阅读说明：本技术 一种面向水陆两栖飞机的海上搜救任务仿真评估方法 (Maritime search and rescue task simulation evaluation method for amphibious aircraft ) 是由 刘虎 施梦琪 田永亮 王睿 殷榕 于 2021-08-25 设计创作，主要内容包括：本发明涉及一种面向水陆两栖飞机的海上搜救任务仿真评估方法,包括如下步骤：水陆两栖飞机海上搜救仿真模型构建——针对水陆两栖飞机特殊的任务模式,基于多智能体建模方法搭建仿真框架,对于搜救力量智能体应用离散事件建模方法展开详细建模；水陆两栖飞机海上搜救处置方案研究——在实际搜救活动或模拟仿真推演开始之前需要确定本次任务的行动方案；基于仿真推演数据的处置方案综合评估——依据仿真推演数据对同一搜救任务下的不同处置方案的预期执行效果展开评估；实现对两栖飞机海上搜救任务的仿真与搜救方案预期执行效果的评估,为两栖飞机未来实际投入使用提供技术支持。(The invention relates to a maritime search and rescue task simulation evaluation method for an amphibious aircraft, which comprises the following steps: constructing a maritime search and rescue simulation model of the amphibious aircraft, namely constructing a simulation framework based on a multi-agent modeling method aiming at a special task mode of the amphibious aircraft, and performing detailed modeling on a search and rescue power agent by applying a discrete event modeling method; research on maritime search and rescue treatment scheme of the amphibious aircraft, namely determining an action scheme of the task before actual search and rescue activities or simulation deduction are started; comprehensive evaluation of treatment schemes based on simulation deduction data, namely performing development evaluation on expected execution effects of different treatment schemes under the same search and rescue task according to the simulation deduction data; the simulation of the maritime search and rescue task of the amphibious aircraft and the evaluation of the expected execution effect of the search and rescue scheme are realized, and technical support is provided for the future practical use of the amphibious aircraft.)

1. A maritime search and rescue task simulation evaluation method for an amphibious aircraft is characterized by comprising the following steps:

step 1, constructing a maritime search and rescue simulation model of an amphibious aircraft;

aiming at a special task mode of an amphibious aircraft, a simulation framework is built based on a multi-agent modeling method, and a discrete event modeling method is applied to search and rescue force agents to carry out detailed modeling;

step 2, researching a maritime search and rescue disposal scheme of the amphibious aircraft;

determining an action scheme of the task before actual search and rescue activities or simulation deduction are started, wherein the action scheme comprises the following components of search and rescue force selection, a navigation and return path, search area planning and search and rescue scheme formulation;

step 3, comprehensively evaluating a disposal scheme based on simulation deduction data;

and carrying out evaluation on the expected execution effects of different treatment schemes under the same search and rescue task according to the simulation deduction data.

2. The amphibious aircraft-oriented maritime search and rescue task simulation evaluation method according to claim 1, wherein the step 1 comprises the following steps:

a1, building a multi-agent simulation framework: the method comprises the following steps that (1) an amphibious aircraft maritime search and rescue task simulation relates to agents including a distress target, a search and rescue command center, search and rescue force and a lifeboat, a state model and a behavior model of each agent are established, and a whole complex system is gradually established through interactive logic among the agents;

a2, modeling a discrete event task flow: the amphibious aircraft is a modeling main body for maritime search and rescue task simulation, and detailed modeling is carried out on the whole task flow aiming at a special task mode of the amphibious aircraft, so that simulation of maritime search and rescue tasks of the amphibious aircraft is realized.

3. The amphibious aircraft-oriented maritime search and rescue task simulation evaluation method according to claim 1, wherein the step 2 comprises the following steps:

B1. search and rescue strength selection: selecting proper search and rescue force as a main unit for executing the search and rescue task according to the search and rescue task limiting information and the search and rescue force deployment condition;

B2. the exit and return route is as follows: making a navigation and return route according to the distress position and the rescue base position where the selected search and rescue force is located, wherein different navigation and return routes may be different route points;

B3. planning a search area: determining a search area plan based on an optimal search theory;

B4. and (3) search and rescue scheme formulation: and determining a search mode and a search path according to the search area information, and determining a rescue mode according to the dangerous case condition and the site environment information.

4. The amphibious aircraft-oriented maritime search and rescue task simulation evaluation method according to claim 3, wherein the search area planning comprises the following steps:

B31. acquiring drift prediction data, screening the drift prediction data according to a time period and generating a drift prediction scatter set;

B32. generating a minimum convex hull boundary according to the position distribution of the drift prediction points, and generating a minimum bounding rectangle according to the minimum convex hull boundary, wherein the minimum bounding rectangle is an initial search area before optimization;

B33. determining an optimization target of an optimized searching area according to an optimal searching theory;

B34. and planning an optimal search area by using an optimization algorithm.

5. The amphibious aircraft-oriented maritime search and rescue task simulation evaluation method according to claim 4, wherein the optimization objective is search success probability, and the search success probability describes the possibility of finding the search objective.

6. The method for simulating and evaluating the maritime search and rescue task for amphibious aircraft according to claim 5, wherein the search success probability is jointly determined by the inclusion Probability (POC) and the discovery Probability (POD), as shown in the following formula:

POS＝POC·POD

POC reflects the probability that the search target is indeed within the search area, which can be calculated from the ratio of the number of scatters contained in the current search area to the number of all scatters, as shown in the following formula:

in the formula (I), the compound is shown in the specification,indicating t contained in the current search area₁To t₂The time drift predicts the number of scatter points,represents t₁To t₂The number of all drift predicted scatter points at that moment;

POD measures the probability that a search target is found when the target is located in a search area, and the calculation method can be expressed by the following formula:

POD＝1-exp(-W·V·T/A)

in the formula, W represents a search width of search and rescue force, V represents a search speed of search and rescue force, T represents a search time of search and rescue force, and a represents an area size of a search region.

7. The amphibious aircraft-oriented maritime search and rescue task simulation evaluation method according to claim 4, wherein the optimization algorithm is a cell iterative search algorithm (CIS), and specifically comprises the following steps:

B341. acquiring an initial search area, namely loading a minimum bounding rectangle;

B342. spending grids in a given number of grids;

B343. calculating POC value of each grid;

B344. let the grid with the maximum POC value be the initial search rectangle R₀；

B345. Along R₀The directions of all the edges of the rectangular region are respectively extended outwards by one line, and the obtained rectangular region is Rx +, Rx-, Ry + and Ry-;

B346. calculating the POS values of Rx +, Rx-, Ry +, Ry-;

B347. making the rectangular area with the maximum POS value as Rmax;

B348. if the POS value of Rmax is larger than R₀The POS value of (1), then order R₀B345-B347 is re-executed as Rmax; if the POS value of Rmax is less than R₀POS value of (1), then R₀The optimal search area is obtained.

8. The amphibious aircraft-oriented maritime search and rescue task simulation evaluation method according to claim 1, wherein the step 3 comprises the following steps:

C1. establishing an index system: an evaluation index system is established from two dimensions of safety and task efficiency, and the established index system can reflect the characteristics of the search and rescue task of the amphibious aircraft;

C2. index value calculation: establishing a calculation model of each evaluation index under an evaluation index system, embedding an amphibious aircraft maritime search and rescue simulation model, and completing calculation and output in the simulation process;

C3. and (3) scheme simulation deduction: completing simulation deduction of a disposal scheme based on an amphibious aircraft maritime search and rescue simulation model and a Geographic Information System (GIS), and outputting each index value;

C4. selecting an evaluation method: selecting a proper evaluation method to empower each index under an evaluation index system and provide a basis for comprehensive evaluation of the scheme;

C5. and (4) comprehensive evaluation results: and carrying out standardization processing on each index under the index system according to the calculation result of the index value and a comprehensive evaluation method, finally obtaining the comprehensive score of the scheme, and giving an evaluation result of the expected execution effect of the disposal scheme.

9. The amphibious aircraft-oriented maritime search and rescue task simulation evaluation method according to claim 8, wherein the evaluation indexes are as follows:

landing residual oil amount I11: calculating the residual fuel quantity after the aircraft completes the search and rescue task;

maximum offshore distance I12: calculating the farthest distance between the aircraft and the base in the task execution process;

distress person remaining life level I21: calculating the remaining life level of the last person in distress when the last person in distress is rescued, wherein the calculating method comprises the following steps:

in the formula, t represents the time for which the person in distress is actually rescued and waits; t is₀The maximum waiting time of the distress personnel under the current condition is related to the sea condition, and the worse the sea condition is, the T is₀The smaller the value is, the longest waiting time T under different sea conditions₀Can be obtained from historical empirical data; the delta T represents the longest waiting time which can be prolonged, and means that the survival time of people in distress is prolonged by means of airdrop rescue goods and materials and the like;

time to search for target I31: calculating the time from the aircraft to arrive at the task area to the time when the distress target is found;

time to rescue I32: calculating the time from landing to finishing rescue and taking off again;

rescue ratio of personnel I33: calculating the proportion of the number of successfully rescued people of the airplane to the total number of people in distress, wherein the rescue proportion of people is 1 if a target is found and rescue actions are taken within the longest waiting time of the people in distress, otherwise the rescue proportion is 0; due to the existence of uncertainty factors, different results can be obtained when multiple times of simulation are carried out on the same treatment scheme, and the meaning of an index value obtained by averaging the multiple times of simulation results is rescue success probability which is used for measuring the reliability of the aircraft in completing search and rescue tasks;

airplane takeoff time I41: calculating the time from the time when the aircraft receives the search and rescue task to the time when the aircraft reaches the task area, wherein the time comprises preparation before flight, guarantee operation and the like, and the index reflects the capability of the aircraft to rapidly move;

aircraft return time I42: and calculating the time from the water surface takeoff of the airplane to the arrival at the nearest airport, wherein the index reflects the capability of the airplane to rapidly transfer the distress personnel.

10. The amphibious aircraft-oriented maritime search and rescue task simulation evaluation method according to claim 8, wherein an accumulative ratio evaluation method is used for carrying out standardization processing on index calculation results and giving comprehensive scores of the method, and the specific steps comprise:

1) establishing a multi-criterion decision matrix;

assuming m alternatives, n criteria (i.e., indices), the form of the multi-criteria decision matrix is shown as follows:

in the formula, x_ijRepresents the performance value of the ith scheme under the jth criterion, i is 0, … m, j is 1,2, … n; x is the number of_0jRepresents the best performance value under the jth criterion;

it should be noted that if the optimal value under the jth criterion is unknown, if j is a benefit-type criterion:

if j is a cost-type criterion then:

2) normalizing the decision matrix;

the normalized decision matrix is of the form:

in the formula (I), the compound is shown in the specification,denotes x_ijNormalized values, i ═ 0.. m, j ═ 1, 2.. n, if j is a benefit-type criterion then:

if j is a cost-type criterion then:

3) calculating a weighted normalized decision matrix

Assume that the jth criterion is weighted by w_jCalculating to obtain index weight w by analytic hierarchy process_jSatisfy 0 < w_jIs < 1, andthe form of the weighted normalized decision matrix is shown as follows:

in the formula (I), the compound is shown in the specification,

4) calculating an optimality function S_iAnd a utility value K_i；

The value of the optimality function for the ith scheme can be calculated as follows:

it can be seen that S_iIs calculated from the property value x_ijAnd a weight w_jDecision, optimality function S_iA larger value of (c) indicates that the scheme i is more efficient, and thus can be based on S_iThe values of (c) rank the priority of alternatives, however, S_iThe value of (A) cannot directly reflect the proximity degree of the scheme i to the ideal optimal scheme, and can be used for S_iIs subjected to normalizationGet the utility value K_i；

The calculation method can be expressed by the following formula:

S₀is the ratio of the optimality function values, K, obtained under an ideal optimal scheme_iTo indicate the degree of utility of the alternative.

Technical Field

The invention relates to the field of computer modeling simulation, in particular to a maritime search and rescue task simulation evaluation method for an amphibious aircraft.

Background

With the vigorous development of maritime trade and shipping industry, the frequent occurrence of maritime distress accidents provides new challenges for maritime search and rescue capability, especially for medium and far maritime search and rescue capability. At present, a maritime search and rescue equipment system mainly comprises a rescue helicopter and a rescue ship, wherein the rescue helicopter and the rescue ship are respectively limited by a navigation range and a navigation speed, and the requirement of remote and rapid support of a middle and far maritime search and rescue task is difficult to meet. The amphibious aircraft is brought into an aviation emergency rescue system, so that the middle and far sea rescue problem can be effectively solved, and the sea rescue capacity is improved from 300 kilometers to 1500 kilometers. With the success of first-time sea flight of a large amphibious aircraft AG600 independently developed in China, research on the marine rescue technology of the amphibious aircraft is urgently needed in order to accelerate the application process of the large amphibious aircraft AG600 in an aviation emergency rescue system in China and exert the special advantages and functions. Because the difficulty of maritime search and rescue drilling is high, the cost is high, maritime search and rescue task simulation is one of effective means for researching the maritime rescue technology of the amphibious aircraft, search and rescue task deduction and efficiency evaluation can be completed before practical drilling by means of virtual simulation means, and reference is provided for the execution of practical tasks. The existing maritime search and rescue simulation evaluation method mainly aims at the existing maritime search and rescue equipment system and cannot reflect the characteristics of an amphibious aircraft and a special task mode of the amphibious aircraft. In addition, most of researches of scholars at home and abroad on the offshore rescue technology of the amphibious aircraft in recent years are focused on theoretical analysis on a maritime rescue task mode and rescue capacity of the amphibious aircraft, few researches related to a simulation evaluation method are carried out, and quantitative results of expected effects of the amphibious aircraft on the maritime search and rescue task cannot be given. Therefore, in order to better meet the requirements of medium and far sea search and rescue, how to establish a maritime search and rescue task simulation evaluation method matched with the special task mode of the amphibious aircraft is a problem to be solved urgently.

Disclosure of Invention

The invention aims to overcome the defects of the prior art, provides a maritime search and rescue task simulation evaluation method for an amphibious aircraft, realizes simulation of maritime search and rescue tasks of the amphibious aircraft and evaluation of expected execution effects of a search and rescue scheme, and provides technical support for future practical use of the amphibious aircraft.

The technical scheme of the invention is as follows: a maritime search and rescue task simulation evaluation method for an amphibious aircraft comprises the following steps:

step 1, constructing a maritime search and rescue simulation model of an amphibious aircraft;

aiming at a special task mode of an amphibious aircraft, a simulation framework is built based on a multi-agent modeling method, and a discrete event modeling method is applied to search and rescue force agents to carry out detailed modeling;

step 2, researching a maritime search and rescue disposal scheme of the amphibious aircraft;

determining an action scheme of the task before actual search and rescue activities or simulation deduction are started, wherein the action scheme comprises the following components of search and rescue force selection, a navigation and return path, search area planning and search and rescue scheme formulation;

step 3, comprehensively evaluating a disposal scheme based on simulation deduction data;

and carrying out evaluation on the expected execution effects of different treatment schemes under the same search and rescue task according to the simulation deduction data.

Further, the step 1 comprises the following steps:

a1, building a multi-agent simulation framework: the method comprises the following steps that (1) an amphibious aircraft maritime search and rescue task simulation relates to agents including a distress target, a search and rescue command center, search and rescue force and a lifeboat, a state model and a behavior model of each agent are established, and a whole complex system is gradually established through interactive logic among the agents;

a2, modeling a discrete event task flow: the amphibious aircraft is a modeling main body for maritime search and rescue task simulation, and detailed modeling is carried out on the whole task flow aiming at a special task mode of the amphibious aircraft, so that simulation of maritime search and rescue tasks of the amphibious aircraft is realized.

Further, the step 2 comprises the following steps:

B1. search and rescue strength selection: selecting proper search and rescue force as a main unit for executing the search and rescue task according to the search and rescue task limiting information and the search and rescue force deployment condition;

B2. the exit and return route is as follows: making a navigation and return route according to the distress position and the rescue base position where the selected search and rescue force is located, wherein different navigation and return routes may be different route points;

B3. planning a search area: determining a search area plan based on an optimal search theory;

B4. and (3) search and rescue scheme formulation: and determining a search mode and a search path according to the search area information, and determining a rescue mode according to the dangerous case condition and the site environment information.

Further, the search area planning comprises the following steps:

B31. acquiring drift prediction data, screening the drift prediction data according to a time period and generating a drift prediction scatter set;

B32. generating a minimum convex hull boundary according to the position distribution of the drift prediction points, and generating a minimum bounding rectangle according to the minimum convex hull boundary, wherein the minimum bounding rectangle is an initial search area before optimization;

B33. determining an optimization target of an optimized searching area according to an optimal searching theory;

B34. and planning an optimal search area by using an optimization algorithm.

Further, the optimization target is a search success probability, and the search success probability describes the possibility of finding the search target.

Further, the search success probability is determined by the inclusion Probability (POC) and the discovery Probability (POD), as shown in the following formula:

POS＝POC·POD

POC reflects the probability that the search target is indeed within the search area, which can be calculated from the ratio of the number of scatters contained in the current search area to the number of all scatters, as shown in the following formula:

in the formula (I), the compound is shown in the specification,indicating t contained in the current search area₁To t₂The time drift predicts the number of scatter points,represents t₁To t₂All drifts of the time instants predict the number of scatter points.

POD measures the probability that a search target is found when the target is located in a search area, and the calculation method can be expressed by the following formula:

POD＝1-exp(-W·V·T/A)

in the formula, W represents a search width of search and rescue force, V represents a search speed of search and rescue force, T represents a search time of search and rescue force, and a represents an area size of a search region.

Further, the optimization algorithm is a cell iterative search algorithm (CIS), and specifically includes the following steps:

B341. acquiring an initial search area, namely loading a minimum bounding rectangle;

B342. spending grids in a given number of grids;

B343. calculating POC value of each grid;

B344. let the grid with the maximum POC value be the initial search rectangle R₀；

B345. Along R₀The directions of all the edges of the rectangular region are respectively extended outwards by one line, and the obtained rectangular region is Rx +, Rx-, Ry + and Ry-;

B346. calculating the POS values of Rx +, Rx-, Ry +, Ry-;

B347. making the rectangular area with the maximum POS value as Rmax;

B348. if the POS value of Rmax is larger than R₀The POS value of (1), then order R₀B345-B347 is re-executed as Rmax; if the POS value of Rmax is less than R₀POS value of (1), then R₀The optimal search area is obtained.

Further, the step 3 comprises the following steps:

C1. establishing an index system: an evaluation index system is established from two dimensions of safety and task efficiency, and the established index system can reflect the characteristics of the search and rescue task of the amphibious aircraft;

C2. index value calculation: establishing a calculation model of each evaluation index under an evaluation index system, embedding an amphibious aircraft maritime search and rescue simulation model, and completing calculation and output in the simulation process;

C3. and (3) scheme simulation deduction: completing simulation deduction of a disposal scheme based on an amphibious aircraft maritime search and rescue simulation model and a Geographic Information System (GIS), and outputting each index value;

C4. selecting an evaluation method: selecting a proper evaluation method to empower each index under an evaluation index system and provide a basis for comprehensive evaluation of the scheme;

C5. and (4) comprehensive evaluation results: and carrying out standardization processing on each index under the index system according to the calculation result of the index value and a comprehensive evaluation method, finally obtaining the comprehensive score of the scheme, and giving an evaluation result of the expected execution effect of the disposal scheme.

Further, the evaluation index is as follows:

landing residual oil amount I11: calculating the residual fuel quantity after the aircraft completes the search and rescue task;

maximum offshore distance I12: calculating the farthest distance between the aircraft and the base in the task execution process;

distress person remaining life level I21: calculating the remaining life level of the last person in distress when the last person in distress is rescued, wherein the calculating method comprises the following steps:

in the formula, t represents the time for which the person in distress is actually rescued and waits; t is₀The maximum waiting time of the distress personnel under the current condition is related to the sea condition, and the worse the sea condition is, the T is₀The smaller the value is, the longest waiting time T under different sea conditions₀Can be obtained from historical empirical data; the delta T represents the longest waiting time which can be prolonged, and means that the survival time of people in distress is prolonged by means of airdrop rescue goods and materials and the like;

time to search for target I31: calculating the time from the aircraft to arrive at the task area to the time when the distress target is found;

time to rescue I32: calculating the time from landing to finishing rescue and taking off again;

rescue ratio of personnel I33: calculating the proportion of the number of successfully rescued people of the airplane to the total number of people in distress, wherein the rescue proportion of people is 1 if a target is found and rescue actions are taken within the longest waiting time of the people in distress, otherwise the rescue proportion is 0; due to the existence of uncertainty factors, different results can be obtained when multiple times of simulation are carried out on the same treatment scheme, and the meaning of an index value obtained by averaging the multiple times of simulation results is rescue success probability which is used for measuring the reliability of the aircraft in completing search and rescue tasks;

airplane takeoff time I41: calculating the time from the time when the aircraft receives the search and rescue task to the time when the aircraft reaches the task area, wherein the time comprises preparation before flight, guarantee operation and the like, and the index reflects the capability of the aircraft to rapidly move;

aircraft return time I42: and calculating the time from the water surface takeoff of the airplane to the arrival at the nearest airport, wherein the index reflects the capability of the airplane to rapidly transfer the distress personnel.

Further, the index calculation result is standardized by using an accumulative ratio evaluation method and a comprehensive score of the method is given, and the method comprises the following specific steps:

1) establishing a multi-criterion decision matrix;

assuming m alternatives, n criteria (i.e., indices), the form of the multi-criteria decision matrix is shown as follows:

in the formula, x_ijRepresents the performance value of the ith scheme under the jth criterion, i is 0,. m, j is 1,2,. n; x is the number of_0jRepresents the best performance value under the jth criterion;

it should be noted that if the optimal value under the jth criterion is unknown, if j is a benefit-type criterion:

if j is a cost-type criterion then:

2) normalizing the decision matrix;

the normalized decision matrix is of the form:

in the formula (I), the compound is shown in the specification,denotes x_ijNormalized values, i ═ 0.. m, j ═ 1, 2.. n, if j is a benefit-type criterion then:

if j is a cost-type criterion then:

3) calculating a weighted normalized decision matrix

Assume that the jth criterion is weighted by w_jCalculating to obtain index weight w by analytic hierarchy process_jSatisfy 0 < w_jIs < 1, andthen the weight is normalizedThe decision matrix is of the form:

in the formula (I), the compound is shown in the specification,

4) calculating an optimality function S_iAnd a utility value K_i；

The value of the optimality function for the ith scheme can be calculated as follows:

it can be seen that S_iIs calculated from the property value x_ijAnd a weight w_jDecision, optimality function S_iA larger value of (c) indicates that the scheme i is more efficient, and thus can be based on S_iThe values of (c) rank the priority of alternatives, however, S_iThe value of (A) cannot directly reflect the proximity degree of the scheme i to the ideal optimal scheme, and can be used for S_iCarrying out normalization processing to obtain utility value K_i；

The calculation method can be expressed by the following formula:

S₀is the ratio of the optimality function values, K, obtained under an ideal optimal scheme_iTo indicate the degree of utility of the alternative.

The invention has the following beneficial effects:

(1) the invention provides a maritime search and rescue task simulation evaluation method for an amphibious aircraft, which expands the application range of the maritime search and rescue task simulation evaluation method and defines the application prospect of the amphibious aircraft in a maritime search and rescue system.

(2) According to the invention, a set of simulative amphibious aircraft maritime search and rescue full-flow model is established, and the execution process of maritime search and rescue tasks of the amphibious aircraft is simulated by adopting a virtual simulation method, so that the actual drilling times are reduced, and the risk and the cost are favorably reduced.

(3) The invention aims at a brand-new evaluation index system established by a maritime search and rescue disposal scheme of an amphibious aircraft, is different from the past research that generally focuses on evaluation of search and rescue force, is a comprehensive evaluation oriented to all elements in the disposal scheme, including search and rescue force, a round-trip path, a search area, the search and rescue scheme and the like, is real and reliable in a comprehensive evaluation result based on simulation deduction data, and can objectively provide decision support for an actual maritime search and rescue task.

Drawings

Fig. 1 is an overall framework diagram of the present invention.

FIG. 2 is a diagram of a multi-agent simulation framework for maritime search and rescue tasks of an amphibious aircraft.

Fig. 3 is a flow chart of the amphibious aircraft for performing maritime search and rescue tasks.

Fig. 4 is a flow chart of search area planning.

FIG. 5 is a flowchart of an iterative cell search algorithm.

Fig. 6 is an evaluation index system for search and rescue efficiency of an amphibious aircraft.

Detailed Description

The technical solutions of the present invention will be described clearly and completely with reference to the accompanying drawings, and it should be understood that the described embodiments are some, but not all embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

In the description of the present invention, it should be noted that the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc., indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings, and are only for convenience of description and simplicity of description, but do not indicate or imply that the device or element being referred to must have a particular orientation, be constructed and operated in a particular orientation, and thus, should not be construed as limiting the present invention. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance.

As shown in fig. 1, the invention provides a maritime search and rescue task simulation evaluation method for an amphibious aircraft, which comprises the following steps:

step 1, constructing a maritime search and rescue simulation model of the amphibious aircraft.

Aiming at a special task mode of an amphibious aircraft, a simulation framework is built based on a multi-agent modeling method, and detailed modeling is carried out on a search and rescue power agent by applying a discrete event modeling method, wherein the specific method comprises the following steps:

a1, building a multi-agent simulation framework: the amphibious aircraft maritime search and rescue task simulation system comprises intelligent bodies, a rescue command center, search and rescue force and a lifeboat, wherein the intelligent bodies are subjected to distress objective, the search and rescue command center, the search and rescue force and the lifeboat, a state model and a behavior model of each intelligent body are established, and the whole complex system is gradually established through interactive logic among the intelligent bodies.

As shown in FIG. 2, the invention discloses a multi-agent simulation framework diagram for maritime search and rescue tasks of an amphibious aircraft.

A101, establishing a state model and a behavior model of the distress target agent.

When the distress target has a distress accident, the distress target intelligent agent gives an alarm to the search and rescue command center intelligent agent, does unpowered drifting until the distress target is found, and stops drifting.

And A102, establishing a state model and a behavior model of the search and rescue command center intelligent agent.

When the search and rescue command center intelligent body receives the alarm information, the alarm information is processed, a disposal scheme is formulated, a search and rescue task is sent to the search and rescue force intelligent body, search and rescue forces are assigned for search and rescue, rescue actions are remotely commanded, and return permission is sent to the search and rescue forces according to search and rescue conditions.

And A103, establishing a state model and a behavior model of the search and rescue strength intelligent agent.

The method comprises the steps that the airplane stands by at a base when no task is available, when a search and rescue task of an intelligent search and rescue command center is received, the airplane performs preparation before navigation, then takes off and cruises to perform marine search, and if no target is found within a specified time, the airplane returns to the navigation and lands after receiving return navigation permission of the search and rescue command center; if the rescue target is found, the lifeboat is controlled to be watered for rescue, the lifeboat returns to the airplane after completing rescue, and the airplane returns to the airplane for landing after receiving the return permission of the search and rescue command center.

And A104, establishing a state model and a behavior model of the lifeboat intelligent agent.

The rescue vehicle is in standby in the cabin in the search and rescue process, after a rescue target is found, the rescue vehicle is ready to move, drives to the distress target and carries out rescue, and after the rescue is finished, the rescue vehicle returns to the plane.

A2, modeling a discrete event task flow: the amphibious aircraft is a modeling main body for maritime search and rescue task simulation, and detailed modeling is carried out on the whole task flow aiming at a special task mode of the amphibious aircraft, so that simulation of maritime search and rescue tasks of the amphibious aircraft is realized.

As shown in FIG. 3, the invention discloses a flow chart for an amphibious aircraft to perform a maritime search and rescue task.

All task stages involved in the whole process from the receiving of the search and rescue task to the completion of the search and rescue task of the amphibious aircraft are abstracted into discrete events and activities so as to represent state change and task stage switching, and a simulative task full-flow model based on discrete events is obtained and covers a sailing stage, a search stage, a rescue stage and a returning stage.

The amphibious aircraft receives a search and rescue task and enters a sailing stage comprising preparation before sailing, flying to a task area and arriving at the task area; the method comprises the steps that after a task area is reached and a searching condition is met, a searching stage is started, an airplane flies along a searching path to search targets in distress, target data are fused and identified through radar searching, lifesaving beacon searching and visual searching, authenticity of the target data is judged, if the target data are judged to be false, searching is continued, a searching area is loaded, a searching mode is selected, a searching path is planned, and the searching stage is restarted; if the target data is true, entering a rescue stage, evaluating the water-landing rescue conditions, including observing meteorological conditions, throwing a sea condition buoy and throwing marker smoke, after meeting the water-landing rescue conditions, landing the plane, sliding on the water surface, lowering rescue personnel and a lifeboat, guiding the rescue personnel to rescue, returning the lifeboat to the plane, completing the water-landing rescue, taking off the plane on the water surface, flying to the nearest airport, and completing the rescue task; when the airplane enters a return stage, the airplane waits for a return instruction, and after receiving a return permission, the airplane returns to the base; in the process, if the searching condition is not met, the aircraft enters a return flight stage.

And step 2, researching a maritime search and rescue treatment scheme of the amphibious aircraft.

The action scheme of the task needs to be determined before actual search and rescue activities or simulation deduction begins, the component elements of the action scheme comprise search and rescue force selection, a navigation and return path, search area planning and search and rescue scheme formulation, and the formulation of a reasonable disposal scheme is the key for successful search and rescue actions, and the specific method comprises the following steps:

B1. search and rescue strength selection: and selecting proper search and rescue force as a main unit for executing the search and rescue task according to the search and rescue task limiting information and the search and rescue force deployment condition.

B2. The exit and return route is as follows: and establishing a navigation and return route according to the distress position and the rescue base position where the selected search and rescue force is positioned, wherein different navigation and return routes may be different route points.

B3. Planning a search area: the search area planning based on the optimal search theory is a core link for formulating a disposal scheme, and a flow chart of the search area planning is shown in fig. 4, and the method specifically comprises the following steps:

B31. obtaining and screening drift prediction data to generate drift prediction scatter set

The method comprises the steps of obtaining drift prediction data by using a blue-sea sky drift prediction system, processing a data structure, screening the drift prediction data according to time periods to generate drift prediction scattered point sets, obtaining different drift prediction scattered point sets by selecting different time periods, and further generating different search areas.

B32. Generating the minimum convex hull boundary and the minimum bounding rectangle, initializing the search area

The minimum convex hull boundary is generated by the position distribution of the drift prediction points, and the minimum convex hull boundary is a convex polygon formed by the outermost points of the screened drift prediction scatter set. After the minimum convex hull boundary is obtained, a minimum bounding rectangle of the scattered point set can be generated by means of a rotating hull-jamming algorithm, and the minimum bounding rectangle is a search area before optimization.

B33. Determining an optimization objective and providing a calculation method

The optimization goal determined by the optimal search theory is to ensure that the search success probability is highest. The search success Probability (POS) describes the probability of finding a search target, which is determined by the inclusion Probability (POC) and the discovery Probability (POD), as shown in the following formula:

POS＝POC·POD

POC reflects the probability that the search target is indeed within the search area, which can be calculated from the ratio of the number of scatters contained in the current search area to the number of all scatters, as shown in the following formula:

in the formula (I), the compound is shown in the specification,indicating t contained in the current search area₁To t₂The time drift predicts the number of scatter points,represents t₁To t₂All drifts of the time instants predict the number of scatter points.

POD measures the likelihood that a search target is found when it is located within the search area. The calculation method can be expressed by the following formula:

POD＝1-exp(-W·V·T/A)

in the formula, W represents a search width of search and rescue force, V represents a search speed of search and rescue force, T represents a search time of search and rescue force, and a represents an area size of a search region.

B34. Planning optimal search area by using optimization algorithm

The invention adopts a cell iterative search algorithm (CIS) to plan an optimal search area, and an algorithm flow chart is shown in figure 5, which comprises the following steps:

B341. acquiring an initial search area, namely loading a minimum bounding rectangle;

B342. spending grids in a given number of grids;

B343. calculating POC value of each grid;

B344. let the grid with the maximum POC value be the initial search rectangle R₀；

B345. Along R₀The directions of all the edges of the rectangular region are respectively extended outwards by one line, and the obtained rectangular region is Rx +, Rx-, Ry + and Ry-;

B346. calculating the POS values of Rx +, Rx-, Ry +, Ry-;

B347. making the rectangular area with the maximum POS value as Rmax;

B348. if the POS value of Rmax is larger than R₀The POS value of (1), then order R₀B345-B347 is re-executed as Rmax; if the POS value of Rmax is less than R₀POS value of (1), then R₀The optimal search area is obtained.

B4. And (3) search and rescue scheme formulation: and determining a search mode and a search path according to the search area information, and determining a rescue mode according to the dangerous case condition and the site environment information, so as to provide a basis for the development of search and rescue work.

And 3, comprehensively evaluating the treatment scheme based on the simulation deduction data.

According to simulation deduction data, expected execution effects of different treatment schemes under the same search and rescue task are evaluated, and the specific method comprises the following steps:

C1. index system establishment

An evaluation index system is established from two dimensions of safety and task efficiency, and the established index system can reflect the characteristics of the search and rescue task of the amphibious aircraft.

As shown in FIG. 6, the invention discloses an amphibious aircraft search and rescue efficiency evaluation index system.

According to the embodiment of the invention, eight indexes are provided from four dimensions of safety, distress target safety, search and rescue efficiency and support efficiency of the amphibious aircraft respectively to form an evaluation index system of search and rescue efficiency of the amphibious aircraft, so that evaluation on different disposal schemes can be realized.

C2. Index value calculation

And establishing a calculation model of each evaluation index under an evaluation index system, embedding an amphibious aircraft maritime search and rescue simulation model, and completing calculation and output in the simulation process.

According to the embodiment of the invention, a calculation method of each index in a simulation deduction process is provided, and the evaluation indexes are as follows:

1) and residual oil mass on landing I11: and calculating the residual fuel quantity of the aircraft after the search and rescue task is completed, wherein the average fuel consumption rate is assumed to be 2000kg/h, which is a conservative value, and the aircraft is not consumed in the stage from the stop to the take-off of the aircraft on the water surface during calculation.

2) Maximum offshore distance I12: and calculating the farthest distance between the aircraft and the base station during the task execution.

3) And the remaining life level of the persons in distress I21: the remaining life level of the last person in distress at the time of rescue is calculated. The calculation method comprises the following steps:

in the formula, t represents the time for which the person in distress is actually rescued and waits; t is₀The maximum waiting time of the distress personnel under the current condition is related to the sea condition, and the worse the sea condition is, the T is₀The smaller the value is, the longest waiting time T under different sea conditions₀Can be obtained from historical empirical data; the delta T represents the longest waiting time which can be prolonged, and means that the survival time of people in danger is prolonged by airdrop rescue goods and materials and the like.

4) When searching for a target I31: the time from the aircraft to the arrival in the mission area to the discovery of the targets in distress is calculated.

5) And the time of water retention rescue I32: and calculating the time of the aircraft from landing to finishing rescue and taking off again.

6) The rescue ratio of people I33: and calculating the proportion of the number of successful rescuers of the airplane to the total number of people in the distress, wherein the rescue proportion of the people is 1 if the target is found and rescue actions are taken within the longest waiting time of the people in the distress, and otherwise the rescue proportion is 0. Due to the existence of uncertainty factors, different results can be obtained when multiple times of simulation are carried out on the same treatment scheme, and the meaning of an index value obtained by averaging the multiple times of simulation results is rescue success probability, so that the reliability of the aircraft for completing search and rescue tasks is measured.

7) Aircraft departure time I41: and calculating the time from the time when the aircraft receives the search and rescue task to the time when the aircraft reaches the task area, wherein the time comprises preparation before flight, guarantee operation and the like, and the index reflects the capability of the aircraft to rapidly move.

8) Aircraft return time I42: and calculating the time from the water surface takeoff of the airplane to the arrival at the nearest airport, wherein the index reflects the capability of the airplane to rapidly transfer the distress personnel.

C3. Scheme simulation deduction

And finishing simulation deduction of a disposal scheme based on an amphibious aircraft maritime search and rescue simulation model and a Geographic Information System (GIS), and outputting each evaluation index numerical value.

C4. Evaluation method selection

And selecting a proper evaluation method to empower each evaluation index under the evaluation index system and providing a basis for the comprehensive evaluation of the scheme. The comprehensive evaluation of the disposal scheme is completed by adopting a comprehensive evaluation method combining an analytic hierarchy process and an accumulation ratio evaluation method.

The invention adopts a single-layer structure analytic hierarchy process to determine the index weight, and the specific process is as follows: the judgment matrix is constructed, the consistency of the judgment matrix is checked, the importance of single-layer elements is sequenced, the matrix calculation can be rapidly completed by utilizing MATLAB programming, and the specific operation steps are not described herein because the application of the analytic hierarchy process is quite mature.

C5. Comprehensive evaluation results

And carrying out standardization processing on each index under the index system according to the calculation result of the index value and a comprehensive evaluation method, finally obtaining the comprehensive score of the scheme, and giving an evaluation result of the expected execution effect of the disposal scheme.

The invention utilizes an accumulation ratio evaluation method to carry out standardization processing on index calculation results and give comprehensive scores of the method, and the method comprises the following specific steps:

1) establishing a multi-criteria decision matrix

Assuming m alternatives, n criteria (i.e., indices), the form of the multi-criteria decision matrix is shown as follows:

in the formula, x_ijRepresents the performance value of the ith scheme under the jth criterion, i is 0,. m, j is 1,2,. n; x is the number of_0jThe best performance value under the jth criterion is shown.

It should be noted that if the optimal value under the jth criterion is unknown, if j is a benefit-type criterion:

if j is a cost-type criterion then:

2) normalization of decision matrix

The normalized decision matrix is of the form:

in the formula (I), the compound is shown in the specification,denotes x_ijNormalized values, i ═ 0.. m, j ═ 1, 2.. n, if j is a benefit-type criterion, then

If j is a cost-type criterion, then

3) Calculating a weighted normalized decision matrix

Assume that the jth criterion is weighted by w_jIn the invention, index weight w is calculated by an analytic hierarchy process_jSatisfy 0 < w_jIs < 1, andthe form of the weighted normalized decision matrix is shown as follows:

in the formula (I), the compound is shown in the specification,

4) calculating an optimality function S_iAnd a utility value K_i

The value of the optimality function for the ith scheme can be calculated as follows:

it can be seen that S_iIs calculated from the property value x_ijAnd a weight w_jDecision, optimality function S_iA larger value of (c) indicates that the scheme i is more efficient, and thus can be based on S_iThe value of (c) ranks the priority of alternatives. However, S_iCannot be directly reflected inThe proximity of the solution i to the ideal optimal solution can be to S_iCarrying out normalization processing to obtain utility value K_i. The calculation method can be expressed by the following formula:

K_iis S_iThe value S of the optimality function obtained under the ideal optimal scheme₀Is used to characterize the degree of utility of the alternative. Obviously, K_iValue of (A) falls in [0,1 ]]The required scheme priority can be obtained by arranging the schemes in ascending order, so the value is used as the comprehensive evaluation result of the scheme.

Example 1

The task set by the embodiment is to rescue the fishermen in the 'Zhedai fishing 03520' round off-line with reference to an actual case, and the case is suitable for being executed by an amphibious aircraft as the power of a search and rescue main body in the middle and far sea in the position 130 sea away from the long river mouth. According to the task scenario, fishermen are out of connection after alarming, due to the fact that a ship is seriously inclined and a large amount of water enters, all crews abandon the ship and escape to the life raft, the distress positions are set to be 31.2254 degrees N and 124.9521 degrees E in the simulation system, the distress time is 2020, 9 and 1 days, the target types are the life raft, the number of people in distress is 10, and the four-level sea condition is achieved.

Search and rescue strength selection: the information such as the distress position and the distress number is set by the task, the search and rescue strength can be selected to be deployed on certain amphibious aircrafts at the Shanghai Gaontang airport and the Zhoushan Putuo mountain airport, and the certain amphibious aircrafts are respectively numbered as H001 and H002. The airplane has the economic cruising speed of 460km/h, the maximum cruising speed of 500km/h, the voyage exceeding 4500km, the endurance time of 12h, the maximum takeoff weight of 53500kg and the empty weight (including rescue equipment) of 39779 kg.

The exit and return route is as follows: the geographical positions of the rescue bases, namely the Shanghai Gaontang airport and the Zhoushan Putuo mountain airport are considered, and the sailing and returning paths are respectively set to the Shanghai Gaontang airport → the search area → the Shanghai Gaontang airport and the Zhoushan Putuo mountain airport under the condition that the positions close to the shore base are not close to the waypoints.

Planning a search area: the search area is planned according to the method.

And (3) search and rescue scheme formulation: the amphibious aircraft adopts a parallel line searching mode, and the corresponding searching line interval is 1.2km when the searching speed is 220km/h and 1.3km when the searching speed is 240km/h according to the calculation result of the scanning width and the turning radius.

Index value calculation: at sea level four T₀Is 5 h. Four disposal schemes with different search and rescue forces, search areas and search and rescue schemes are formulated, simulation deduction is carried out respectively, index values are output, and multiple times of simulation averaging can be carried out in consideration of the existence of uncertainty factors. Taking the first scheme as an example, the simulation output index values are as follows: i11 ═ 3256.2kg, I12 ═ 313.8km, I21 ═ 57.2%, I31 ═ 83.5s, I32 ═ 1987.4s, I33 ═ 1.0, I41 ═ 4326.7s, and I42 ═ 2698.9 s.

The index weight results calculated by the analytic hierarchy process are 0.325, 0.099, 0.157, 0.070, 0.108, 0.082, 0.122 and 0.037 in sequence. The comprehensive assessment result of the treatment scheme obtained based on the simulation assessment data and the index weight is 0.94,0.81,0.86 and 0.91, and the scheme is the optimal scheme and is one of four times.

The above embodiments are preferred embodiments of the present invention, but the present invention is not limited to the above embodiments, and any other changes, modifications, substitutions, combinations, and simplifications which do not depart from the spirit and principle of the present invention should be construed as equivalents thereof, and all such changes, modifications, substitutions, combinations, and simplifications are intended to be included in the scope of the present invention.