Reconfigurable ship electronic information system task reliability test sample generation method

Abstract

The invention discloses a reconfigurable ship electronic information system task reliability test sample generation method, and belongs to the technical field of ship electronic information system reliability tests. The invention aims to solve the problem that the credibility of a task reliability evaluation test result adopting an existing digital simulation method is doubted. Comprising the following steps: taking fault occurrence time of each device as a test factor, and determining a value parameter range; calculating the coverage intensity of different value parameters of the test factor based on the fault probability distribution function; then defining a test sample matrix form based on the number of test samples, the selected test factor dimensions and the value parameter ranges of all test factors, and determining all value parameter combinations covering the selected test factors by adopting a myxobacteria optimization algorithm; and in combination with the coverage intensity of different value parameters of each test factor, arranging all the value parameter combinations in the test sample matrix from large to small according to the coverage intensity, determining a final test sample matrix, and obtaining a reliability test sample. The method is used for generating the reliability test sample.

Description

Technical Field

[0001] The invention relates to a method for generating task reliability test samples of a reconfigurable ship electronic information system, and belongs to the technical field of ship electronic information system reliability tests. Background Art

[0002] Ship electronic information system usually refers to a complex electronic information system carried on a surface ship platform that can realize detection and perception, command and control, equipment engagement, combat support and other functions. It is an important part of modern ships and one of the key factors that determine the ship's mission-performing capabilities. Traditional ship electronic information systems generally adopt a design method that divides the secondary subsystems according to their functions, which are divided into front-end perception systems, mid-end command and control systems, and back-end strike systems. However, due to the internal hardware and software coupling of its subsystems, it is relatively closed, which easily leads to problems such as low overall system utilization, insufficient flexibility and scalability. Once a failure occurs, it may cause the entire subsystem to be paralyzed, which seriously restricts the improvement of the ship's mission-performing capabilities. In recent years, with the rapid development of electronic, computer and network technologies, the new reconfigurable ship electronic information system is based on an open system architecture, splits the secondary subsystem into various components, realizes the sharing and integration of all-factor information, provides diversified and high-quality services, greatly improves the ship's mission execution capabilities, and becomes one of the main development directions of future ship electronic information systems.

[0003] The new reconfigurable ship electronic information system has the characteristics of "resource element sharing, software and hardware separation, and dynamic task reconstruction", which makes it difficult to obtain reliable task reliability indicators using traditional reliability assessment methods. The use of digital simulation tests to carry out task reliability assessments faces the problem of doubtful credibility, while the use of physical experiments to carry out task reliability assessments faces the constraints of time, cost, safety and other factors. Semi-physical simulation tests can complete task reliability assessments in a laboratory environment by designing and executing test samples, thereby solving the drawbacks of digital simulation tests and physical tests, and achieving a balance between the credibility of reliability assessment results and factors such as time, cost, and safety.

[0004] At present, there is still a lack of effective test sample generation methods in the field of mission reliability assessment of reconfigurable ship electronic information systems. The test sample generation strategy with full factor coverage faces the problem of sample space explosion and is difficult to apply in actual engineering. Summary of the invention

[0005] In view of the problem that the credibility of the existing mission reliability evaluation test results using digital simulation methods is questionable, the present invention provides a method for generating mission reliability test samples for a reconfigurable ship electronic information system.

[0006] A method for generating task reliability test samples of a reconfigurable ship electronic information system of the present invention comprises:

[0007] The hardware equipment of the reconfigurable ship electronic information system is divided into three components, including perception equipment, basic support equipment and equipment equipment; the failure time of each device in each component unit is used as the test factor, and the value parameter range of each test factor is determined based on the system mission duration cycle;

[0008] Calculate the coverage strength of different parameters of each test factor based on the failure probability distribution function of each device;

[0009] Then, based on the number of test samples, the dimensions of the selected test factors and the range of the value parameters of all test factors, the test sample matrix form is defined, and the slime mold optimization algorithm is used to determine all the value parameter combinations covering the selected test factors; at the same time, combined with the coverage strength of different value parameters of each test factor, all value parameter combinations are arranged in the test sample matrix from large to small according to the coverage strength, and the final test sample matrix is ​​determined, thereby obtaining the reliability test sample.

[0010] According to the method for generating test samples for mission reliability of reconfigurable ship electronic information system of the present invention, the test factor is expressed as x i , where i = 1, 2, 3, ..., I; I is the total number of experimental factors;

[0011] Set the system task duration period to T, divide it into N intervals according to the fixed time Δt, and get N intervals, N = T / Δt; set {1,2,3,…,N} intervals as x i The value parameter range of x i =nΔt, n∈{1,2,3,…,N}.

[0012] According to the method for generating task reliability test samples of reconfigurable ship electronic information system of the present invention, the coverage strength calculation method of different value parameters of each test factor is as follows:

[0013] Failure probability distribution function F of device i i (x i )for:

[0014]

[0015] Where λ i is the failure probability of device i;

[0016] The coverage intensity of different parameters of each test factor is for:

[0017]

[0018] According to the method for generating test samples for mission reliability of reconfigurable ship electronic information system of the present invention, the test sample matrix is ​​defined as L(m, t, I N ), which is a two-dimensional matrix of m×I; m is the number of matrix rows, indicating the number of test samples; t is the dimension of the selected test factor, indicating the dimension of the combination of value parameters of the test samples; I N Represents I experimental factors, each of which has N value parameters.

[0019] According to the method for generating task reliability test samples of a reconfigurable ship electronic information system of the present invention, a method for determining all parameter combinations covering the selected test factors by using a slime mold optimization algorithm is as follows:

[0020] Assume that the t selected experimental factors are where i1,i2,...,i t ∈[1,I], and they are not equal to each other; make L(m,t,I N )cover Corresponding value parameters

[0021] L(m,t,I N ) is represented by all the parameter combinations with different values ​​as Π L :

[0022]

[0023] Combine the calculation results of the coverage intensity of different parameters of each test factor to make L(m,t,I N ) in which the coverage strength of the value parameters in each row from top to bottom is arranged from large to small.

[0024] According to the method for generating samples of mission reliability test of reconfigurable ship electronic information system of the present invention, in the slime mold optimization algorithm, the fitness value of each slime mold individual is composed of the combination Π L The number of elements in the test is determined by the coverage strength of the parameters of each test factor. L If the number of elements in is greater than 0, the coverage strength of the experimental factor value parameter is taken as the adaptation value; if the combination Π L If the number of elements in is 0, the fitness value is 0;

[0025] For the test sample matrix L(m,t,I N ) selects a set number of slime mold individuals for the test samples in each row, performs iterative optimization based on the fitness value, and obtains the final reliability test samples.

[0026] According to the method for generating task reliability test samples of a reconfigurable ship electronic information system of the present invention, the value of Δt is T / 10 or T / 100.

[0027] According to the method for generating samples of mission reliability test of reconfigurable ship electronic information system of the present invention, the sensing equipment includes radio frequency integrated equipment, optical frequency equipment, radar and sonar;

[0028] Basic support equipment includes public computing service equipment, public display and control equipment, access integrated network equipment and core integrated network equipment;

[0029] Equipment includes long-range air defense equipment, short-range air defense equipment, electronic jamming equipment and underwater equipment.

[0030] According to the method for generating task reliability test samples of a reconfigurable ship electronic information system of the present invention, the test factors include the time when a radio frequency integrated device fails, the time when an optical frequency device fails, the time when a radar fails, the time when a sonar fails, the time when a public computing service device fails, the time when a public display and control device fails, the time when an access integrated network device fails, the time when a core integrated network device fails, the time when a long-range air-to-air equipment fails, the time when a short-range air-to-air equipment fails, the time when an electronic jamming equipment fails, and the time when an underwater equipment fails; I=12.

[0031] Beneficial effects of the present invention: The method of the present invention uses the failure occurrence time of various components in the reconfigurable ship electronic information system as the test factor, discretizes the failure occurrence time to obtain the value parameters of the test factor, calculates the coverage strength of each value parameter according to the failure probability distribution function, and finally generates task reliability test samples by combining the coverage idea to cover different strengths of different value parameters of each test factor.

[0032] The method of the present invention can provide a test sample generation strategy for task reliability evaluation based on semi-physical simulation tests, thereby solving the problems of doubtful credibility of digital simulation test results, long time, high cost and poor safety of physical tests. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 It is a schematic diagram of the composition structure of the reconfigurable ship electronic information system of the present invention;

[0034] Figure 2 It is a schematic diagram of the hardware structure of the reconfigurable ship electronic information system of the present invention. DETAILED DESCRIPTION

[0035] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0036] It should be noted that, in the absence of conflict, the embodiments of the present invention and the features in the embodiments may be combined with each other.

[0037] The present invention will be further described below in conjunction with the accompanying drawings and specific embodiments, but they are not intended to limit the present invention.

[0038] Specific implementation method 1. Combination Figure 1 and Figure 2 As shown, the present invention provides a method for generating task reliability test samples of a reconfigurable ship electronic information system, comprising:

[0039] The hardware equipment of the reconfigurable ship electronic information system is divided into three components, including perception equipment, basic support equipment and equipment equipment; the failure time of each device in each component unit is used as the test factor, and the value parameter range of each test factor is determined based on the system mission duration cycle;

[0040] Calculate the coverage strength of different parameters of each test factor based on the failure probability distribution function of each device;

[0041] Then, based on the number of test samples, the dimensions of the selected test factors and the range of the value parameters of all test factors, the test sample matrix form is defined, and the slime mold optimization algorithm is used to determine all the value parameter combinations covering the selected test factors; at the same time, combined with the coverage strength of different value parameters of each test factor, all value parameter combinations are arranged in the test sample matrix from large to small according to the coverage strength, and the final test sample matrix is ​​determined, thereby obtaining the reliability test sample.

[0042] In this embodiment, the secondary subsystem structure of the reconfigurable ship electronic information system is divided into hardware units and software units. The software units include command and control software, such as Figure 1 shown.

[0043] Further, the experimental factor is represented as x i , where i = 1, 2, 3, ..., I; I is the total number of experimental factors;

[0044] Set the system task duration period to T, divide it into N intervals according to the fixed time Δt, and get N intervals, N = T / Δt; set {1,2,3,…,N} intervals as x i The value parameter range of x i =nΔt, n∈{1,2,3,…,N}.

[0045] In this implementation, the calculation method of the coverage intensity of different value parameters of each test factor is:

[0046] Most hardware units in the reconfigurable ship electronic information system are electronic devices. When they fail, the failure probability density function generally obeys an exponential distribution. The failure probability density f of device i is i (x i ) is expressed as:

[0047]

[0048] Failure probability distribution function F of device i i (x i )for:

[0049]

[0050] Where λ i is the failure probability of device i;

[0051] The coverage intensity of different parameters of each test factor is for:

[0052]

[0053] As shown in Table 2, there are 12 test factors for the mission reliability of the reconfigurable ship electronic information system, which are denoted as x1, x2, ..., x 12 , the value parameters of each experimental factor are {1,2,3,...,N}, and the experimental factor x i The coverage strength of the parameter n∈{1,2,3,...,N} is p xi (n). Define the experimental sample matrix as L(m,t,I N ), which is an m×I two-dimensional matrix; m is the number of matrix rows, indicating the number of test samples, I columns correspond to I test factors, and a value of the test factor is placed in the intersection of each row and column; t is the selected test factor dimension, indicating the combination coverage dimension of the test sample value parameters, that is, any t test factors satisfy the N×N full factor coverage; I N Represents I experimental factors, each of which has N value parameters.

[0054] This embodiment proposes a combination coverage generation method for reliability test samples of reconfigurable ship electronic information systems based on a slime mold optimization algorithm. The slime mold optimization algorithm is inspired by the foraging behavior of slime molds. The algorithm simulates the various behaviors and morphological changes of slime molds in the process of searching for food (searching for targets). During the foraging process, slime molds will approach the food source through the smell in the air (optimization process) to form a venous network of varying thicknesses. The thickness of the venous network is related to the quality of the food source. When the slime mold approaches the food, it will oscillate and shrink. This behavior is used to simulate the search and update process in the optimization algorithm. The slime mold optimization algorithm has fast convergence speed, strong optimization ability, and global and local search capabilities. In view of this, this embodiment uses the slime mold optimization algorithm to generate test samples L(m, t, 12 N ). Each slime mold position represents a solution (a row in the test sample), and the solution with the largest fitness value represents the location of the food. All solutions are found by using the slime mold's process of finding food.

[0055] Furthermore, the method of using the slime mold optimization algorithm to determine all parameter combinations covering the selected test factors is as follows:

[0056] Assume that the t selected experimental factors are where i1,i2,...,i t ∈[1,I], and they are not equal to each other; Any set of value parameters It must be possible to N ) is found in a row, that is, L(m,t,12 N ) Override value parameters Therefore, L(m,t,12 N ) must satisfy the condition that all possible combinations of values ​​of any t experimental factors are covered, L(m, t, I N ) is represented by all the parameter combinations with different values ​​as Π L :

[0057]

[0058] Combine the calculation results of the coverage intensity of different parameters of each test factor to make L(m,t,I N ) in which the coverage strength of the value parameters in each row from top to bottom is arranged from large to small.

[0059] In this embodiment, L(m,t,12 N ) covers all the parameter combinations, generating L(m,t,12 N ) is to find Π L The process of calculating all the elements in L(m,t,12 N ) In addition to covering Π LIn addition to all the elements in the above formula, it is also necessary to generate the coverage strength of the value parameters of each test factor from large to small to ensure that L(m,t,12 N ) The coverage strength of the value parameters in the upper row is the greatest.

[0060] In the slime mold optimization algorithm, for each individual, coverage Π L The number of elements in and the coverage strength of each experimental factor parameter will determine the size of the fitness value, that is, the fitness value of each slime mold individual is determined by the combination Π L The number of elements in the matrix is ​​determined by the coverage strength of the parameters of each test factor. In order to ensure the priority coverage of the test factors, if the combination Π L If the number of elements in is greater than 0, the coverage strength of the experimental factor value parameter is taken as the adaptation value; if the combination Π L If the number of elements in is 0, the fitness value is 0;

[0061] For the test sample matrix L(m,t,I N ) selects a set number of slime mold individuals for the test samples in each row, performs iterative optimization based on the fitness value, and obtains the final reliability test samples.

[0062] As an example, Δt takes a value of T / 10 or T / 100.

[0063] The perception devices include radio frequency integrated devices, optical frequency devices, radars and sonars, etc.; different from the front-end perception system in the secondary subsystem of the traditional ship electronic information system, the reconfigurable ship electronic information system separates most of the information processing functions of the front-end perception system, such as point generation and target recognition, into the command and control software, which relies on the public resource hardware in the basic support equipment to complete the information processing.

[0064] Basic support equipment includes public computing service equipment, public display and control equipment, access integrated network equipment and core integrated network equipment; among them, integrated network equipment, public computing service equipment and public display and control equipment are public resource hardware of reconfigurable ship electronic information system, which mainly provide network, computing, display and control and other resource support for the operation of command and control software. Command and control software is dynamically deployed on public resource hardware to realize software functions.

[0065] Command and control software includes point trace generation software, target recognition software, track generation software, situation display software, etc. The completion of the ship's electronic information system tasks depends on the normal operation of the command and control software functions, and the normal operation of the command and control software functions depends on the working performance and equipment integrity of the public resource hardware in the basic support equipment.

[0066] Equipment equipment includes multi-channel equipment such as long-range air defense equipment, short-range air defense equipment, electronic jamming equipment, and underwater equipment. Different from the back-end equipment system in the secondary subsystem of the traditional ship electronic information system, the reconfigurable ship electronic information system separates most of the information processing functions of the back-end equipment system, such as equipment allocation, target command, etc., into the command software, which relies on the public resource hardware in the basic support equipment to complete the information processing.

[0067] Integrated network equipment, public computing service equipment, and public display and control equipment are public resource hardware of the ship's electronic information system, which mainly provide network, computing, display and control and other resource support for the operation of the ship's electronic information system command and control software. The public resource hardware of the ship's electronic information system has redundant backup.

[0068] The common resource hardware and its numbering of the reconfigurable ship electronic information system are shown in Table 1.

[0069] Table 1 Common resource hardware and serial numbers of ship electronic information systems

[0070] Public resource hardware Main device number Backup device number Public computing service equipment 1、2、3、4 5、6、7、8 Public display and control equipment 1 2 Access integrated network equipment 1、2 3、4 Core integrated network equipment 1 2

[0071] Figure 2 The figure shows the hardware structure of the reconfigurable ship electronic information system. The redundant backup mechanism of the common resource hardware is the key to enable the reconfigurable ship electronic information system to complete its mission after a fatal failure. Figure 2 In the figure, the solid-line box represents the main device, and the dotted-line box represents the backup device. Under normal circumstances, when the ship's electronic information system performs a task, only the main device of the common resource hardware works, and the backup device does not work. The command and control software is deployed on the main device of the common resource hardware to complete its function. However, when the main device fails, the hardware failure will affect the normal operation of the command and control software functions deployed on it, thereby interfering with the task execution capability of the entire system. At this time, the reconfigurable ship electronic information system will perform redundant reconstruction behavior, and through redundant switching, the backup device of the common resource hardware will replace the original device to complete the work, so that the command and control software can resume normal working state and ensure the normal execution of the task.

[0072] Since ship electronic information systems usually undergo rigorous software evaluation before delivery, it is generally believed that the command and control software itself has no defects. Since public resource hardware is the resource support for software, and the software is deployed on public resource hardware, when the public resource hardware fails, the failure will spread to the command and control software deployed on it. Under the effect of the propagation of this failure, the command and control software will change from a normal working state to a faulty state, affecting the processing and transmission of information in the command and control software, thereby affecting the normal execution of the ship electronic information system mission.

[0073] From the above analysis, we can see that the factors affecting the mission reliability of the reconfigurable ship electronic information system include hardware failure and software failure. Hardware failure is a spontaneous failure, and its probability of occurrence is related to the running time, which is an independent variable; while software failure is caused by the failure of the deployed hardware, which is a dependent variable. Therefore, the hardware failure occurrence time is selected as the test factor of the mission reliability of the reconfigurable ship electronic information system.

[0074] The test factors include the failure time of radio frequency integrated equipment, optical frequency equipment, radar, sonar, public computing service equipment, public display and control equipment, access integrated network equipment, core integrated network equipment, air defense long-range equipment, air defense short-range equipment, electronic jamming equipment, and underwater equipment; I = 12. See Table 2 for details:

[0075] Table 2 Mission reliability test factors and their value parameters for reconfigurable ship electronic information system

[0076] <![CDATA[Test factor x i > Value parameter n RF integrated device failure occurrence time 1,2,3,…,N Optical frequency equipment failure time 1,2,3,…,N Radar failure time 1,2,3,…,N Sonar failure time 1,2,3,…,N Public computing service equipment 1-8 fault occurrence time 1,2,3,…,N Public display and control equipment 1-2 fault occurrence time 1,2,3,…,N Access integrated network device 1-4 fault occurrence time 1,2,3,…,N Core integrated network device 1-2 fault occurrence time 1,2,3,…,N Time when the air defense remote equipment failure occurs 1,2,3,…,N Time when short-range air defense equipment failure occurs 1,2,3,…,N Time when electronic jamming equipment failure occurs 1,2,3,…,N Time when underwater equipment failure occurs 1,2,3,…,N

[0077] Going further, the method to determine the final test sample matrix is:

[0078] Step 1: Initialize the combination Π L , set the test sample matrix L(m,t,I N ) The initial number of slime mold individuals corresponding to each row of test samples is M = 50; the positions Y of 50 slime mold individuals are initialized d ,d=1,2,...,M, the position of the slime mold individual Y d is a vector of length 12, Y d The value of each element in is randomly selected from Select; Initialize the number of iterations K = 500 and the current number of iterations k = 1;

[0079] Step 2: If k≤K, go to step 3; otherwise go to step 7;

[0080] Step 3: Check Y d Whether each element in exceeds the value parameter range of the test factor; if it exceeds, randomly select a value in the value parameter range {1,2,3,…,N} to replace the corresponding element, so that Y d All elements in are within the value parameter range of the test factor;

[0081] Step 4: Calculate Y d The fitness values ​​of , and sort them from large to small according to the fitness values, and get the sorted Y d ;

[0082] Step 5: Generate a random number Rand in [0,1], and sort Y according to the size of the random number Rand. d To update:

[0083] Y d (k+1)=Randγ(N-1)+1, Rand<z,

[0084]

[0085] Where Y b (k) represents the position of the slime mold individual with the best current fitness value, Y A (k) and Y B (k) represents the positions of two random slime mold individuals, A, B = 1, 2, ..., M; v b It oscillates in the range of [-a, a] and eventually tends to 0. W represents the weight coefficient of the slime mold individual, r represents a random number between [0, 1], p represents the control parameter, and v c is a random number, v c ∈[-1,1], z=0.06;

[0086]

[0087] p = tanh|S(d)-DF|,

[0088] Where S(d) represents the fitness value of the dth slime mold individual, and DF represents the optimal fitness value obtained in the completed k iterations;

[0089]

[0090] Where SmellIndex(d) represents the sorted Y d , r1 represents a random number between [0,1], represents the slime mold individuals in the top half of S(d), bF represents the best fitness value obtained in the current k-th iteration, and ωF represents the worst fitness value obtained in the current k-th iteration;

[0091] Step 6: Set k=k+1 and return to step 2;

[0092] Step 7: Output the position of the slime mold individual with the largest fitness value to L(m,t,12 N ), the value parameter combination of the t experimental factors covered is changed from Π L Remove;

[0093] Step 8: If Π L=Φ, the iteration ends; then combine the coverage strength of different value parameters of each test factor, arrange all value parameter combinations in the test sample matrix from large to small according to the coverage strength, and output the current L(m, t, 12 N ) as the final test sample matrix; otherwise, set k = 1 and return to step 2 to continue iterating until the end.

[0094] Although the present invention is described herein with reference to specific embodiments, it should be understood that these embodiments are merely examples of the principles and applications of the present invention. It should therefore be understood that many modifications may be made to the exemplary embodiments and that other arrangements may be devised without departing from the spirit and scope of the present invention as defined by the appended claims. It should be understood that the various dependent claims and features described herein may be combined in a manner different from that described in the original claims. It should also be understood that the features described in conjunction with a single embodiment may be used in other described embodiments.

Claims

1. A method for generating task reliability test samples for a reconfigurable ship electronic information system, characterized in that: include: The hardware equipment of the reconfigurable ship electronic information system is divided into three components, including perception equipment, basic support equipment and equipment equipment; The failure occurrence time of each device in each component unit is used as the test factor, and the value parameter range of each test factor is determined based on the system task duration cycle; Calculate the coverage strength of different parameters of each test factor based on the failure probability distribution function of each device; Then, based on the number of test samples, the dimensions of the selected test factors and the range of the value parameters of all test factors, the test sample matrix form is defined, and the slime mold optimization algorithm is used to determine all the value parameter combinations covering the selected test factors; at the same time, combined with the coverage strength of different value parameters of each test factor, all value parameter combinations are arranged in the test sample matrix from large to small according to the coverage strength, and the final test sample matrix is ​​determined, thereby obtaining the reliability test sample.

2. The method for generating task reliability test samples of a reconfigurable ship electronic information system according to claim 1 is characterized in that: Let the experimental factor be x i , where i = 1, 2, 3, ..., I; I is the total number of experimental factors; Set the system task duration period to T, divide it into N intervals according to the fixed time Δt, and get N intervals, N = T / Δt; set {1,2,3,…,N} intervals as x i The value parameter range of x i =nΔt, n∈{1,2,3,…,N}.

3. The method for generating task reliability test samples of a reconfigurable ship electronic information system according to claim 2 is characterized in that: The calculation method of coverage intensity of different parameters of each test factor is: Failure probability distribution function F of device i i (x i )for: Where λ i is the failure probability of device i; The coverage intensity of different parameters of each test factor is for:

4. The method for generating task reliability test samples of a reconfigurable ship electronic information system according to claim 3 is characterized in that: Define the test sample matrix as L(m,t,I N ), which is a two-dimensional matrix of m×I; m is the number of matrix rows, indicating the number of test samples; t is the dimension of the selected test factor, indicating the dimension of the combination of value parameters of the test samples; I N Represents I experimental factors, each of which has N value parameters.

5. The method for generating task reliability test samples of a reconfigurable ship electronic information system according to claim 4 is characterized in that: The method of using the slime mold optimization algorithm to determine all parameter combinations covering the selected test factors is as follows: Assume that the t selected experimental factors are where i1,i2,...,i t ∈[1,I], and they are not equal to each other; make L(m,t,I N )cover Corresponding value parameters L(m,t,I N ) is represented by all the parameter combinations with different values ​​as Π L : Combine the calculation results of the coverage intensity of different parameters of each test factor to make L(m,t,I N ) in which the coverage strength of the value parameters in each row from top to bottom is arranged from large to small.

6. The method for generating task reliability test samples of a reconfigurable ship electronic information system according to claim 5 is characterized in that: In the slime mold optimization algorithm, the fitness value of each slime mold individual is determined by the combination Π L The number of elements in the test is determined by the coverage strength of the parameters of each test factor. L If the number of elements in is greater than 0, the coverage strength of the experimental factor value parameter is taken as the adaptation value; if the combination Π L If the number of elements in is 0, the fitness value is 0; For the test sample matrix L(m,t,I N ) selects a set number of slime mold individuals for the test samples in each row, performs iterative optimization based on the fitness value, and obtains the final reliability test samples.

7. The method for generating task reliability test samples of a reconfigurable ship electronic information system according to claim 6 is characterized in that: The value of Δt is T / 10 or T / 100.

8. The method for generating task reliability test samples of a reconfigurable ship electronic information system according to claim 7 is characterized in that: The sensing devices include radio frequency integrated devices, optical frequency devices, radars and sonars; Basic support equipment includes public computing service equipment, public display and control equipment, access integrated network equipment and core integrated network equipment; Equipment includes long-range air defense equipment, short-range air defense equipment, electronic jamming equipment and underwater equipment.

9. The method for generating task reliability test samples of a reconfigurable ship electronic information system according to claim 8, characterized in that: The test factors include the failure time of radio frequency integrated equipment, optical frequency equipment, radar, sonar, public computing service equipment, public display and control equipment, access integrated network equipment, core integrated network equipment, long-range air defense equipment, short-range air defense equipment, electronic jamming equipment and underwater equipment. I＝12。 10. The method for generating task reliability test samples of a reconfigurable ship electronic information system according to claim 9, characterized in that: The method to determine the final test sample matrix is: Step 1: Initialize the combination Π L , set the test sample matrix L(m,t,I N ) The initial number of slime mold individuals corresponding to each row of test samples is M = 50; the positions Y of 50 slime mold individuals are initialized d ,d=1,2,...,M, the position of the slime mold individual Y d is a vector of length 12, Y d The value of each element in is randomly selected from Select; Initialize the number of iterations K = 500 and the current number of iterations k = 1; Step 2: If k≤K, go to step 3; Otherwise, proceed to step 7; Step 3: Check Y d Whether each element in exceeds the value parameter range of the test factor; if it exceeds, randomly select a value in the value parameter range {1,2,3,…,N} to replace the corresponding element, so that Y d All elements in are within the value parameter range of the test factor; Step 4: Calculate Y d The fitness values ​​of , and sort them from large to small according to the fitness values, and get the sorted Y d ; Step 5: Generate a random number Rand in [0,1], and sort Y according to the size of the random number Rand. d To update: Y d (k+1)=Randγ(N-1)+1,Rand<z, Where Y b (k) represents the position of the slime mold individual with the best current fitness value, Y A (k) and Y B (k) represents the positions of two random slime mold individuals, A, B = 1, 2, ..., M; v b It oscillates in the range of [-a, a] and eventually tends to 0. W represents the weight coefficient of the slime mold individual, r represents a random number between [0, 1], p represents the control parameter, and v c is a random number, v c ∈[-1,1], z=0.06; p = tanh|S(d)-DF|, Where S(d) represents the fitness value of the dth slime mold individual, and DF represents the optimal fitness value obtained in the completed k iterations; Where SmellIndex(d) represents the sorted Y d , r1 represents a random number between [0,1], bF represents the best fitness value obtained in the current k-th iteration, and ωF represents the worst fitness value obtained in the current k-th iteration; Step 6: Set k=k+1 and return to step 2; Step 7: Output the position of the slime mold individual with the largest fitness value to L(m,t,12 N ), the value parameter combination of the t experimental factors covered is changed from Π L Remove; Step 8: If Π L =Φ, the iteration ends; then combine the coverage strength of different value parameters of each test factor, arrange all value parameter combinations in the test sample matrix from large to small according to the coverage strength, and output the current L(m, t, 12 N ) as the final test sample matrix; otherwise, set k = 1 and return to step 2 to continue iterating until the end.

Images