A method for checking the connection of equipment components in power grid monitoring system based on neural network technology

Abstract

The present application relates to a method for verifying the connection of equipment components in a power grid monitoring system based on neural network technology. The method comprises: responding to a power site drawing detection operation, obtaining the connection information of the component interface in the power site drawing, determining the component interface information that does not meet the preset component interface connection specification requirements based on the component interface connection information and the trained component interface specification model, obtaining component interface problem information, and generating an error prompt image based on the component interface problem information, wherein the component interface specification model is trained based on the component interface specification information. The above method can save the tedious work of manually detecting the component interface, and can realize accurate detection of the component interface connection without repeated detection, which greatly improves the detection efficiency.

Description

Technical Field

[0001] The present application relates to the field of electric power grid technology, and in particular to a method, device, computer equipment and storage medium for verifying the connection of equipment components in a power grid monitoring system based on neural network technology. Background Art

[0002] With the increasing application of electronic technology in power grid systems, research on graphic systems applied to power systems has attracted much attention. Electrical wiring diagrams are relatively important graphics in power grids. Power workers can use them to monitor the operating status of each node in the entire distribution network and analyze important data such as the topological structure of the power grid.

[0003] Traditionally, the wiring diagram of electrical equipment components is mainly drawn by technicians on a drawing system. Due to the high complexity of power stations, it is inevitable that there will be problems with incorrect connections between components during the drawing process. Therefore, it is essential to detect the electrical equipment components of power stations.

[0004] At present, the detection method of electrical equipment components at power stations is usually to manually check the drawings of electrical equipment components by non-drawing technicians. The above method takes a long time to check and is prone to misjudgment due to the high workload, so that the power station needs to perform multiple inspections. As a result, the current detection method of electrical equipment components at power stations has the problem of low detection efficiency. Summary of the invention

[0005] Based on this, it is necessary to provide a method, device, computer equipment and storage medium for verifying the connection of equipment components in a power grid monitoring system based on neural network technology that can detect efficiency in order to solve the above technical problems.

[0006] A method for verifying connection of equipment components in a power grid monitoring system based on neural network technology, the method comprising:

[0007] In response to the power site drawing detection operation, obtaining connection information of component interfaces in the power site drawing;

[0008] According to the connection information of the component interface and the trained component interface specification model, the component interface information that does not meet the preset component interface connection specification requirements is determined to obtain the component interface problem information;

[0009] Generate error prompt images based on component interface problem information;

[0010] Among them, the component interface specification model is trained based on the specification information of the component interface.

[0011] In one embodiment, according to the connection information of the component interface and the trained component interface specification model, the component interface information that does not meet the preset component interface connection specification requirements is determined, and before obtaining the component interface problem information, the method further includes:

[0012] Build the initial component interface specification model;

[0013] Obtain the specification information of component interfaces and construct a specification information matrix;

[0014] According to the specification information matrix and the operating status labels of the preset power sites, the initial component interface specification model is trained and constructed to obtain the component interface specification model.

[0015] In one embodiment, generating an error prompt image based on component interface problem information includes:

[0016] If the component interface problem information indicates that the interfaces of two components of different types do not meet the preset component interface connection specification requirements, an error prompt image corresponding to a power line is generated according to the component interface problem information, and the power line is used to connect the interfaces of the two components of different types.

[0017] In one embodiment, generating an error prompt image based on component interface problem information includes:

[0018] If the component interface problem information indicates that an interface of a component does not meet the preset component interface connection specification requirements, an error prompt image corresponding to the interface is generated according to the component interface problem.

[0019] In one embodiment, after generating an error prompt image based on the component interface problem information, the method further includes:

[0020] In response to the operation information of the error prompt image, the component interface problem information is displayed, and according to the component interface specification model, modification suggestion information is generated and displayed.

[0021] In one embodiment, generating an error prompt image based on component interface problem information includes:

[0022] Based on the component interface problem information, combined with the preset correspondence between the component interface problem information and the error prompt image, an error prompt image is generated.

[0023] In one embodiment, the error prompt image includes error prompt images of different colors and different shapes.

[0024] A device for checking connection of equipment components in a power grid monitoring system based on neural network technology, the device comprising:

[0025] A data acquisition module, for responding to a power site drawing detection operation and acquiring connection information of component interfaces in the power site drawing;

[0026] A component interface detection module is used to determine the component interface information that does not meet the preset component interface connection specification requirements according to the component interface connection information and the trained component interface specification model, and obtain component interface problem information, wherein the component interface specification model is trained based on the component interface specification information;

[0027] The visualization processing module is used to generate error prompt images based on component interface problem information.

[0028] A computer device comprises a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the following steps are implemented:

[0029] In response to the power site drawing detection operation, obtaining connection information of component interfaces in the power site drawing;

[0030] According to the connection information of the component interface and the trained component interface specification model, the component interface information that does not meet the preset component interface connection specification requirements is determined to obtain the component interface problem information;

[0031] Generate error prompt images based on component interface problem information;

[0032] Among them, the component interface specification model is trained based on the specification information of the component interface.

[0033] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the following steps:

[0034] In response to the power site drawing detection operation, obtaining connection information of component interfaces in the power site drawing;

[0035] According to the connection information of the component interface and the trained component interface specification model, the component interface information that does not meet the preset component interface connection specification requirements is determined to obtain the component interface problem information;

[0036] Generate error prompt images based on component interface problem information;

[0037] Among them, the component interface specification model is trained based on the specification information of the component interface.

[0038] The above-mentioned power grid monitoring system equipment component connection verification method, device, computer equipment and storage medium based on neural network technology pre-trains the component interface specification model according to the component interface specification information, detects the connection information of the component interface through the component interface specification model, obtains non-standard component interface problem information, and generates an error prompt image based on the component interface problem information, so that the user can know the location of the problem at the power station according to the error prompt image, and then can solve the interface problem of the detection component, and improve the accuracy of component connection detection. In summary, the above scheme saves the tedious work of manually detecting the component interface, and can realize the accurate detection of the component interface connection without repeated detection, which greatly improves the detection efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 A schematic diagram of a flow chart of a method for verifying connection of equipment components of a power grid monitoring system based on a neural network technology in one embodiment;

[0040] Figure 2 A flowchart of the steps of training a component interface specification model in one embodiment;

[0041] Figure 3 A schematic diagram of a flow chart of a method for verifying connection of equipment components of a power grid monitoring system based on a neural network technology in another embodiment;

[0042] Figure 4 A structural block diagram of a device for checking the connection of equipment components of a power grid monitoring system based on a neural network technology in one embodiment;

[0043] Figure 5 It is a structural block diagram of a device for checking the connection of equipment components of a power grid monitoring system based on a neural network technology in another embodiment;

[0044] Figure 6 FIG. 4 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0045] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0046] In one embodiment, Figure 1 As shown, a method for checking the connection of equipment components in a power grid monitoring system based on neural network technology is provided. This embodiment uses the method applied to a terminal as an example. It can be understood that the method can also be applied to a server, and can also be applied to a system including a terminal and a server, and is implemented through the interaction between the terminal and the server. In this embodiment, the method includes the following steps:

[0047] Step 202, in response to the power site drawing detection operation, obtain connection information of component interfaces in the power site drawing.

[0048] In actual applications, after completing the power site drawing work, or after completing the phased work of the power site drawing work, the user needs to detect the existing power site drawing, and can perform the power site drawing detection operation on the power grid drawing platform of the terminal, and then, in response to the power site drawing detection operation, start the detection process of the connection information of the component interface in the power site, and obtain the connection information of the component interface in the pre-stored power site drawing. The connection information of the component interface can be a connection diagram of the component interface. It should be noted that the power site drawing detection operation can be a single-click operation on the power site, or a double-click operation on the power site, and this embodiment does not specifically limit it.

[0049] Step 204, according to the connection information of the component interface and the trained component interface specification model, determine the component interface information that does not meet the preset component interface connection specification requirements, and obtain component interface problem information. The component interface specification model is trained based on the component interface specification information.

[0050] The specification information includes IEC 61970 specification information. Each component interface in the power site needs to comply with the IEC 61970 specification information when connected, so that the power site can operate normally. Specifically, the specification information refers to the connection logic relationship between devices and the connection line information of the connection. By learning the neural network based on the specification information, a component interface specification model (hereinafter referred to as the specification model) can be obtained. The specification model includes the correct connection image of each component interface in the power site. Different power sites have different power site specifications. For example, the specification information in the power site complies with the IEC 61970 standard, and the connection logic relationship between devices and the connection line information of the connection can be generated according to the IEC 61970 standard.

[0051] In this embodiment, the component interface specification model is obtained by training based on the specification information of the component interface. Specifically, the component interface specification model can be obtained by performing deep learning convolution calculation on the specification information of the component interface according to the neural network algorithm. Then, the connection information of each component interface can be traversed according to the specification model, so that the component interface information that does not conform to the specification information can be determined, and the component interface information is analyzed to obtain interface problem information. Assuming that the connection information of the component interface is a connection diagram of at least 3 control lines and one transmission line between device A and device B, then whether the connection between device A and device B in the power site drawing conforms to the specification model can be determined by comparing the power site drawing with the specification model. When the power site drawing has a missing connection line or a connection error, an error prompt image is generated. By checking the connection information of each component interface through the component interface specification model, the interface problem of the component can be quickly detected, such as the lack of a connection line or a connection error, and the component interface problem information is obtained.

[0052] Step 206: Generate an error prompt image based on the component interface problem information.

[0053] After obtaining component interface problem information, an error prompt image may be generated at the component interface where the problem occurs. Specifically, different types of error prompt images may be generated according to different interface problem information. The error prompt image may include image information, or may include image information and error prompt text information. By generating an error prompt image, the user can intuitively know the component interface where the problem occurs, and then solve the interface problem of the detection component.

[0054] In the above-mentioned power grid monitoring system equipment component connection verification method based on neural network technology, the component interface specification model is pre-trained according to the specification information of the component interface, and the connection information of the component interface is detected through the component interface specification model to obtain non-standard component interface problem information, and based on the component interface problem information, an error prompt image is generated, so that the user can know where the problem occurs at the power station according to the error prompt image, and then the interface problem of the detection component can be solved, and the accuracy of component connection detection is improved. In summary, the above-mentioned scheme saves the tedious work of manual detection, and can realize accurate detection of component interface connection without repeated detection, which greatly improves the detection efficiency.

[0055] like Figure 2 As shown, in one embodiment, before step 204, the method further includes:

[0056] Step 203, constructing an initial component interface specification model;

[0057] Step 223, obtaining the specification information of the component interface and constructing a specification information matrix;

[0058] Step 243 , training and constructing an initial component interface specification model according to the specification information matrix and the operation status label of the preset power site, to obtain a component interface specification model.

[0059] The operating status labels of the preset power sites include 4 status labels: operation, hot standby, cold standby and maintenance. In this embodiment, before obtaining the specification model, it is necessary to build a learning model first. Specifically, firstly, the initial model of the convolutional neural network is created in advance, and the input layer, the first feature extraction layer, the first feature mapping layer, the second feature extraction layer, the second feature mapping layer, the convolution layer and the output layer are constructed in sequence to obtain the initial component interface specification model. Then, the specification information of the component interface is obtained, the specification information matrix is ​​constructed, and the convolutional neural network is trained layer by layer. The specification information matrix and the operating status label of the interface between the two devices are used as the input layer. After step-by-step transformation, the model parameters are determined to obtain the specification model. In this embodiment, by training the component interface specification model, the component interface detection can be quickly completed through the component interface specification model, thereby improving the detection efficiency.

[0060] In one embodiment, the error prompt image includes error prompt images of different colors and different shapes.

[0061] During specific implementation, the error prompt image can be divided into images with different filling colors and shapes according to different component interface problems. For example, a red cross-shaped image is generated on a certain component interface, and a blue dot-shaped image is generated on another component interface. This embodiment does not specifically limit it. In practical applications, the error prompt image corresponding to the power line is displayed as a connecting line image in the power grid drawing platform. For example, when the power line is overloaded, the error prompt image is a red image, when the power line overload reaches 80%, the error prompt image is a blue image, and when the power line overload is less than 80%, the error prompt image is a green image. In this embodiment, by generating error prompt images of different colors and shapes, the problem type of the component interface can be very intuitively reflected.

[0062] like Figure 3 As shown, in one embodiment, generating an error prompt image based on component interface problem information includes: Step 226, generating an error prompt image based on the component interface problem information and a preset correspondence between the component interface problem information and the error prompt image.

[0063] In specific implementation, different correspondences between component interface problem information and output images are preset, and corresponding error prompt images can be directly generated based on the component interface problem information. For example, when the interface problem information is a connection error between interfaces, an image corresponding to the connection error is output. In this embodiment, the corresponding error prompt image can be quickly and accurately generated through the preset correspondence between component interface problem information and error prompt images.

[0064] In one embodiment, generating an error prompt image based on component interface problem information includes: if the component interface problem information indicates that the interface of two different types of components does not meet the preset component interface connection specification requirements, then generating an error prompt image corresponding to the power line according to the component interface problem information, and the power line is used to connect the interfaces of two different types of components.

[0065] In a specific implementation, if the component interface problem information is characterized as a problem with the interface of two different types of components, it is determined that the problem is a problem with the power line connecting the two interfaces. Then, the power line used to connect the interface of the two different types of components can be visualized according to the component interface problem information to generate an error prompt image corresponding to the power line. In this embodiment, an error prompt image can be generated on the power line to inform the user that there is a problem with the power line. Specifically, the problem with the power line can be a problem with the specification of the power line, or a problem with the type of the power line, which is not specifically limited in this embodiment. The error prompt image can be a linear image of a first color generated on the power line, or a cross-shaped image generated in the middle of the power line, which is not specifically limited in this embodiment. In this embodiment, by generating an error prompt image, the user can be intuitively informed of the problem so that the problem can be quickly solved.

[0066] In one embodiment, generating an error prompt image based on component interface problem information includes: if the component interface problem information indicates that an interface of a component does not meet the preset component interface connection specification requirements, then generating an error prompt image corresponding to the interface according to the component interface problem.

[0067] If the component interface problem information is characterized as a problem with an interface of a component, the problematic interface can be visualized according to the interface problem information, and an error prompt image can be generated on the interface to inform the user that there is a problem with the interface. Specifically, a dot-shaped image can be generated on the interface. It is understandable that in other embodiments, images of triangles and other shapes can be generated on the interface, which is not limited here. In this embodiment, by generating different error prompt images according to different component interface problems, it is possible to easily distinguish interface problems, which is intuitive and clear.

[0068] In one embodiment, after generating an error prompt image based on component interface problem information, it also includes: step 208, responding to the operation information of the error prompt image, displaying the component interface problem information, and generating and displaying modification suggestion information according to the component interface specification model.

[0069] In specific implementation, after the error prompt image is generated, the user can know the specific location of the component interface with the problem through the error prompt image, and then the user can click on the error prompt image to obtain the interface problem information and modification suggestion information. In response to the click operation of the error prompt image, the component interface problem information is displayed, and at the same time, the modification suggestion information is generated according to the specification model. After the modification suggestion information is generated, the modification suggestion information can be visualized to generate a connection line, which can include a correct connection relationship or a correct power line specification, which is not specifically limited in this embodiment. The operation information of the error prompt image can be a single-click operation on the error prompt image or a double-click operation on the error prompt image, which is not specifically limited in this embodiment. The component interface problem information can be displayed in the form of a dialog box and text, or in the form of pure text, which is not specifically limited here. In this embodiment, by displaying the component interface problem information and generating modification suggestions, the correct component interface connection relationship can be intuitively reflected, so that the user can quickly know the specific problem points, and adjust the connection relationship of the component interface in time accordingly, so as to improve the efficiency of correcting drawing problems.

[0070] It should be understood that, although the steps in each flow chart involved in the above-described embodiment are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be executed in other orders. Moreover, at least a portion of the steps in each flow chart involved in the above-described embodiment may include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily carried out in sequence, but can be executed in turn or alternately with other steps or at least a portion of the steps or stages in other steps.

[0071] In one embodiment, Figure 4 As shown, a device for checking the connection of equipment components of a power grid monitoring system based on a neural network technology is provided, comprising: a data acquisition module 510, a component interface detection module 520 and a visualization processing module 530, wherein:

[0072] The data acquisition module 510 is used to respond to the power site drawing detection operation and acquire the connection information of the component interface in the power site drawing.

[0073] The component interface detection module 520 is used to determine the component interface information that does not meet the preset component interface connection specification requirements based on the component interface connection information and the trained component interface specification model, and obtain component interface problem information, wherein the component interface specification model is trained based on the component interface specification information.

[0074] The visualization processing module 530 is used to generate an error prompt image based on the component interface problem information.

[0075] The above-mentioned power grid monitoring system equipment component connection verification device based on neural network technology pre-trains the component interface specification model according to the component interface specification information, detects the connection information of the component interface through the component interface specification model, obtains the non-standard component interface problem information, and generates an error prompt image based on the component interface problem information, so that the user can know the location of the problem at the power station according to the error prompt image, and then can solve the interface problem of the detection component, and improve the accuracy of component connection detection. In summary, by using the above-mentioned device, the tedious work of manual detection is eliminated, and the accurate detection of component interface connection can be achieved without repeated detection, which greatly improves the detection efficiency.

[0076] like Figure 5 As shown, in one embodiment, the device also includes a model training module 540, which is used to construct an initial component interface specification model, obtain specification information of the component interface, construct a specification information matrix, and train and construct the initial component interface specification model based on the specification information matrix and the operating status label of the preset power site to obtain the component interface specification model.

[0077] In one embodiment, the visualization processing module 530 is also used to generate an error prompt image corresponding to a power line based on the component interface problem information if the component interface problem information indicates that the interface of two different types of components does not meet the preset component interface connection specification requirements. The power line is used to connect the interfaces of two different types of components.

[0078] In one embodiment, the visualization processing module 530 is further configured to generate an error prompt image corresponding to the interface according to the component interface problem if the component interface problem information indicates that an interface of a component does not meet the preset component interface connection specification requirements.

[0079] In one embodiment, the device further includes a modification suggestion generating module 550, which is used to respond to the operation information of the error prompt image, display the component interface problem information, and generate modification suggestion information according to the component interface specification model.

[0080] In one embodiment, the visualization processing module 530 is further used to perform visualization processing on the modification suggestion information to generate connection lines.

[0081] For the specific embodiments of the power grid monitoring system equipment component connection verification device based on neural network technology, please refer to the embodiments of the power grid monitoring system equipment component connection verification method based on neural network technology mentioned above, which will not be repeated here. Each module in the above-mentioned power grid monitoring system equipment component connection verification device based on neural network technology can be fully or partially implemented by software, hardware and their combination. The above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0082] In one embodiment, a computer device is provided. The computer device may be a terminal, and its internal structure diagram may be as follows: Figure 6 As shown. The computer device includes a processor, a memory, a communication interface, a display screen and an input device connected through a system bus. Among them, 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 the computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be achieved through WIFI, an operator network, NFC (near field communication) or other technologies. When the computer program is executed by the processor, a method for connecting and checking components of a power grid monitoring system device based on neural network technology is implemented. The display screen of the computer device 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 covered on the display screen, or a key, trackball or touchpad set on the computer device housing, or an external keyboard, touchpad or mouse, etc.

[0083] Those skilled in the art will understand that 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 those shown in the figure, or combine certain components, or have a different arrangement of components.

[0084] In one embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the computer program, the steps in the above-mentioned method for verifying the connection of equipment components of a power grid monitoring system based on neural network technology are implemented.

[0085] In one embodiment, 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 power grid monitoring system device element connection verification method based on neural network technology are implemented.

[0086] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and 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. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory or optical memory, etc. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

[0087] The technical features of the above embodiments may be combined arbitrarily. 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 specification.

[0088] The above-mentioned embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the patent of the present application shall be subject to the attached claims.

Claims

1. A method for checking the connection of equipment components in a power grid monitoring system based on neural network technology, characterized in that: The method comprises: In response to the power site drawing detection operation, obtaining connection information of component interfaces in the power site drawing; According to the connection information of the component interface and the trained component interface specification model, the component interface information that does not meet the requirements of the preset component interface connection specification is determined to obtain component interface problem information; Based on the component interface problem information, generate an error prompt image; Before determining the component interface information that does not meet the preset component interface connection specification requirements based on the connection information of the component interface and the trained component interface specification model, and obtaining the component interface problem information, the method includes: Build the initial component interface specification model; Obtain the specification information of component interfaces and construct a specification information matrix; The initial component interface specification model is trained according to the specification information matrix and the operation status labels of the preset power sites to obtain the component interface specification model, wherein the operation status labels include: operation, hot standby, cold standby and maintenance.

2. The method for checking the connection of equipment components in a power grid monitoring system based on neural network technology according to claim 1 is characterized in that: The generating an error prompt image based on the component interface problem information includes: If the component interface problem information indicates that the interfaces of two different types of components do not meet the preset component interface connection specification requirements, an error prompt image corresponding to a power line is generated according to the component interface problem information, and the power line is used to connect the interfaces of the two different types of components.

3. The method for checking the connection of equipment components in a power grid monitoring system based on neural network technology according to claim 2 is characterized in that: The generating an error prompt image based on the component interface problem information includes: If the component interface problem information indicates that an interface of a component does not meet the requirements of a preset component interface connection specification, an error prompt image corresponding to the interface is generated according to the component interface problem information.

4. The method for checking the connection of equipment components in a power grid monitoring system based on neural network technology according to claim 1 is characterized in that: After generating an error prompt image based on the component interface problem information, the method further includes: In response to a click operation on the error prompt image, component interface problem information is displayed, and modification suggestion information is generated and displayed based on the component interface specification model.

5. The method for checking the connection of equipment components in a power grid monitoring system based on neural network technology according to claim 1 is characterized in that: The generating an error prompt image based on the component interface problem information includes: Based on the component interface problem information and in combination with the preset correspondence between the component interface problem information and the error prompt image, an error prompt image is generated.

6. The method for checking the connection of equipment components in a power grid monitoring system based on neural network technology according to claim 1 is characterized in that: The error prompt images include error prompt images of different colors and different shapes.

7. A device for checking the connection of equipment components in a power grid monitoring system based on neural network technology, characterized in that: The device comprises: A data acquisition module, for responding to a power site drawing detection operation and acquiring connection information of component interfaces in the power site drawing; A component interface detection module is used to determine the component interface information that does not meet the requirements of the preset component interface connection specification based on the connection information of the component interface and the trained component interface specification model, and obtain component interface problem information; A visualization processing module, used for generating an error prompt image based on the component interface problem information; The model training module is used to construct an initial component interface specification model; obtain the specification information of the component interface and construct a specification information matrix; train the initial component interface specification model according to the specification information matrix and the operation status label of the preset power site to obtain the component interface specification model, wherein the operation status label includes: operation, hot standby, cold standby and maintenance.

8. The device according to claim 7, characterized in that The device also includes: a modification suggestion generating module, which is used to respond to the operation information of the error prompt image, display the component interface problem information, and generate modification suggestion information according to the component interface specification model.

9. 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.

10. 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.

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