An analysis method for fusion importance of influencing factors of aircraft dispatchability

Abstract

The application belongs to the technical field of aviation support, and particularly relates to a fusion importance analysis method based on influencing factors of aircraft sortie generation capability. The method comprises the following steps: S1, identifying usage availability influencing factors according to the usage scene, task demand, environmental condition and usage availability calculation formula of the aircraft; S2, carrying out simulation analysis modeling of the usage availability; S3, adjusting the value of each usage availability influencing factor by using the control variable method, and obtaining simulation analysis results of the usage availability under different values of the usage availability influencing factors; S4, calculating the fusion importance of each usage availability influencing factor; and S5, optimizing and adjusting the value of the usage availability influencing factor according to the fusion importance, and verifying the rationality and effectiveness of the optimization and adjustment through simulation analysis. The application can promote the improvement of the usage availability and effectively improve the aircraft sortie generation capability.

Description

Technical Field

[0001] This application belongs to the field of aviation support technology, and specifically relates to a fusion importance analysis method based on factors affecting aircraft sortie capability. Background Technology

[0002] Aircraft sortie capability is a crucial indicator of mission effectiveness, and operational availability is a core parameter characterizing this capability. Operational availability reflects the probability that an aircraft can perform its mission normally within a specific timeframe. Given the limited space and resources of maritime platforms, improving aircraft availability is vital for enhancing mission effectiveness when the number of aircraft is limited. During the aircraft design and development phase, rationally designing the aircraft to achieve high operational availability can effectively ensure mission effectiveness and mission completion rates.

[0003] Currently in China's aircraft industry, during the aircraft design and development phase, operational availability is typically assessed through simulation, taking into account mission requirements, general mass characteristic design data, and support plans. Based on the simulation results, design parameters such as aircraft performance and general mass characteristics are then optimized and adjusted. However, the lack of quantitative analysis of the importance of factors influencing aircraft operational availability in multi-mission scenarios means that adjustments and optimizations of aircraft design parameters lack scientific quantitative basis and are largely based on subjective experience, failing to provide positive guidance for design. Therefore, quantitatively calculating the importance of factors influencing aircraft operational availability in multi-mission scenarios can help identify key aspects for improving operational availability, formulate more scientific resource allocation strategies and maintenance plans, and provide theoretical support for optimizing aircraft design.

[0004] Therefore, there is an urgent need for a technical solution to overcome or mitigate at least one of the aforementioned defects in the existing technology. Summary of the Invention

[0005] The purpose of this application is to provide a fusion importance analysis method based on factors affecting aircraft sortie capability, in order to solve at least one problem existing in the prior art.

[0006] The technical solution of this application is:

[0007] A fusion importance analysis method based on factors influencing aircraft sortie capability includes:

[0008] Step S1: Identify the factors affecting availability based on the aircraft's usage scenarios, mission requirements, environmental conditions, and availability calculation formula.

[0009] Step S2: Conduct usability simulation analysis and modeling;

[0010] Step S3: Use the control variable method to adjust the values ​​of each usability influencing factor and obtain the usability simulation analysis results under different values ​​of usability influencing factors;

[0011] Step S4: Calculate the combined importance of each factor affecting usability;

[0012] Step S5: Optimize and adjust the values ​​of the factors affecting usability based on the importance of fusion, and verify the rationality and effectiveness of the optimization and adjustment through simulation analysis.

[0013] In at least one embodiment of this application, in step S1, the availability calculation formula is as follows:

[0014] ;

[0015] Among them, A o To utilize availability, T BF T is the mean time between failures. CT T represents the average repair time. MLD To average out the time of resource delays.

[0016] In at least one embodiment of this application, availability influencing factors include mean time between failures, mean time to repair, pre-maintenance preparation time, direct maintenance preparation time, scheduled maintenance time, and task duration.

[0017] In at least one embodiment of this application, step S4, calculating the fusion importance of each usability influencing factor, includes:

[0018] The value range of the fusion importance is defined as [0,1];

[0019] Define evaluation metrics for the importance of integration, including relevance metrics, monotonicity metrics, and trend metrics;

[0020] Based on correlation indicators, monotonicity indicators, and trend indicators, calculate the combined importance of each factor affecting usability;

[0021] The factors influencing usability are ranked according to their importance in integration.

[0022] In at least one embodiment of this application, the correlation index is:

[0023] ;

[0024] in, Let be the correlation index for the i-th factor affecting usability. For the i-th usability influencing factor, the j-th value is... n The number of possible values. This represents the average of the array of different values ​​for the i-th availability influencing factor. To use the j-th calculation result of availability, This is the average of the array of results calculated using different availability levels.

[0025] In at least one embodiment of this application, the monotonicity index is:

[0026] ;

[0027] ;

[0028] in, Let i be the monotonicity index of the i-th factor affecting usability. For the i-th usability influencing factor, the (j+1)-th value is... It is a unit step function.

[0029] In at least one embodiment of this application, the trend indicator is:

[0030] ;

[0031] in, For the i-th factor influencing availability, This is an array of different values ​​for the i-th available availability influencing factor. This is an array of different calculation results using availability, where ρ is the resolution coefficient.

[0032] In at least one embodiment of this application, the fusion importance is:

[0033] ;

[0034] Among them, Z i The fusion importance of the i-th usability influencing factor. Attribute weights for integrating importance assessment metrics;

[0035] The attribute weights of different evaluation indicators are determined using a weighting formula:

[0036] ;

[0037] Where q is the number of evaluation indicators and h is the rank level.

[0038] The invention has at least the following beneficial technical effects:

[0039] The fusion importance analysis method based on factors affecting aircraft sortie capability proposed in this application can identify the design parameters of important factors affecting operational availability, providing a theoretical basis for design optimization, resource allocation, and other work, thereby promoting the improvement of operational availability and effectively enhancing aircraft sortie capability. Attached Figure Description

[0040] Figure 1 This is a flowchart of a method for fusion importance analysis based on factors affecting aircraft sortie capability, according to one embodiment of this application.

[0041] Figure 2 This is a schematic diagram showing the detailed steps of a fusion importance analysis method based on factors affecting aircraft sortie capability according to one embodiment of this application;

[0042] Figure 3 This is a schematic diagram of the main components of a certain type of aircraft according to one embodiment of this application;

[0043] Figure 4 This is a typical cross-sectional schematic diagram of a single mission of a certain type of aircraft according to one embodiment of this application.

[0044] Figure 5 This is a cross-sectional schematic diagram of a certain type of aircraft performing continuous missions according to one embodiment of this application. Detailed Implementation

[0045] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions in the embodiments of this application will be described in more detail below with reference to the accompanying drawings. In the drawings, the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The described embodiments are some, but not all, embodiments of this application. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain this application, and should not be construed as limiting this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application. The embodiments of this application will be described in detail below with reference to the accompanying drawings.

[0046] The following is in conjunction with the appendix Figures 1 to 5 This application will be described in further detail.

[0047] This application provides a fusion importance analysis method based on factors influencing aircraft sortie capability, such as... Figure 1 As shown, it includes the following steps:

[0048] Step S1: Identify the factors affecting availability based on the aircraft's usage scenarios, mission requirements, environmental conditions, and availability calculation formula.

[0049] Step S2: Conduct usability simulation analysis and modeling;

[0050] Step S3: Use the control variable method to adjust the values ​​of each usability influencing factor and obtain the usability simulation analysis results under different values ​​of usability influencing factors;

[0051] Step S4: Calculate the combined importance of each factor affecting usability;

[0052] Step S5: Optimize and adjust the values ​​of the factors affecting usability based on the importance of fusion, and verify the rationality and effectiveness of the optimization and adjustment through simulation analysis.

[0053] Specifically, such as Figure 2 As shown, in step S1, the factors influencing aircraft availability are identified from two dimensions. Firstly, a comprehensive analysis is conducted based on the aircraft's usage scenarios, mission requirements, and environmental conditions to identify factors that may affect its availability. Secondly, based on the availability calculation formula, influencing factors related to availability are extracted. Combining data from similar aircraft designs and operations, factors with a high impact on availability are preliminarily selected, their initial design values ​​and ranges are determined, the boundaries of the problem are clarified, and a foundation is laid for subsequent importance analysis.

[0054] In this embodiment, aircraft availability is a parameter related to aircraft operating time, and its measurement method is as follows:

[0055] ;

[0056] Among them, A o To utilize availability, T BF T is the mean time between failures. CT T represents the average repair time. MLD To average out the time of resource delays.

[0057] In this embodiment, the availability influencing factors mainly include mean time between failures (MTBF), mean time to repair (MTTR), pre-maintenance preparation time, direct maintenance preparation time, scheduled maintenance time, and task duration.

[0058] Then, in step S2, usability simulation analysis and modeling are carried out. Aircraft usability simulation modeling is conducted based on simulation software (such as Simulox and other simulation software). An aircraft usability simulation model is constructed, simulating aircraft missions, failures, maintenance, and other events based on aircraft mission characteristics. Using design results from the preliminary aircraft design phase, including reliability and maintainability design data, performance simulations are performed on typical aircraft missions, and the aircraft usability calculation results are statistically output.

[0059] Further, in step S3, an analysis of the factors influencing aircraft availability is performed. Using the controlled variable method, the impact of different values ​​on aircraft availability is calculated by successively changing the value of each factor. Specifically, for each identified factor, multiple different values ​​are set, and the aircraft availability result is calculated after adjusting these values ​​in simulation software. Based on this single-factor variation simulation method, the logical relationship between each factor and aircraft availability is clarified, providing data support for subsequent importance calculation.

[0060] Step S3 primarily involves simulating and calculating the usability results under different values ​​of various usability influencing factors. The purpose of these calculations is to preliminarily clarify the correlation between each influencing factor and usability, providing an analytical basis for step S4. After completing step S3, step S4 is carried out, analyzing and ranking the importance of the influencing factors using a fusion importance analysis method. The aim is to determine which influencing factors are more important and which are less important, providing a basis for optimization in the subsequent step S5. The fusion importance analysis method in step S4 avoids bias caused by calculating a single indicator; therefore, it integrates three evaluation indicators to jointly calculate importance.

[0061] Specifically, in step S4, the fusion importance of availability influencing factors is calculated, including:

[0062] The value range of the fusion importance is defined as [0,1];

[0063] Define evaluation metrics for the importance of integration, including relevance metrics, monotonicity metrics, and trend metrics;

[0064] Based on correlation indicators, monotonicity indicators, and trend indicators, calculate the combined importance of each factor affecting usability;

[0065] The factors influencing usability are ranked according to their importance in integration.

[0066] This paper defines the importance of fusion for factors influencing usability and proposes an importance analysis method based on the fusion of three evaluation indicators: relevance, monotonicity, and trend. The quantitative results of the relevance, monotonicity, and trend importance of each factor influencing usability are calculated separately. Based on the importance fusion formula, the importance analysis results of each factor influencing usability after fusion are calculated and normalized to obtain the final fused importance calculation result. Based on the fused importance calculation results, the importance of factors influencing usability is ranked.

[0067] In this embodiment, the importance of each factor affecting availability is defined as the magnitude of its impact on aircraft availability, with a value range of [0,1].

[0068] From a data analysis perspective, three evaluation indicators—correlation, monotonicity, and trend—are used to comprehensively assess the importance of each factor from the perspectives of correlation, monotonicity, and trend between various factors affecting availability and aircraft availability, effectively avoiding calculation bias caused by a single evaluation indicator.

[0069] The correlation index reflects the degree of correlation between various factors affecting aircraft availability and aircraft availability. The closer the correlation index is to 1, the higher the correlation and importance of that factor with aircraft availability. Conversely, the closer the correlation index is to 0, the lower the correlation and importance of that factor with aircraft availability. The correlation index is calculated as follows:

[0070] ;

[0071] in, Let be the correlation index for the i-th factor affecting usability. For the i-th usability influencing factor, the j-th value is... n The number of possible values. This represents the average of the array of different values ​​for the i-th availability influencing factor. To use the j-th calculation result of availability, This is the average of the array of results calculated using different availability levels.

[0072] The monotonicity index reflects the monotonicity of the change between various factors affecting availability and availability, and its value ranges from [0,1]. When the availability changes monotonically along with the influencing factor, the factor is considered to have a high degree of influence; when the aircraft availability changes randomly and does not exhibit a monotonic trend along with the influencing factor, the factor is considered to have a low degree of influence, and the monotonicity index is correspondingly 0. The calculation method for the monotonicity index is as follows:

[0073] ;

[0074] ;

[0075] in, Let i be the monotonicity index of the i-th factor affecting usability. For the i-th usability influencing factor, the (j+1)-th value is... It is a unit step function.

[0076] The higher the monotonicity index, the more important the influencing factor is considered, and vice versa.

[0077] Trend indicators reflect the consistency of the changing trends between various factors influencing usability and usability itself. The closer a trend indicator is to 1, the higher the consistency and importance of the trend between that factor and usability. Conversely, the closer a trend indicator is to 0, the lower the consistency and importance of the trend between that factor and usability. The trend indicator is calculated as follows:

[0078] ;

[0079] in, For the i-th factor influencing availability, This is an array of different values ​​for the i-th available availability influencing factor. This is an array of different calculation results using availability, where ρ is the resolution coefficient.

[0080] By integrating the above three evaluation indicators, the relationship between various factors influencing usability and usability is comprehensively reflected from three dimensions: relevance, monotonicity, and trend. This allows for a more reasonable and effective assessment of their importance. The method for calculating the integrated importance is as follows:

[0081] ;

[0082] Among them, Z i The fusion importance of the i-th usability influencing factor. Attribute weights for integrating importance assessment metrics;

[0083] Different evaluation indicators have different attribute weights due to their inherent characteristics. The attribute weights of different evaluation indicators are determined by a weighting formula:

[0084] ;

[0085] Where q is the number of evaluation indicators and h is the ranking level (i.e., the ranking of the importance of the evaluation indicators).

[0086] Finally, in step S5, optimization and verification are implemented. Based on the fusion importance of each factor affecting aircraft availability calculated in step S4, the parameters of these factors are optimized and adjusted. The fusion importance is used as the adjustment weight for each parameter. Parameters with high fusion importance are given priority and a larger adjustment weight, while parameters with low fusion importance have a more relaxed requirement and a smaller adjustment weight. The availability simulation analysis model from step S2 is repeated to simulate and analyze the aircraft availability after parameter adjustments, and the results are compared to verify the rationality and effectiveness of the optimization.

[0087] In one embodiment of this application, taking a certain type of aircraft as an example, the application of this application is described in detail. Basic information about the aircraft type is obtained, including basic aircraft details (such as...). Figure 3 (As shown), usage plan, and support plan. Aircraft mission profile as follows: Figure 4 , 5 As shown, the aircraft employs a two-level maintenance system. The following section presents a comprehensive importance analysis of the factors influencing the aircraft's sortie rate.

[0088] First, through preliminary analysis, the factors influencing availability were identified as follows: mean time between failures (MTBF), mean time to repair (MTBT), pre-maintenance preparation time, direct maintenance preparation time, scheduled maintenance time, and task duration. The initial values ​​and ranges for each factor influencing availability were then determined.

[0089] Secondly, based on Simlox simulation software, we conducted simulation modeling of aircraft availability. The availability simulation analysis model was used to perform performance simulation on typical aircraft tasks, and the aircraft availability calculation results were statistically output.

[0090] Then, the availability of the aircraft was simulated and calculated under different values ​​of each factor affecting availability, so as to clarify the logical relationship between each factor affecting availability and availability.

[0091] Furthermore, based on the fusion importance analysis method, the quantitative results of the importance of each factor affecting usability are calculated as shown in Table 1.

[0092] Table 1

[0093]

[0094] Based on the table above, the importance of the factors affecting availability under this deployment capability requirement is ranked as follows: Mean Time Between Failures (MTBF) > Mission Duration > Pre-deployment Preparation Time > Direct Deployment Preparation Time > Mean Time To Repair (MTBF) > Scheduled Maintenance Time.

[0095] Finally, using the importance of fusion as the adjustment ratio weight for each parameter, the mean time between failures (MTBF) parameter requirements and mission duration were appropriately adjusted. This was supplemented by optimization adjustments to the pre-maintenance preparation time, direct maintenance preparation time, and mean time of maintenance. The optimized availability was verified again through simulation analysis. Compared to the initial situation, the optimized availability reached over 0.85, showing a significant improvement.

[0096] This application's fusion importance analysis method based on factors influencing aircraft sortie capacity enables quantitative calculation of the importance of these factors, helping to identify key aspects for improving sortie capacity. This provides a quantitative basis for optimizing aircraft design parameters to meet high sortie capacity requirements, positively influencing aircraft maintainability, reliability, and supportability designs, and clarifying more scientific resource allocation strategies, maintenance plans, and aircraft parameter design to improve sortie capacity. By employing a fusion importance analysis method combining correlation, monotonicity, and trend, the limitations of single methods are avoided. This allows for a more comprehensive and accurate analysis of the importance of sortie capacity influencing factors from three dimensions, resulting in more reasonable analysis results and providing positive guidance for aircraft design.

[0097] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for fusion importance analysis based on factors influencing aircraft sortie capability, characterized in that, include: Step S1: Identify the factors affecting availability based on the aircraft's usage scenarios, mission requirements, environmental conditions, and availability calculation formula. Step S2: Conduct usability simulation analysis and modeling; Step S3: Use the control variable method to adjust the values ​​of each usability influencing factor and obtain the usability simulation analysis results under different values ​​of usability influencing factors; Step S4: Calculate the combined importance of each factor affecting usability; Step S5: Optimize and adjust the values ​​of the factors affecting usability based on the importance of fusion, and verify the rationality and effectiveness of the optimization and adjustment through simulation analysis.

2. The method for fusion importance analysis based on factors influencing aircraft sortie capability according to claim 1, characterized in that, In step S1, the availability calculation formula is as follows: ； Among them, A o To utilize availability, T BF T is the mean time between failures. CT T represents the average repair time. MLD To average out the delay time for ensuring resources.

3. The method for fusion importance analysis based on factors influencing aircraft sortie capability according to claim 2, characterized in that, Factors affecting availability include mean time between failures (MTBF), mean time to repair (MTBF), pre-maintenance preparation time, direct maintenance preparation time, scheduled maintenance time, and mission duration.

4. The method for fusion importance analysis based on factors influencing aircraft sortie capability according to claim 3, characterized in that, In step S4, the combined importance of each usability influencing factor is calculated, including: The value range of the fusion importance is defined as [0,1]; Define evaluation metrics for the importance of integration, including relevance metrics, monotonicity metrics, and trend metrics; Based on correlation indicators, monotonicity indicators, and trend indicators, calculate the combined importance of each factor affecting usability; The factors influencing usability are ranked according to their importance in integration.

5. The method for fusion importance analysis based on factors influencing aircraft sortie capability according to claim 4, characterized in that, The correlation index is: ； in, Let be the correlation index for the i-th factor affecting usability. For the i-th usability influencing factor, the j-th value is... n The number of possible values. This represents the average of the array of different values ​​for the i-th availability influencing factor. To use the j-th calculation result of availability, This is the average of the array of results calculated using different availability levels.

6. The method for fusion importance analysis based on factors influencing aircraft sortie capability according to claim 5, characterized in that, The monotonicity index is: ； ； in, Let i be the monotonicity index of the i-th factor affecting usability. For the i-th usability influencing factor, the (j+1)-th value is... It is a unit step function.

7. The method for fusion importance analysis based on factors influencing aircraft sortie capability according to claim 6, characterized in that, Trend indicators are: ； in, For the i-th factor influencing availability, This is an array of different values ​​for the i-th available availability influencing factor. This is an array of different calculation results using availability, where ρ is the resolution coefficient.

8. The method for fusion importance analysis based on factors influencing aircraft sortie capability according to claim 7, characterized in that, The importance of fusion is: ； Among them, Z i The fusion importance of the i-th usability influencing factor. Attribute weights for integrating importance assessment metrics; The attribute weights of different evaluation indicators are determined using a weighting formula: ； Where q is the number of evaluation indicators and h is the rank level.

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