[0048] The present invention also proposes an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the reliability evaluation method for the coordinated retraction and extension of the aircraft landing gear hydraulic system described above.

[0049] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0050] (1) This invention combines interval-based nonprobabilistic reliability theory with high-fidelity co-simulation technology, eliminating the reliance of traditional probabilistic methods on massive amounts of data and high computational costs. Only the parameter fluctuation range needs to be determined using easily obtainable engineering information such as design specifications and tolerances, and the evaluation can be completed on the AMESim-MATLAB automated simulation platform without the need to obtain the difficult-to-measure precise probability distribution in advance. On the one hand, it greatly reduces the data requirements and computational complexity, solving the bottleneck of scarce experimental data for aerospace equipment and the difficulty in implementing traditional methods. On the other hand, it strictly represents cognitive uncertainty with intervals, avoiding model errors introduced by improper assumptions about probability distributions, making the evaluation results more in line with engineering reality, and significantly improving the feasibility and accuracy of this technology in the reliability analysis of complex electromechanical-hydraulic systems.

[0051] (2) This invention not only achieves refined classification and quantification of the overall reliability status of the system through non-probabilistic reliability indicators, overcoming the limitations of traditional binary criteria; but also, through deeply integrated global sensitivity analysis, it can accurately trace whether the key failure modes affecting reliability are timely or symmetrical, and quantitatively identify the uncertain parameters that dominate the failure mode and their influence weights, forming a complete analysis chain from system-level status assessment to parameter-level weak link location, which improves reliability work from traditional ex-post judgment to ex-ante prediction and accurate diagnosis, providing direct and quantitative scientific basis for design optimization, tolerance allocation and the formulation of preventive maintenance strategies, and realizing the initiative and refinement of reliability management.

[0052] (3) This invention establishes a rigorously validated AMESim-MATLAB joint performance simulation model, which completely and accurately reproduces the dynamic physical process of the landing gear's hydraulically coordinated retraction and extension, ensuring the reliability of the analysis basis. Furthermore, by developing a main control program to achieve automatic parameter range sampling, batch simulation operation, and automatic result acquisition and processing, the complex reliability evaluation process is transformed into a standardized and automated software analysis system. On the one hand, this greatly improves analysis efficiency and reduces human error; on the other hand, it ensures the standardization and uniformity of the evaluation process and the repeatability of the results, making the evaluation conclusions more objective and credible. Attached Figure Description

[0053] Figure 1 This is a diagram of the initial simulation model built in the AMESim environment according to an embodiment of the present invention;

[0054] Figure 2The figures below are displacement-time simulation response curves of each actuator in the embodiments of the present invention; wherein, (a) is the displacement-time response curve of the front landing gear strut actuator; (b) is the displacement-time response curve of the front landing gear retraction actuator; (c) is the displacement-time response curve of the left main landing gear retraction actuator; and (d) is the displacement-time response curve of the right main landing gear retraction actuator.

[0055] Figure 3 The diagram illustrates the influence of each input variable on the function output range in this embodiment of the invention. Specifically, (a) is an example diagram showing the change in the output range of the time-dependent function corresponding to the left main landing gear actuator when the motor speed parameter is fixed; (b) is an example diagram showing the change in the output range of the time-dependent function corresponding to the left main landing gear actuator when the hydraulic oil viscosity parameter is fixed; and (c) is an example diagram showing the change in the output range of the time-dependent function corresponding to the left main landing gear actuator when the leakage coefficient parameter of the left main landing gear actuator is fixed.

[0056] Figure 4 The following are the sensitivity analysis results of the influence of each input variable on the output in the embodiments of the present invention; wherein, (a) is the sensitivity analysis result of each uncertain parameter on the timeliness of the left main landing gear actuator; (b) is the sensitivity analysis result of each uncertain parameter on the timeliness of the right main landing gear actuator; and (c) is the sensitivity analysis result of each uncertain parameter on the symmetry of the retraction and extension of the left and right main landing gears of the system. Detailed Implementation

[0057] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. 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 are within the scope of protection of the present invention.

[0058] Example

[0059] This embodiment proposes a reliability evaluation method for the coordinated retraction and extension of an aircraft landing gear hydraulic system, including the following steps:

[0060] S1. Construct a joint performance simulation model of the landing gear hydraulic system based on AMESim-MATLAB; specifically, follow these sub-steps:

[0061] S11. In AMESim's Sketch Mode, based on the actual composition of the landing gear hydraulic system, drag the hydraulic oil tank, electric pump assembly, check valve, high-pressure combination oil filter, overflow valve, retraction solenoid valve, nose landing gear strut actuator, nose landing gear retraction actuator, left / right main landing gear retraction actuator, and flow limiter, etc., and build the system according to the actual hydraulic circuit logic as follows: Figure 1 The initial simulation model shown.

[0062] S12. In Sub-model Mode, assign corresponding mathematical sub-models to each component of the initial simulation model. Then, in Parameter Mode, set the initial physical parameters of each component according to the aircraft maintenance manual and design data, such as basic parameters like hydraulic oil density of 850 kg / m³, actuator cylinder inner diameter of 60 mm, and stroke of 300 mm.

[0063] S13. In Simulation Mode, select the transient solver. In this embodiment, set the simulation duration to 60 seconds (the first 50 seconds are the lowering phase, and the last 10 seconds are the locking and holding phase), and the sampling frequency to 100Hz. Start the simulation and obtain the following data: Figure 2 The displacement-time curves of each actuator shown are compared with the simulated displacement-time response curves of the left and right main landing gear actuators to verify the model. If the verification passes, proceed to step S14; otherwise, return to step S12 to correct the initial physical parameters and re-verify until successful. The method for determining whether the verification passes is as follows: if the relative error between the simulated value and the corresponding measured value of the left and right main landing gear actuator deployment time is less than 5%, the verification is considered successful; otherwise, the verification is considered unsuccessful. In this embodiment, the relative errors between the simulated value and the corresponding measured value of the left and right main landing gear actuator deployment time are 3.09% and 2.81%, respectively, meaning the model verification is successful.

[0064] S14. In the MATLAB environment, develop the main control program and use the interface tools provided by AMESim (such as the AMESimSimulink Co-simulation interface or command line call) to establish the control link for the verified intermediate model in MATLAB. The developed main control program can input different parameter combinations into the verified intermediate model in batches, automatically start the simulation, and read the simulation result data. At this point, the co-performance simulation model is completed.

[0065] S2. Determine the uncertain parameters affecting the coordinated retraction and extension of the landing gear and their interval boundaries:

[0066] At the hydraulic power level, hydraulic oil viscosity, motor speed, and safety valve pressure are the fundamental variables determining system flow, pressure, and energy transfer. At the actuator level, the viscous friction coefficient and leakage coefficient of each actuator directly determine its dynamic response accuracy and power retention capability. Furthermore, the actuators of the front, left, and right main landing gears, due to their independent structures and working circuits, need to be considered as independent parameters to account for their characteristic fluctuations. Therefore, the uncertain parameters include: hydraulic oil viscosity, motor speed, safety valve pressure, viscous friction coefficient of each actuator, and leakage coefficient of each actuator. The interval boundaries of each uncertain parameter are determined based on aircraft design specifications, manufacturing tolerances, engineering measurement data, and aircraft maintenance manuals. In this embodiment, the uncertain parameters and their interval boundaries are shown in Table 1.

[0067] Table 1 Uncertain parameters and their interval boundaries

[0068] Serial Number Variable name The Lower World Upper Realm unit 1 Hydraulic oil viscosity 35.2 43.0 cp 2 motor speed 1470 1530 rev / min 3 Safety valve pressure 207 217 bar 4 coefficient of viscous friction of the front landing gear strut actuator 100 300 N / (m / s) 5 Left main landing gear actuator coefficient of viscous friction 100 300 N / (m / s) 6 Right main landing gear actuator coefficient of viscous friction 100 300 N / (m / s) 7 coefficient of viscous friction of nose landing gear actuator 100 300 N / (m / s) 8 Leakage coefficient of front landing gear strut actuator 0.001 0.01 L / min / bar 9 Leakage coefficient of left main landing gear actuator 0.001 0.01 L / min / bar 10 Right main landing gear actuator leakage coefficient 0.001 0.01 L / min / bar 11 Leakage coefficient of front landing gear actuator 0.001 0.01 L / min / bar

[0069] S3. Construct a function representing the coordinated extension and retraction of the landing gear. Using the constructed joint performance simulation model, perform sampling calculations within the range of uncertain parameters. Evaluate the reliability of the system under uncertainty through the output range of the function. Specifically, follow these sub-steps:

[0070] S31. Based on the interval boundaries of uncertain parameters, construct a functional function characterizing the coordinated retraction and extension function of the landing gear, the functional function including a time-sensitive functional function. and symmetric function The effectiveness function and symmetric function System function :

[0071]

[0072]

[0073]

[0074] In the formula, The maximum allowable opening and closing time. For uncertain parameter combinations Next Simulated retraction and extension time of each actuator cylinder =1, 2, 3, 4; The maximum allowable time difference between the retraction and extension of the left and right main landing gear actuators. For uncertain parameter combinations Simulated retraction and extension time of the lower left main landing gear actuator. For uncertain parameter combinations Simulated retraction and extension time of the lower right main landing gear actuator.

[0075] In this embodiment, the first actuator is the front landing gear strut actuator, the second actuator is the left main landing gear actuator, the third actuator is the right main landing gear actuator, and the fourth actuator is the front landing gear actuator. =50s; =3s; When the value is ≤0, the system is considered to have failed. When the value is ≤0, it is considered to be time-limited invalid. When the value is ≤0, it is considered that the symmetry has failed.

[0076] S32. In the MATLAB main program, the boundary values ​​are discretized; the interval of each uncertain parameter in Table 1 is uniformly discretized into 20 level values. Through nested loops, all possible combinations of discrete values ​​for the uncertain parameters are traversed, theoretically resulting in 20 possible combinations. 11 Each combination of uncertain parameters is selected using a scientific sampling method (such as Latin hypercube sampling) to select representative samples as uncertain parameter combinations. For each uncertain parameter combination, the joint performance simulation model established by S1 is called to calculate the simulated deployment and retraction time of each actuator corresponding to that uncertain parameter combination. Then, the symmetric function output value, the time-dependent function output value of each actuator, and the system function output value are calculated under that uncertain parameter combination. The time-dependent function output value of each actuator under all uncertain parameter combinations constitutes the time-dependent function output interval of that actuator; the symmetric function output value under all uncertain parameter combinations constitutes the symmetric function output interval; and the system function output value under all uncertain parameter combinations constitutes the system function output interval.

[0077] S33. Output the lower bound of the interval for each function. Upper Realm Calculate its corresponding nonprobabilistic reliability index :

[0078]

[0079]

[0080]

[0081] In the formula, The median value. This is the deviation.

[0082] The time-dependent function output range, symmetric function output range, system function output range, and non-probabilistic reliability index corresponding to each output range obtained in this embodiment are shown in Table 2.

[0083] Table 2. Calculation results of output range and non-probabilistic reliability index for each function.

[0084] Serial Number Function The Lower World Upper Realm Median Deviation 1 37.86 38.37 38.115 0.255 149.471 2 2.47 10.3 6.385 3.915 1.631 3 2.41 10.4 6.405 3.995 1.603 4 2.48 10.02 6.25 3.77 1.658 5 -3.48 3 -0.24 3.24 -0.074 6 -3.48 37.86 17.19 20.67 0.831

[0085] S34. Based on non-probabilistic reliability indicators Determine system status: when When ≥1, it indicates complete reliability; when -1 < When <1, it indicates an uncertain state; when A value ≤-1 indicates complete failure. Table 2 shows that the R value for the nose landing gear strut actuator is 149.471 (fully reliable), the R values ​​for the nose landing gear and left and right main landing gear actuators are 1.631, 1.603, and 1.658 (fully reliable), respectively, the R value for the time difference between the left and right main landing gears is -0.074 (uncertain state), and the overall system reliability R is 0.831 (uncertain state, with a risk of failure).

[0086] S4. Based on the output range of each function, perform global sensitivity analysis to identify the two uncertain parameters that have the greatest impact on system reliability, and use these two identified uncertain parameters as key variables; the specific process is as follows:

[0087] S41, Reference Figure 3 A single uncertain parameter is fixed at a certain value within its range, while other parameters fluctuate discretely within their ranges. The output range of each functional function under the current state is obtained through co-simulation. For example, taking the leakage coefficient of the left main landing gear actuator as an example, a specific value (such as 0.005) within its range [0.001, 0.01] L / min / bar is set, while the other 10 uncertain parameters fluctuate discretely within their ranges. The output range of each functional function under the current state is obtained through co-simulation.

[0088] S42. Cyclicly switch different fixed values ​​within the entire value range of the single uncertain parameter, repeat step S41, and obtain the output range of each function corresponding to each fixed value. The output range of each function corresponding to all fixed values ​​constitutes the set of output ranges of the function corresponding to the uncertain parameter within its entire range.

[0089] S43. Repeat S41 and S42 for all uncertain parameters to obtain the set of output intervals of each function corresponding to each uncertain parameter in its entire interval.

[0090] S44. Based on each set of output intervals corresponding to each uncertain parameter, calculate the sensitivity index of that uncertain parameter:

[0091]

[0092] In the formula For the first Sensitivity index for an uncertain parameter For the first When an uncertain parameter varies within its interval, the function outputs the actual cumulative total within that interval. The baseline cumulative total of the function output interval when all uncertain parameters vary within their intervals.

[0093] For example, to evaluate the impact of each uncertain parameter on the timeliness of the left-hand main landing gear actuator, then For the first When an uncertain parameter changes within its interval, the actual cumulative total output of the time-efficiency function corresponding to the main landing gear actuator from the left within its range. The baseline cumulative total of the output range of the time-efficiency function corresponding to the main landing gear actuator from the left, when all uncertain parameters vary within their range;

[0094] To evaluate the impact of each uncertain parameter on the timeliness of the right-hand main landing gear actuator, then For the first When an uncertain parameter changes within its interval, the actual cumulative total output of the time-efficiency function corresponding to the right-hand main landing gear actuator interval is given. The baseline cumulative total of the output range of the time-efficiency function corresponding to the right-hand main landing gear actuator when all uncertain parameters vary within their range;

[0095] To evaluate the impact of each uncertain parameter on the system symmetry, then For the first When an uncertain parameter varies within its interval, the actual cumulative total of the output interval of the symmetric function. The baseline cumulative total of the output interval of the symmetric function when all uncertain parameters vary within their intervals.

[0096] S45. Compare the sensitivity indices of all uncertain parameters to identify the two key variables that have the greatest impact on the reliability of the system or individual components.

[0097] refer to Figure 4 It can be seen that in this embodiment, the timeliness of the left main landing gear actuator is ( Figure 4 a) The leakage coefficient of the left main landing gear actuator and the sensitivity of the motor speed are significantly higher than other parameters, making them key variables; for the timeliness of the right main landing gear actuator ( Figure 4 b), the leakage coefficients of the right main landing gear actuator and the nose landing gear actuator are key variables; for system symmetry ( Figure 4 c) The leakage coefficient of the nose landing gear actuator and the viscosity of the hydraulic oil are key variables.

[0098] As can be seen from the above steps, this invention not only quantitatively evaluates the reliability of the coordinated retraction and extension of the landing gear hydraulic system, but also accurately identifies uncertain parameters leading to system risks through global sensitivity analysis. This provides a direct and quantitative basis for subsequent targeted design optimizations and maintenance support measures, such as improving the sealing performance of the actuator cylinder and controlling the viscosity range of the hydraulic oil, thereby significantly improving the accuracy and effectiveness of reliability management.

[0099] The specific embodiments of the present invention are provided to enable those skilled in the art to understand or implement the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention.

[0100] It should be understood that the present invention is not limited to the content already described above, and various modifications and changes can be made without departing from its scope. The scope of the present invention is limited only by the appended claims.

Claims

1. A reliability evaluation method for the coordinated retraction and extension actuation of an aircraft landing gear hydraulic system, characterized in that, Includes the following steps: S1. Construct a joint performance simulation model of the landing gear hydraulic system based on AMESim-MATLAB; S2. Determine the uncertain parameters affecting the coordinated retraction and extension of the landing gear and their interval boundaries; S3. Based on the interval boundaries of uncertain parameters, construct a functional function characterizing the coordinated retraction and extension function of the landing gear; sample and calculate the interval of uncertain parameters through the joint performance simulation model to obtain the output interval of the functional function; calculate a non-probabilistic reliability index based on the output interval; and determine the system state based on the non-probabilistic reliability index. S4. Based on the output range, perform global sensitivity analysis to identify key variables affecting system reliability from the uncertain parameters.

2. The reliability evaluation method for the coordinated retraction and extension of the aircraft landing gear hydraulic system according to claim 1, characterized in that, In S1, the construction process of the joint performance simulation model specifically includes: S11. In the AMESim environment, based on the physical composition and oil circuit logic of the landing gear hydraulic system, build an initial simulation model including hydraulic oil tank, electric pump assembly, check valve, high pressure combined oil filter, relief valve, retraction solenoid valve, front landing gear strut actuator, front landing gear retraction actuator, left / right main landing gear retraction actuator and flow limiter. S12. Assign corresponding mathematical sub-models to each component in the initial simulation model and set initial physical parameters; S13. Run the initial simulation model and perform dynamic simulation to obtain the displacement-time response curves of each actuator. Compare the displacement-time response curves with the measured data to verify the initial simulation model. If the verification is successful, proceed to S14. Otherwise, return to S12 to correct the initial physical parameters and re-verify until the verification is successful. S14. Compile the main control program in the MATLAB environment and call the verified initial simulation model to obtain the joint performance simulation model.

3. The reliability evaluation method for the coordinated retraction and extension of the aircraft landing gear hydraulic system according to claim 1, characterized in that, In S2, the interval boundaries of the uncertain parameters are determined based on the aircraft's design specifications, manufacturing tolerances, engineering measurement data, and aircraft support manual.

4. The reliability evaluation method for the coordinated retraction and extension of the aircraft landing gear hydraulic system according to claim 1, characterized in that, In S2, the uncertain parameters include at least: hydraulic oil viscosity, motor speed, safety valve pressure, viscous friction coefficient of each actuator, and leakage coefficient of each actuator.

5. The reliability evaluation method for the coordinated retraction and extension of the aircraft landing gear hydraulic system according to claim 1, characterized in that, In S3, the function includes a time-sensitive function. and symmetric function The effectiveness function and symmetric function Constitutes system function : In the formula, The maximum allowable opening and closing time. For uncertain parameter combinations Next Simulated retraction and extension time of each actuator cylinder; The maximum allowable time difference between the retraction and extension of the left and right main landing gear actuators. For uncertain parameter combinations Simulated retraction and extension time of the lower left main landing gear actuator. For uncertain parameter combinations Simulated retraction and extension time of the lower right main landing gear actuator.

6. The reliability evaluation method for the coordinated retraction and extension of the aircraft landing gear hydraulic system according to claim 1, characterized in that, In S3, the specific process for determining the system state is as follows: S31. Discretize the interval boundaries of each uncertain parameter and take values; S32. By iterating through all discretized uncertain parameter combinations, the joint simulation model is called to perform calculations to obtain the output range of the function. S33, based on the lower bound of the output interval Upper Realm Calculate its corresponding nonprobabilistic reliability index : In the formula, The median value. For deviation; S34. Based on non-probabilistic reliability indicators Determine system status: when When ≥1, it indicates complete reliability; when -1 < When <1, it indicates an uncertain state; when When the value is ≤-1, it indicates complete failure.

7. The reliability evaluation method for the coordinated retraction and extension of the aircraft landing gear hydraulic system according to claim 1, characterized in that, The global sensitivity analysis is performed through the following steps: S41. Fix a single uncertain parameter to a certain value within its range, while other parameters fluctuate discretely within their ranges. Obtain the output range of the function function under the current state through co-simulation. S42. Cyclicly switch different fixed values ​​within the entire value range of the single uncertain parameter, repeat S41, and obtain the set of output intervals corresponding to the uncertain parameter within its entire range; S43. Repeat S41 and S42 for all uncertain parameters to obtain the set of output intervals corresponding to each uncertain parameter in its entire interval. S44. Based on the set of output intervals corresponding to each uncertain parameter, calculate the sensitivity index of the uncertain parameter. The sensitivity index is used to quantify the influence of the uncertain parameter on the fluctuation of the function output. S45. Compare the sensitivity indices of all uncertain parameters to identify the key variables that have the greatest impact on system reliability.

8. The reliability evaluation method for the coordinated retraction and extension of the aircraft landing gear hydraulic system according to claim 7, characterized in that, In S44, the formula for calculating the sensitivity index is: In the formula For the first Sensitivity index for an uncertain parameter For the first When an uncertain parameter varies within its interval, the function outputs the actual cumulative total within that interval. The baseline cumulative total of the function output interval when all uncertain parameters vary within their intervals.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by the processor, the program implements the reliability evaluation method for the coordinated retraction and extension of the aircraft landing gear hydraulic system as described in any one of claims 1 to 8.

10. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the reliability evaluation method for the coordinated retraction and extension of the aircraft landing gear hydraulic system as described in any one of claims 1 to 8.

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