UQ-based flight control servo actuation system reliability multi-objective optimization method and system

Abstract

The invention provides a UQ-based flight control servo actuation system reliability multi-objective optimization method, and relates to the technical field of aviation system reliability, and the method comprises the following steps: S1, respectively constructing a system safety optimization objective, a reliability optimization objective and a testability optimization objective; s2, constructing a target constraint function based on a security optimization target, a reliability optimization target and a testability optimization target, and determining a non-deterministic constraint variable; and S3, solving the target constraint function to obtain an optimized constraint target result. According to the method, uncertainty constraint parameters such as system weight, material consumption, system redundancy and unit failure rate are constructed in combination with a system safety and reliability testability calculation model for uncertain factors influencing system safety and reliability testability in a system design process; and an optimization algorithm is determined, an optimization solution process is defined, different design schemes and optimization results are obtained through optimization solution, and collaboration and tradeoff of different design characteristics of the system are supported.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of aviation system reliability, in particular to a reliability multi-objective optimization method and system for a flight control servo actuation system based on UQ. BACKGROUND

[0002] In the aviation system design process, there are various uncertain factors affecting system reliability, and due to the inconsistency of safety, reliability, testability work purposes and design process, the independent work between each nature cannot be coordinated and unified, resulting in inconsistent quantification and control analysis process and results of some uncertain factors, low referenceability of design results, and inability to effectively support design implementation and other problems.

[0003] In the process of uncertainty design and control of aviation system, in addition to considering safety, reliability, testability and other design requirements and implementation process, the weight and material consumption of the aviation system itself are important factors affecting its design architecture. For multi-disciplinary optimization design involving safety, reliability, testability, the current main method is to construct multi-objective constraints for solving and calculation, to construct a reliability optimization objective, to determine the redundancy quantity of system composition unit, and to carry out optimization solving, but it mainly has the following two defects: one is that the current reliability design optimization method mainly considers MTBF (mean time between failures), and there is a lack of unified weighing and optimization of reliability and safety, testability indicators; the second is that the current reliability optimization cannot realize the unified consideration of weight and material consumption, although some scholars have constructed optimization functions and constraint conditions of reliability and weight, but they have not fully considered the correlation and constraint conditions of material consumption, weight, redundancy quantity, failure rate and other uncertain factors of system unit on safety, reliability, testability, overall weight and overall material consumption, the above two points are the fundamental reasons that restrict the current reliability optimization and cannot support the design. SUMMARY

[0004] Based on the above differences of the prior art, the purpose of the present application is to provide a reliability multi-objective optimization method and system for a flight control servo actuation system based on UQ, to form constraint conditions by constructing safety, reliability and testability optimization objectives, to add optimization constraint variable weight coefficients, to obtain a more convenient calculation of comprehensive optimization objective constraint function, to carry out multi-objective optimization and to solve the optimization objective to obtain the optimal constraint, and to realize the optimization design of safety, reliability and testability.

[0005] Specifically, in a first aspect, the present application provides a reliability multi-objective optimization method for a flight control servo actuation system based on UQ, comprising: S1, constructing system safety optimization objective, reliability optimization objective and testability optimization objective respectively; S2, based on the safety optimization target, reliability optimization target and testability optimization target, an optimization target constraint function is constructed and a non-deterministic constraint variable is determined, and the optimization target constraint function is as follows: ; ; ; ; wherein, is the safety optimization target, i.e. the function failure state set to be optimized, and is , wherein is the total number of function failure states to be optimized, I indicates the safety index set to be optimized, represents the number of underlying units affecting failure, represents the corresponding failure probability, represents the redundancy configuration number of the corresponding underlying unit, is the testability optimization target, is the quality of the unit , M is the maximum weight requirement of the system, is the material consumption of the unit , is the maximum material consumption requirement of the system, and are the minimum and maximum values of the corresponding , and are the minimum and maximum values of the number of redundancy of the corresponding underlying unit ; In the actual solving process, based on the multi-objective optimization requirement, the weight of each optimization target is determined, and a comprehensive optimization target constraint function is constructed as follows: ; wherein, is the coefficient corresponding to the safety optimization target, and is , is the reliability optimization target coefficient, is the testability optimization target coefficient.

[0006] S3, the comprehensive optimization target constraint function in step S2 is solved to obtain the optimization constraint target result.

[0007] Preferably, the safety optimization target in step S1 is: ; ; In the formula, represents the number of underlying units affecting The number of failed bottom-level units, Represents the corresponding failure probability, where This represents the failure rate of the i-th failure mode in unit l.

[0008] Preferably, the reliability optimization objective in step S2 is: ; In the formula, This indicates the number of redundant configurations for the corresponding underlying unit.

[0009] Preferably, the objective of the test optimization in step S2 is: ; In the formula, FDR is defined as the system fault detection rate, which is calculated using the D matrix or a fault propagation model. ; In the formula, This represents the total failure rate of the detected failure modes. This represents the total failure rate across all failure modes. Indicates the first Failure rate of each detected failure mode Indicates the first Failure rate of each failure mode.

[0010] Preferably, the constraint variables of the objective constraint function include the total system weight constraint, system material consumption constraint, number of system components constraint, failure rate constraint, system safety optimization objective, system reliability optimization objective, and system testability optimization objective.

[0011] Preferably, the total system weight constraint is: ; In the formula, For unit The mass is M, where M is the maximum required weight of the system.

[0012] Preferably, the system material consumption constraint is: ; In the formula, For unit Material consumption, This represents the maximum required material consumption for the system.

[0013] Secondly, the present invention provides an optimization system for a multi-objective reliability optimization method for a flight control servo actuation system based on UQ, which includes an optimization objective construction module, an objective constraint function construction module, and an objective constraint function solving module; The optimization target construction module is used for constructing system safety optimization target, reliability optimization target and testability optimization target respectively; the target constraint function construction module constructs target constraint functions based on the safety optimization target, the reliability optimization target and the testability optimization target and determines the optimization target; and the target constraint function solving module is used for solving the target constraint functions to obtain the optimization constraint target result.

[0014] Preferably, the reliability multi-objective optimization system can be stored in a computer device.

[0015] Compared with the prior art, the present application has the following beneficial effects: (1) The multi-objective optimization method for reliability and performance design of the flight control servo actuation system based on UQ provided by the present application combines a system safety reliability testability calculation model to establish an optimization target function, constructs system weight, material consumption constraints and system safety reliability testability constraints, and the optimization target includes a functional failure probability, a mean time between failures MTBF and a fault detection rate, and the constraint conditions include a system total weight, a material consumption constraint, a number constraint of system component units, a failure rate constraint and an optimization target constraint of system safety reliability testability.

[0016] (2) The multi-objective optimization method for reliability and performance design of the flight control servo actuation system based on UQ provided by the present application faces the uncertainty factors affecting system safety reliability testability in the system design process, combines a system safety reliability testability calculation model, constructs uncertainty constraints such as system weight, material consumption, system redundancy and unit failure rate, determines an optimization algorithm, clearly defines the optimization solving process, and obtains different design schemes and optimization results through optimization solving, thereby supporting the coordination and trade-off of different design characteristics of the system.

[0017] (3) The multi-objective optimization method for reliability and performance design of the flight control servo actuation system based on UQ provided by the present application determines the weight of the optimization target in the actual solving process, which facilitates the calculation and solving of the optimization algorithm, constructs a comprehensive optimization target constraint function, and can more quickly and accurately solve the optimization result to meet the optimization requirements of the flight control servo actuation system.

[0018] (4) The reliability multi-objective optimization system for the flight control servo actuation system based on UQ provided by the present application supports the trade-off and optimization of system safety, reliability and testability indexes, realizes the comprehensive trade-off of weight and material consumption, supports the integrated design of system safety, reliability and testability, and has practical popularization value. BRIEF DESCRIPTION OF DRAWINGS

[0019] Figure 1 is a reliability multi-objective optimization method flowchart of the flight control servo actuation system of the present application; Figure 2 is a performance model schematic diagram of the flight control servo actuation subsystem of the application; Figure 3 is a function implementation principle schematic diagram of the servo actuation system of the application; Figure 4 is a function loss FTA schematic diagram of the servo actuation system of the application; Figure 5 is a reliability multi-objective optimization system block diagram of the flight control servo actuation system of the application. DETAILED DESCRIPTION

[0020] Hereinafter, embodiments of the application will be described with reference to the accompanying drawings.

[0021] Figure 1 is a safety reliability testability multi-objective optimization method flow chart of the application facing system weight and material consumption constraints. As shown in Figure 1 , the application provides a reliability multi-objective optimization method of a flight control servo actuation system based on UQ, UQ being Uncertainty Quantification, indicating uncertainty quantification. The method comprises the following steps: S1, respectively constructing system safety optimization target, reliability optimization target and testability optimization target. In specific embodiments, the safety model is a function failure probability calculation model based on FTA, the reliability model is a basic reliability calculation model, and the testability model is a detection rate calculation model, such as D matrix, etc.

[0022] Among them, the safety optimization target is: ; ; In the formula, represents the number of bottom units affecting failure, represents the corresponding failure probability, wherein represents the failure rate of the i th failure mode of unit l.

[0023] Mainly combined with fault logic (and, or, voting, etc.) for numerical calculation. f is a solution function, which can be determined according to different components in specific embodiments.

[0024] The reliability optimization target is: ; In the formula, represents the number of corresponding bottom units of the redundancy configuration.

[0025] The testability optimization target is: ; wherein FDR is the system fault detection rate defined by the D matrix or the fault propagation model, wherein, ; wherein, represents the total failure rate of the detected fault modes, represents the total failure rate of all fault modes, represents the failure rate of the th detected fault mode, represents the failure rate of the th fault mode.

[0026] The constraints of the target constraint function include the total weight of the system, material consumption constraints, the number of constraints of system constituent units, failure rate constraints, and safety reliability testability optimization target constraints.

[0027] Preferably, the system weight constraint is: ; wherein, is the mass of the unit , and M is the maximum value of the system weight requirement.

[0028] The system material consumption constraint is: ; wherein, is the material consumption of the unit , and M is the maximum value of the system material consumption requirement.

[0029] S2, based on the above determined safety optimization target, reliability optimization target and testability optimization target, construct a target constraint function and determine non-deterministic constraint variables, the target constraint function is as follows: ; ; ; ; wherein, is the safety optimization target, represents the number of underlying units affecting failure, represents the corresponding failure probability, represents the number of redundancy configurations of the corresponding underlying units, is the testability optimization target, is the mass of the unit , and M is the maximum value of the system weight requirement, is the mass of the unit ​The material consumption of the system, The maximum value of the system material consumption requirement, And The minimum value and the maximum value of respectively, And The minimum value and the maximum value of the number of the bottom unit redundancy corresponding to the number of the bottom unit redundancy.

[0030] In the actual solving process, the weight of each optimization target is determined based on the multi-objective optimization requirement, which is convenient for optimization algorithm calculation and solving, and the comprehensive optimization target constraint function is constructed as follows: ; Among them, is the coefficient corresponding to the safety optimization target, and , is the reliability optimization target coefficient, is the testability optimization target coefficient. By constructing the comprehensive optimization target constraint function, the target constraint function can be more conveniently and accurately solved to obtain the optimization target result. At the same time, according to the comprehensive optimization target constraint function, the necessary uncertain constraint variables are determined to solve the subsequent steps, such as system weight, material consumption, system redundancy, unit failure rate, etc.

[0031] S3, determine the optimization algorithm, and determine the optimization solving process, and obtain different design schemes and optimization results through optimization solving. The optimization target and constraint form an optimization function, and the optimization algorithm is combined to carry out optimization solving. The target constraint function is solved to obtain the optimization constraint target result. In specific embodiments, the NSGA-II algorithm can be combined to carry out multi-objective optimization solving to obtain the solving result of the optimization target and the constraint variable. The optimal value of weight ( / kg), material consumption ( / ten thousand), safety, reliability, testability, unit redundancy, and failure mode failure rate constraint is obtained.

[0032] On the other hand, the application provides an optimization system for the reliability multi-objective optimization method of the flight control servo actuation system based on UQ, as shown in Figure 5 , which comprises an optimization target construction module 1, a target constraint function construction module 2, and a target constraint function solving module 3.

[0033] The optimization target construction module 1 is used to construct the system safety optimization target, the reliability optimization target, and the testability optimization target respectively; the target constraint function construction module 2 constructs the target constraint function based on the safety optimization target, the reliability optimization target, and the testability optimization target and determines the optimization target; and the target constraint function solving module 3 is used to solve the target constraint function to obtain the optimization constraint target result.

[0034] In specific embodiments, the reliability multi-objective optimization system can be stored in a computer device. When used, the reliability multi-objective optimization method of the flight control servo actuation system of the application can be called at any time.

[0035] The reliability multi-objective optimization system of the flight control servo actuation system provided in the embodiments supports the trade-off and optimization of system safety, reliability, and testability indicators when used, realizes the comprehensive trade-off with weight and consumables, can support the integrated optimization design of system safety, reliability, and testability, and has practical popularization value.

[0036] Application Embodiments The embodiments take a certain flight control servo actuation system as an example to further illustrate the method of the application. In specific applications, the flight control servo actuation system receives flight control computer instructions, realizes the driving direction and flow size control of the hydraulic circuit (dual redundancy) through the control of electromagnetic valves, to achieve the extension and retraction of the actuator cylinder, and further realize the control of the aircraft rudder surface and attitude. The specific principle of the related work of the flight control servo actuation system is shown in Figure 2 .

[0037] First, the optimization objectives of system safety, reliability, and testability are determined. For the servo subsystem, the output is the actuator displacement, and therefore the optimization objective of system safety is: .

[0038] The optimization objective of reliability is to maximize the mean time between failures, i.e.: .

[0039] The optimization objective of testability is to maximize the detection rate, i.e.: .

[0040] Second, the system safety, reliability, and testability design model information is obtained, and the safety model is constructed by combining the servo actuation subsystem implementation model shown in Figure 3 , i.e. the FTA model of the loss of actuator output function, as shown in Figure 4 .

[0041] Among them, the servo actuation subsystem composition and the fault mode information of each unit are shown in the following table: Table 1 Fault information of the servo actuation subsystem From Figure 4 and Table 1 above, the safety optimization objective calculation method is selected as follows, and the probability of loss of actuator output function can be calculated as: .

[0042] The reliability optimization target calculation method is as follows, and the calculation process of the reliability optimization target is as follows: .

[0043] For the testability optimization target, the detection means of each fault mode is clear, as shown in the following table: Table 2 BIT information of the servo actuation subsystem In combination with the foregoing detection rate optimization target and implementation process, the testability optimization target calculation method is selected as follows, and the servo actuation subsystem detection rate calculation process is obtained according to the above table as follows: .

[0044] On the basis of the optimization target, the constraint variables that need to be optimized are clear, including the weight, material consumption design constraints, and safety, reliability and testability constraints. In this embodiment, the servo actuation subsystem constraint parameters are shown in the following table: Table 3 Optimization constraint parameters of the servo actuation subsystem For the above optimization target and constraint condition, in combination with Table 1 and Table 2 design information, the system weight, material consumption, safety, reliability and testability indicators before optimization are calculated, and the calculation results are as follows: The total weight is 112 kg; The material consumption is 980,000; The actuator actuation function failure probability is 0.00335; The basic reliability index is MTBF = 298.15 h; The testability detection rate is 98.51%.

[0045] The actuator actuation function failure probability in the foregoing does not meet the index requirement, and therefore trade-off optimization needs to be carried out.

[0046] Finally, in combination with the NSGA-II algorithm, the optimization solution is carried out, and the target optimization result is as follows: Table 4 Optimization result of the servo actuation subsystem The embodiment combines the system safety reliability testability calculation model, establishes the optimization objective function of the servo actuation subsystem, constructs the system weight, material consumption constraint and system safety reliability testability constraint, and the optimization objective includes the functional failure probability, the mean time between failures MTBF, and the fault detection rate. The constraint conditions include the system total weight, the material consumption constraint, the number constraint of the system component unit, the failure rate constraint, and the optimization objective constraint of the system safety reliability testability. The method of the embodiment faces the uncertainty factors affecting the system safety reliability testability in the system design process, combines the system safety reliability testability calculation model, constructs the uncertainty constraint parameters such as the system weight, the material consumption, the system redundancy, and the unit failure rate, determines the optimization algorithm, clearly defines the optimization solving process, obtains different design schemes and optimization results through the optimization solving, and supports the coordination and trade-off of different design characteristics of the system.

[0047] The above-described embodiments only describe the preferred embodiments of the present application, and do not limit the scope of the present application. Various modifications and improvements made by those skilled in the art to the technical solutions of the present application without departing from the design spirit of the present application shall fall within the protection scope of the present application defined by the claims.

Claims

1. A multi-objective reliability optimization method for a flight control servo actuation system based on UQ, characterized in that: It includes: S1. Construct system security optimization objectives, reliability optimization objectives, and testability optimization objectives respectively; S2. Based on the safety optimization objective, reliability optimization objective, and testability optimization objective, construct the optimization objective constraint function and determine the non-deterministic constraint variables. The optimization objective constraint function is as follows: ； ； ； ； in, The goal of security optimization is to optimize the set of functional failure states that need to be optimized. ,in Let I represent the total number of functional failure states that need optimization, and let I represent the set of security metrics that need optimization. Indicates impact The number of failed bottom-level units, This represents the corresponding failure probability. This indicates the number of redundant configurations for the corresponding underlying unit. For the purpose of test optimization, For unit The mass, M is the maximum system weight requirement. For unit Material consumption, This represents the maximum required material consumption for the system. and They are respectively the corresponding The minimum and maximum values, and For the corresponding number of bottom-level unit redundancy The minimum and maximum number of; In the actual solution process, based on the multi-objective optimization requirements, the weights of each optimization objective are determined, and the comprehensive optimization objective constraint function is constructed as follows: ； in, The coefficient corresponding to the security optimization objective is... , To optimize the target coefficient for reliability, Optimize the target coefficients for testing purposes; S3. Solve the comprehensive optimization objective constraint function in step S2 to obtain the optimization constraint objective result.

2. The reliability multi-objective optimization method for a flight control servo actuation system based on UQ according to claim 1, characterized in that: The security optimization objective in step S1 is: ； ； In the formula, Indicates impact The number of failed bottom-level units, Represents the corresponding failure probability, where S represents the failure rate of the i-th failure mode of unit l, and S represents the number of failure modes of a single bottom unit.

3. The reliability multi-objective optimization method for a flight control servo actuation system based on UQ according to claim 1, characterized in that: The reliability optimization objective in step S2 is: ； In the formula, This indicates the number of redundant configurations for the corresponding underlying unit.

4. The reliability multi-objective optimization method for a flight control servo actuation system based on UQ according to claim 1, characterized in that: The objective of the test optimization in step S2 is: ； In the formula, FDR is defined as the system fault detection rate, which is calculated using the D matrix or a fault propagation model. ； In the formula, This represents the total failure rate of the detected failure modes. This represents the total failure rate across all failure modes. Indicates the first The failure rate of each detected failure mode. Indicates the first Failure rate of each failure mode.

5. The reliability multi-objective optimization method for a flight control servo actuation system based on UQ according to claim 1, characterized in that: The nondeterministic constraint variables of the objective constraint function include total system weight constraint, system material consumption constraint, number of system components constraint, failure rate constraint, system safety optimization objective, system reliability optimization objective, and system testability optimization objective.

6. The reliability multi-objective optimization method for a flight control servo actuation system based on UQ according to claim 5, characterized in that: The total system weight constraint is: ； In the formula, For unit The mass is M, where M is the maximum required weight of the system.

7. The reliability multi-objective optimization method for a flight control servo actuation system based on UQ according to claim 5, characterized in that: The system material consumption constraint is: ； In the formula, For unit Material consumption, This represents the maximum required material consumption for the system.

8. The reliability multi-objective optimization method for a flight control servo actuation system based on UQ according to claim 1, characterized in that: In S3, the NSGA-II algorithm is used to perform multi-objective optimization to solve the objective constraint function and obtain the optimization constraint objective result.

9. An optimization system for the reliability multi-objective optimization method of the UQ-based flight control servo actuation system as described in claim 1, characterized in that: It includes an optimization objective construction module, an objective constraint function construction module, and an objective constraint function solving module. The optimization target construction module is used to construct system security optimization targets, reliability optimization targets, and testability optimization targets respectively. The objective constraint function construction module constructs objective constraint functions and determines optimization objectives based on security optimization objectives, reliability optimization objectives, and testability optimization objectives. The objective constraint function solving module is used to solve the objective constraint function and obtain the optimization constraint objective result.

10. The optimization system of the multi-objective reliability optimization method for the flight control servo actuation system according to claim 9, characterized in that: Reliability multi-objective optimization systems can be stored in computer devices.

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