Aircraft parallel collaborative test method, device and equipment and storage medium

Abstract

The invention discloses an aircraft parallel collaborative test method, device and equipment and a storage medium, and the method comprises the steps: decomposing a total test process of a single aircraft, and obtaining a plurality of test items of the single aircraft; sorting the plurality of test items on the basis of the association and dependency relationship among the test items, and sorting the test items of the plurality of aircrafts in sequence on the basis of a sorting result to obtain a double-code network diagram of the plurality of aircrafts; based on the double-code network diagram, identifying a test item link with longest time consumption when a plurality of aircrafts are tested at the same time, so as to generate a critical path; and based on the established test process optimization model, optimizing all test items on the critical path by taking test time and test resources as optimization targets, and outputting an optimal parallel test scheme of the plurality of aircrafts. The aircraft test launching efficiency and the resource utilization rate can be effectively improved, the preparation time is shortened, and it is ensured that the test process is completed on time with high quality.

Description

Technical Field

[0001] The present invention relates to the technical field of aircraft collaborative testing, and in particular to an aircraft parallel collaborative testing method, apparatus, equipment and storage medium. Background Art

[0002] With the explosive development of aerospace technology and the rapid advancement of commercial aerospace power, the scale, efficiency and style of space launches are constantly being refreshed. The traditional launch frequency has gradually changed from monthly to weekly, daily and even hourly. Space launches will gradually develop in the direction of large-scale and high-frequency.

[0003] When carrying out a launch mission for a carrier spacecraft, in order to ensure that each spacecraft is functioning normally, performing well, and in the correct technical condition before launch, and can be launched safely and on time, it is necessary to conduct comprehensive and integrated tests at the launch site to verify the coordination and matching of the satellite, carrier spacecraft, and launch site systems.

[0004] When implementing missions such as large-scale cluster launches of spacecraft, it's not just about testing a single vehicle. Given limited launch site testing resources and tight launch schedules, it's also necessary to consider collaborative testing across multiple launch vehicles. To improve testing efficiency and resource utilization, it's crucial to rationally schedule the test and launch process, comprehensively consider the order in which test resources are allocated, fully utilize resources, shorten technical preparation time, and ensure the testing process is completed on time and with high quality, meeting launch mission requirements. Currently, the scheduling of spacecraft testing processes is still manual, which is inefficient and unable to meet the demands of collaborative testing.

[0005] Therefore, under the condition of limited resources, how to effectively improve the efficiency of large-scale launch tests and resource utilization of spacecraft, shorten the technical preparation time, and ensure that the test process is completed on time and with high quality is a technical problem that needs to be solved urgently. Summary of the Invention

[0006] The main purpose of the present invention is to provide a method, device, equipment and storage medium for parallel collaborative testing of aircraft, which can effectively improve the efficiency and resource utilization of large-scale aircraft testing launches, shorten technical preparation time, and ensure that the testing process is completed on time and with high quality.

[0007] In a first aspect, the present application provides a method for parallel collaborative testing of aircraft, wherein the method comprises the steps of: Decompose the overall test process of a single aircraft to obtain multiple test items for the single aircraft; Sorting the plurality of test items based on associations and dependencies between the test items, and sequentially sorting the test items of the plurality of aircraft based on the sorting results to obtain dual-code network diagrams of the plurality of aircraft; Based on the dual-code network diagram, identifying the test item link that takes the longest time when multiple aircraft are tested simultaneously to generate a critical path; Based on the established test process optimization model, all test items on the critical path are optimized with test time and test resources as optimization targets, and the optimal parallel test plan for multiple aircraft is output.

[0008] In combination with the first aspect above, as an optional implementation method, a test process optimization model is established; Applying a genetic algorithm to the optimization model, with all test items on the target path as optimization objects, the test start time, test end time, and required resources of the test items as optimization variables, the test resources and test cycle as constraints, and the total test time and test resources as optimization targets, searching for the optimal solution by simulating gene inheritance, mutation, and selection, and calculating the fitness function value of the critical path by providing benefits or penalties to the test items on the critical path; Based on the calculated fitness function value, the maximum fitness function value is used as the optimal multi-aircraft parallel test process solution, and an optimal test plan network diagram is generated.

[0009] In combination with the first aspect above, as an optional implementation, according to the formula:

[0010]

[0011]

[0012]

[0013]

[0014] Calculate the fitness function value of the critical path, where are the time benefit coefficient and resource constraint benefit coefficient respectively. 、 are the penalty coefficients, 、 are the time benefit and resource constraint benefit of completing the j-th test of the i-th aircraft, is the total critical path duration, For the required test cycle, is the total amount of test resources, For resource constraints, For test items, is the aircraft serial number, is the test item number, is the process name, The test start time, The test end time, For pre-test projects, This is a post-test item.

[0015] In conjunction with the first aspect above, as an optional implementation, it is determined whether the constraints of each test item are met, wherein the constraints include: whether the test time exceeds the test cycle and whether the test resources exceed the total resource quantity; If satisfied, output the optimal result; If not, continue to adjust the time consumption and test resources of the test items of multiple aircraft to optimize the multi-aircraft parallel testing process plan.

[0016] In combination with the first aspect above, as an optional implementation method, checking whether the required test resources exceed the total amount of set resources; If it does not exceed, the optimal multi-aircraft parallel testing process plan is output; if it does not meet the requirements, the number of test resources is increased.

[0017] In combination with the first aspect above, as an optional implementation method, the association and dependency relationship between the test items is analyzed to determine the pre- and post- logical relationship between the test items; Based on the preceding and following logical relationships of the test items, an execution order of the test items is determined to sort the multiple test items.

[0018] In conjunction with the first aspect above, as an optional implementation, the start time and end time of each aircraft test item are determined through the dual-code network diagram; Based on the start time and the end time, sequentially determine the longest test item for each aircraft; Connect the test items that take the longest time to generate the critical path.

[0019] In a second aspect, the present application provides an aircraft parallel collaborative testing device, the device comprising: A decomposition module is used to decompose the overall test process of a single aircraft to obtain multiple test items of the single aircraft; a sorting module, configured to sort the plurality of test items based on associations and dependencies between the test items, and to sequentially sort the test items of the plurality of aircraft based on the sorting results to obtain a dual-code network diagram of the plurality of aircraft; A generation module, configured to identify, based on the dual-code network diagram, a test item link that consumes the longest time when multiple aircraft are tested simultaneously, so as to generate a critical path; The processing module is used to optimize all test items on the critical path based on the established test process optimization model, taking test time and test resources as optimization targets, and output an optimal parallel test plan for multiple aircraft.

[0020] In a third aspect, the present application further provides an electronic device comprising: a processor; and a memory, wherein the memory stores computer-readable instructions, and when the computer-readable instructions are executed by the processor, the method described in any one of the first aspects is implemented.

[0021] In a fourth aspect, the present application further provides a computer-readable storage medium storing computer program instructions, which, when executed by a computer, enables the computer to execute any one of the methods described in the first aspect.

[0022] The present application provides a method, apparatus, device and storage medium for parallel collaborative testing of aircraft, wherein the method includes the following steps: decomposing the overall test process of a single aircraft to obtain multiple test items for the single aircraft; sorting the multiple test items based on the association and dependency relationship between the test items, and sorting the test items of multiple aircraft in turn based on the sorting results to obtain a dual-code network diagram of the multiple aircraft; based on the dual-code network diagram, identifying the test item link that takes the longest time when multiple aircraft are tested simultaneously to generate a critical path; based on the established test process optimization model, optimizing all test items on the critical path with test time and test resources as optimization targets, and outputting the optimal parallel testing plan for multiple aircraft. The present application can effectively improve the efficiency and resource utilization of large-scale aircraft test launches, shorten technical preparation time, and ensure that the test process is completed on time and with high quality.

[0023] It should be understood that the foregoing general description and the following detailed description are exemplary only and are not restrictive of the invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention.

[0025] Figure 1 This is a flow chart of a parallel collaborative testing method for aircraft provided in an embodiment of the present application; Figure 2 This is a schematic diagram of an aircraft parallel collaborative testing device provided in an embodiment of the present application; Figure 3 The parallel collaborative test scheduling process provided in the embodiment of this application; Figure 4 The parallel collaborative test optimization algorithm process provided in the embodiments of this application; Figure 5 A schematic diagram of an electronic device provided in an embodiment of the present application; Figure 6 A schematic diagram of a computer-readable program medium provided in an embodiment of the present application. DETAILED DESCRIPTION

[0026] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. In the following description, when referring to the drawings, like numbers in different figures represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments are not intended to represent all possible embodiments consistent with the present invention. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present invention, as detailed in the appended claims.

[0027] Furthermore, the drawings are merely schematic illustrations of the present disclosure and are not necessarily drawn to scale. Some of the blocks shown in the drawings are functional entities that do not necessarily correspond to physically or logically separate entities.

[0028] The embodiments of the present application are further described in detail below with reference to the accompanying drawings.

[0029] Reference Figure 1 , Figure 1 The figure shows a flow chart of a parallel collaborative testing method for aircraft provided by the present invention. Figure 1 As shown, the method includes the steps of: Step S101: Decompose the overall test process of a single aircraft to obtain multiple test items for the single aircraft.

[0030] Specifically, the entire process of testing the launch vehicle from state recovery to loading onto the vehicle is sorted out (the vehicle testing process covers all test items from vehicle storage to transfer to the launch room, specifically including vehicle assembly, subsystem testing (including electrical system testing, structural system testing, power system testing), general inspection testing, satellite-rocket docking, loading the vehicle onto the launch vehicle, and transporting it to the launch site), and each task is broken down into specific executable test items. For example For the The first aircraft For example, A11 represents the first test item of the first aircraft, A12 represents the second test item of the first aircraft, and A21 represents the first test item of the second aircraft.

[0031] Test items Defined as: = ( N, , , , , R), where is the aircraft serial number, is the test item number, N is the process name, The test start time, The test end time, For pre-test projects, is the post-test item, and R is the resource constraint.

[0032] Analyze the relationships and dependencies between test items, and clarify the logical relationships between each test item. Based on the actual test process, sort out the detailed resource requirements of each test item, including cranes, lifting equipment, workstations, etc.; and calculate the specific time required for each test item based on the actual test time.

[0033] Step S102: sorting the plurality of test items based on the association and dependency relationship between the test items, and sorting the test items of the plurality of aircraft in turn based on the sorting result to obtain a dual-code network diagram of the plurality of aircraft.

[0034] Specifically, the single-launch vehicle test items are first sequenced (analyzing the associations and dependencies between test items to determine the logical relationships between pre- and post-order items; based on these pre- and post-order relationships, the execution order of each test item is determined to sort the multiple test items). The complete test process is then organized, and the execution order of each test item is determined based on the pre- and post-order logical relationships. Finally, using the test item sequence for a single vehicle as a benchmark, the test item sequence for multiple launch vehicles is sequentially determined, resulting in a test item network diagram for the multiple-launch vehicle, known as a dual-code network diagram.

[0035] Generally, three scheduling methods can be considered, mainly including: forward scheduling, backward scheduling (the arrangement of project activities starts from the final completion date of the project, and works backward to determine the start and end dates of each activity) and hybrid scheduling (combines the characteristics of forward scheduling and backward scheduling. Hybrid scheduling aims to take advantage of the advantages of both methods to adapt to the specific needs and environmental conditions of the project). Among them, forward scheduling refers to scheduling as closely as possible according to the planned process sequence; backward scheduling refers to scheduling as closely as possible according to the planned process sequence; hybrid scheduling refers to the comprehensive use of forward and backward scheduling to reasonably arrange the project testing process. Taking forward scheduling as an example, it is to arrange activities as closely as possible after their predecessor activities according to the process sequence in the project plan. Forward scheduling takes into account the dependency relationship between activities, that is, an activity must be started after the completion of another activity. This dependency relationship is called a "predecessor relationship."

[0036] Step S103: Based on the dual-code network diagram, identify the test item link that takes the longest time when multiple aircraft are tested simultaneously to generate a critical path.

[0037] Specifically, the dual-code network diagram is used to determine the start and end times of each aircraft test item. Based on these start and end times, the longest test item for each aircraft is sequentially determined. These sequentially determined longest test items are then connected to generate a critical path. For example, A11, A12, A13, A21, A22, A23, A31, A32, A33, and these aircraft test items can form multiple routes. The most time-consuming route is then identified, such as A11 to A23 to A32. This path takes the longest time and is therefore the critical path.

[0038] To facilitate understanding of the specific instructions, based on the multi-vehicle test ranking results, identify the test item within the test flow that has the greatest impact on the overall process time. Calculate the earliest start time and latest completion time for this task, and find the longest-consuming task sequence in the entire test process that determines the overall test time, i.e., the critical path (dual-code network diagram).

[0039] Step S104: Based on the established test process optimization model, all test items on the critical path are optimized with test time and test resources as optimization targets, and an optimal parallel test plan for multiple aircraft is output.

[0040] Establish a test process optimization model; Applying a genetic algorithm to the optimization model, with all test items on the target path as optimization objects, the test start time, test end time, and required resources of the test items as optimization variables, the test resources and test cycle as constraints, and the total test time and test resources as optimization targets, searching for the optimal solution by simulating gene inheritance, mutation, and selection, and calculating the fitness function value of the critical path by providing benefits or penalties to the test items on the critical path; Based on the calculated fitness function value, the maximum fitness function value is used as the optimal multi-aircraft parallel test process solution, and an optimal test plan network diagram is generated.

[0041] According to the formula:

[0042]

[0043]

[0044]

[0045]

[0046] Calculate the fitness function value of the critical path, where are the time benefit coefficient and resource constraint benefit coefficient respectively. 、 are the penalty coefficients, 、 are the time benefit and resource constraint benefit of completing the j-th test of the i-th aircraft, is the total critical path duration, For the required test cycle, is the total amount of test resources, For resource constraints, For test items, is the aircraft serial number, is the test item number, is the process name, The test start time, The test end time, For pre-test projects, This is a post-test item.

[0047] To facilitate understanding of the specific instructions, the multi-aircraft parallel test process is parameterized, a test process optimization model is established, and the genetic algorithm is applied to the optimization process of the entire process. After determining the critical path, all test items on the critical path are optimized, and the test start time, test end time, and required resources of the test item Aij are used as optimization variables. The test resources and test cycle are used as constraints. The total test time and test resources are used as optimization goals. The optimal solution is searched by simulating gene inheritance, mutation, and selection, and finally the optimal multi-aircraft parallel test process arrangement is given, that is, the time for each test of each aircraft is determined, and then the parallel test plan for multiple aircraft is determined.

[0048] The global total benefit of multi-vehicle parallel testing is The total benefit score is determined by different test times and different resource consumptions. The benefit coefficient is used to adjust the score results with inconsistent time and resource benefit dimensions. The penalty coefficient is used to punish the test process that exceeds the constraint range. The fitness function of the genetic algorithm is defined as

[0049] Reference Figure 2 , Figure 2 FIG. 1 is a schematic diagram of an aircraft parallel collaborative testing device provided by the present invention, as shown in FIG. Figure 2 As shown, the device includes: Decomposition module 201: It is used to decompose the overall test process of a single aircraft to obtain multiple test items of the single aircraft.

[0050] Sorting module 202: It is used to sort the multiple test items based on the association and dependency relationship between the test items, and based on the sorting results, sort the test items of multiple aircraft in turn to obtain dual-code network diagrams of the multiple aircraft.

[0051] The generating module 203 is used to identify the test item link that takes the longest time when multiple aircraft are tested simultaneously based on the dual-code network diagram, so as to generate a critical path.

[0052] The processing module 204 is configured to optimize all test items on the critical path based on the established test process optimization model, taking test time and test resources as optimization targets, and output an optimal parallel test plan for multiple aircraft.

[0053] Furthermore, in a possible implementation, the processing module is further configured to establish a test process optimization model; Applying a genetic algorithm to the optimization model, with all test items on the target path as optimization objects, the test start time, test end time, and required resources of the test items as optimization variables, the test resources and test cycle as constraints, and the total test time and test resources as optimization targets, searching for the optimal solution by simulating gene inheritance, mutation, and selection, and calculating the fitness function value of the critical path by providing benefits or penalties to the test items on the critical path; Based on the calculated fitness function value, the maximum fitness function value is used as the optimal multi-aircraft parallel test process solution, and an optimal test plan network diagram is generated.

[0054] Furthermore, in a possible implementation manner, the processing module is further configured to calculate the output signal according to the formula:

[0055]

[0056]

[0057]

[0058]

[0059] Calculate the fitness function value of the critical path, where are the time benefit coefficient and resource constraint benefit coefficient respectively. 、 are the penalty coefficients, 、 are the time benefit and resource constraint benefit of completing the j-th test of the i-th aircraft, is the total critical path duration, For the required test cycle, is the total amount of test resources, For resource constraints, For test items, is the aircraft serial number, is the test item number, is the process name, The test start time, The test end time, For pre-test projects, This is a post-test item.

[0060] Furthermore, in a possible implementation, the processing module is further configured to determine whether the constraints of each test item are satisfied, wherein the constraints include: whether the test time exceeds the test cycle and whether the test resources exceed the total resource quantity; If satisfied, output the optimal result; If not, continue to adjust the time consumption and test resources of the test items of multiple aircraft to optimize the multi-aircraft parallel testing process plan.

[0061] Furthermore, in a possible implementation, the processing module is further configured to check whether the required test resources exceed the total amount of set resources; If it does not exceed, the optimal multi-aircraft parallel testing process plan is output; if it does not meet the requirements, the number of test resources is increased.

[0062] Furthermore, in a possible implementation, the sorting module is further configured to analyze the association and dependency relationships between the test items to determine the preceding and following logical relationships between the test items; Based on the preceding and following logical relationships of the test items, an execution order of the test items is determined to sort the multiple test items.

[0063] Furthermore, in a possible implementation, the generating module is further configured to determine the start time and end time of each aircraft test item through the dual-code network diagram; Based on the start time and the end time, sequentially determine the longest test item for each aircraft; Connect the test items that take the longest time to generate the critical path.

[0064] Reference Figure 3 , Figure 3 The following is a parallel collaborative test scheduling process provided by the present invention: Figure 3 As shown: Step 1: Refine the test process of single-engine launch vehicles and break it down into specific test items. For example, the final assembly of a vehicle can be broken down into basic stage docking, terminal stage docking with basic stage, etc. Step 2: Determine the specific start and end time of each test task according to the aircraft's regular test process; Step 3: Using the dual-code network diagram, determine the test item link that takes the longest time when testing multiple launch vehicles simultaneously, i.e., the critical path; Step 4: Determine the test resources required for each test item on the critical path; Step 5: Use a genetic algorithm to optimize the parameterized test problem. Calculate the fitness function value for optimization objectives such as minimizing test time or minimizing test resource consumption. The solution with the highest fitness function value is the optimal solution. It should be noted that each test process solution has a corresponding total test time and total resource consumption. A score is assigned based on the test time and resource consumption, and the fitness value is multiplied by the corresponding benefit and penalty coefficients. A higher fitness value means greater benefits, indicating the optimal solution. Furthermore, different test solutions have a corresponding fitness value for the critical path. The solution with the highest fitness value is found among many test solutions.

[0065] Step 6: Based on the optimization results, check whether the required test resources exceed the total amount of launch site resources. If not, provide the optimal test scheduling plan. If not, supplement the number of test resources. Step 7: Generate the optimal test plan network diagram.

[0066] Reference Figure 4 , Figure 4 The following is the parallel collaborative test optimization algorithm flow provided by the present invention, as shown in FIG. Figure 4 As shown: Step 1: Determine the optimization variables. Use the start and end times of each test item as the optimization variables. At the same time, determine the value range of the optimization variables based on the constraints of the actual test process. Step 2: Generate the initial population optimized by genetic algorithm; Step 3: Based on the specific test items decomposed from the aircraft test process, statistically identify the test links with the longest test time as the critical path; Step 4: Calculate the total benefit based on the results of different time consumption and different resource consumption; Step 5: Determine whether the constraints of each test item are met, that is, whether the total test time exceeds the test cycle requirements and whether the test resources exceed the total resource quantity. If so, output the optimal result; if not, continue to optimize the test scheduling results. Step 6: Output the optimal test solution results.

[0067] Refer to the following Figure 5 An electronic device 500 according to this embodiment of the present invention will be described. Figure 5 The electronic device 500 shown is merely an example and should not limit the functions and scope of use of the embodiments of the present invention.

[0068] like Figure 5 As shown, electronic device 500 is implemented as a general-purpose computing device. Components of electronic device 500 may include, but are not limited to, the aforementioned at least one processing unit 510, the aforementioned at least one storage unit 520, and a bus 530 connecting various system components (including storage unit 520 and processing unit 510).

[0069] The storage unit stores program codes, which can be executed by the processing unit 510, so that the processing unit 510 performs the steps according to various exemplary embodiments of the present invention described in the above "Example Method" section of this specification.

[0070] The storage unit 520 may include a readable medium in the form of a volatile memory unit, such as a random access memory unit (RAM) 521 and / or a cache memory unit 522 , and may further include a read-only memory unit (ROM) 523 .

[0071] The storage unit 520 may also include a program / utility 524 having a set (at least one) of program modules 525, such program modules 525 including but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment.

[0072] Bus 530 may represent one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a processing unit, or a local bus using any of a variety of bus architectures.

[0073] The electronic device 500 may also communicate with one or more external devices (e.g., a keyboard, pointing device, Bluetooth device, etc.), one or more devices that enable a user to interact with the electronic device 500, and / or any device that enables the electronic device 500 to communicate with one or more other computing devices (e.g., a router, modem, etc.). This communication may occur via an input / output (I / O) interface 550. Furthermore, the electronic device 500 may also communicate with one or more networks (e.g., a local area network (LAN), a wide area network (WAN), and / or a public network such as the Internet) via a network adapter 560. As shown, the network adapter 560 communicates with other modules of the electronic device 500 via a bus 530. It should be understood that, although not shown in the figure, other hardware and / or software modules may be used in conjunction with the electronic device 500, including but not limited to microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0074] Through the description of the above embodiments, it will be readily understood by those skilled in the art that the example embodiments described herein can be implemented via software or via a combination of software and necessary hardware. Therefore, the technical solutions according to the embodiments of the present disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (such as a CD-ROM, USB flash drive, or mobile hard drive) or on a network and includes several instructions for enabling a computing device (such as a personal computer, server, terminal device, or network device) to execute the methods according to the embodiments of the present disclosure.

[0075] According to the solution of the present disclosure, a computer-readable storage medium is also provided, on which a program product capable of implementing the above-mentioned method of this specification is stored. In some possible implementations, various aspects of the present invention may also be implemented in the form of a program product, which includes program code. When the program product is executed on a terminal device, the program code is used to cause the terminal device to perform the steps according to various exemplary embodiments of the present invention described in the "Exemplary Methods" section of this specification.

[0076] 6 shows a program product 600 for implementing the above method according to an embodiment of the present invention. The program product 600 may be a portable compact disc read-only memory (CD-ROM) and include program code, and may be run on a terminal device, such as a personal computer. However, the program product of the present invention is not limited thereto. In this document, a readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0077] The program product may utilize any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. The readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or component, or any combination thereof. More specific examples (a non-exhaustive list) of readable storage media include: an electrical connection having one or more wires, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof.

[0078] A computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, which carries readable program code. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A readable signal medium may also be any readable medium other than a readable storage medium that can transmit, propagate, or transfer a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0079] The program code embodied on the readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

[0080] Program code for performing the operations of the present invention can be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code can be executed entirely on the user computing device, partially on the user device, as a stand-alone software package, partially on the user computing device and partially on a remote computing device, or entirely on a remote computing device or server. In the case of a remote computing device, the remote computing device can be connected to the user computing device via any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0081] Furthermore, the above-described figures are merely illustrative of the processes included in the method according to exemplary embodiments of the present invention and are not intended to be limiting. It is readily understood that the processes illustrated in the above-described figures do not indicate or limit the temporal order of these processes. Furthermore, it is readily understood that these processes may be executed synchronously or asynchronously, for example, in multiple modules.

[0082] The foregoing is merely a list of specific embodiments of the present application, intended to enable those skilled in the art to understand or implement the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application is not limited to the embodiments shown herein, but is intended to conform to the broadest scope consistent with the principles and novel features of the present application.

[0083] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowcharts and / or block diagrams, as well as combinations of processes and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowcharts and / or block diagrams. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

Claims

1. A method for parallel collaborative testing of aircraft, characterized in that: include: Decompose the overall test process of a single aircraft to obtain multiple test items for the single aircraft; Sorting the plurality of test items based on associations and dependencies between the test items, and sequentially sorting the test items of the plurality of aircraft based on the sorting results to obtain dual-code network diagrams of the plurality of aircraft; Based on the dual-code network diagram, identifying the test item link that takes the longest time when multiple aircraft are tested simultaneously to generate a critical path; Based on the established test process optimization model, all test items on the critical path are optimized with test time and test resources as optimization targets, and the optimal parallel test plan for multiple aircraft is output.

2. The method according to claim 1, characterized in that The genetic algorithm fitness function is used to optimize all test items on the critical path with test time and test resources as optimization targets, and output the optimal parallel test plan for multiple aircraft, including: Establish a test process optimization model; Applying a genetic algorithm to the optimization model, with all test items on the target path as optimization objects, the test start time, test end time, and required resources of the test items as optimization variables, the test resources and test cycle as constraints, and the total test time and test resources as optimization targets, searching for the optimal solution by simulating gene inheritance, mutation, and selection, and calculating the fitness function value of the critical path by providing benefits or penalties to the test items on the critical path; Based on the calculated fitness function value, the maximum fitness function value is used as the optimal multi-aircraft parallel test process solution, and an optimal test plan network diagram is generated.

3. The method according to claim 2, characterized in that include: According to the formula: Calculate the fitness function value of the critical path, where are the time benefit coefficient and resource constraint benefit coefficient respectively. 、 are the penalty coefficients, 、 are the time benefit and resource constraint benefit of completing the j-th test of the i-th aircraft, is the total critical path duration, For the required test cycle, is the total amount of test resources, For resource constraints, For test items, is the aircraft serial number, is the test item number, is the process name, The test start time, The test end time, For pre-test projects, This is a post-test item.

4. The method according to claim 2, characterized in that After optimizing all test items on the critical path based on the established test process optimization model with test time and test resources as optimization targets, the method further includes: Determine whether the constraints of each test item are met, wherein the constraints include: whether the test time exceeds the test cycle and whether the test resources exceed the total resource quantity; If satisfied, output the optimal result; If not, continue to adjust the time consumption and test resources of the test items of multiple aircraft to optimize the multi-aircraft parallel testing process plan.

5. The method according to claim 2, characterized in that Before generating the optimal test plan network diagram, the method further includes: Check whether the required test resources exceed the total amount of set resources; If it does not exceed, the optimal multi-aircraft parallel testing process plan is output; if it does not meet the requirements, the number of test resources is increased.

6. The method according to claim 1, characterized in that The sorting of the plurality of test items based on the association and dependency relationship between the test items includes: Analyze the association and dependency between test items to determine the pre- and post-test logical relationships; Based on the preceding and following logical relationships of the test items, an execution order of the test items is determined to sort the multiple test items.

7. The method according to claim 1, characterized in that The step of identifying the longest test item link when multiple aircraft are tested simultaneously based on the dual-code network diagram to generate a critical path includes: Determine the start and end time of each aircraft test item through the dual-code network diagram; Based on the start time and the end time, sequentially determine the longest test item for each aircraft; Connect the test items that take the longest time to generate the critical path.

8. An aircraft parallel collaborative testing device, wherein the characteristics are: include: A decomposition module is used to decompose the overall test process of a single aircraft to obtain multiple test items of the single aircraft; a sorting module, configured to sort the plurality of test items based on associations and dependencies between the test items, and to sequentially sort the test items of the plurality of aircraft based on the sorting results to obtain a dual-code network diagram of the plurality of aircraft; A generation module, configured to identify, based on the dual-code network diagram, a test item link that consumes the longest time when multiple aircraft are tested simultaneously, so as to generate a critical path; The processing module is used to optimize all test items on the critical path based on the established test process optimization model, taking test time and test resources as optimization targets, and output an optimal parallel test plan for multiple aircraft.

9. An electronic device, characterized in that: The electronic device comprises: processor; A memory having computer-readable instructions stored thereon, wherein when the computer-readable instructions are executed by the processor, the method according to any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium, characterized in that The computer program instructions are stored therein, and when the computer program instructions are executed by a computer, the computer is caused to execute the method according to any one of claims 1 to 7.

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