Aviation equipment supportability reference comparison system construction method and system based on similarity analysis

Abstract

The invention belongs to the technical field of aviation equipment supportability design analysis, and particularly relates to an aviation equipment supportability reference comparison system construction method and system based on similarity analysis, and the method comprises the steps: S1, determining the construction demands of an aviation equipment supportability reference comparison system according to an application scene of a to-be-analyzed aviation equipment supportability system; s2, analyzing the to-be-analyzed aviation equipment supportability system based on a similarity analysis method to obtain the similarity and weight of the characteristic parameters, and establishing an aviation equipment supportability reference comparison system; and S3, carrying out validity verification analysis on the aviation equipment supportability reference comparison system, and constructing a data model of the aviation equipment supportability reference comparison system. According to the method, a reasonable reference comparison system can be determined for different levels of aviation equipment supportability systems such as an equipment level, a system level, an equipment level and a guarantee system; perfect reference basis and data support are provided for new research equipment guarantee design, aviation equipment guarantee analysis and verification are efficiently supported, and the task execution capacity is improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of aviation equipment supportability design and analysis, and in particular relates to a method and system for constructing an aviation equipment supportability benchmark comparison system based on similarity analysis. Background Art

[0002] In the flight missions of modern aviation equipment, agile, efficient and accurate support has become the key factor to determine the success of the mission. With the continuous improvement of the requirements for aviation equipment, aviation equipment has become more and more complex, and its performance has become more and more dependent on aviation equipment support. As a combination of a series of analysis methods to study the impact of support issues on aviation equipment design and determine support resources, supportability analysis plays a role of connecting the past and the future in the development of aviation equipment, and is a bridge between aviation equipment design and support system development. However, for a long time, aviation equipment supportability analysis has generally had a series of problems such as unreasonable analysis results and disconnection from actual support needs, resulting in poor matching between the support system and the main aviation equipment when new aviation equipment is delivered, insufficient compatibility with the support system, and slow generation of support capabilities, making it difficult to meet the growing mission needs. Through analysis, it is found that the main reasons for the above problems are as follows: First, there is a lack of supportability integrated analysis methods that connect mission support needs, aviation equipment supportability design, and support system development, resulting in the generated support plan being out of touch with actual support needs. Second, supportability analysis does not make sufficient use of objective and historical data, the degree of knowledge of data is not high, the value of data assets is not fully utilized, and knowledge cannot be pushed in the process of supportability analysis, which affects the effect and efficiency of supportability analysis. Third, the requirements for building a benchmark comparison system were not fully implemented in the support analysis, and the benchmark comparison system was not fully utilized to integrate support data to improve the effectiveness of support analysis. Fourth, the verification of the support analysis results lacked data and methodological support, and the support verification was insufficient and untimely, making it impossible to discover and solve support problems early.

[0003] As the combination of existing aviation equipment that is closest to the design, use and support characteristics of newly developed aviation equipment, the aviation equipment supportability benchmark comparison system is the most important design reference for newly developed aviation equipment in the early stages of demonstration and development. However, due to the lack of attention to the accumulation of supportability data in the past development and use of aviation equipment, the existing aviation equipment supportability benchmark comparison system is not sound and complete, and cannot provide sufficient reference and data support for the supportability design analysis of newly developed aviation equipment. In addition, the supportability benchmark comparison system and the supportability analysis work are not highly integrated, making it impossible to fully carry out supportability analysis and verification work based on the supportability benchmark comparison system in the early stages of demonstration and development of newly developed aviation equipment, and it is impossible to discover and solve problems in the early stages of development.

[0004] In order to address the deficiencies of the above-mentioned existing technologies, it is urgent to conduct research on the methods of determining the aviation equipment supportability benchmark comparison system and building the data model. According to the principle of integrating supportability analysis work and integrating similar products and usage data, a supportability benchmark comparison system and its data model should be constructed to drive supportability analysis, drive early assessment of support capabilities and rapidly form a support system. Summary of the invention

[0005] In view of the shortcomings of the prior art, the present invention provides a method and system for constructing an aviation equipment supportability benchmark comparison system based on similarity analysis, which can determine a reasonable benchmark comparison system for aviation equipment supportability systems at different levels, such as equipment level, system level, equipment level, and support system; provide a complete reference benchmark and data support for the support design of newly developed equipment, efficiently support aviation equipment supportability analysis and verification, and improve the mission execution capability of the support system.

[0006] To achieve the above object, the present invention discloses the following technical solution:

[0007] A method for constructing an aviation equipment supportability benchmark comparison system based on similarity analysis, comprising:

[0008] S1: Determine the requirements for building an aviation equipment supportability benchmark comparison system based on the application scenarios of the aviation equipment supportability system to be analyzed;

[0009] Analyze the application scenarios of the aviation equipment supportability system to be analyzed for the full life cycle supportability business of the aviation equipment supportability system to be analyzed, and determine the requirements for building the aviation equipment supportability benchmark comparison system;

[0010] S2: Analyze the aviation equipment supportability system to be analyzed based on the similarity analysis method, obtain the similarity and weight of the characteristic parameters, and establish an aviation equipment supportability benchmark comparison system, which specifically includes the following sub-steps:

[0011] S21: According to the requirements for building the aviation equipment supportability benchmark comparison system in step S1, the characteristic parameters of the aviation equipment supportability benchmark comparison system to be analyzed are determined by using the hierarchical analysis method, which are used to analyze the similarity between the systems; the characteristic parameters include: text type data characteristic parameters and numerical type data characteristic parameters;

[0012] S22: Calculate the similarity r of the characteristic parameters of the numerical data in step S21 using the similarity element method ih ;

[0013] S23: Calculate the similarity Sim(A, B) of the feature parameters of the text type data in step S21;

[0014] S24: Establish a hierarchical structure model of the aviation equipment supportability benchmark comparison system, construct a judgment matrix of characteristic parameters, use the proportional scaling method to measure the characteristic parameters, and calculate the characteristic parameter weights of the aviation equipment supportability benchmark comparison system as follows:

[0015]

[0016] Among them, U is the characteristic parameter weight of the aviation equipment supportability benchmark comparison system; U i is the weight of the i-th characteristic parameter of the aviation equipment supportability benchmark comparison system at this level; U h is the weight of the hth characteristic parameter of the previous level of the aviation equipment supportability benchmark comparison system; W hi is the weight of the i-th characteristic parameter of the current level of the aviation equipment supportability benchmark comparison system relative to the h-th characteristic parameter of the previous level; h is the characteristic parameter number of the previous level of the aviation equipment supportability benchmark comparison system, h = 1, 2, ..., m; i is the characteristic parameter number of the current level of the aviation equipment supportability benchmark comparison system, i = 1, 2, ..., h; m is the dimension of the judgment matrix of the previous level;

[0017] S25: Determine the similarity of the aviation equipment supportability benchmark comparison system. By performing weighted calculation on the similarity and weight of each characteristic parameter, determine the aviation equipment supportability benchmark comparison system with the highest similarity to the aviation equipment to be analyzed. The similarity analysis result is:

[0018]

[0019] Among them, Q(A,B) is the similarity between the aviation equipment system to be analyzed and the aviation equipment supportability benchmark comparison system; r j is the similarity of the jth feature parameter; a j is the weight of the jth characteristic parameter; k is the number of characteristic parameters of the aviation equipment supportability system to be analyzed; A is the aviation equipment supportability system to be analyzed; B is the aviation equipment supportability benchmark comparison system; l is the number of characteristic parameters of the aviation equipment supportability benchmark comparison system; n is the dimension of the judgment matrix at this level;

[0020] S26: Establish an aviation equipment supportability benchmark comparison system by comparing the characteristic parameters of the aviation equipment supportability system to be analyzed with the aviation equipment supportability system in the existing database;

[0021] S3: Conduct validity verification analysis based on support simulation on the aviation equipment supportability benchmark comparison system in step S2; and construct a data model of the aviation equipment supportability benchmark comparison system in accordance with the modeling methods of supportability business, conceptual data modeling, logical data modeling, and physical data modeling, and save and apply the aviation equipment supportability benchmark comparison system.

[0022] Preferably, in step S22, the similarity of the characteristic parameters of the numerical data in step S21 is calculated using a similar element method, specifically:

[0023] S221: Determine similar elements of aviation equipment supportability system; use similarity theory to establish a unified and quantitative similarity comparison standard between the aviation equipment supportability system A to be analyzed and the aviation equipment supportability benchmark comparison system B; then the similar element u(a i ,b i ) is the first characteristic parameter a in the aviation equipment support system A to be analyzed i Compare the second characteristic parameter b in the aviation equipment supportability benchmark system B i similar elements of

[0024] S222: Quantify similarity element of aviation equipment support system; the similarity element u(a i ,b i ) are s1,s2,…s m ,S=[s1,s2,…s m ]; then record u h (a i ) is the first characteristic parameter a i Relative to the characteristic element s h The eigenvalue of h (b i ) is the second characteristic parameter b i Relative to element s h The first characteristic parameter a i , the second characteristic parameter b i Relative to the characteristic element s h The feature similarity is:

[0025]

[0026] Among them, r ih is the first characteristic parameter a i With the second characteristic parameter b i The feature similarity of ; min is the minimum function; max is the maximum function; u h (a i ) is the first characteristic parameter a i Relative to the characteristic element s h The characteristic value of u h (b i ) is the characteristic parameter b i Relative to the characteristic element s h The characteristic value of a i is the first characteristic parameter; b i is the second characteristic parameter.

[0027] Preferably, in step S23, the similarity of the feature parameters of the text type data in step S21 is calculated as follows:

[0028] S231: For the first character string s of the text type data characteristic parameter in the aviation equipment support system A and the second string s B , calculate the matching window MW as:

[0029]

[0030] Among them, MW is the matching window of the characteristic parameters of text type data; For the first string The length of |s B | is the second string s B Length;

[0031] S232: Use the matching window MW of the text type data feature parameter to filter out the same characters that are relatively far away, and obtain a new character string sn after filtering. A and sn B , because the number of matching characters is the same, the string length m is:

[0032] m=|sn A |=|sn B |

[0033] Where m is the length of the string; sn is A For the first string s A The string obtained after filtering; sn B For the first string s B The string obtained after filtering;

[0034] By exchanging characters, sn A Transformed into sn B , and the number of exchanges is recorded as t s , then the number of string transpositions t is half of the number of transpositions that occur, which is t = t s / 2; for the first string s A and the second string s B Perform character deletion without changing the character order, and set the resulting character sequence of the same length as the first string s A and the second string s B The length of the character sequence LCS(s A ,s B ), the first string s A and the second string s B The common subsequence similarity coefficient of the string is:

[0035]

[0036] Among them, P LCS is the common subsequence similarity coefficient of the string; L LCS is the length of the character sequence;

[0037] Then the first string s A and the second string s B The similarity formula is:

[0038]

[0039] Among them, Sim(A,B) is the first string s A and the second string s B similarity; t is the number of string transpositions.

[0040] Preferably, in step S24, a judgment matrix of characteristic parameters is constructed, the characteristic parameters are measured using a proportional scaling method, and the characteristic parameter weight U of the aviation equipment supportability benchmark comparison system is calculated, specifically:

[0041] S241: Constructing the judgment matrix A of feature parameters p ; There is K m criteria that need to be judged, then the kth criterion uses the judgment criterion B k (k=1,2,...,K m ) indicates that there exists K for each criterion n There are specific indicators that need to be analyzed, then the lth indicator uses the characteristic parameter C l (l=1,2,...,K n )express;

[0042] Established to judge the criteria B k Characteristic parameters C1, C2, ...C of the judgment criteria l Comparison judgment matrix A p , in the judgment criterion B k Then, they are sorted by relative importance, that is, the characteristic parameters C1, C2, ...C l The weight of p is a positive reciprocal matrix, then it satisfies the relationship:

[0043]

[0044] Among them, C rl is the characteristic parameter C r With C l Criteria B k The weight ratio of lr is the characteristic parameter C l With C rCriteria B k The weight ratio of ; k is the judgment criterion number; l is the feature parameter number; r is the feature parameter auxiliary number;

[0045] S242: Introduce the 1-9 ratio scaling method, in the judgment matrix A p The importance of dividing the feature parameters in

[0046] S243: Calculation of feature parameter weights; judgment matrix A p In , find the product of the elements in each row:

[0047] M l =ΠC rl (rl=1,2,…,K n )

[0048] Among them, M l Determine the product of the elements in row l;

[0049] S244: Calculate the judgment matrix A p , normalize the eigenvector, and obtain the components; find the judgment matrix A p The components of the eigenvector of are:

[0050]

[0051] Among them, W i is the i-th judgment matrix A p The components of the eigenvector of ;

[0052] S245: Standardize the feature vector to calculate the relative weight value W hi , to calculate the characteristic parameter weight U of the aviation equipment supportability benchmark comparison system; the relative weight value W hi for:

[0053]

[0054] Among them, W hi It is the weight of the i-th characteristic parameter at this level of the aviation equipment supportability benchmark comparison system relative to the characteristic parameters at the upper level.

[0055] Preferably, the analysis of the application scenarios of the aviation equipment support system to be analyzed in step S1 is divided into four application scenarios: the demonstration and project establishment stage, the engineering development stage, the installation and finalization stage, and the batch production and support stage;

[0056] The establishment of the aviation equipment supportability benchmark comparison system is based on the existing aviation equipment supportability system that is closest to the design, use and support characteristics of the aviation equipment supportability system to be analyzed. It can be composed of a combination of aviation equipment support systems and their subsystems in the existing database, and the aviation equipment supportability benchmark comparison system is saved and applied according to the data structure paradigm.

[0057] Preferably, in step S21, the characteristic parameters of the aviation equipment supportability benchmark comparison system to be analyzed are determined by using the hierarchical analysis method, specifically including: characteristic parameters of the equipment-level supportability benchmark comparison system of aviation equipment, characteristic parameters of the system-level supportability benchmark comparison system of aviation equipment, characteristic parameters of the equipment-level supportability benchmark comparison system of aviation equipment, and characteristic parameters of the support system supportability benchmark comparison system of aviation equipment;

[0058] The equipment-level supportability benchmark comparison system characteristic parameters of the aviation equipment specifically include: equipment function characteristic parameters, equipment performance characteristic parameters, equipment size and volume characteristic parameters, equipment weight characteristic parameters, equipment energy consumption characteristic parameters, equipment material characteristic parameters, equipment reliability characteristic parameters, equipment maintainability characteristic parameters, equipment supportability characteristic parameters, equipment testability characteristic parameters, equipment safety characteristic parameters, and equipment environmental adaptability characteristic parameters;

[0059] The system-level supportability benchmark comparison system characteristic parameters of the aviation equipment specifically include: system function characteristic parameters, system architecture characteristic parameters, system reliability characteristic parameters, system maintainability characteristic parameters, system testability characteristic parameters and system safety characteristic parameters;

[0060] The equipment-level supportability benchmark comparison system characteristic parameters of the aviation equipment specifically include: equipment function characteristic parameters, equipment size characteristic parameters, equipment weight characteristic parameters, equipment material characteristic parameters, equipment interface characteristic parameters, equipment power characteristic parameters, equipment rated working voltage characteristic parameters, equipment load current characteristic parameters, and equipment life characteristic parameters;

[0061] The support system benchmark comparison system characteristic parameter analysis of the aviation equipment is as follows: the support system benchmark comparison system characteristic parameter analysis is carried out from two aspects of support plan and support resources; the aviation equipment support system benchmark comparison system characteristic parameters in the support plan are analyzed separately according to the use support plan and the maintenance support plan; the aviation equipment support system benchmark comparison system characteristic parameter analysis in the support resources is carried out according to the supply support characteristic parameters, support equipment characteristic parameters, technical data characteristic parameters, support facility characteristic parameters, packaging characteristic parameters, loading and unloading characteristic parameters, storage and transportation characteristic parameters and computer resource support characteristic parameters.

[0062] Preferably, in step S3, the aviation equipment supportability benchmark comparison system in step S2 is subjected to effectiveness verification analysis based on support simulation, specifically:

[0063] The aviation equipment supportability benchmark comparison system support simulation model is constructed, including the mission model, equipment model, support organization model, support resource model, support process model, as well as the evaluation model and optimization model construction; the aviation equipment supportability benchmark comparison system verification analysis based on support simulation, the mission success rate and usability are obtained through simulation, and the simulation indicators are compared with the design requirement indicators of the aviation equipment supportability system to be analyzed. If the design requirements are met, it means that the constructed aviation equipment supportability benchmark comparison system to be analyzed meets the requirements. If it does not meet the requirements, the benchmark comparison system is further iteratively optimized.

[0064] Preferably, in step S3, the aviation equipment supportability benchmark comparison system data model is constructed according to the modeling methods of supportability business, conceptual data modeling, logical data modeling, and physical data modeling, specifically:

[0065] S31: Business data demand analysis of the aviation equipment supportability benchmark comparison system. On the basis of determining the key supportability business of the aviation equipment supportability benchmark comparison system throughout its life cycle, sort out various supportability requirement processes and establish the corresponding relationship between the supportability requirement processes and data forms; then, further sort out detailed data elements for each data form;

[0066] S32: Construct the conceptual data model of the aviation equipment supportability benchmark comparison system, identify and extract the core data entities, core data structures and the relationship between data entities from the supportability business activities, and use ER diagram to construct the conceptual data model;

[0067] S33: Construct the logical data model of the aviation equipment supportability benchmark comparison system. On the basis of the conceptual data model, improve the entities, the relationships between entities and the structural feature information of the entities, and adopt the class diagram modeling method in the unified modeling language to construct the logical data model of the aviation equipment supportability benchmark comparison system.

[0068] S34: construct a physical data model of the aviation equipment supportability benchmark comparison system. Based on the logical data model, the database storage requirements are further considered, and the physical data model of the supportability benchmark comparison system is constructed in the form of a data table to realize the rapid construction of the database.

[0069] S35: Construction of data model for aviation equipment supportability benchmark comparison system based on EA; Use EA software to carry out data modeling to meet the needs of constructing conceptual data model, logical data model and physical data model of aviation equipment supportability benchmark comparison system.

[0070] The second aspect of the present invention proposes an aviation equipment supportability benchmark comparison system based on similarity analysis, which includes: an aviation equipment supportability benchmark comparison system data management module, an aviation equipment supportability system information entry module and an aviation equipment supportability benchmark comparison system determination module;

[0071] The aviation equipment supportability benchmark comparison system data management module can store and display the entered aviation equipment supportability system information, including the characteristic information of the aviation equipment supportability system itself and the use supportability information;

[0072] The aviation equipment supportability system information input module can input existing aviation equipment supportability system information, help users input aviation equipment supportability system information, and display it in the aviation equipment supportability benchmark comparison system data management module;

[0073] The aviation equipment supportability benchmark comparison system determination module can automatically match the aviation equipment supportability system that is closest to the aviation equipment supportability system to be analyzed from the database of the aviation equipment supportability benchmark comparison system data management module based on the basic information of the aviation equipment supportability system to be analyzed, and construct an aviation equipment supportability benchmark comparison system.

[0074] Compared with the prior art, the present invention has the following beneficial effects:

[0075] (1) The method adopted by the present invention can solve the problems that the aviation equipment supportability benchmark comparison system is not sound and complete and cannot provide sufficient reference and data support for the supportability design analysis of newly developed aviation equipment. The constructed aviation equipment supportability benchmark comparison system can fully realize the functions of the newly developed aviation equipment supportability system and meet the requirements of the test stage.

[0076] (2) The present invention takes the aviation equipment supportability benchmark comparison system data as its basis and core, and realizes seamless connection with the front-end and back-end work by efficiently supporting the development of aviation equipment supportability analysis and verification work, scientifically and rationally planning the support system and support plan, and improving the support system's support capabilities for the tasks of the newly developed aviation equipment supportability system.

[0077] (3) The present invention can be applied to all stages of the equipment life cycle, including equipment model supportability demonstration, engineering development, test and appraisal, use and service support. In the model demonstration stage, a benchmark comparison system is constructed based on the support status of similar equipment, systems and equipment to provide support for the determination of model supportability index requirements. In the engineering development stage, the use support data of similar equipment is integrated to provide intelligent data services for supportability design analysis. At each milestone node and test and appraisal stage, input is provided for the simulation evaluation of model supportability indicators and the compliance evaluation of qualitative supportability requirements to support the optimization of support solutions. In the use stage, the use data of similar products and historical experience data are integrated to provide support for maintenance optimization analysis. BRIEF DESCRIPTION OF THE DRAWINGS

[0078] Figure 1 It is a control block diagram of the method for constructing an aviation equipment supportability benchmark comparison system based on similarity analysis of the present invention;

[0079] Figure 2 The application scenario of the aviation equipment supportability benchmark comparison system of the present invention and the construction demand analysis flow chart;

[0080] Figure 3 A flowchart of the construction of the aviation equipment supportability benchmark comparison system based on similarity analysis of the present invention;

[0081] Figure 4 Constructing a flow chart for the aviation equipment supportability benchmark comparison system data model of the present invention;

[0082] Figure 5 The data demand analysis flow chart of aviation equipment support business of the present invention;

[0083] Figure 6 This is an example diagram of the conceptual model of the aviation equipment supportability benchmark comparison system of the present invention;

[0084] Figure 7 This is an example diagram of the logic model of the aviation equipment supportability benchmark comparison system of the present invention;

[0085] Figure 8 This is an example diagram of the physical model of the aviation equipment supportability benchmark comparison system of the present invention;

[0086] Fig. 9 It is a conceptual data model diagram of the aviation equipment supportability benchmark comparison system based on EA of the present invention;

[0087] Fig.10 The logical data model diagram of the aviation equipment supportability benchmark comparison system of the present invention based on EA;

[0088] Fig.11This is a physical data model diagram of the aviation equipment supportability benchmark comparison system of the present invention based on EA. DETAILED DESCRIPTION

[0089] The exemplary embodiments, features and aspects of the present invention will be described in detail below with reference to the accompanying drawings. The same reference numerals in the accompanying drawings represent elements with the same or similar functions. Although various aspects of the embodiments are shown in the accompanying drawings, the drawings are not necessarily drawn to scale unless otherwise specified.

[0090] The embodiment of the present invention is based on the aviation equipment support system in the existing database and aims at the needs of the newly developed aviation equipment support system, and provides a method for constructing an aviation equipment supportability benchmark comparison system based on similarity analysis, such as Figure 1 As shown, according to the application scenario of the aviation equipment supportability system to be analyzed, the construction requirements of the aviation equipment supportability benchmark comparison system are determined; the aviation equipment supportability system to be analyzed is analyzed based on the similarity analysis method, the similarity and weight of the characteristic parameters are obtained, and the aviation equipment supportability benchmark comparison system is established; the aviation equipment supportability benchmark comparison system is validated and analyzed, and the aviation equipment supportability benchmark comparison system data model is constructed; it includes:

[0091] Step S1: According to the application scenario of the aviation equipment supportability system to be analyzed, determine the construction requirements of the aviation equipment supportability benchmark comparison system. According to the full life cycle supportability business of the aviation equipment supportability system to be analyzed, analyze the application scenario of the aviation equipment supportability system to be analyzed, and determine the construction requirements of the aviation equipment supportability benchmark comparison system.

[0092] Step S11: Analysis of the business requirements of aviation equipment supportability throughout the life cycle. The establishment of the aviation equipment supportability benchmark comparison system is based on the existing aviation equipment supportability system that is closest to the design, use and support characteristics of the aviation equipment supportability system to be analyzed. It can be composed of the aviation equipment support system and its subsystems in the existing database, and the aviation equipment supportability benchmark comparison system is saved and applied according to the data structure paradigm. The system can be a real system or a virtual synthetic system with similar technology and complexity to the proposed system. The aviation equipment supportability benchmark comparison system is hierarchical and combined. In the stages of equipment demonstration, engineering development, test identification, use and support, the benchmark comparison system established for different analysis objects and supportability analysis work items is also different. Therefore, it is necessary to start with the composition and support characteristics of different types of aviation equipment systems, analyze the basic situation of equipment support, the selection and implementation of comprehensive support work items throughout the life cycle, and summarize the common and individual characteristics of various types of equipment.

[0093] Step S12: Analysis of the application scenarios of the aviation equipment supportability benchmark comparison system in the full life cycle supportability business. The application scenarios of the aviation equipment supportability system to be analyzed are divided into four application scenarios: demonstration and project establishment stage, engineering development stage, installation and finalization stage, and batch production and support stage; Figure 2 The figure shows the application scenario of the aviation equipment supportability benchmark comparison system of the present invention and the construction demand analysis flow chart; based on the above-mentioned supportability business requirements of different types of equipment throughout the life cycle, the application scenario of the aviation equipment supportability benchmark comparison system in the process of carrying out various support businesses is analyzed, and the whole process of how the demonstration unit, research and development unit, test unit, user unit and other stakeholders establish an aviation equipment supportability benchmark comparison system, carry out collaborative work based on the aviation equipment supportability benchmark comparison system, and update and adjust the data of the aviation equipment supportability benchmark comparison system is described.

[0094] Step S121: The application scenario analysis of the aviation equipment supportability benchmark comparison system in the demonstration phase can be used to support the transition decision-making in terms of improvement direction of supportability constraints, alternative support plans, initial supportability goals, supportability target values ​​and threshold values.

[0095] Step S122: The application scenario analysis of the aviation equipment supportability benchmark comparison system during the engineering development phase can be used to support the transition decision-making in terms of determining support plans, proposing support resource requirements, revising supportability target values ​​and threshold values, etc.

[0096] Step S123: The application scenario analysis of the aviation equipment supportability benchmark comparison system during the test and appraisal phase can be used to support the ability of existing and planned aviation equipment support systems to meet support objectives; evaluate whether the threshold values ​​of relevant support, the adequacy of support plans and resources, and the impact on cost and mission integrity objectives are met.

[0097] Step S124: The use phase aviation equipment supportability benchmark comparison system application scenario analysis can be used to support supportability and mission integrity assessment, as well as support improvement plans.

[0098] Step S2: Analyze the aviation equipment supportability system to be analyzed based on the similarity analysis method, obtain the similarity and weight of the characteristic parameters, and establish an aviation equipment supportability benchmark comparison system, such as Figure 3 The flowchart of the construction of the aviation equipment supportability benchmark comparison system based on similarity analysis of the present invention is shown; it specifically includes the following sub-steps:

[0099] Step S21: According to the requirements for building the aviation equipment supportability benchmark comparison system in step S1, the analytic hierarchy process is used to determine the characteristic parameters of the aviation equipment supportability benchmark comparison system to be analyzed, which are used to analyze the similarity between the systems.

[0100] The analytic hierarchy process is used to determine the characteristic parameters of the aviation equipment supportability benchmark comparison system to be analyzed, including: the characteristic parameters of the equipment-level supportability benchmark comparison system of aviation equipment, the characteristic parameters of the system-level supportability benchmark comparison system of aviation equipment, the characteristic parameters of the equipment-level supportability benchmark comparison system of aviation equipment, and the characteristic parameters of the support system supportability benchmark comparison system of aviation equipment.

[0101] The equipment-level supportability benchmark comparison system characteristic parameters of aviation equipment specifically include: equipment function characteristic parameters, equipment performance characteristic parameters, equipment size and volume characteristic parameters, equipment weight characteristic parameters, equipment energy consumption characteristic parameters, equipment material characteristic parameters, equipment reliability characteristic parameters, equipment maintainability characteristic parameters, equipment supportability characteristic parameters, equipment testability characteristic parameters, equipment safety characteristic parameters and equipment environmental adaptability characteristic parameters.

[0102] The system-level supportability benchmark comparison system characteristic parameters of aviation equipment include: system function characteristic parameters, system architecture characteristic parameters, system reliability characteristic parameters, system maintainability characteristic parameters, system testability characteristic parameters and system safety characteristic parameters.

[0103] The equipment-level security benchmark comparison system characteristic parameters of aviation equipment include: equipment function characteristic parameters, equipment size characteristic parameters, equipment weight characteristic parameters, equipment material characteristic parameters, equipment interface characteristic parameters, equipment power characteristic parameters, equipment rated working voltage characteristic parameters, equipment load current characteristic parameters and equipment life characteristic parameters.

[0104] The support system benchmark comparison system characteristic parameter analysis of aviation equipment is as follows: the support system benchmark comparison system characteristic parameter analysis is carried out from two aspects of support plan and support resources; the aviation equipment support system benchmark comparison system characteristic parameters in the support plan are analyzed separately according to the use support plan and the maintenance support plan; the aviation equipment support system benchmark comparison system characteristic parameter analysis in the support resources is carried out according to the supply support characteristic parameters, support equipment characteristic parameters, technical data characteristic parameters, support facility characteristic parameters, packaging characteristic parameters, loading and unloading characteristic parameters, storage and transportation characteristic parameters and computer resource support characteristic parameters.

[0105] The three-dimensional types of feature parameters obtained above include: text type data feature parameters and numerical type data feature parameters.

[0106] Step S22: Calculate the similarity r of the characteristic parameters of the numerical data in step S21 using the similarity element method ih , specifically:

[0107] Step S221: Determine similar elements of the aviation equipment supportability system; use similarity theory to establish a unified and quantitative similarity comparison standard between the aviation equipment supportability system A to be analyzed and the aviation equipment supportability benchmark comparison system B; then the aviation equipment supportability system similar element u(a i ,b i ) is the first characteristic parameter a in the aviation equipment support system A to be analyzed i Compare the second characteristic parameter b in the aviation equipment supportability benchmark system B i similar elements.

[0108] Step S222: Quantify the similarity element of the aviation equipment support system; the similarity element u(a i ,b i ) are s1,s2,…s m ,S=[s1,s2,…s m ]; then record u h (a i ) is the first characteristic parameter a i Relative to the characteristic element s h The eigenvalue of h (b i ) is the second characteristic parameter b i Relative to element s h The first characteristic parameter a i , the second characteristic parameter b i Relative to the characteristic element s h The feature similarity is:

[0109]

[0110] Among them, r ih is the first characteristic parameter a i With the second characteristic parameter b i The feature similarity of ; min is the minimum function; max is the maximum function; u h (a i ) is the first characteristic parameter a i Relative to the characteristic element s h The characteristic value of u h (b i ) is the characteristic parameter b i Relative to the characteristic element s h The characteristic value of a i is the first characteristic parameter; b i is the second characteristic parameter.

[0111] Step S23: Use the Jaro-Winkler algorithm to calculate the similarity Sim(A, B) of the text type data feature parameters in step S21, specifically:

[0112] Step S231: For the first character string s of the text type data characteristic parameter in the aviation equipment support system A and the second string s B , calculate the matching window MW (match window) as:

[0113]

[0114] Among them, MW is the matching window of the characteristic parameters of text type data; |s A | is the first string s A The length of |s B | is the second string s B Length.

[0115] The first string s A and the second string s B The lengths of both characters are 2 strings. When the distance between two identical characters is not greater than the matching window MW, the two characters are considered to be matched. Therefore, the matching window MW can filter out identical characters that are relatively far away.

[0116] Step S232: Use the matching window MW of the text type data feature parameter to filter out the same characters that are relatively far away, and obtain a new string sn after filtering. A and sn B , because the number of matching characters is the same, the string length m is:

[0117] m=|sn A |=|sn B |;

[0118] Where m is the length of the string; sn is A For the first string s A The string obtained after filtering; sn B For the first string s B The string obtained after filtering.

[0119] By exchanging characters, sn A Transformed into sn B , and the number of exchanges is recorded as t s , then the number of string transpositions t is half of the number of transpositions that occur, which is t = t s / 2; for the first string s A and the second string s B Perform character deletion without changing the character order, and set the resulting character sequence of the same length as the first string s A and the second string s BThe length of the character sequence (number of characters) LCS (s A ,s B ), the first string s A and the second string s B The common subsequence similarity coefficient of the string is:

[0120]

[0121] Among them, P LCS is the common subsequence similarity coefficient of the string; L LCS The length of the character sequence.

[0122] Then the first string s A and the second string s B The similarity formula is:

[0123]

[0124] Among them, Sim(A,B) is the first string s A and the second string s B similarity; t is the number of string transpositions.

[0125] Step S24: Establishing a hierarchical structure model of the aviation equipment supportability benchmark comparison system, constructing a judgment matrix of characteristic parameters, using a proportional scaling method to measure characteristic parameters, and calculating the characteristic parameter weight U of the aviation equipment supportability benchmark comparison system, specifically including the following steps:

[0126] Step S241: Constructing a judgment matrix A of feature parameters p ; There is K m criteria that need to be judged, then the kth criterion uses the judgment criterion B k (k=1,2,...,K m ) indicates that there exists K for each criterion n There are specific indicators that need to be analyzed, then the lth indicator uses the characteristic parameter C l (l=1,2,...,K n ) represents. Construct the judgment matrix A of feature parameters p As shown in Table 1:

[0127] Table 1 Judgment matrix of feature parameters

[0128]

[0129] Established to judge the criteria B k Characteristic parameters C1, C2, ...C of the judgment criteria l Comparison judgment matrix A p , in the judgment criterion B kThen, they are sorted by relative importance, that is, the characteristic parameters C1, C2, ...C l The weight of p is a positive reciprocal matrix, then it satisfies the relationship:

[0130]

[0131] Among them, C rl is the characteristic parameter C r With C l Criteria B k The weight ratio of lr is the characteristic parameter C l With C r Criteria B k The weight ratio of ; k is the judgment criterion number; l is the feature parameter number; r is the feature parameter auxiliary number.

[0132] Step S242: Introduce the 1-9 ratio scaling method, in the judgment matrix A p The importance of feature parameters is divided in the table. The meaning of the importance scale from level 1 to level 9 is listed in Table 2:

[0133] Table 2 Meaning of importance scale

[0134] <![CDATA[C rl Importance Scale]]> <![CDATA[C rl Importance Scale]]> meaning 1 r <![CDATA[C r Parameter ratio C l Parameters Level 1 Important]]> 3 1 / 3 <![CDATA[C r Parameter ratio C l Parameter level 3 importance]]> 5 1 / 5 <![CDATA[C r Parameter ratio C l Parameters are five levels important]]> 7 1 / 7 <![CDATA[C r Parameter ratio C l Parameters are seven levels important]]> 9 1 / 9 <![CDATA[C r Parameter ratio C l Parameters are of level nine importance]]> 2,4,6,8 1 / 2,1 / 4,1 / 6,1 / 8 The scale of the state between the above two judgments

[0135] Step S243: Calculation of feature parameter weights; Judgment matrix A p In , find the product of the elements in each row:

[0136] M l =ΠC rl (rl=1,2,…,K n );

[0137] Among them, M l Determine the product of the elements in row l.

[0138] Step S244: Calculate the judgment matrix A p , normalize the eigenvector, and obtain the components; find the judgment matrix A p The components of the eigenvector of are:

[0139]

[0140] Among them, W i is the i-th judgment matrix A p The components of the eigenvector of .

[0141] Step S245: Standardize the feature vector to calculate the relative weight value W hi for:

[0142]

[0143] Among them, W hi It is the weight of the i-th characteristic parameter at this level of the aviation equipment supportability benchmark comparison system relative to the characteristic parameters at the upper level.

[0144] The characteristic parameter weight U of the aviation equipment supportability benchmark comparison system is calculated as:

[0145]

[0146] Among them, U is the characteristic parameter weight of the aviation equipment supportability benchmark comparison system; U i is the weight of the i-th characteristic parameter of the aviation equipment supportability benchmark comparison system at this level; U h is the weight of the hth characteristic parameter of the previous level of the aviation equipment supportability benchmark comparison system; W hi is the weight of the i-th characteristic parameter of this level of the aviation equipment supportability benchmark comparison system relative to the h-th characteristic parameter of the previous level; h is the characteristic parameter number of the previous level of the aviation equipment supportability benchmark comparison system, h = 1, 2, ..., m; i is the characteristic parameter number of this level of the aviation equipment supportability benchmark comparison system, i = 1, 2, ..., h; m is the dimension of the judgment matrix of the previous level.

[0147] Calculate the maximum eigenvalue λmax of the judgment matrix as:

[0148]

[0149] Among them, λmax is the maximum eigenvalue of the judgment matrix; E is the eigenvalue parameter of the judgment matrix; W is the eigenvector parameter of the judgment matrix.

[0150] The judgment matrix is ​​tested for consistency; in order to ensure that the importance of each feature parameter is coordinated and consistent, a consistency test is required, that is, to determine whether the degree of inconsistency exceeds the allowable range. Usually, when the relative consistency index CI is less than or equal to 0.1, it means that the judgment matrix has passed the consistency test; conversely, when the relative consistency index CI is greater than or equal to 0.1, it means that it has not passed the consistency test, and the larger the relative consistency index CI value, the more serious the inconsistency. The calculation of the relative consistency index CI and the relative consistency ratio CR is as follows:

[0151]

[0152] Among them, CI is the relative consistency index; CR is the relative consistency ratio; RI is the relative consistency ratio parameter.

[0153] When λmax=n, the relative consistency index CI value is 0. However, in general, λmax is greater than n, so the relative consistency index CI value is greater than or equal to 0. The smaller the relative consistency index CI value is, the higher the consistency is.

[0154] Step S25: Determine the similarity of the aviation equipment supportability benchmark comparison system, and determine the aviation equipment supportability benchmark comparison system with the highest similarity to the aviation equipment to be analyzed by performing weighted calculation on the similarity and weight of each characteristic parameter; in the embodiment of the present invention, the aviation equipment supportability system A to be analyzed has a total of k characteristic parameters, and the aviation equipment supportability benchmark comparison system B in the product library has l parameters. The number of similar parameters between the two is n, and the similarity analysis result is:

[0155]

[0156] Among them, Q(A,B) is the similarity between the aviation equipment system to be analyzed and the aviation equipment supportability benchmark comparison system; r j is the similarity of the jth feature parameter; a j is the weight of the jth characteristic parameter; k is the number of characteristic parameters of the aviation equipment supportability system to be analyzed; A is the aviation equipment supportability system to be analyzed; B is the aviation equipment supportability benchmark comparison system; l is the number of characteristic parameters of the aviation equipment supportability benchmark comparison system; n is the dimension of the judgment matrix at this level.

[0157] Step S26: Establishing an aviation equipment supportability benchmark comparison system by comparing the characteristic parameters of the aviation equipment supportability system to be analyzed with the aviation equipment supportability systems in the existing database.

[0158] Step S3: Performing validity verification analysis based on the support simulation on the aviation equipment supportability benchmark comparison system in step S2, specifically:

[0159] The aviation equipment supportability benchmark comparison system support simulation model is constructed, including the mission model, equipment model, support organization model, support resource model, support process model, as well as the evaluation model and optimization model construction; the aviation equipment supportability benchmark comparison system verification analysis based on support simulation, the mission success rate and usability are obtained through simulation, and the simulation indicators are compared with the design requirement indicators of the aviation equipment supportability system to be analyzed. If the design requirements are met, it means that the constructed aviation equipment supportability benchmark comparison system to be analyzed meets the requirements. If it does not meet the requirements, the benchmark comparison system is further iteratively optimized.

[0160] Then, according to the modeling methods of support business, conceptual data modeling, logical data modeling, and physical data modeling, the aviation equipment support benchmark comparison system data model is constructed, such as Figure 4The flowchart of the data model construction of the aviation equipment supportability benchmark comparison system of the present invention is shown; specifically:

[0161] Step S31: Business data demand analysis of the aviation equipment supportability benchmark comparison system. On the basis of determining the key supportability business of the aviation equipment supportability benchmark comparison system throughout its life cycle, sort out various supportability requirement processes and establish the corresponding relationship between the supportability requirement processes and data forms; then, further sort out the detailed data elements for each data form. Figure 5 Shown is a flow chart of aviation equipment support business data demand analysis according to the present invention.

[0162] Step S32: construct a conceptual data model of the aviation equipment supportability benchmark comparison system, identify and extract core data entities, core data structures and the relationship between data entities from supportability business activities, and use ER diagrams to construct the conceptual data model; Figure 6 Shown is an example diagram of the conceptual model of the aviation equipment supportability benchmark comparison system of the present invention.

[0163] Step S33: Construct the logical data model of the aviation equipment supportability benchmark comparison system. On the basis of the conceptual data model, improve the entities, the relationships between entities, and the structural characteristic information of the entities, and use the class diagram modeling method in the Unified Modeling Language (UML2.0) to construct the logical data model of the aviation equipment supportability benchmark comparison system. Focusing on different topics, set data units of different levels such as "functional domain", "functional unit", "class" and "attribute", and establish various logical associations such as "generalization", "combination", "aggregation", "dependency" and "realization" between "classes" to form a hierarchical and standardized logical data model; Figure 7 Shown is an example diagram of the logic model of the aviation equipment supportability benchmark comparison system of the present invention.

[0164] Step S34: construct the physical data model of the aviation equipment supportability benchmark comparison system. Based on the logical data model, the database storage requirements are further considered, and the physical data model of the supportability benchmark comparison system is constructed in the form of a data table to achieve rapid database construction. The physical data model is a modeling implementation of the logical database model considering database characteristics. The data entity is established in the form of a data table model. Each data table can directly generate SQL code, and then directly generate a database table. Figure 8 Shown is an example diagram of the physical model of the aviation equipment supportability benchmark comparison system of the present invention.

[0165] Step S35: Data model construction of aviation equipment supportability benchmark comparison system based on EA (Enterprise Architect); Use EA software to carry out data modeling for the needs of conceptual data model, logical data model and physical data model construction of aviation equipment supportability benchmark comparison system. First, create a project in EA, then select ModelWizard for the project, first select the "Simple Entity Relationship Model" model to import the ER model template, such as Fig. 9 Shown is a conceptual data model diagram of the aviation equipment supportability benchmark comparison system based on EA of the present invention.

[0166] When building a conceptual data model, you can directly build a UML block diagram to construct a data structure, or you can select the "Data Dictionary" model for the project, that is, you can import the data structure model template. The logical model modeling template is shown in the figure below. The block diagram in the logical model only consists of a logical structure and does not yet reflect the physical storage characteristics, such as Fig.10 Shown is a logical data model diagram of the aviation equipment supportability benchmark comparison system based on EA of the present invention.

[0167] When building a physical data model, you can also quickly find the model template through the model wizard. Select ModelWizard for the project. First, select the "Data Modeling" model to import the template of the physical data model. The physical data model template is shown in the figure below. The data type in the physical model is generated in combination with the specific database, and the primary and foreign key information is generated according to the data association relationship. All fields are named using the underscore method; Fig.11 Shown is a physical data model diagram of the aviation equipment supportability benchmark comparison system based on EA of the present invention.

[0168] In EA, ER and UML can be used to carry out data modeling. In the conceptual modeling stage, ER can be used to establish a conceptual data model, and UML can be used to similarly express structural entities and relationships. Therefore, UML can be used in EA to fully express data modeling needs. In data modeling, there is a certain data conversion relationship between the three models.

[0169] ER diagram to data model conversion; Entity Relationship Diagram (ERD) to data model conversion converts the ERD logical model to a data model for the default database type, ready to generate DDL statements to run in one of the database products supported by the system. Before conversion, you need to define a common data type for each attribute and then select a database type as the default database. Then the data physical model can be automatically generated. The element mapping between ERD and data physical model is shown in Table 3 below.

[0170] Table 3 Mapping relationship from ERD to physical data model

[0171] ERD Physical Data Model entity surface property Fields Primary Key Primary Key Connectors Foreign Keys

[0172] Conversion of logical data model to physical data model; DDL transformation converts the logical model into a data model structured to conform to one of the supported DBMS. The target database type is determined by which DBMS is set as the default database in the model. The data model can then be used to automatically generate DDL statements to run in one of the database products supported by the system. The DDL transformation uses and demonstrates the intermediate language's support for many database-specific concepts. The element mapping relationship between the logical data model and the data-physical model is shown in Table 4 below.

[0173] Table 4 Mapping relationship between logical data model and physical data model

[0174] Logical Data Model Physical Data Model Class surface property Fields Primary Key Primary Key relation Foreign Keys

[0175] The second aspect of the embodiment of the present invention proposes an aviation equipment supportability benchmark comparison system based on similarity analysis, which includes: an aviation equipment supportability benchmark comparison system data management module, an aviation equipment supportability system information entry module and an aviation equipment supportability benchmark comparison system determination module. The aviation equipment supportability benchmark comparison system data management module can store and display the aviation equipment supportability system information that has been entered, including the characteristic information of the aviation equipment supportability system itself and the use supportability information. The aviation equipment supportability system information entry module can enter the existing aviation equipment supportability system information, help users to enter the information of the aviation equipment supportability system, and display it in the aviation equipment supportability benchmark comparison system data management module. The aviation equipment supportability benchmark comparison system determination module can automatically match the aviation equipment supportability system that is closest to the aviation equipment supportability system to be analyzed from the database of the aviation equipment supportability benchmark comparison system data management module according to the basic information of the aviation equipment supportability system to be analyzed, and construct an aviation equipment supportability benchmark comparison system.

[0176] The beneficial effects of the present invention are as follows: the embodiment of the present invention provides a method for constructing an aviation equipment supportability benchmark comparison system based on similarity analysis, which can currently solve the problems that the aviation equipment supportability benchmark comparison system is not sound and complete, and cannot provide sufficient reference and data support for the supportability design analysis of newly developed aviation equipment. The present invention is based on and centered on the data of the aviation equipment supportability benchmark comparison system. By efficiently supporting the development of aviation equipment supportability analysis and verification work, it achieves seamless connection with front-end and back-end work, scientifically and rationally plans aviation equipment support systems and support plans, and improves the support capabilities of aviation equipment support systems for equipment to perform tasks. The analysis of the aviation equipment supportability benchmark comparison system constructed by the embodiment proves that the present invention can be applied to all stages of the entire life cycle of aviation equipment model supportability demonstration, engineering development, test identification, use and support.

[0177] The embodiments described above are only descriptions of the preferred implementation modes of the present invention, and are not intended to limit the scope of the present invention. Without departing from the design spirit of the present invention, various modifications and improvements made to the technical solutions of the present invention by ordinary technicians in this field should all fall within the protection scope determined by the claims of the present invention.

Claims

1. A method for constructing an aviation equipment supportability benchmark comparison system based on similarity analysis, characterized in that: It includes: S1: Determine the requirements for building an aviation equipment supportability benchmark comparison system based on the application scenarios of the aviation equipment supportability system to be analyzed; Analyze the application scenarios of the aviation equipment supportability system to be analyzed for the full life cycle supportability business of the aviation equipment supportability system to be analyzed, and determine the requirements for building the aviation equipment supportability benchmark comparison system; S2: Analyze the aviation equipment supportability system to be analyzed based on the similarity analysis method, obtain the similarity and weight of the characteristic parameters, and establish an aviation equipment supportability benchmark comparison system, which specifically includes the following sub-steps: S21: According to the requirements for building the aviation equipment supportability benchmark comparison system in step S1, the characteristic parameters of the aviation equipment supportability benchmark comparison system to be analyzed are determined by using the hierarchical analysis method, which are used to analyze the similarity between the systems; the characteristic parameters include: text type data characteristic parameters and numerical type data characteristic parameters; S22: Calculate the similarity r of the characteristic parameters of the numerical data in step S21 using the similarity element method ih ; S23: Calculate the similarity Sim(A, B) of the feature parameters of the text type data in step S21; S24: Establish a hierarchical structure model of the aviation equipment supportability benchmark comparison system, construct a judgment matrix of characteristic parameters, use the proportional scaling method to measure the characteristic parameters, and calculate the characteristic parameter weights of the aviation equipment supportability benchmark comparison system as follows: U=(U1,U2,…U i …,U h ) Among them, U is the characteristic parameter weight of the aviation equipment supportability benchmark comparison system; U i is the weight of the i-th characteristic parameter of the aviation equipment supportability benchmark comparison system at this level; U h is the weight of the hth characteristic parameter of the previous level of the aviation equipment supportability benchmark comparison system; W hi is the weight of the i-th characteristic parameter of the current level of the aviation equipment supportability benchmark comparison system relative to the h-th characteristic parameter of the previous level; h is the characteristic parameter number of the previous level of the aviation equipment supportability benchmark comparison system, h = 1, 2, ..., m; i is the characteristic parameter number of the current level of the aviation equipment supportability benchmark comparison system, i = 1, 2, ..., h; m is the dimension of the judgment matrix of the previous level; S25: Determine the similarity of the aviation equipment supportability benchmark comparison system. By performing weighted calculation on the similarity and weight of each characteristic parameter, determine the aviation equipment supportability benchmark comparison system with the highest similarity to the aviation equipment to be analyzed. The similarity analysis result is: Among them, Q(A,B) is the similarity between the aviation equipment system to be analyzed and the aviation equipment supportability benchmark comparison system; r j is the similarity of the jth feature parameter; a j is the weight of the jth characteristic parameter; k is the number of characteristic parameters of the aviation equipment supportability system to be analyzed; A is the aviation equipment supportability system to be analyzed; B is the aviation equipment supportability benchmark comparison system; l is the number of characteristic parameters of the aviation equipment supportability benchmark comparison system; n is the dimension of the judgment matrix at this level; S26: Establish an aviation equipment supportability benchmark comparison system by comparing the characteristic parameters of the aviation equipment supportability system to be analyzed with the aviation equipment supportability system in the existing database; S3: Conduct validity verification analysis based on support simulation on the aviation equipment supportability benchmark comparison system in step S2; and construct a data model of the aviation equipment supportability benchmark comparison system in accordance with the modeling methods of supportability business, conceptual data modeling, logical data modeling, and physical data modeling, and save and apply the aviation equipment supportability benchmark comparison system.

2. The method for constructing an aviation equipment supportability benchmark comparison system based on similarity analysis according to claim 1 is characterized in that: In step S22, the similarity of the characteristic parameters of the numerical data in step S21 is calculated using the similarity element method, specifically: S221: Determine similar elements of aviation equipment supportability system; use similarity theory to establish a unified and quantitative similarity comparison standard between the aviation equipment supportability system A to be analyzed and the aviation equipment supportability benchmark comparison system B; then the similar element u(a i ,b i ) is the first characteristic parameter a in the aviation equipment support system A to be analyzed i Compare the second characteristic parameter b in the aviation equipment supportability benchmark system B i similar elements of S222: Quantify similarity element of aviation equipment support system; the similarity element u(a i ,b i ) are s1,s2,…s m ,S=[s1,s2,…s m ]; then record u h (a i ) is the first characteristic parameter a i Relative to the characteristic element s h The eigenvalue of h (b i ) is the second characteristic parameter b i Relative to element s h The first characteristic parameter a i , the second characteristic parameter b i Relative to the characteristic element s h The feature similarity is: Among them, r ih is the first characteristic parameter a i With the second characteristic parameter b i The feature similarity of ; min is the minimum function; max is the maximum function; u h (a i ) is the first characteristic parameter a i Relative to the characteristic element s h The characteristic value of u h (b i ) is the characteristic parameter b i Relative to the characteristic element s h The characteristic value of a i is the first characteristic parameter; b i is the second characteristic parameter.

3. The method for constructing an aviation equipment supportability benchmark comparison system based on similarity analysis according to claim 1, characterized in that: In step S23, the similarity of the feature parameters of the text type data in step S21 is calculated, specifically: S231: For the first character string s of the text type data characteristic parameter in the aviation equipment support system A and the second string s B , calculate the matching window MW as: Among them, MW is the matching window of the characteristic parameters of text type data; |s A | is the first string s A The length of |s B | is the second string s B Length; S232: Use the matching window MW of the text type data feature parameter to filter out the same characters that are relatively far away, and obtain a new character string sn after filtering. A and sn B , because the number of matching characters is the same, the string length m is: m=|sn A |=|sn B | Where m is the length of the string; sn is A For the first string s A The string obtained after filtering; sn B For the first string s B The string obtained after filtering; By exchanging characters, sn A Transformed into sn B , and the number of exchanges is recorded as t s , then the number of string transpositions t is half of the number of transpositions that occur, which is t = t s / 2; for the first string s A and the second string s B Perform character deletion without changing the character order, and set the resulting character sequence of the same length as the first string s A and the second string s B The length of the character sequence LCS(s A ,s B ), the first string s A and the second string s B The common subsequence similarity coefficient of the string is: Among them, P LCS is the common subsequence similarity coefficient of the string; L LCS is the length of the character sequence; Then the first string s A and the second string s B The similarity formula is: Among them, Sim(A,B) is the first string s A and the second string s B similarity; t is the number of string transpositions.

4. The method for constructing an aviation equipment supportability benchmark comparison system based on similarity analysis according to claim 1, characterized in that: In step S24, a judgment matrix of characteristic parameters is constructed, and the characteristic parameters are measured using the proportional scaling method to calculate the characteristic parameter weight U of the aviation equipment supportability benchmark comparison system, which is specifically: S241: Constructing the judgment matrix A of feature parameters p ; There is K m criteria that need to be judged, then the kth criterion uses the judgment criterion B k (k=1,2,...,K m ) indicates that there exists K for each criterion n There are specific indicators that need to be analyzed, then the lth indicator uses the characteristic parameter C l (l=1,2,...,K n )express; Established to judge the criteria B k Characteristic parameters C1, C2, ...C of the judgment criteria l Comparison judgment matrix A p , in the judgment criterion B k Then, they are sorted by relative importance, that is, the characteristic parameters C1, C2, ...C l The weight of p is a positive reciprocal matrix, then it satisfies the relationship: Among them, C rl is the characteristic parameter C r With C l Criteria B k The weight ratio of lr is the characteristic parameter C l With C r Criteria B k The weight ratio of ; k is the judgment criterion number; l is the feature parameter number; r is the feature parameter auxiliary number; S242: Introduce the 1-9 ratio scaling method, in the judgment matrix A p The importance of dividing the feature parameters in S243: Calculation of feature parameter weights; judgment matrix A p In , find the product of the elements in each row: M l =ΠC rl (rl=1,2,…,K n ) Among them, M l Determine the product of the elements in row l; S244: Calculate the judgment matrix A p , normalize the eigenvector, and obtain the components; find the judgment matrix A p The components of the eigenvector of are: Among them, W i is the i-th judgment matrix A p The components of the eigenvector of ; S245: Standardize the feature vector to calculate the relative weight value W hi , to calculate the characteristic parameter weight U of the aviation equipment supportability benchmark comparison system; the relative weight value W hi for: Among them, W hi It is the weight of the i-th characteristic parameter at this level of the aviation equipment supportability benchmark comparison system relative to the characteristic parameters at the upper level.

5. The method for constructing an aviation equipment supportability benchmark comparison system based on similarity analysis according to claim 1, characterized in that: In step S1, the analysis of the application scenarios of the aviation equipment support system to be analyzed is divided into four application scenarios: the demonstration and project establishment stage, the engineering development stage, the installation and finalization stage, and the batch production and support stage; The establishment of the aviation equipment supportability benchmark comparison system is based on the existing aviation equipment supportability system that is closest to the design, use and support characteristics of the aviation equipment supportability system to be analyzed. It can be composed of a combination of aviation equipment support systems and their subsystems in the existing database, and the aviation equipment supportability benchmark comparison system is saved and applied according to the data structure paradigm.

6. The method for constructing an aviation equipment supportability benchmark comparison system based on similarity analysis according to claim 1, characterized in that: In step S21, the characteristic parameters of the aviation equipment supportability benchmark comparison system to be analyzed are determined by using the hierarchical analysis method, specifically including: characteristic parameters of the equipment-level supportability benchmark comparison system of aviation equipment, characteristic parameters of the system-level supportability benchmark comparison system of aviation equipment, characteristic parameters of the equipment-level supportability benchmark comparison system of aviation equipment, and characteristic parameters of the support system supportability benchmark comparison system of aviation equipment; The equipment-level supportability benchmark comparison system characteristic parameters of the aviation equipment specifically include: equipment function characteristic parameters, equipment performance characteristic parameters, equipment size and volume characteristic parameters, equipment weight characteristic parameters, equipment energy consumption characteristic parameters, equipment material characteristic parameters, equipment reliability characteristic parameters, equipment maintainability characteristic parameters, equipment supportability characteristic parameters, equipment testability characteristic parameters, equipment safety characteristic parameters, and equipment environmental adaptability characteristic parameters; The system-level supportability benchmark comparison system characteristic parameters of the aviation equipment specifically include: system function characteristic parameters, system architecture characteristic parameters, system reliability characteristic parameters, system maintainability characteristic parameters, system testability characteristic parameters and system safety characteristic parameters; The equipment-level supportability benchmark comparison system characteristic parameters of the aviation equipment specifically include: equipment function characteristic parameters, equipment size characteristic parameters, equipment weight characteristic parameters, equipment material characteristic parameters, equipment interface characteristic parameters, equipment power characteristic parameters, equipment rated working voltage characteristic parameters, equipment load current characteristic parameters, and equipment life characteristic parameters; The support system benchmark comparison system characteristic parameter analysis of the aviation equipment is as follows: the support system benchmark comparison system characteristic parameter analysis is carried out from two aspects of support plan and support resources; the aviation equipment support system benchmark comparison system characteristic parameters in the support plan are analyzed separately according to the use support plan and the maintenance support plan; the aviation equipment support system benchmark comparison system characteristic parameter analysis in the support resources is carried out according to the supply support characteristic parameters, support equipment characteristic parameters, technical data characteristic parameters, support facility characteristic parameters, packaging characteristic parameters, loading and unloading characteristic parameters, storage and transportation characteristic parameters and computer resource support characteristic parameters.

7. The method for constructing an aviation equipment supportability benchmark comparison system based on similarity analysis according to claim 1, characterized in that: In step S3, the aviation equipment supportability benchmark comparison system in step S2 is subjected to effectiveness verification analysis based on support simulation, specifically: The aviation equipment supportability benchmark comparison system support simulation model is constructed, including the mission model, equipment model, support organization model, support resource model, support process model, as well as the evaluation model and optimization model construction; the aviation equipment supportability benchmark comparison system verification analysis based on support simulation, the mission success rate and usability are obtained through simulation, and the simulation indicators are compared with the design requirement indicators of the aviation equipment supportability system to be analyzed. If the design requirements are met, it means that the constructed aviation equipment supportability benchmark comparison system to be analyzed meets the requirements. If it does not meet the requirements, the benchmark comparison system is further iteratively optimized.

8. The method for constructing an aviation equipment supportability benchmark comparison system based on similarity analysis according to claim 1, characterized in that: In step S3, according to the modeling methods of supportability business, conceptual data modeling, logical data modeling, and physical data modeling, the aviation equipment supportability benchmark comparison system data model is constructed, specifically: S31: Business data demand analysis of the aviation equipment supportability benchmark comparison system. On the basis of determining the key supportability business of the aviation equipment supportability benchmark comparison system throughout its life cycle, sort out various supportability requirement processes and establish the corresponding relationship between the supportability requirement processes and data forms; then, further sort out detailed data elements for each data form; S32: Construct the conceptual data model of the aviation equipment supportability benchmark comparison system, identify and extract the core data entities, core data structures and the relationship between data entities from the supportability business activities, and use ER diagram to construct the conceptual data model; S33: Construct the logical data model of the aviation equipment supportability benchmark comparison system. On the basis of the conceptual data model, improve the entities, the relationships between entities and the structural feature information of the entities, and adopt the class diagram modeling method in the unified modeling language to construct the logical data model of the aviation equipment supportability benchmark comparison system. S34: construct a physical data model of the aviation equipment supportability benchmark comparison system. Based on the logical data model, the database storage requirements are further considered, and the physical data model of the supportability benchmark comparison system is constructed in the form of a data table to realize the rapid construction of the database. S35: Construction of data model for aviation equipment supportability benchmark comparison system based on EA; Use EA software to carry out data modeling to meet the needs of constructing conceptual data model, logical data model and physical data model of aviation equipment supportability benchmark comparison system.

9. An aviation equipment supportability benchmark comparison system based on similarity analysis, characterized in that: These include: Aviation Equipment supportability benchmark comparison system data management module, aviation equipment supportability system information entry module and aviation equipment supportability benchmark comparison system determination module; The aviation equipment supportability benchmark comparison system data management module can store and display the entered aviation equipment supportability system information, including the characteristic information of the aviation equipment supportability system itself and the use supportability information; The aviation equipment supportability system information input module can input existing aviation equipment supportability system information, help users input aviation equipment supportability system information, and display it in the aviation equipment supportability benchmark comparison system data management module; The aviation equipment supportability benchmark comparison system determination module can automatically match the aviation equipment supportability system that is closest to the aviation equipment supportability system to be analyzed from the database of the aviation equipment supportability benchmark comparison system data management module based on the basic information of the aviation equipment supportability system to be analyzed, and construct an aviation equipment supportability benchmark comparison system.

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