Unmanned aerial vehicle airport multi-dimensional timing inspection method, system and equipment

Abstract

The invention provides an unmanned aerial vehicle airport multi-dimensional timing inspection method, system and device. The method comprises the following steps: selecting a multi-dimensional time strategy for airport multi-dimensional timing inspection; analyzing the selected multi-dimensional time strategy to obtain candidate dates; discretizing the candidate dates, and mapping the discretized candidate dates into Cron expression parameters; combining the Cron expressions with the same time strategy; and a trigger group of the merged Cron expression is operated in batches by adopting a scheduler, so that cascade operation of the timed inspection task plan is realized, and an airport multi-dimensional timed inspection plan is output. Based on the method, the invention further provides an unmanned aerial vehicle airport multi-dimensional timing inspection system and equipment. According to the invention, a complex inspection strategy is determined through a multi-dimensional time strategy selector and an exception calendar; a time discretization algorithm is adopted to analyze the plan to generate a plurality of Cron expressions, and multi-time-dimension cross constraint is supported; and extending the JobStore to realize plan cascade operation and task atomicity update.

Description

Technical Field

[0001] The present invention belongs to the technical field of UAV airport inspection, and particularly relates to a multi-dimensional timed inspection method, system and device for UAV airports. Background Art

[0002] Multi-dimensional timed inspection of UAV airports refers to using UAV airports and combining advanced technical means to conduct inspection work at multiple dimensions according to preset time. When formulating the multi-dimensional timed inspection plan for UAV airports in the current technology, simple timers are usually used to configure fixed time points to trigger tasks, such as Java Timer, Spring Scheduler, etc.; when parsing tasks, the preset time is directly mapped to a single execution instruction, resulting in a lack of dynamic parsing ability for periodic strategies; when scheduling tasks, it relies on the basic scheduling framework to execute a single Cron expression and cannot handle multi-dimensional time constraints; the task status management is coarse-grained and does not support plan-level cascaded suspension or atomic operations of tasks.

[0003] Therefore, the technical defects of the existing technology for multi-dimensional timed inspection of UAV airports include: inability to support complex plans, inability to dynamically suspend a certain task without affecting the overall plan, difficulty in covering multi-time dimension combination scenarios with a single Cron expression, and lack of a retry mechanism for task execution exceptions, which easily leads to task failures due to reasons such as network fluctuations. Summary of the Invention

[0004] In order to solve the above technical problems, the present invention proposes a multi-dimensional timed inspection method, system and device for UAV airports. The time discretization algorithm is used to parse the plan into multiple Cron expressions, supporting cross-constraints of multiple time dimensions.

[0005] To achieve the above object, the present invention adopts the following technical solutions:

[0006] A multi-dimensional timed inspection method for UAV airports includes the following steps:

[0007] Select a multi-dimensional time strategy for multi-dimensional timed inspection of the airport; obtain candidate dates by parsing the selected multi-dimensional time strategy;

[0008] Discretize the candidate dates and map them to Cron expression parameters; merge the Cron expressions with the same time strategy;

[0009] Use the Quartz scheduler to batch-operate the trigger group of the merged Cron expressions to implement plan-level cascaded operations of timed inspection tasks and output the multi-dimensional timed inspection plan for the airport.

[0010] Further, the multi-dimensional time strategy for multi-dimensional timed inspection at the airport includes a single inspection plan, a daily inspection plan, a weekly inspection plan, a monthly inspection plan, and an annual inspection plan; and determining the blacklist dates to be removed in each inspection plan.

[0011] Further, the process of parsing the selected multi-dimensional time strategy includes:

[0012] Extracting the absolute time range in the multi-dimensional time strategy;

[0013] Splitting the relative constraints within the absolute time range;

[0014] Parsing out the blacklist dates;

[0015] Generating candidate dates for the relative constraints within the absolute time range.

[0016] Further, the process of discretizing the candidate dates includes:

[0017] Sorting the candidate dates in ascending order of timestamp;

[0018] Excluding duplicate dates after sorting in ascending order.

[0019] Further, after mapping to Cron expression parameters, it also includes filtering out blacklist dates.

[0020] Further, the process of merging the Cron expressions includes:

[0021] Merging tasks with the same time strategy into a single Cron expression;

[0022] If it is determined that the length of a single Cron expression exceeds the expression length threshold, it is split into multiple single Cron expressions.

[0023] Further, the process of using the Quartz scheduler to batch operate on the trigger group of the merged Cron expressions to implement the creation, update, and deletion of the timed inspection task plan includes:

[0024] Using a trigger table to save the dependency relationships of the tasks of the merged Cron expressions;

[0025] Using a cascading job repository to implement outputting the multi-dimensional timed inspection plan for the airport or a rollback plan.

[0026] Further, the method also includes using the Quartz scheduler to implement atomic updates of the inspection task plan.

[0027] Embodiment 1 of the present invention also proposes a multi-dimensional timed inspection system for an unmanned aerial vehicle airport, including a preprocessing module, a merging module, and an inspection module;

[0028] The preprocessing module is used to select a multi-dimensional time strategy for multi-dimensional timed inspection of the airport; and obtain candidate dates by parsing the selected multi-dimensional time strategy.

[0029] The merging module is used to discretize the candidate dates and map them to Cron expression parameters; and merge the Cron expressions with the same time strategy.

[0030] The inspection module is used to batch-operate the trigger group of the merged Cron expression by using a Quartz scheduler to implement the creation, update, and deletion of the timed inspection task plan, and output the multi-dimensional timed inspection plan of the airport.

[0031] Embodiment 1 of the present invention also proposes a device, including:

[0032] A memory, used to store a computer program;

[0033] A processor, used to implement the method steps when executing the computer program.

[0034] The effects provided in the summary of the invention are only the effects of the embodiments, rather than all the effects of the invention. One of the above technical solutions has the following advantages or beneficial effects:

[0035] The present invention proposes a method, system, and device for multi-dimensional timed inspection of a drone airport. The method includes the following steps: selecting a multi-dimensional time strategy for multi-dimensional timed inspection of the airport; obtaining candidate dates by parsing the selected multi-dimensional time strategy; discretizing the candidate dates and mapping them to Cron expression parameters; merging the Cron expressions with the same time strategy; batch-operating the trigger group of the merged Cron expression by using a Quartz scheduler to implement cascaded operations of the timed inspection task plan, and outputting the multi-dimensional timed inspection plan of the airport. Based on a method for multi-dimensional timed inspection of a drone airport, a system and a device for multi-dimensional timed inspection of a drone airport are also proposed. The present invention determines a complex inspection strategy through a multi-dimensional time strategy selector and an exception calendar; uses a time discretization algorithm to parse the plan into multiple Cron expressions to support cross-constraints of multiple time dimensions; extends the JobStore to implement cascaded operations of the plan and atomic update of tasks; and controls the task execution process based on a state machine model to adapt to multi-airport vendor protocols. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 It is a flowchart of a method for multi-dimensional timed inspection of a drone airport proposed in Embodiment 1 of the present invention;

[0037] Figure 2 It is an architecture diagram of a method for multi-dimensional timed inspection of a drone airport proposed in Embodiment 1 of the present invention;

[0038] Figure 3 The process of implementing the output or rollback of the multi - dimensional timed inspection plan for the airport in Embodiment 1 of the present invention;

[0039] Figure 4 A schematic diagram of a multi - dimensional timed inspection system for an unmanned aerial vehicle (UAV) airport proposed in Embodiment 2 of the present invention;

[0040] Figure 5 A schematic diagram of a multi - dimensional timed inspection device for an unmanned aerial vehicle (UAV) airport proposed in Embodiment 3 of the present invention. Detailed implementation manners

[0041] To clearly illustrate the technical features of this solution, the present invention will be elaborated in detail below through specific implementation manners and in conjunction with its accompanying drawings. The following disclosure provides many different embodiments or examples for implementing different structures of the present invention. To simplify the disclosure of the present invention, the components and settings of specific examples are described below. In addition, the present invention may repeat reference numerals and / or letters in different examples. This repetition is for the purpose of simplification and clarity, and does not itself indicate the relationship between the various embodiments and / or settings discussed. It should be noted that the components illustrated in the drawings are not necessarily drawn to scale. The present invention omits the description of well - known components and processing technologies and processes to avoid unnecessarily limiting the present invention.

[0042] Embodiment 1

[0043] Embodiment 1 of the present invention proposes a multi - dimensional timed inspection method for an unmanned aerial vehicle (UAV) airport to solve the technical problems existing in the multi - dimensional timed inspection of UAV airports in the prior art. Figure 1 A flowchart of a multi - dimensional timed inspection method for an unmanned aerial vehicle (UAV) airport proposed in Embodiment 1 of the present invention;

[0044] Select a multi - dimensional time strategy for multi - dimensional timed inspection of the airport; obtain candidate dates by parsing the selected multi - dimensional time strategy;

[0045] The multi - dimensional time strategy for multi - dimensional timed inspection of the airport includes a single - inspection plan, a daily inspection plan, a weekly inspection plan, a monthly inspection plan, and an annual inspection plan; and determine the black - list dates to be removed in each inspection plan.

[0046] Define multiple types of strategies (single / hour / day / week / month), supporting parameters such as interval base (interval), date set (days), week - day set (weekDays), month - day set (monthDays), etc.; Table 1 below shows the information of each strategy;

[0047] Table 1: Information of each strategy

[0048]

[0049]

[0050] Store the blacklist dates (e.g., tasks are suspended from October 1, 2025 to October 7, 2025), with a higher priority than the main plan.

[0051] The process of parsing the selected multi-dimensional time strategy includes: extracting the absolute time range in the multi-dimensional time strategy; splitting the relative constraints within the absolute time range; parsing out the blacklist dates; generating candidate dates for the relative constraints within the absolute time range.

[0052] For example: Input example: 10:00 am on the second Tuesday / Thursday of the 1st, 4th, 7th, and 10th months from 2025 to 2030, excluding October 1 to October 7, 2025.

[0053] Extract the absolute time range (from 2025 to 2030);

[0054] Split the relative constraints (month set [1, 4, 7, 10]; the second week → week number = 2; time → 10:00:00);

[0055] Parse the exception dates (October 1 - 7 every year).

[0056] Loop through and generate candidate dates for each year (2025 - 2030), month (1, 4, 7, 10), and week number (the second week).

[0057] Result set: Generate the original date set {2025-01-07, 2025-01-09, 2025-04-08......}.

[0058] Discretize the candidate dates and map them to Cron expression parameters; merge the Cron expressions with the same time strategy.

[0059] The process of discretizing the candidate dates includes: arranging the candidate dates in ascending order of timestamp; excluding duplicate dates after ascending order, such as date overlaps in the cross-year strategy.

[0060] The specific mapping rule is: map the dates to Cron expression parameters (e.g., date field → 7, 9, 8, month field → 1, 4, 7, 10, week field → 2#2, 4#2, year field → 2025 - 2030). After mapping to Cron expression parameters, it also includes filtering the blacklist dates.

[0061] The process of merging the Cron expressions includes: merging the tasks with the same time strategy into a single Cron expression; if it is determined that the length of a single Cron expression exceeds the expression length threshold, split it into multiple single Cron expressions.

[0062] Tasks in the same month / week are merged into a single expression (e.g., 0 0 10? 1,4,7,10 2#2,4#22025 - 2030); if the expression length exceeds the Quartz limit (e.g., number of characters > 250), it is automatically split into multiple triggers. And batch update the triggers affected by the policy change.

[0063] Use the Quartz scheduler to batch operate on the trigger group of the merged Cron expression to implement the cascading operation of the regular inspection task plan and output the airport multi - dimensional regular inspection plan.

[0064] In the Quartz scheduling framework, JobStore is the core component responsible for storing and managing Jobs and Triggers. Implementing cascading operations usually involves extending the creation, update, and deletion operations of Jobs and Triggers to ensure that when a certain operation is executed, the relevant cascading operations can be automatically triggered.

[0065] Figure 3 This is the process for implementing the output or rollback of the airport multi - dimensional regular inspection plan proposed in Embodiment 1 of the present invention.

[0066] Use the trigger table to save the dependency relationship of the tasks with the merged Cron expression; that is, extend the CascadingJobStore class on the basis of JobStore, and add a dependency_triggers table to store the task dependency relationship.

[0067] Use the cascading job repository to implement the output of the airport multi - dimensional regular inspection plan or the rollback plan; that is, extend CascadingJobStore based on ACID transactions to achieve "all successful" or "all rollback" of the group operation.

[0068] When pausing / resuming the plan, automatically pause / resume all dependent subtasks; when pausing a subtask, it does not affect the parent task and other subtasks. In this application, an exponential back - off algorithm (5s → 30s → 5min) is integrated, and the maximum number of retries is 3 times.

[0069] Figure 2 This is the architecture diagram of a multi - dimensional regular inspection method for an unmanned aerial vehicle airport proposed in Embodiment 1 of the present invention. In the configuration layer, configure the multi - dimensional plan modeling engine and the dynamic Corn generator; in the support layer, provide a policy database, a task status database, and a log database; in the scheduling layer, set up the Quartz scheduler and the unmanned aerial vehicle instruction orchestration engine; in the execution layer, it is used to adapt the protocol.

[0070] Embodiment 1 of the present invention proposes a multi-dimensional timed inspection method for an unmanned aerial vehicle (UAV) airport, which determines a complex inspection strategy through a multi-dimensional time strategy selector and an exception calendar; uses a time discretization algorithm to parse and generate multiple Cron expressions for the plan, supporting cross-constraints in multiple time dimensions; extends the JobStore to implement plan cascading operations and atomic task updates; and controls the task execution process based on a state machine model to adapt to multi-airport vendor protocols.

[0071] Embodiment 2

[0072] Based on the multi-dimensional timed inspection method for an unmanned aerial vehicle airport proposed in Embodiment 1 of the present invention, Embodiment 2 of the present invention also proposes a multi-dimensional timed inspection system for an unmanned aerial vehicle airport. Figure 4 The figure shows a schematic diagram of a multi-dimensional timed inspection system for an unmanned aerial vehicle airport proposed in Embodiment 2 of the present invention. The system includes: a preprocessing module, a merging module, and an inspection module.

[0073] The preprocessing module is used to select a multi-dimensional time strategy for multi-dimensional timed inspection of the airport; and obtain candidate dates by parsing the selected multi-dimensional time strategy.

[0074] The merging module is used to map the discretized candidate dates to Cron expression parameters after discretization; and merge the Cron expressions with the same time strategy.

[0075] The inspection module is used to batch-operate the trigger groups of the merged Cron expressions using a Quartz scheduler to implement the creation, update, and deletion of timed inspection task plans, and output a multi-dimensional timed inspection plan for the airport.

[0076] In the preprocessing module, the multi-dimensional time strategies for multi-dimensional timed inspection of the airport include single inspection plans, daily inspection plans, weekly inspection plans, monthly inspection plans, and annual inspection plans; and blacklist dates to be removed in each inspection plan are determined.

[0077] The process of parsing the selected multi-dimensional time strategy includes: extracting the absolute time range in the multi-dimensional time strategy; splitting the relative constraints within the absolute time range; parsing out the blacklist dates; and generating candidate dates of relative constraints within the absolute time range.

[0078] In the merging module, the process of discretizing the candidate dates includes: arranging the candidate dates in ascending order of timestamp; excluding duplicate dates after ascending order arrangement. After mapping to Cron expression parameters, it also includes filtering blacklist dates.

[0079] The process of merging the Cron expressions includes: merging tasks with the same time strategy into a single Cron expression; and splitting it into multiple single Cron expressions if it is determined that the length of a single Cron expression exceeds the expression length threshold.

[0080] In the patrol inspection module, the Quartz scheduler is used to batch operate on the trigger group of the merged Cron expressions to implement the creation, update, and deletion of the timed patrol inspection task plan. The process includes: using the trigger table to save the dependency relationship of the tasks with the merged Cron expressions; using the cascading job repository to implement the output of the multi-dimensional timed patrol inspection plan for the airport or the rollback plan. The Quartz scheduler is also used in this module to implement the atomic update of the patrol inspection task plan.

[0081] Embodiment 2 of the present invention proposes a multi-dimensional timed patrol inspection system for an unmanned aerial vehicle airport. The complex patrol inspection strategy is determined by the multi-dimensional time policy selector and the exception calendar; the time discretization algorithm is used to parse the plan into multiple Cron expressions, supporting cross-constraints in multiple time dimensions; the JobStore is extended to implement plan cascading operations and task atomic updates; the task execution process is controlled based on the state machine model to adapt to the protocols of multiple airport manufacturers.

[0082] Embodiment 3

[0083] The present invention also proposes a device Figure 5 which is a schematic diagram of a multi-dimensional timed patrol inspection device for an unmanned aerial vehicle airport proposed in Embodiment 3 of the present invention, including:

[0084] A memory for storing computer programs;

[0085] A processor for implementing the following method steps when executing the computer program:

[0086] Select a multi-dimensional time policy for multi-dimensional timed patrol inspection of the airport; obtain candidate dates by parsing the selected multi-dimensional time policy;

[0087] Discretize the candidate dates and map them to Cron expression parameters; merge the Cron expressions with the same time policy;

[0088] Use the Quartz scheduler to batch operate on the trigger group of the merged Cron expressions to implement the cascading operation of the timed patrol inspection task plan and output the multi-dimensional timed patrol inspection plan for the airport.

[0089] Embodiment 3 of the present invention proposes a multi-dimensional timed patrol inspection device for an unmanned aerial vehicle airport. The complex patrol inspection strategy is determined by the multi-dimensional time policy selector and the exception calendar; the time discretization algorithm is used to parse the plan into multiple Cron expressions, supporting cross-constraints in multiple time dimensions; the JobStore is extended to implement plan cascading operations and task atomic updates; the task execution process is controlled based on the state machine model to adapt to the protocols of multiple airport manufacturers.

[0090] It should be noted that the technical solution of the present invention also provides an electronic device, including: a communication interface capable of interacting with other devices such as network devices; a processor connected to the communication interface to achieve information interaction with other devices and, when running a computer program, execute a multi-dimensional timed inspection method for an unmanned aerial vehicle airport provided by one or more of the above technical solutions, and the computer program is stored on a memory. Of course, in actual application, each component in the electronic device is coupled together through a bus system. It can be understood that the bus system is used to realize the connection and communication between these components. The bus system includes not only a data bus, but also a power bus, a control bus, and a status signal bus. The memory in the embodiment of the present application is used to store various types of data to support the operation of the electronic device. Examples of these data include: any computer program for operating on the electronic device. It can be understood that the memory can be a volatile memory or a non-volatile memory, or can include both volatile and non-volatile memories. Among them, the non-volatile memory can be a read-only memory (ROM, Read Only Memory), a programmable read-only memory (PROM, Programmable Read-Only Memory), an erasable programmable read-only memory (EPROM, Erasable Programmable Read-Only Memory), an electrically erasable programmable read-only memory (EEPROM, Electrically Erasable Programmable Read-Only Memory), a ferromagnetic random access memory (FRAM, ferromagnetic random access memory), a flash memory (FlashMemory), a magnetic surface memory, an optical disc, or a compact disc read-only memory (CD-ROM, Compact Disc Read-Only Memory); the magnetic surface memory can be a disk memory or a tape memory. The volatile memory can be a random access memory (RAM, Random AccessMemory), which is used as an external cache.By way of example and not limitation, many forms of RAM are available, such as static random access memory (SRAM), synchronous static random access memory (SSRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), enhanced synchronous dynamic random access memory (ESDRAM), sync link dynamic random access memory (SLDRAM), direct rambus random access memory (DRRAM). The memories described in the embodiments of the present application are intended to include but not be limited to these and any other suitable types of memories. The methods disclosed in the embodiments of the present application above can be applied to or implemented by a processor. The processor may be an integrated circuit chip with signal processing capabilities. In the implementation process, the steps of the above methods can be completed by the integrated logic circuit in the hardware of the processor or instructions in software form. The above processor may be a general-purpose processor, a DSP (Digital Signal Processing, that is, a chip capable of implementing digital signal processing technology), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The processor can implement or execute the various methods, steps, and logic block diagrams disclosed in the embodiments of the present application. The general-purpose processor may be a microprocessor or any conventional processor, etc. Combining the steps of the methods disclosed in the embodiments of the present application can be directly embodied as being executed and completed by a hardware decoding processor, or by a combination of hardware and software modules in the decoding processor. The software module may be located in a storage medium, and the storage medium is located in the memory. The processor reads the program in the memory and combines its hardware to complete the steps of the foregoing methods. When the processor executes the program, it implements the corresponding processes in the various methods of the embodiments of the present application. For the sake of brevity, it will not be elaborated here.

[0091] For the description of relevant parts in the multi-dimensional timed inspection device for an unmanned aerial vehicle (UAV) airport provided in Embodiment 3 of this application, reference can be made to the detailed description of the corresponding parts in the multi-dimensional timed inspection method for an unmanned aerial vehicle airport provided in Embodiment 1 of this application, which will not be elaborated here.

[0092] It should be noted that in this text, relative terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the term "including", "comprising" or any other variant thereof is intended to cover non-exclusive inclusion, so that the elements inherent in a process, method, article or device including a series of elements are included. Without more limitations, the element defined by the statement "including one..." does not exclude the existence of additional identical elements in the process, method, article or device including the said element. In addition, parts of the above technical solutions provided in the embodiments of this application that are consistent with the corresponding technical solutions in the prior art in terms of implementation principles are not described in detail to avoid excessive elaboration.

[0093] Although the specific implementation manners of the present invention are described above in conjunction with the accompanying drawings, it is not a limitation on the protection scope of the present invention. For those skilled in the art, other different forms of modifications or deformations can be made on the basis of the above description. It is not necessary and impossible to enumerate all the implementation manners here. Various modifications or deformations that can be made by those skilled in the art without creative efforts on the basis of the technical solutions of the present invention are still within the protection scope of the present invention.

Claims

1. A multi-dimensional timed inspection method for an unmanned aerial vehicle airport, characterized in that, It includes the following steps: Select a multi-dimensional time strategy for multi-dimensional timed inspections at the airport; Obtain candidate dates by parsing the selected multi-dimensional time strategy; After discretizing the candidate dates, map them to Cron expression parameters; Merge the Cron expressions with the same time strategy; Use the Quartz scheduler to batch-operate on the trigger group of the merged Cron expressions to implement the cascading operation of the timed inspection task plan and output the multi-dimensional timed inspection plan for the airport.

2. The multi-dimensional timed inspection method for an unmanned aerial vehicle airport according to claim 1, characterized in that, The multi-dimensional time strategy for multi-dimensional timed inspections at the airport includes single inspection plans, daily inspection plans, weekly inspection plans, monthly inspection plans, and annual inspection plans; And determine the blacklist dates to be removed in each inspection plan.

3. The multi-dimensional timed inspection method for a drone airport according to claim 1, wherein The process of parsing the selected multi-dimensional time strategy includes: Extract the absolute time range in the multi-dimensional time strategy; Split the relative constraints within the absolute time range; Parse out the blacklist dates; Generate candidate dates for the relative constraints within the absolute time range.

4. A multi-dimensional timed inspection method for an unmanned aerial vehicle airport according to claim 1, characterized in that The process of discretizing the candidate dates includes: Arrange the candidate dates in ascending order of timestamps; Exclude duplicate dates after ascending order.

5. A multi-dimensional timed inspection method for an unmanned aerial vehicle airport according to claim 1, characterized in that, After mapping to Cron expression parameters, it also includes filtering blacklist dates.

6. The multi-dimensional timed inspection method for an unmanned aerial vehicle airport according to claim 1, characterized in that, The process of merging the Cron expressions includes: Merge the tasks with the same time strategy into a single Cron expression; If it is determined that the length of a single Cron expression exceeds the expression length threshold, split it into multiple single Cron expressions.

7. A multi-dimensional timed inspection method for an unmanned aerial vehicle airport according to claim 1, characterized in that, The process of using the Quartz scheduler to batch-operate on the trigger group of the merged Cron expressions to implement the creation, update, and deletion of the timed inspection task plan includes: Use a trigger table to save the dependency relationships of the tasks of the merged Cron expressions; Use a cascading job repository to implement the output of the multi-dimensional timed inspection plan for the airport or the rollback plan.

8. A multi-dimensional timed inspection method for an unmanned aerial vehicle airport according to claim 1, characterized in that, The method also includes using the Quartz scheduler to implement atomic updates of the inspection task plan.

9. A multi-dimensional timed inspection system for an unmanned aerial vehicle airport, characterized in that, It includes a preprocessing module, a merging module, and an inspection module; The preprocessing module is used to select a multi-dimensional time strategy for multi-dimensional timed inspections at the airport; obtain candidate dates by parsing the selected multi-dimensional time strategy; The merging module is used to map the discretized candidate dates to Cron expression parameters; Merge the Cron expressions with the same time strategy; The inspection module is used to use the Quartz scheduler to batch-operate on the trigger group of the merged Cron expressions to implement the creation, update, and deletion of the timed inspection task plan and output the multi-dimensional timed inspection plan for the airport.

10. A device, characterized in that, It includes: A memory for storing computer programs; A processor for implementing the method steps described in any one of claims 1 to 8 when executing the computer program.

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