Multi-scheme comprehensive evaluation method for unmanned helicopter system

Abstract

The invention relates to a multi-scheme comprehensive evaluation method for an unmanned helicopter system, and the method comprises the steps: 1, building an unmanned helicopter system scheme evaluation index system according to the composition characteristics of the unmanned helicopter system; step 2, acquiring evaluation data including expert evaluation suggestions, design data, simulation data and actual test data, and constructing an evaluation index data set through standard quantitative operation; 3, determining the weight of each level of index in the evaluation index system by adopting an entropy weight method; and 4, performing comprehensive evaluation score calculation and sorting on the unmanned helicopter system scheme according to the weight of each level of index and the evaluation index data set. Compared with the prior art, the method can solve the problems that in the unmanned helicopter system scheme evaluation process, comprehensive evaluation actual test data is difficult to obtain, evaluation is too subjective and the like, the comprehensive evaluation result of the unmanned helicopter system scheme is more scientific, objective and reliable, and the comprehensive evaluation result comprehensively considering scheme feasibility and functionality is given.

Description

Technical Field

[0001] The present invention relates to, in particular to, a multi-scheme comprehensive evaluation method for an unmanned helicopter system. Background Art

[0002] Compared with fixed-wing UAV systems, unmanned helicopter systems have the advantages of vertical take-off and landing, hovering in the air at a fixed point, and low-altitude and ultra-low-altitude flight. Therefore, they are widely used in both military and civilian fields, mainly for reconnaissance and surveillance, firepower strike information assurance, agricultural and forestry plant protection, geological monitoring and other tasks.

[0003] In order to fully promote the design optimization of unmanned helicopters, reduce unnecessary investment in the development of unmanned helicopter systems, and shorten the development cycle as much as possible, it is necessary to conduct a comprehensive evaluation of unmanned helicopter system solutions. Establishing an evaluation index system and evaluation method suitable for unmanned helicopter systems is of great significance for evaluating system capabilities and clarifying the direction of design optimization.

[0004] The unmanned helicopter system is a complex system formed by combining the unmanned helicopter platform, mission payload, measurement and control link, control station and other subsystems with independent functions according to functional requirements. It has the characteristics of complex composition, wide technical fields, many influencing factors, and tight coupling of evaluation dimensions. The evaluation of the unmanned helicopter system solution is a typical multi-factor and multi-objective decision-making problem. The comprehensive evaluation of complex systems often proposes an evaluation index system, establishes an evaluation model, and then uses the weight evaluation method to obtain a comprehensive evaluation result after index weighting. Therefore, the establishment of the evaluation index system and the selection of the evaluation method are particularly important.

[0005] In terms of the evaluation index system, it is necessary to determine the basis that can reflect the characteristics of the unmanned helicopter system according to the mission requirements of the unmanned helicopter system. Therefore, each evaluation index needs to characterize certain characteristics of the unmanned helicopter system from different aspects. The index system is an organic whole composed of multiple interconnected and interacting evaluation indicators in a certain hierarchical structure. The evaluation index system is a bridge connecting evaluation experts and evaluation objects, and it is also a link between evaluation methods and evaluation objects. Only by constructing a scientific and reasonable evaluation index system can we draw scientific and fair evaluation conclusions. However, at present, the evaluation research on unmanned helicopter systems at home and abroad is focused on combat effectiveness, reliability and other aspects, and the comprehensive evaluation research on the overall plan is still blank.

[0006] In terms of evaluation methods, comprehensive evaluation is a multi-factor and multi-indicator evaluation process, which needs to be progressive, and the feasibility of the scheme and the system combat capability indicators need to be further decomposed, and the overall combat capability of the system can be evaluated through the evaluation of each lower-level indicator. The traditional system evaluation method is mainly carried out through subjective analysis and weighting, which is mainly based on the analysis and judgment of the evaluator, without considering the indicator data of the specific system, and directly conducts subjective scoring and obtains weights. The calculation process is relatively simple, but it is highly subjective and arbitrary, which can easily cause relatively large errors. Summary of the invention

[0007] The purpose of the present invention is to provide a multi-scheme comprehensive evaluation method for an unmanned helicopter system in order to overcome the defects of the above-mentioned prior art, solve the problems of difficulty in obtaining actual test data for comprehensive evaluation and excessive subjectivity in the evaluation process of unmanned helicopter system schemes, and make the comprehensive evaluation results of unmanned helicopter system schemes more scientific.

[0008] The purpose of the present invention can be achieved by the following technical solution: A multi-scheme comprehensive evaluation method for an unmanned helicopter system, comprising the following steps:

[0009] Step 1: Establish an evaluation index system for unmanned helicopter system solutions based on the composition characteristics of the unmanned helicopter system;

[0010] Step 2: Collect evaluation data including expert evaluation opinions, design data, simulation data, and actual test data, and construct an evaluation index data set through standardized quantitative operations;

[0011] Step 3: Use the entropy weight method to determine the weights of indicators at all levels in the evaluation index system;

[0012] Step 4: Calculate and rank the comprehensive evaluation scores of the unmanned helicopter system solutions based on the weights of indicators at all levels and the evaluation indicator data set.

[0013] Furthermore, the step 1 specifically establishes an unmanned helicopter system solution evaluation index system based on the composition characteristics of the unmanned helicopter by adopting a method of vertical stratification and same-layer horizontal classification.

[0014] Furthermore, the evaluation index system of the unmanned helicopter system solution in step 1 includes three levels of indicators from top to bottom:

[0015] The first-level indicators are overall program indicators, including program feasibility and system combat capability;

[0016] Secondary indicators break down the feasibility of the solution into the rationality of the technical solution and the schedule risk, and break down the system combat capability into platform capability, mission load capability, weapon capability, measurement and control transmission capability, and aircraft-ship adaptation capability;

[0017] The third-level indicators include the sub-indicators that constitute each second-level indicator.

[0018] Furthermore, the step 2 includes the following process:

[0019] The first step is to divide the indicators into two categories: qualitative indicators and quantitative indicators;

[0020] The second step is to use expert survey method to obtain qualitative indicator data;

[0021] The third step is to establish a test evaluation plan and obtain quantitative indicator data by combining simulation and flight test;

[0022] The fourth step is to standardize and quantify the quantitative indicator data and divide the unmanned helicopter system indicators into benefit-based, cost-based and fixed types.

[0023] Furthermore, the qualitative indicators include the first-level indicator scheme feasibility and its subordinate second-level indicators and third-level indicators; the quantitative indicators include the first-level indicator system combat capability and its subordinate second-level indicators and third-level indicators.

[0024] Furthermore, the standardized quantitative curve of the benefit-based indicator is:

[0025]

[0026] Among them, x xd is the target value of the benefit indicator, x xa is the benefit indicator threshold value, x x0 This is an unacceptable value for a benefit indicator.

[0027] Furthermore, the standard quantification curve of the cost-based indicator is:

[0028]

[0029] Among them, x cd is the target value of the cost indicator, x ca is the cost indicator threshold, x c0 This is an unacceptable value for a cost-based indicator.

[0030] Furthermore, the standard quantification curve of the fixed indicator is:

[0031]

[0032] Among them, x gd is the target value of the fixed indicator, x ga is the distance between the threshold value and the fixed indicator target value, x g0 It is the distance between the unacceptable value and the target value of the fixed indicator.

[0033] Furthermore, the step three includes the following steps:

[0034] The first step is data standardization;

[0035] Standardize the data of each indicator that has been quantified. Assume that there are n schemes and k indicators X1, X2,…, X k , where X i ={x i1 ,x i2 ,…,x in}, assuming that the standardized values ​​of each indicator data are Y1, Y2, …, Y k ,So

[0036] The second step is to find the information entropy of each indicator;

[0037] According to the definition of information entropy in information theory, the information entropy of a set of data in If p ij =0, then define p ij lnp ij =0;

[0038] The third step is to determine the weight of each indicator;

[0039] According to the calculation formula of information entropy, the information entropy of each indicator is calculated as E1, E2,…, E k , the weights of indicators at all levels are calculated by information entropy:

[0040] Furthermore, the comprehensive evaluation score calculation formula of the unmanned helicopter system solution in step 4 is:

[0041]

[0042] Among them, P j is the comprehensive evaluation score of the j-th unmanned helicopter system solution.

[0043] Compared with the prior art, the present invention has the following advantages:

[0044] The present invention firstly establishes an unmanned helicopter system index system according to the composition characteristics of the unmanned helicopter system, and relies on expert opinions, simulation data, and actual test data to obtain a comprehensive evaluation data set through standardized quantification. Then, the entropy weight method is used to determine the weight of each index, and a comprehensive evaluation of the scheme is performed. Thus, the functional performance index data of each subsystem / subsystem of different schemes are integrated and processed, and quantitative weighting is performed to perform a comprehensive evaluation, which effectively solves the problems of multiple dimensions of comprehensive evaluation index data, difficulty in obtaining actual test data, and excessive subjectivity in the evaluation process of the unmanned helicopter system scheme, so that the comprehensive evaluation result of the unmanned helicopter system scheme is more scientific.

[0045] The present invention adopts the method of vertical stratification and same-layer horizontal classification to establish an unmanned helicopter system program evaluation index system, including three-layer combined indicators from top to bottom, which can effectively aggregate the combined evaluation indicators and construct a universal unmanned helicopter system program comprehensive evaluation index system, providing a basis for the acquisition of subsequent evaluation data sets.

[0046] According to the different types of indicators to be evaluated, the present invention adopts expert investigation method, simulation or actual flight test to obtain qualitative or quantitative indicator data, and standardizes and quantifies the obtained data, laying the foundation for the next step of determining indicator weights and conducting comprehensive evaluation of the scheme, and effectively solving the problems of low efficiency, long cycle and high cost that exist in using only actual test data.

[0047] The present invention adopts the entropy weight method to determine the indicator weights, which effectively avoids the influence of subjective factors in the unmanned helicopter system solution evaluation process and is conducive to obtaining a more objective comprehensive evaluation result. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Figure 1 It is a schematic diagram of the method flow of the present invention;

[0049] Figure 2 It is a schematic diagram of the application process of the embodiment;

[0050] Figure 3 Schematic diagram of a comprehensive evaluation index system constructed in the embodiment;

[0051] Figure 4 It is the standardized quantitative curve of benefit-based indicators;

[0052] Figure 5 It is the standard quantitative curve of cost-type indicators;

[0053] Figure 6 It is the standardized quantitative curve of the fixed indicator. DETAILED DESCRIPTION

[0054] The present invention is described in detail below with reference to the accompanying drawings and specific embodiments.

[0055] Example

[0056] like Figure 1 As shown, a multi-scheme comprehensive evaluation method for an unmanned helicopter system includes the following steps:

[0057] Step 1: Establish an evaluation index system for unmanned helicopter system solutions based on the composition characteristics of the unmanned helicopter system;

[0058] Step 2: Collect evaluation data including expert evaluation opinions, design data, simulation data, and actual test data, and construct an evaluation index data set through standardized quantitative operations;

[0059] Step 3: Use the entropy weight method to determine the weights of indicators at all levels in the evaluation index system;

[0060] Step 4: Calculate and rank the comprehensive evaluation scores of the unmanned helicopter system solutions based on the weights of indicators at all levels and the evaluation indicator data set.

[0061] This embodiment applies the above solution, such as Figure 2 As shown, the main ones are:

[0062] Step 1: Establish an evaluation index system for unmanned helicopter system solutions based on the composition and characteristics of the unmanned helicopter system.

[0063] In view of the composition characteristics of unmanned helicopters, a method of vertical stratification and horizontal classification at the same level is used to establish an evaluation index system for unmanned helicopter system solutions. In order to facilitate the processing and analysis of comprehensive evaluation issues of system solutions, evaluation indicators should be appropriately aggregated and combined, and a three-layer combined multi-level analysis structure should be used as much as possible. According to the principle of top-down description, the unmanned helicopter overall solution evaluation index system established in this plan includes the following levels: the first-level indicators are overall solution indicators, including solution feasibility and system combat capability; the second-level indicators break down the feasibility of the solution into the rationality of the technical solution and progress risk, and the system combat capability is broken down into platform capability, mission load capability, weapon capability, measurement and control transmission capability, and aircraft-ship adaptation capability; the third-level indicators include the sub-indicators that constitute each second-level indicator, such as platform capability can be further subdivided into basic flight capability, including maximum level flight speed, cruising speed, endurance time, operating ceiling and hovering ceiling and other sub-indicators (such as Figure 3 shown).

[0064] Step 2: Collect evaluation data such as expert evaluation opinions, design data, simulation data, and actual tests, and use them as evaluation data sets after standardized quantification.

[0065] Depending on the type of indicator to be evaluated, qualitative or quantitative indicator data are obtained by means of expert survey, simulation or actual flight testing, and the obtained data are standardized and quantified, laying the foundation for the next step of determining indicator weights and conducting comprehensive evaluation of the plan.

[0066] The data collection and data standardization quantification process in this embodiment is specifically divided into the following steps:

[0067] The first step is to divide the indicators into two categories: qualitative indicators and quantitative indicators. Among them, the qualitative indicators are mainly the first-level indicator scheme feasibility and its subordinate second-level indicators and third-level indicators; the quantitative indicators are mainly the first-level indicator unmanned helicopter system combat capability and its subordinate second-level indicators and third-level indicators.

[0068] The second step is to use the expert survey method to obtain qualitative indicator data. For the feasibility indicators of the scheme, a qualitative evaluation method is used to score, and the evaluation experts fill in the specific score value in the "Score" column. The corresponding relationship between the qualitative evaluation of rationality indicators and the score value is shown in Table 1, and the corresponding relationship between the qualitative evaluation of schedule risk indicators and the score value is shown in Table 2.

[0069] Table 1 Correspondence table of rationality index scores

[0070]

[0071] Table 2 Progress risk indicator score correspondence table

[0072]

[0073] The third step is to establish a test and evaluation plan, and use a combination of simulation and flight tests to obtain quantitative indicator data. In combination with specific tactical applications and the performance requirements of unmanned helicopter systems, establish a simulation test and evaluation plan for unmanned helicopter systems. For unmanned helicopter system models and typical flight missions, conduct simulation tests in combination with each subject unit in the simulation test and evaluation plan, and record simulation test data such as maximum level flight speed, cruising speed, endurance time, service ceiling, and hovering ceiling; for plans with existing prototypes, use flight tests as much as possible to obtain corresponding data.

[0074] The fourth step is to standardize and quantify the quantitative indicator data. The unmanned helicopter system indicators can be divided into benefit type, cost type and fixed type. Among them, the larger the benefit type indicator, the better, mainly including the endurance time, etc. Set the target value of the benefit type indicator to x xd , threshold value x xa , unacceptable value is x x0 , then its standard quantization calculation formula is as follows, and its standard quantization curve is as follows Figure 4 shown.

[0075]

[0076] The smaller the cost index, the better, such as navigation accuracy, mission payload positioning accuracy, etc. Suppose the target value of the cost index is x cd , threshold value x ca , unacceptable value is x c0 , then its standard quantization calculation formula is as follows, and its standard quantization curve is as follows Figure 5 shown.

[0077]

[0078] The closer the fixed indicator is to the target value, the better, such as flight altitude, cruising speed, etc. Suppose the target value of the fixed indicator is x gd , the distance between the threshold value and the target value is x ga , the distance between the unacceptable value and the target value is x g0 , then its standard quantization calculation formula is as follows, and its standard quantization curve is as follows Figure 6 shown.

[0079]

[0080] Step 3: Use the following method to determine the weights of indicators at all levels. The specific steps are as follows:

[0081] The first step is data standardization. Standardize the data of each quantified indicator. Assume that there are n schemes and k indicators X1, X2,…, X k , where X i ={x i1 ,x i2 ,…,x in}. Assume that the standardized values ​​of each indicator data are Y1, Y2, …, Y k ,So

[0082] Step 2: Calculate the information entropy of each indicator. According to the definition of information entropy in information theory, the information entropy of a set of data in If p ij =0, then define p ij lnp ij =0.

[0083] Step 3: Determine the weight of each indicator. According to the calculation formula of information entropy, the information entropy of each indicator is calculated as E1, E2, …, E k The weights of indicators at all levels are calculated by information entropy:

[0084] In this embodiment, the weights of indicators at each level are determined as follows:

[0085] (w1,w2,w3,…,w n )=(0.012,0.013,0.020,…,0.014)

[0086] Step 4: Comprehensively evaluate the unmanned helicopter system scheme based on the weights of each indicator and the indicator data set. The evaluation score of a single scheme is After calculating the score of each solution, sort the solutions according to the score.

[0087] This embodiment conducts comprehensive evaluation on three unmanned helicopter system solutions respectively. The results are shown in Table 3. It can be seen from the results in Table 3 that Solution 3 has the highest comprehensive evaluation score.

[0088] Table 3

[0089] Indicator Solution 1 Solution 2 Solution 3 <![CDATA[x1]]> 0.8 0.96 1 <![CDATA[x2]]> 0.92 1 0.71 <![CDATA[x3]]> 0.82 1 0.856 <![CDATA[x4]]> 0.83 1 0.89 <![CDATA[x5]]> 0.69 0.6 1 … … … … <![CDATA[x k ]]> 0.71 0.89 1 comprehensive 0.68 0.69 0.75

[0090] In summary, this scheme establishes an evaluation index system for unmanned helicopter system schemes based on the composition characteristics of unmanned helicopter systems and with reference to the classification methods of other weapon systems. It also establishes an unmanned helicopter system scheme evaluation data set acquisition and processing method that comprehensively considers expert opinions, simulation and flight test results, as well as an index weight determination method based on the entropy weight method. It solves the problems of difficulty in obtaining actual test data for comprehensive evaluation and overly subjective evaluation in the evaluation process of unmanned helicopter system schemes, and can provide scientific, objective and reliable comprehensive evaluation results on the feasibility and functional performance of unmanned helicopter system schemes.

Claims

1. A multi-scheme comprehensive evaluation method for an unmanned helicopter system, characterized in that: The following steps are involved: Step 1: Establish an evaluation index system for unmanned helicopter system solutions based on the composition characteristics of the unmanned helicopter system; Step 2: Collect evaluation data including expert evaluation opinions, design data, simulation data, and actual test data, and construct an evaluation index data set through standardized quantitative operations; Step 3: Use the entropy weight method to determine the weights of indicators at all levels in the evaluation index system; Step 4: Calculate and rank the comprehensive evaluation scores of the unmanned helicopter system solutions based on the weights of indicators at all levels and the evaluation indicator data set.

2. The multi-scheme comprehensive evaluation method for an unmanned helicopter system according to claim 1 is characterized in that: The step 1 specifically establishes an evaluation index system for unmanned helicopter system solutions based on the composition characteristics of the unmanned helicopter by adopting a method of vertical stratification and horizontal classification at the same level.

3. The multi-scheme comprehensive evaluation method for an unmanned helicopter system according to claim 1 is characterized in that: The evaluation index system of the unmanned helicopter system solution in step 1 includes three levels of indicators from top to bottom: The first-level indicators are overall program indicators, including program feasibility and system combat capability; Secondary indicators break down the feasibility of the solution into the rationality of the technical solution and the schedule risk, and break down the system combat capability into platform capability, mission load capability, weapon capability, measurement and control transmission capability, and aircraft-ship adaptation capability; The third-level indicators include the sub-indicators that constitute each second-level indicator.

4. The multi-scheme comprehensive evaluation method for an unmanned helicopter system according to claim 3 is characterized in that: Step 2 The process includes: The first step is to divide the indicators into two categories: qualitative indicators and quantitative indicators; The second step is to use expert survey method to obtain qualitative indicator data; The third step is to establish a test evaluation plan and obtain quantitative indicator data by combining simulation and flight test; The fourth step is to standardize and quantify the quantitative indicator data and divide the unmanned helicopter system indicators into benefit-based, cost-based and fixed types.

5. The multi-scheme comprehensive evaluation method for an unmanned helicopter system according to claim 4 is characterized in that: The qualitative indicators are the first-level indicator plan feasibility and its subordinate second-level indicators and third-level indicators; the quantitative indicators are the first-level indicator system combat capability and its subordinate second-level indicators and third-level indicators.

6. The multi-scheme comprehensive evaluation method for an unmanned helicopter system according to claim 4 is characterized in that: The standard quantitative curve of the benefit-based indicator is: Among them, x xd is the target value of the benefit indicator, x xa is the benefit indicator threshold value, x x0 This is an unacceptable value for a benefit indicator.

7. The multi-scheme comprehensive evaluation method for an unmanned helicopter system according to claim 4 is characterized in that: The standard quantitative curve of the cost-based indicator is: Among them, x cd is the target value of the cost indicator, x ca is the cost indicator threshold, x c0 This is an unacceptable value for a cost-based indicator.

8. The multi-scheme comprehensive evaluation method for an unmanned helicopter system according to claim 4 is characterized in that: The standard quantitative curve of the fixed indicator is: Among them, x gd is the target value of the fixed indicator, x ga is the distance between the threshold value and the fixed indicator target value, x g0 It is the distance between the unacceptable value and the target value of the fixed indicator.

9. The multi-scheme comprehensive evaluation method for an unmanned helicopter system according to claim 4 is characterized in that: Step three The following steps are involved: The first step is data standardization; Standardize the data of each indicator that has been quantified. Assume that there are n schemes and k indicators X1, X2,…, X k , where X i ={x i1 ,x i2 ,…,x in }, assuming that the standardized values ​​of each indicator data are Y1, Y2, …, Y k ,So The second step is to find the information entropy of each indicator; According to the definition of information entropy in information theory, the information entropy of a set of data in If p ij =0, then define p ij lnp ij =0; The third step is to determine the weight of each indicator; According to the calculation formula of information entropy, the information entropy of each indicator is calculated as E1, E2,…, E k , the weights of indicators at all levels are calculated by information entropy:

10. The multi-scheme comprehensive evaluation method for an unmanned helicopter system according to claim 9, characterized in that: The calculation formula for the comprehensive evaluation score of the unmanned helicopter system solution in step 4 is: Among them, P j is the comprehensive evaluation score of the j-th unmanned helicopter system solution.

Images