Inspection plan generation method and device, equipment, storage medium and program product

Abstract

The invention relates to an inspection plan generation method and device, equipment, a storage medium and a program product. The method comprises the following steps: obtaining task description information corresponding to an inspection task of a transformer substation, and analyzing the task description information to obtain a region keyword, an object keyword and an algorithm keyword; determining an algorithm name matched with the algorithm keyword, and querying to obtain matched target preset bit information according to the region keyword, the object keyword and the algorithm name, the target preset bit information including a preset bit identifier and a visual acquisition equipment identifier; and generating an inspection plan corresponding to the inspection task based on the algorithm name, the preset bit identifier and the visual acquisition equipment identifier. By adopting the method, the inspection efficiency can be improved.

Description

Technical Field

[0001] The present application relates to the technical field of substations, and in particular to a method, apparatus, device, storage medium, and program product for generating an inspection plan. Background Art

[0002] As the scale of substation equipment continues to expand, the traditional manual inspection model can no longer meet the needs of efficient and accurate operation and maintenance. The in-depth advancement of digital power grid construction has further promoted the transformation of inspection operations towards digitalization and intelligence.

[0003] In traditional technology, in order to inspect the substation, an inspection plan is manually generated in advance, and the inspection plan is executed when the inspection is required.

[0004] However, manually generating inspection plans is time-consuming and cumbersome, affecting inspection efficiency. Summary of the Invention

[0005] Based on this, it is necessary to provide a method, device, computer equipment, computer-readable storage medium and computer program product for generating an inspection plan that can improve inspection efficiency in response to the above technical problems.

[0006] On the one hand, the present application provides a method for generating an inspection plan, including: obtaining task description information corresponding to the inspection task of the substation, parsing the task description information to obtain area keywords, object keywords and algorithm keywords; determining the algorithm name that matches the algorithm keyword, and querying and obtaining matching target preset position information based on the area keyword, the object keyword and the algorithm name, wherein the target preset position information includes a preset position identifier and a visual acquisition device identifier; generating an inspection plan corresponding to the inspection task based on the algorithm name, the preset position identifier and the visual acquisition device identifier.

[0007] On the other hand, the present application also provides an inspection plan generation device, including: an information parsing module, used to obtain task description information corresponding to the inspection task of the substation, and parse the task description information to obtain area keywords, object keywords and algorithm keywords; an information query module, used to determine the algorithm name that matches the algorithm keyword, and query the matching target preset position information based on the area keyword, the object keyword and the algorithm name, and the target preset position information includes a preset position identifier and a visual acquisition device identifier; a plan generation module, used to generate an inspection plan corresponding to the inspection task based on the algorithm name, the preset position identifier and the visual acquisition device identifier.

[0008] In some embodiments, the target preset position information further includes an area name, an object name and a preset acquisition type, and the information query module is further used to determine the target acquisition type based on the algorithm name; based on the area keyword, the object keyword and the target acquisition type, the matching target preset position information is queried, wherein the area name matches the area keyword, the object keyword matches the object name, and the preset acquisition type matches the target acquisition type.

[0009] In some embodiments, the information query module is further used to query and obtain at least one matching target preset position information based on the area keyword, the object keyword and the target acquisition type; wherein the query conditions include: the area name contains the area keyword, the object name contains the object keyword, and the preset acquisition type is consistent with the target acquisition type.

[0010] In some embodiments, the plan generation module is further used to form a triplet with the algorithm name, the preset position identifier and the visual acquisition device identifier; and generate an inspection plan corresponding to the inspection task based on the triplet.

[0011] In some embodiments, the plan generation module is also used to, when there are multiple target preset position information, for each target preset position information, form a triple with the preset position identifier and visual acquisition device identifier in the target preset position information and the algorithm name; and generate an inspection plan corresponding to the inspection task based on each of the triples.

[0012] In some embodiments, the target preset position information is queried from a preset position table, and the device also includes an update module, which is used to perform at least one of the following: regularly updating the inspection plan; or updating the relevant inspection plan when the visual acquisition device identifier in any preset position information in the preset position table changes.

[0013] On the other hand, the present application also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps in the above-mentioned inspection plan generation method when executing the computer program.

[0014] On the other hand, the present application also provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the steps in the above-mentioned inspection plan generation method are implemented.

[0015] On the other hand, the present application also provides a computer program product, including a computer program, which implements the steps in the above-mentioned inspection plan generation method when executed by a processor.

[0016] The above-described inspection plan generation method, apparatus, computer device, computer-readable storage medium, and computer program product obtain task description information corresponding to a substation inspection task, parse the task description information to obtain regional keywords, object keywords, and algorithm keywords, determine the algorithm name that matches the algorithm keyword, and query and obtain matching target preset position information based on the regional keywords, object keywords, and algorithm name. The target preset position information includes a preset position identifier and a visual acquisition device identifier. Based on the algorithm name, preset position identifier, and visual acquisition device identifier, an inspection plan corresponding to the inspection task is generated. This achieves a solution that can automatically generate inspection plans and improves inspection efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the following briefly introduces the drawings required for use in the embodiments of the present application or related technical descriptions. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without any creative work.

[0018] Figure 1 A diagram showing an application environment of the inspection plan generation method in some embodiments;

[0019] Figure 2 Schematic diagram of a flow chart of a method for generating an inspection plan in some embodiments;

[0020] Figure 3 Schematic diagram of the flow of the inspection plan generation method in some other embodiments;

[0021] Figure 4 is a structural block diagram of an inspection plan generating device in some embodiments;

[0022] Figure 5 is a diagram of the internal structure of a computer device in some embodiments;

[0023] Figure 6 1 is a diagram of the internal structure of a computer device in some other embodiments. DETAILED DESCRIPTION

[0024] In order to make the purpose, technical solutions and advantages of this application more clear, the following further describes this application in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.

[0025] The inspection plan generation method provided in the embodiment of the present application can be applied to Figure 1The illustrated application environment includes a substation 102 and a computer device 104. The substation includes devices and multiple visual acquisition devices, such as visual acquisition device 1 through visual acquisition device n, where n ≥ 2. Alternatively, there may be only one visual acquisition device. The visual acquisition device may be, but is not limited to, an image acquisition device or a video acquisition device, such as a camera or an infrared thermal imager. Computer device 104 can communicate with the visual acquisition device in the substation, either directly or indirectly via wired or wireless communication, which is not a limitation of this application.

[0026] Specifically, during a substation inspection, the computer device 104 can control the visual acquisition device to rotate and acquire visual content, such as images or videos, from the visual acquisition device. The computer device 104 can then analyze the acquired visual content to determine whether a fault exists in the substation.

[0027] The computer device can be a terminal or a server. Terminals include, but are not limited to, desktop computers, laptops, smartphones, and tablets. Servers can be standalone physical servers, server clusters or distributed systems consisting of multiple physical servers, or cloud servers providing cloud computing services. Cloud servers are used to provide basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, CDN (Content Delivery Network), and big data and artificial intelligence platforms.

[0028] In some embodiments, as Figure 2 As shown, a method for generating an inspection plan is provided. The method can be executed by a terminal or a server, or by both the terminal and the server. Figure 1 Taking the computer device 104 in the example as an example, the method includes the following steps:

[0029] Step 202: Obtain task description information corresponding to the inspection task of the substation, and parse the task description information to obtain area keywords, object keywords, and algorithm keywords.

[0030] The task description information describes the monitoring area, monitored objects, and information recognition algorithms. The monitored objects belong to this monitoring area. The information recognition algorithm is used to identify the information contained in the collected visual content, such as images or videos, of the monitored objects. The monitoring area may include, but is not limited to, high-voltage equipment, main transformers, cable trenches, terminal boxes, and perimeters. Monitored objects may include, but are not limited to, circuit breakers, disconnectors, lightning arresters, oil pillows, bushings, oil level gauges, cable connectors, walls, and gates. The information recognition algorithm may include, but is not limited to, artificial intelligence (AI) algorithms. For example, these algorithms may include, but are not limited to, equipment appearance recognition, infrared temperature measurement, abnormal location, and meter recognition.

[0031] The task description information may be the name of the inspection task, and the task description information (task name) may be used to represent an inspection task. For example, if the inspection task is a "special inspection for main transformer bushing temperature overheating" task, "special inspection for main transformer bushing temperature overheating" is the task description information (task name).

[0032] Regional keywords are words related to the monitoring area and are used to identify the monitoring area. Object keywords are words related to the monitoring object and are used to identify the monitoring object. Algorithm keywords are words related to the information recognition algorithm and are used to identify the information recognition algorithm. For example, if the task description is "main transformer bushing temperature inspection," the regional keyword is "main transformer," the object keyword is "bushing," and the algorithm keyword is "temperature."

[0033] Specifically, the computer device can perform semantic analysis on the task description information, for example, analyzing the semantic intent through natural language processing technology to obtain regional keywords, object keywords and algorithm keywords.

[0034] Step 204: determine the algorithm name that matches the algorithm keyword, and query and obtain matching target preset position information based on the region keyword, object keyword and algorithm name. The target preset position information includes a preset position identifier and a visual acquisition device identifier.

[0035] Among them, the visual acquisition device identifier is used to uniquely identify a visual acquisition device. The preset position represented by the preset position identifier contained in the preset position information belongs to the visual acquisition device represented by the visual acquisition device identifier in the preset position information. The preset position of the visual acquisition device is a fast positioning function that allows the user to pre-store the spatial position parameters of the visual acquisition device (such as angle or zoom, etc.). The preset position can be called through instructions to make the visual acquisition device automatically turn and lock the preset viewing angle. The preset position identifier can be a preset position number. The visual acquisition device identifier can be a visual acquisition device code. For example, if the visual acquisition device is a camera, the visual acquisition device identifier can be a camera code. The target preset position information is the preset position information queried based on the area keyword, object keyword and algorithm name.

[0036] Specifically, the computer device may search for an algorithm name that matches the algorithm keyword from the algorithm name set. Each algorithm name represents an information identification algorithm. For example, the computer device may calculate the correlation between the algorithm keyword and each algorithm name and determine the algorithm name with the highest correlation as the matching algorithm name.

[0037] Step 206: Generate an inspection plan corresponding to the inspection task based on the algorithm name, the preset position identifier, and the visual acquisition device identifier.

[0038] Specifically, the computer device can combine the algorithm name, the preset position identifier, and the visual acquisition device identifier to form an inspection plan corresponding to the inspection task. By executing the inspection plan, fault detection can be performed on the object corresponding to the object keyword.

[0039] In some embodiments, when an inspection task needs to be executed, the computer device performs inspection calculations. During the execution of the inspection plan, a preset position call instruction is generated based on the preset position identifier in the inspection plan. The preset position call instruction is sent to the target visual acquisition device represented by the visual acquisition device identifier in the inspection plan. The target visual acquisition device is adjusted based on the preset position represented by the preset position identifier, visual content collected by the target visual acquisition device when it is in the target preset position is obtained, and the visual content is recognized based on the information recognition algorithm corresponding to the algorithm name. Taking the "main transformer bushing overheating special inspection" task as an example, if the inspection plan corresponding to this task is {"target camera code", "target preset position identifier", "infrared temperature recognition algorithm"}, the specific execution of the inspection plan includes: the computer device turns on the target camera in the substation, controls the target camera to rotate to the target preset position, controls the target camera to capture an image (i.e., capture the main transformer bushing), obtains the captured image, and then calls the infrared temperature measurement and recognition algorithm to recognize the image, such as for abnormality detection. If the bushing temperature exceeds the standard, an alarm is triggered.

[0040] In some embodiments, the database stores a visual acquisition device table, which stores device information corresponding to the visual acquisition devices in the substation. The device information may include a code, name, substation name, etc., and may also include the communication address of the visual acquisition device. The computer device can query the communication address corresponding to the target visual acquisition device from the visual acquisition device table and send a preset position call instruction to the target visual acquisition device based on the communication address. If the visual acquisition device is a camera, the visual acquisition device table is a camera table, and the camera table is shown in Table 1:

[0041] Table 1 Camera table (camera_info)

[0042]

[0043] In the above inspection plan generation method, task description information corresponding to the substation inspection task is obtained. The task description information is parsed to obtain regional keywords, object keywords, and algorithm keywords. The algorithm name that matches the algorithm keyword is determined. Based on the regional keywords, object keywords, and algorithm name, matching target preset position information is retrieved. The target preset position information includes a preset position identifier and a visual acquisition device identifier. Based on the algorithm name, preset position identifier, and visual acquisition device identifier, an inspection plan corresponding to the inspection task is generated. This achieves a solution that can automatically generate inspection plans and improves inspection efficiency.

[0044] Since a substation typically has thousands of cameras, and each camera can contain 50 to 100 preset positions, manual inspection plans must be developed one by one, which is labor-intensive and prone to omissions. The inspection plan generation method provided in this application can automatically generate inspection calculations, is highly efficient, and is not prone to omissions. The inspection plan generation method provided in this application can be applied to the digital operation and maintenance system of a substation to automatically generate intelligent inspection plans, thereby improving operation and maintenance efficiency and intelligence.

[0045] In some embodiments, the target preset position information further includes an area name, an object name, and a preset acquisition type. According to the area keyword, object keyword, and algorithm name, the matching target preset position information is queried, including: determining the target acquisition type according to the algorithm name; according to the area keyword, object keyword, and target acquisition type, the matching target preset position information is queried, wherein the area name matches the area keyword, the object keyword matches the object name, and the preset acquisition type matches the target acquisition type.

[0046] Preset positions are named using a three-part structured naming convention: {area name}{object name}{collection type}. The area name refers to the name of the monitored area, the object name refers to the name of the monitored object, and the collection type is divided into white light and infrared. For example, preset position names could be "#4 Main Transformer_Phase C Low-Voltage Bushing_White Light," "#4 Main Transformer_Phase C Neutral Bushing_Infrared," and "#4 Main Transformer_Phase C Voltage Regulator Box_White Light."

[0047] Specifically, the first acquisition type is infrared, and the second acquisition type is white light. If the algorithm name contains the first acquisition type, the target acquisition type is determined to be the first acquisition type; otherwise, the target acquisition type is determined to be the second acquisition type.

[0048] In some embodiments, a region name matches a region keyword, which means the region name and the region keyword are identical or the region name contains the region keyword. An object keyword matches an object name, which means the object name and the object keyword are identical or the object name contains the object keyword. A preset collection type matches a target collection type, which means the preset collection type and the target collection type are identical.

[0049] In this embodiment, since the target preset position information also includes the area name, object name and preset acquisition type, and the acquisition type can be determined according to the algorithm name, the target preset position information can be quickly queried based on the keyword and the target acquisition type.

[0050] In some embodiments, querying and obtaining matching target pre-position information according to the area keyword, object keyword and target acquisition type includes querying and obtaining matching at least one piece of target pre-position information according to the area keyword, object keyword and target acquisition type.

[0051] The query conditions include: the area name contains the area keyword, the object name contains the object keyword, and the preset collection type is consistent with the target collection type.

[0052] In some embodiments, the preset position information is a row in a preset position table. The preset position table includes multiple preset position information, each of which includes a preset position identifier, a visual acquisition device identifier, and a preset position name. For example, if the visual acquisition device is a camera, the preset position table is shown in Table 2.

[0053] Table 2 Preset position table (preset_info)

[0054]

[0055] In some embodiments, the preset position table is stored in a database. The computer device can use SQL (Structured Query Language) query statements to search the preset position table for matching target preset position information, and fuzzy query can be used. For example, if the region keyword is "main transformer", the object keyword is "casing", and the target acquisition type is "infrared", the SQL query statement is, for example:

[0056] SELECT * FROM preset_info;

[0057] WHERE area_name LIKE '%main variable%';

[0058] AND object_name LIKE '%casing%';

[0059] AND camera_type = 'infrared'.

[0060] Correspondingly, the query result may be: {(camera_id: 10b6f11028XXX), (preset_no: 119), (area_name: #4 main transformer), (object_name: C phase neutral point bushing), (camera_type, infrared)}.

[0061] In this embodiment, since the query conditions include: the area name contains the area keyword, the object name contains the object keyword, and the preset collection type is consistent with the target collection type, it is possible that there are multiple preset position information that meet the query conditions, so that at least one target preset position information can be queried. Therefore, when generating an inspection plan, the inspection plan can be generated in combination with at least one target preset position information. Compared with generating an inspection plan for one target preset position information, the inspection efficiency of the inspection plan can be improved.

[0062] In some embodiments, an inspection plan corresponding to the inspection task is generated based on the algorithm name, preset position identifier and visual acquisition device identifier, including: forming a triplet of the algorithm name, preset position identifier and visual acquisition device identifier; and generating an inspection plan corresponding to the inspection task based on the triplet.

[0063] The inspection plan contains a triple. For example, the triple is:

[0064] {

[0065] "device_id": "10b6f11028XXX";

[0066] "preset_id": 119;

[0067] “algorithm”: “Infrared temperature recognition algorithm”;

[0068] }.

[0069] In this embodiment, the algorithm name, preset position identifier and visual acquisition device identifier are formed into a triplet, and an inspection plan corresponding to the inspection task is generated based on the triplet. The inspection plan can be automatically generated, thereby improving the efficiency of generating the inspection plan.

[0070] In some embodiments, the algorithm name, preset position identifier and visual acquisition device identifier are formed into a triplet, including: in the case where there are multiple target preset position information, for each target preset position information, the preset position identifier and visual acquisition device identifier and the algorithm name in the target preset position information are formed into a triplet; based on the triplet, an inspection plan corresponding to the inspection task is generated, including: based on each triplet, an inspection plan corresponding to the inspection task is generated.

[0071] The inspection plan may include the generated triples.

[0072] Specifically, if the query conditions include: the area name contains the area keyword, the object name contains the object keyword, and the preset acquisition type is consistent with the target acquisition type, it is a fuzzy query, and it is possible to query multiple target preset position information, and multiple means at least two.

[0073] In some embodiments, when performing an inspection plan, each triplet may be executed sequentially, or each triplet may be executed in parallel. Each triplet may be understood as a sub-inspection plan.

[0074] In this embodiment, an inspection plan corresponding to an inspection task is generated based on each triplet. Compared with only one triplet in the inspection plan, multiple triplets can be executed simultaneously, thereby improving the inspection efficiency of the inspection plan.

[0075] In some embodiments, the target preset position information is retrieved from a preset position table, and the method further includes at least one of the following: regularly updating the inspection plan; or, when the visual acquisition device identifier in any preset position information in the preset position table changes, updating the relevant inspection plan.

[0076] Specifically, the computer equipment can adopt a dynamic update mechanism to synchronize the preset position data in full every day through a scheduled task, that is, to update the preset position identifier in the inspection plan.

[0077] In some embodiments, when the computer device determines that the visual acquisition device has changed, an incremental update is triggered in real time.

[0078] In this embodiment, the inspection plan is updated regularly, or when the visual acquisition device identifier in any preset position information in the preset position table changes, the relevant inspection plan is updated. The inspection plan can be updated in time to ensure that the data recorded in the inspection plan is always consistent with the actual situation on site, thereby enhancing the reliability and adaptability of the inspection.

[0079] In some embodiments, as Figure 3 As shown, a method for generating an inspection plan is provided. The method can be executed by a terminal or a server, or can be executed by both the terminal and the server. The method is described by taking the application of the method to a computer device as an example, including:

[0080] Step 302: Obtain task description information corresponding to the inspection task of the substation, and parse the task description information to obtain area keywords, object keywords, and algorithm keywords.

[0081] Step 304: Determine the algorithm name that matches the algorithm keyword, and determine the target acquisition type based on the algorithm name.

[0082] Step 306: According to the region keyword, the object keyword and the target acquisition type, the matching target preset position information is queried and obtained. The target preset position information includes a preset position identifier and a visual acquisition device identifier.

[0083] Step 308: The algorithm name, the preset position identifier, and the visual acquisition device identifier are combined into a triplet.

[0084] Step 310: Generate an inspection plan corresponding to the inspection task based on the triplet.

[0085] In this embodiment, a solution is implemented that can automatically generate inspection plans, eliminating the tedious work of manually pre-configuring special inspection plans. This not only reduces time-consuming and error-prone manual operations, but also improves the efficiency and accuracy of substation equipment inspections.

[0086] It should be understood that, although the various steps in the flowcharts involved in the various embodiments described above are displayed in sequence according to the instructions of the arrows, these steps are not necessarily executed in sequence in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and these steps can be executed in other orders. Moreover, at least a portion of the steps in the flowcharts involved in the various embodiments described above can include multiple steps or multiple stages, and these steps or stages are not necessarily executed and completed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a portion of steps or stages in other steps.

[0087] Based on the same inventive concept, the present application also provides an inspection plan generation device for implementing the inspection plan generation method described above. The implementation solution provided by this device is similar to the implementation solution described in the above method. Therefore, the specific limitations in one or more embodiments of the inspection plan generation device provided below can be found in the above limitations on the inspection plan generation method and will not be repeated here.

[0088] In some embodiments, as Figure 4 As shown, an inspection plan generation device is provided, including: an information parsing module 402, an information query module 404 and a plan generation module 406, wherein:

[0089] The information parsing module 402 is used to obtain task description information corresponding to the inspection task of the substation, and parse the task description information to obtain area keywords, object keywords and algorithm keywords.

[0090] The information query module 404 is used to determine the algorithm name that matches the algorithm keyword, and query and obtain the matching target preset position information based on the area keyword, object keyword and algorithm name. The target preset position information includes a preset position identifier and a visual acquisition device identifier.

[0091] The plan generation module 406 is used to generate an inspection plan corresponding to the inspection task based on the algorithm name, the preset position identifier and the visual acquisition device identifier.

[0092] In some embodiments, the target preset position information also includes the area name, object name and preset acquisition type. The information query module 404 is also used to determine the target acquisition type based on the algorithm name; based on the area keyword, object keyword and target acquisition type, the query obtains the matching target preset position information, wherein the area name matches the area keyword, the object keyword matches the object name, and the preset acquisition type matches the target acquisition type.

[0093] In some embodiments, the information query module 404 is further used to query and obtain at least one matching target preset position information based on the area keyword, object keyword and target acquisition type; wherein the query conditions include: the area name contains the area keyword, the object name contains the object keyword, and the preset acquisition type is consistent with the target acquisition type.

[0094] In some embodiments, the plan generation module 406 is further configured to form a triplet of the algorithm name, the preset position identifier, and the visual acquisition device identifier; and generate an inspection plan corresponding to the inspection task based on the triplet.

[0095] In some embodiments, the plan generation module 406 is also used to form a triplet of the preset position identifier, visual acquisition device identifier and algorithm name in the target preset position information when there are multiple target preset position information; and generate an inspection plan corresponding to the inspection task based on each triplet.

[0096] In some embodiments, the target preset position information is queried from a preset position table, and the device also includes an update module, which is used to perform at least one of the following: regularly updating the inspection plan; or updating the relevant inspection plan when the visual acquisition device identifier in any preset position information in the preset position table changes.

[0097] Each module in the inspection plan generation device can be implemented in whole or in part through software, hardware, or a combination thereof. Each module can be embedded in or independent of a processor in a computer device in hardware form, or can be stored in a memory in the computer device in software form, so that the processor can call and execute the corresponding operations of each module.

[0098] In some embodiments, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as follows: Figure 5 As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, abbreviated as I / O) and a communication interface. The processor, memory and input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and computer program in the non-volatile storage medium. The database of the computer device is used to store data involved in the inspection plan generation method. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a method for generating an inspection plan is implemented.

[0099] In some embodiments, a computer device is provided. The computer device may be a terminal, and its internal structure diagram may be as follows: Figure 6As shown. The computer device includes a processor, memory, an input / output interface, a communication interface, a display unit, and an input device. The processor, memory, and input / output interface are connected via a system bus, and the communication interface, display unit, and input device are connected to the system bus via the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and computer program in the non-volatile storage medium. The input / output interface of the computer device is used to exchange information between the processor and external devices. The communication interface of the computer device is used to communicate with external terminals via wired or wireless means, and the wireless means can be implemented via Wi-Fi, a mobile cellular network, near-field communication (NFC), or other technologies. When the computer program is executed by the processor, a method for generating an inspection plan is implemented. The display unit of the computer device is used to form a visually visible image, and can be a display screen, a projection device, or a virtual reality imaging device. The display screen can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covering the display screen, or a button, trackball or touchpad set on the computer device casing, or an external keyboard, touchpad or mouse.

[0100] Those skilled in the art will understand that Figure 5 and Figure 6 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0101] In some embodiments, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the steps in the above-mentioned inspection plan generation method when executing the computer program.

[0102] In some embodiments, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps in the above-mentioned inspection plan generation method are implemented.

[0103] In some embodiments, a computer program product is provided, comprising a computer program, which implements the steps in the above-mentioned inspection plan generation method when executed by a processor.

[0104] Those skilled in the art will understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. In particular, any reference to memory, database, or other media used in the embodiments provided in this application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The databases involved in the various embodiments provided herein may include at least one of a relational database and a non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the various embodiments provided herein may be, but are not limited to, general-purpose processors, central processing units (CPUs), graphics processing units (GPUs), digital signal processors (DSPs), programmable logic devices (PLDs), quantum computing-based data processing logic devices, artificial intelligence (AI) processors, and the like.

[0105] The technical features of the above embodiments can be combined arbitrarily. In order to make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0106] The above-described embodiments merely represent several implementation methods of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present application. It should be noted that a person of ordinary skill in the art may make various modifications and improvements without departing from the spirit of the present application, and these modifications and improvements fall within the scope of protection of the present application. Therefore, the scope of protection of the present application shall be determined by the appended claims.

Claims

1. A method for generating an inspection plan, characterized in that: The method comprises: Obtaining task description information corresponding to the inspection task of the substation, and parsing the task description information to obtain area keywords, object keywords, and algorithm keywords; Determine an algorithm name that matches the algorithm keyword, and query and obtain matching target preset position information based on the area keyword, the object keyword, and the algorithm name, where the target preset position information includes a preset position identifier and a visual acquisition device identifier; An inspection plan corresponding to the inspection task is generated based on the algorithm name, the preset position identifier and the visual acquisition device identifier.

2. The method according to claim 1, characterized in that The target preset position information further includes an area name, an object name, and a preset acquisition type. The querying and obtaining the matching target preset position information based on the area keyword, the object keyword, and the algorithm name includes: Determine the target acquisition type according to the algorithm name; According to the area keyword, the object keyword and the target acquisition type, matching target preset position information is queried and obtained, wherein the area name matches the area keyword, the object keyword matches the object name, and the preset acquisition type matches the target acquisition type.

3. The method according to claim 2, characterized in that The querying and obtaining matching target preset position information according to the area keyword, the object keyword, and the target acquisition type includes: querying and obtaining at least one matching target preset position information according to the area keyword, the object keyword, and the target acquisition type; The query conditions include: the area name contains the area keyword, the object name contains the object keyword, and the preset acquisition type is consistent with the target acquisition type.

4. The method according to any one of claims 1 to 3, characterized in that Generating an inspection plan corresponding to the inspection task based on the algorithm name, the preset position identifier, and the visual acquisition device identifier includes: The algorithm name, the preset position identifier and the visual acquisition device identifier form a triplet; An inspection plan corresponding to the inspection task is generated based on the triplet.

5. The method according to claim 4, characterized in that The algorithm name, the preset position identifier, and the visual acquisition device identifier are formed into a triplet, including: In the case where there are multiple target preset position information, for each target preset position information, the preset position identifier and the visual acquisition device identifier in the target preset position information and the algorithm name are combined to form a triplet; Generating an inspection plan corresponding to the inspection task based on the triplet includes: An inspection plan corresponding to the inspection task is generated based on each of the triples.

6. The method according to any one of claims 1 to 3, characterized in that The target preset position information is retrieved from a preset position table, and the method further includes at least one of the following: regularly updating the inspection plan; or, When the visual acquisition device identifier in any preset position information in the preset position table changes, the relevant inspection plan is updated.

7. A patrol inspection plan generating device, characterized in that: The device comprises: An information parsing module is used to obtain task description information corresponding to the inspection task of the substation, and parse the task description information to obtain area keywords, object keywords and algorithm keywords; An information query module, configured to determine an algorithm name that matches the algorithm keyword, and query and obtain matching target preset position information based on the area keyword, the object keyword, and the algorithm name, wherein the target preset position information includes a preset position identifier and a visual acquisition device identifier; A plan generation module is used to generate an inspection plan corresponding to the inspection task based on the algorithm name, the preset position identifier and the visual acquisition device identifier.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

10. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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