Transparent cable display method and device, electronic equipment and medium

Abstract

The embodiment of the invention discloses a transparent cable display method and device, electronic equipment and a medium. A specific embodiment of the method comprises the steps of inputting cable inquiry information on a cable digital twinning interface in response to determining that current time is abnormal detection time corresponding to a target substation area; receiving reply information; in response to the received abnormal click entry, highlighting each cable control in the target cable area, and popping up an abnormal information entry pop-up window; in response to the received input anomaly detection information and the received saving click information corresponding to the real-time digital twin model, sending model parameter information to a transformer substation anomaly monitoring end so as to display cable anomaly information according to the model parameter information; and in response to the received maintenance request information and the maintenance scheme, indicating cable abnormity maintenance and transparent cable display. According to the embodiment, automatic cable anomaly detection in the target cable area can be timely and efficiently realized, and electric power accidents are avoided.

Description

Technical Field

[0001] Embodiments of this disclosure relate to the field of computer technology, and more specifically to transparent cable display methods, apparatus, electronic devices, and media. Background Technology

[0002] Currently, anomaly detection in power equipment has become a major research direction in the power industry. Timely detection of power equipment can prevent power accidents and the resulting loss of electrical property. For anomaly detection and related repair of cables in power equipment, the common approach is as follows: First, anomalies are directly detected manually using methods such as the bridge method. Then, the anomaly detection information is communicated to the anomaly monitoring terminal via communication equipment. Finally, repairs are performed manually based on relevant maintenance experience.

[0003] However, when using the above methods for cable anomaly detection and related repairs, the following technical problems often arise: Inspection and maintenance personnel may lack sufficient knowledge of the cable layout corresponding to the target substation, making inspection and maintenance more difficult and hindering timely detection and repair of cable anomalies. This leads to low inspection and maintenance efficiency and may result in power accidents.

[0004] The information disclosed in this background section is only intended to enhance the understanding of the background of the inventive concept, and therefore may contain information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0005] The summary portion of this disclosure is intended to provide a brief overview of the concepts, which will be described in detail in the detailed description portion. This summary portion is not intended to identify key or essential features of the claimed technical solutions, nor is it intended to limit the scope of the claimed technical solutions.

[0006] Some embodiments of this disclosure provide methods, apparatus, electronic devices, and media for displaying transparent cables to address one or more of the technical problems mentioned in the background section above.

[0007] In a first aspect, some embodiments of this disclosure provide a transparent cable display method, including: responding to the current time being the anomaly detection time corresponding to the target substation area, inputting cable inquiry information on the cable digital twin interface of the target handheld terminal; receiving response information sent by the substation anomaly monitoring terminal regarding the cable inquiry information, so as to display a real-time digital twin model corresponding to the target substation area on the target handheld terminal based on the response information; responding to receiving an anomaly click entry for the target cable area, highlighting each cable control within the target cable area in the real-time digital twin model, and popping up a pop-up for each cable control... An abnormal information entry pop-up window is generated; in response to receiving the abnormal detection information entered in each abnormal information entry pop-up window and receiving the save click information corresponding to the real-time digital twin model, the model parameter information of the real-time digital twin model for the target cable area is sent to the substation abnormal monitoring terminal to display the cable abnormal information corresponding to the target cable area according to the model parameter information. Each abnormal detection information is determined based on at least one cable abnormality detection method; in response to receiving the maintenance request information and maintenance plan for the target cable area, the target cable handling robot is instructed to perform cable abnormality maintenance and transparent cable display.

[0008] Secondly, some embodiments of this disclosure provide a transparent cable display device, including: an input unit configured to input cable inquiry information on a cable digital twin interface of a target handheld terminal in response to an anomaly detection time corresponding to a target substation area; a receiving unit configured to receive a response message sent by a substation anomaly monitoring terminal to the cable inquiry information, so as to display a real-time digital twin model of the target substation area on the target handheld terminal based on the response message; and a highlight display unit configured to, in response to receiving an anomaly click input for the target cable area, highlight each cable control within the target cable area in the real-time digital twin model, and pop up a pop-up for the cable control. The system includes a pop-up window for recording abnormal information for each cable control; a sending unit configured to, in response to receiving abnormal detection information entered in each abnormal information entry pop-up window and receiving save click information corresponding to the real-time digital twin model, send the model parameter information for the target cable area in the real-time digital twin model containing the added information to the substation abnormal monitoring terminal, so as to display the cable abnormal information corresponding to the target cable area according to the model parameter information, wherein each abnormal detection information is determined based on at least one cable abnormal detection method; and an instruction unit configured to, in response to receiving maintenance request information and maintenance plan for the target cable area, instruct the target cable handling robot to perform cable abnormality maintenance and transparent cable display.

[0009] Thirdly, some embodiments of this disclosure provide an electronic device, including: one or more processors; and a storage device having one or more programs stored thereon, such that when the one or more programs are executed by the one or more processors, the one or more processors implement the method as described in any implementation of the first aspect.

[0010] Fourthly, some embodiments of this disclosure provide a computer-readable medium having a computer program stored thereon, wherein the program, when executed by a processor, implements the method as described in any implementation of the first aspect.

[0011] The above embodiments of this disclosure have the following beneficial effects: Through the transparent cable display method of some embodiments of this disclosure, automated anomaly detection of cables within the target cable area can be achieved in a timely and efficient manner, avoiding power accidents. Specifically, the reason for the low efficiency of related anomaly detection is that inspection and maintenance personnel may not have sufficient understanding of the cable layout corresponding to the target substation, making inspection and maintenance more difficult and preventing timely anomaly detection and maintenance. This leads to low inspection and maintenance efficiency and may result in power accidents. Based on this, the transparent cable display method of some embodiments of this disclosure firstly, in response to the current time being the anomaly detection time corresponding to the target substation area, inputs cable query information into the cable digital twin interface of the target handheld terminal. Here, upon reaching the anomaly detection time, the target handheld terminal requests cable query information to obtain a real-time digital twin model of the target substation area at the current time. Here, by inputting information through the cable digital twin interface, model parameter information can be requested to initially construct a real-time digital twin model based on the model parameter information. Then, the system receives response information from the substation anomaly monitoring terminal regarding the aforementioned cable inquiry, and displays a real-time digital twin model of the target substation area on the target handheld terminal based on this response. By receiving the response information, a real-time digital twin model representing the layout of the target substation area can be constructed, allowing personnel at the target handheld terminal to understand the current layout. Next, in response to receiving an anomaly entry for the target cable area, the system highlights each cable control within the target cable area in the real-time digital twin model and displays an anomaly information entry pop-up for each cable control. The anomaly entry method, the highlighting method, and the generation of the anomaly information entry pop-up allow for timely and efficient recording of anomalies for each cable control, achieving efficient management of cable control anomaly information. Subsequently, in response to receiving anomaly detection information entered in each anomaly information entry pop-up window and receiving a save click notification for the corresponding real-time digital twin model, the system sends the model parameter information for the target cable area in the real-time digital twin model containing the added information to the substation anomaly monitoring terminal. This allows the system to display the cable anomaly information corresponding to the target cable area based on the model parameter information. Each anomaly detection information is determined based on at least one cable anomaly detection method. By sending the model parameter information to the substation anomaly monitoring terminal, the terminal can promptly obtain information on cable anomalies corresponding to the target substation area, facilitating timely detection of potential hazards and preventing power accidents. Finally, in response to receiving maintenance request information and maintenance plans for the target cable area, the system instructs the target cable handling robot to perform cable anomaly repairs and display the transparent cable.In summary, by transmitting the relevant parameter information of the digital twin model, not only can the operators of the target handheld terminal understand the layout of the target substation area in a timely manner, but the substation anomaly monitoring terminal can also obtain abnormal situations in a timely manner. Thus, the automated anomaly detection of cables in the target cable area can be realized in a timely and efficient manner, avoiding power accidents. Attached Figure Description

[0012] The above and other features, advantages, and aspects of the embodiments of this disclosure will become more apparent from the accompanying drawings and the following detailed description. Throughout the drawings, the same or similar reference numerals denote the same or similar elements. It should be understood that the drawings are schematic, and elements are not necessarily drawn to scale.

[0013] Figure 1 This is a flowchart of some embodiments of the transparent cable display method according to the present disclosure; Figure 2 These are schematic diagrams illustrating the structure of some embodiments of the transparent cable display device according to this disclosure; Figure 3 This is a schematic diagram of the structure of an electronic device suitable for implementing some embodiments of the present disclosure. Detailed Implementation

[0014] Embodiments of this disclosure will now be described in more detail with reference to the accompanying drawings. While some embodiments of this disclosure are shown in the drawings, it should be understood that this disclosure can be implemented in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided to provide a more thorough and complete understanding of this disclosure. It should be understood that the accompanying drawings and embodiments of this disclosure are for illustrative purposes only and are not intended to limit the scope of protection of this disclosure.

[0015] It should also be noted that, for ease of description, only the parts relevant to the invention are shown in the accompanying drawings. Unless otherwise specified, the embodiments and features described in this disclosure can be combined with each other.

[0016] It should be noted that the concepts of "first" and "second" mentioned in this disclosure are used only to distinguish different devices, modules or units, and are not used to limit the order of functions performed by these devices, modules or units or their interdependencies.

[0017] It should be noted that the terms "a" and "a plurality of" used in this disclosure are illustrative rather than restrictive, and those skilled in the art should understand that, unless otherwise expressly indicated in the context, they should be understood as "one or more".

[0018] The names of messages or information exchanged between multiple devices in the embodiments of this disclosure are for illustrative purposes only and are not intended to limit the scope of such messages or information.

[0019] This disclosure will now be described in detail with reference to the accompanying drawings and embodiments.

[0020] refer to Figure 1 The diagram illustrates a flow 100 of some embodiments of a transparent cable display method according to the present disclosure. This transparent cable display method includes the following steps: Step 101: In response to the anomaly detection time corresponding to the target substation area at the current time, input cable inquiry information into the cable digital twin interface corresponding to the target handheld terminal.

[0021] In some embodiments, in response to the current time being the anomaly detection time corresponding to the target substation area, the executing entity of the above transparent cable display method (e.g., an electronic device) can input cable query information on the cable digital twin interface corresponding to the target handheld terminal. Here, the current time is the current moment. The target substation area can be the location area of ​​the substation currently under anomaly monitoring. The target substation area can be represented by a coordinate set or by an area identifier. The anomaly detection time can be the time when anomaly detection of the cable is performed. The target handheld terminal can be a handheld electronic device. For example, the target handheld terminal can be a tablet computer. The target handheld terminal has a pre-installed cable digital twin application. Through the cable digital twin application, cable-related information can be queried and processed. The cable digital twin interface can be an operation interface related to the cable digital twin model. The cable digital twin interface supports various cable-related processing operations. For example, the cable digital twin interface can be an interface that supports querying the real-time cable digital twin model. The real-time cable digital twin model can be a digital twin model representing the cable layout within the target substation area at real-time. The aforementioned cable query information requests model parameter information from the digital twin model corresponding to the target substation area. The model parameter information can be the model structure parameters that constitute the digital twin model. In practice, the model parameter information may include: cable entity parameters, cable-related equipment entity parameters, virtual entity parameters, and connection parameters. Cable-related equipment may include: cabinet equipment and cable tray equipment.

[0022] Step 102: Receive the response information sent by the substation anomaly monitoring terminal regarding the above-mentioned cable inquiry information, so as to display the real-time digital twin model corresponding to the above-mentioned target substation area on the above-mentioned target handheld terminal based on the above-mentioned response information.

[0023] In some embodiments, the aforementioned executing entity can receive response information from the substation anomaly monitoring terminal regarding the cable inquiry information, and display a real-time digital twin model corresponding to the target substation area on the target handheld terminal based on the response information. The substation anomaly monitoring terminal can be a terminal monitoring abnormal conditions corresponding to a substation. In practice, the substation anomaly monitoring terminal can correspond to multiple substations. That is, it can monitor the occurrence of abnormal conditions corresponding to multiple substations. In practice, abnormal conditions can be abnormal conditions of various devices within a substation. That is, abnormal monitoring of various devices within the substation. The response information can be the current model parameter information of the cable digital twin model in response to the cable inquiry information.

[0024] Here, displaying a real-time digital twin model on the target handheld terminal allows operators to understand the layout of various devices within the target substation area at the current time, enabling targeted detection of subsequent anomalies.

[0025] Step 103: In response to receiving an abnormal click entry for the target cable area, the real-time digital twin model highlights each cable control within the target cable area and pops up an abnormal information entry pop-up window for each cable control.

[0026] In some embodiments, in response to receiving an abnormal click entry for a target cable area, the executing entity can highlight each cable control within the target cable area in the real-time digital twin model and pop up an abnormal information entry pop-up window for each cable control. The target cable area can be the area to be detected for cable anomalies after the relevant operator clicks and circles the area or inputs area information on the corresponding display interface of the real-time digital twin model. The highlighted display can be high brightness and target color display. Each cable control has a corresponding abnormal information entry pop-up window. The abnormal information entry pop-up window can be a pop-up window for entering abnormal information. By entering abnormal information in the abnormal information entry pop-up window, the abnormal status of the cable control at the current time can be determined, thereby realizing abnormal monitoring of each cable control. The abnormal information entry pop-up window can support the entry of detection information corresponding to the cable control for subsequent registration in the system.

[0027] In some optional implementations of certain embodiments, after step 103, the steps further include: The first step involves obtaining an anomaly detection information set for each cable control stored on the target handheld terminal, in response to the determination that the number of anomaly detection information to be input is higher than a first number and the number of devices corresponding to the target substation area is higher than a second number. The anomaly detection information includes: anomaly severity, anomaly type, anomaly description, and anomaly image. The number of anomaly detection information can be the number of anomaly detection information entries for each cable control entered by relevant technicians. The second method here can be a method where relevant technicians have already summarized the anomaly detection information for each cable control with anomalies, obtained an anomaly detection information set, and then entered the overall anomaly detection information based on this set. The first method here does not involve relevant technicians manually determining the anomalies of each cable control one by one using the target handheld terminal. The first number can be a pre-set number. The first number can be used as a metric to measure whether the anomaly detection information is massive. That is, when it exceeds the first number, it indicates that the number of anomaly detection information is massive. For example, the first number can be 300. The number of devices can be the number of devices in each substation in the target substation area. The second number can be a pre-set number. The second number can be used to measure the scale of the target substation area. That is, when the number exceeds the second number, it indicates that the target substation area is relatively large. In practice, the anomaly detection information set can be a pre-collected, pre-selected information set stored in the target handheld terminal.

[0028] The second step involves generating an anomaly instruction for at least one first anomaly detection piece of information, in response to the determination that at least one anomaly detection piece of information in the aforementioned anomaly detection information set has an anomaly severity higher than the target severity. The target severity can be a pre-set anomaly severity level. In practice, the target severity level can be an indicator used to measure the anomaly severity. In practice, for anomaly severity in the form of a score, anomaly detection information higher than the target severity level indicates a severe anomaly, while anomaly detection information lower than the target severity level indicates a milder anomaly. For example, for information in the form of a label, a label with a severity higher than the label corresponding to the target severity level indicates that the anomaly detection information corresponds to a more severe anomaly severity. The target severity level can be set based on historical experience. The anomaly instruction can be a pre-formatted instruction to expedite the processing of at least one anomaly detection piece of information. That is, the anomaly detection information within the anomaly instruction is the detection information that needs to be prioritized and is of a more severe severity. The anomaly detection information includes: anomaly severity, anomaly type, anomaly description, and anomaly image. The anomaly type can be the type of anomaly occurring in the cable control, or the problem type of the anomaly. The anomaly description can be a textual description of the anomaly detection information. The anomaly image can be an image captured in real-time of the anomaly condition of the cable control.

[0029] As an example, the aforementioned execution entity can fill at least one first anomaly detection instruction into the initial anomaly instruction (i.e., the instruction that has not yet been filled with information) to obtain the anomaly instruction.

[0030] The third step is to send the above-mentioned abnormal instructions to the substation abnormal monitoring terminal for rapid processing of at least one first abnormality detection information.

[0031] The fourth step is to query at least one cable control location corresponding to at least one of the aforementioned first anomaly detection information. Each first anomaly detection information has a unique corresponding cable control location. This cable control location can be the actual storage location of the cable control.

[0032] Here, given that the number of first anomaly detection information is often small, directly querying the cable control location is more efficient.

[0033] Fifth step: Based on the location of at least one cable control and the first anomaly detection information, update the real-time digital twin model to obtain the first updated real-time digital twin model.

[0034] In practice, for at least one cable control location, the state of the cable control at at least one model location corresponding to the real-time digital twin model can be determined. Then, the state of at least one cable control is replaced with the aforementioned first anomaly detection information to obtain the first updated real-time digital twin model.

[0035] The sixth step involves displaying the first real-time digital twin model difference parameter information, based on the first updated real-time digital twin model, in a first highlighted format. This first real-time digital twin model difference parameter information can be at least one module in the first updated real-time digital twin model where the state of a cable control has changed. This at least one module can be at least one element in the real-time digital twin model. That is, at least one simulated cable control element with a changed state is displayed in the first highlighted format. The first highlighting method can be a pre-set highlighting method. For example, the first highlighting method can be specially set for types of severe anomalies. For example, the first highlighting method can be a special display in red and with high brightness.

[0036] Step 7: At least one second anomaly detection message is sent to the target server corresponding to the substation anomaly monitoring terminal. This allows the control recognition model deployed on the target server to identify at least one cable control information corresponding to the at least one second anomaly detection message. The anomaly detection message set includes at least one first anomaly detection message and at least one second anomaly detection message. The target server can be a server providing computing resources. The server deploys a control recognition model. The control recognition model can be a neural network model for identifying cable controls. This control recognition model can be a conventional recognition model. However, the control recognition model can be pre-trained based on a cable control-related dataset. For example, the control recognition model can be a residual network-based recognition model. The cable control information can include: cable control type and cable location.

[0037] Here, the input to the control recognition model can be a single image or multiple images. When multiple images are input, the control recognition model can output the most matching cable control information with the highest probability among the multiple images. That is, given that the equipment information of each device within the substation area is fixed, in order to determine the most matching cable control information corresponding to multiple images, all multiple images can be input into the control recognition model to output at least one cable control information with the highest overall cable control recognition probability. Here, the control recognition model uses a cross-loss function during training to constrain the overall output to the highest probability.

[0038] As an example, the aforementioned execution entity can input at least one abnormal image from at least one second abnormal detection information into the control recognition model to obtain cable control information (i.e., the recognition result of the cable control).

[0039] Step 8: Based on the obtained at least one cable control information, arrange the positions of the at least one second anomaly detection information to obtain an anomaly detection information diagram. The anomaly detection information diagram can be a layout diagram where the second anomaly detection information is arranged according to the positions of the cable controls. The information layout of at least one second anomaly detection information in the anomaly detection information diagram corresponds one-to-one with the layout of at least one control position corresponding to at least one cable control information.

[0040] As an example, firstly, the aforementioned execution entity can generate an initial control layout diagram based on at least one control position included in at least one cable control information. Then, each of the second anomaly detection information from at least one second anomaly detection information is filled into the corresponding control position in the initial control layout diagram to obtain an anomaly detection information diagram.

[0041] Step nine involves inputting the aforementioned anomaly detection information graph into the real-time digital twin model to extract at least one second anomaly detection information. This information is then used to update the real-time digital twin model, resulting in a second updated real-time digital twin model. Here, the real-time digital twin model supports directly updating the element state of at least one relevant cable control element based on the information layout of the anomaly detection information in the anomaly detection information graph. By generating the anomaly detection information graph, the real-time digital twin model can directly replace the corresponding abnormal state of elements based on the information layout diagram in the anomaly detection information, thus obtaining the second updated real-time digital twin model.

[0042] Step 10 involves displaying the difference parameter information of the second real-time digital twin model in a second highlighted format, based on the aforementioned second updated real-time digital twin model. This difference parameter information can be at least one model element corresponding to a state change in the second updated real-time digital twin model. The second highlighted format can be a pre-set display format representing a minor anomaly. For example, the second highlighted display format can be a yellow, high-brightness display. Steps 1-10 above, as another inventive point of this disclosure, address another technical problem: "When the substation is large in scale and the number of anomaly detection information is large, if data is entered one by one through pop-up windows, there are problems of input errors and low efficiency. Furthermore, during the input process, due to the large number of control elements displayed in the real-time digital twin model, it is impossible to immediately click on the control element for which the anomaly detection information needs to be entered." Based on this, this application, firstly, when the number of anomaly detection information is higher than the first number and the number of device data is higher than the second number, indicates that the current substation is large in scale and has a large amount of anomaly detection information for input. Therefore, the first method is adopted for anomaly information entry. That is, based on the first method, each anomaly detection information is divided into at least one first anomaly detection information and at least one second anomaly detection information according to its degree of anomaly. Based on this, different methods are used to enter information for each of the at least one first anomaly detection information and at least one second anomaly detection information. Here, by utilizing a control recognition model, at least one cable control information corresponding to at least one second anomaly detection information can be effectively identified. Based on this, by generating an anomaly detection information graph, the rapid entry of each anomaly detection information can be achieved and entered into the real-time digital twin model. Thus, real-time display of the digital twin model for anomaly detection information of different degrees of anomaly can be realized.

[0043] Step 104: In response to receiving the anomaly detection information entered in each anomaly information entry pop-up window and receiving the save click information corresponding to the real-time digital twin model, the model parameter information of the real-time digital twin model for the target cable area is sent to the substation anomaly monitoring terminal to display the cable anomaly information corresponding to the target cable area based on the model parameter information.

[0044] In some embodiments, in response to receiving anomaly detection information entered in each anomaly information entry pop-up window and receiving save click information corresponding to the real-time digital twin model, the model parameter information for the target cable area in the real-time digital twin model with added information is sent to the substation anomaly monitoring terminal to display cable anomaly information corresponding to the target cable area based on the model parameter information. The save click information can be the information after the real-time digital twin model has been clicked to input anomaly detection information. Cable anomaly information can characterize the real-time anomaly situation corresponding to each cable within the target cable area. Anomaly detection information can be the anomaly detection situation corresponding to each cable. Each anomaly detection information is determined based on at least one cable anomaly detection method. The cable anomaly detection method can be a method for performing cable anomaly detection. In practice, at least one cable anomaly detection method can include: electrical detection method, bridge method, partial discharge detection method, and acoustic detection method.

[0045] In some optional implementations of certain embodiments, the above-mentioned anomaly detection information is generated through the following steps: Step 1. Determine the actual position of each cable control among the aforementioned cable controls. The actual position of the control can be its regional deployment location within the target substation area. For example, by establishing a three-dimensional coordinate system for the target substation area, the actual position of the control can be a three-dimensional coordinate representing the regional deployment location of the cable control.

[0046] The second step is to determine the actual distance between every two cable controls based on their actual positions. This actual distance can be the cosine of the actual distance between the actual positions of the two corresponding cable controls.

[0047] The third step involves grouping the cable controls based on the actual distance between each pair of cable controls, resulting in cable control groups. Within each cable control group, the furthest distance between two cable controls is less than the target distance. In practice, the target distance can be a pre-set distance based on historical experience. Alternatively, the target distance can be a value set based on the size of the target substation area. The furthest control distance can be the largest actual distance among the controls in the actual distance group.

[0048] The fourth step is to determine the control area location corresponding to each cable control group in the above cable control group set. The control area location represents the location of the area where the cable control group is situated.

[0049] The fifth step involves sorting the cable control groups in the above set according to their control area location, from closest to furthest, to obtain a cable control group sequence. That is, the cable control group closest to the target location is positioned to the left of the sequence. The target location can be a pre-set location within the target substation area. For example, the target location could be the location corresponding to the control room.

[0050] Step 6: Based on the cable control group sequence corresponding to the above-mentioned cable control group sequence, perform anomaly detection for each cable control group to generate initial anomaly detection information, thus obtaining each initial anomaly detection message. The initial anomaly detection information can be the detection results obtained from the preliminary anomaly detection. The initial anomaly detection information can characterize the anomaly detection status within the cable area corresponding to the cable control group.

[0051] Here, anomaly detection is performed sequentially according to the position of the corresponding control area in the cable control group from near to far, which can greatly improve detection efficiency.

[0052] Step 7: Generate the various anomaly detection information based on the initial anomaly detection information.

[0053] As an example, the aforementioned execution entity can directly identify each initial anomaly detection information as its own anomaly detection information.

[0054] Optionally, the aforementioned execution entity may perform anomaly detection for each cable control group to generate initial anomaly detection information, including the following steps: The first step involves controlling the target cable handling robot to capture infrared video images of the cable control group corresponding to the cable control group using the aforementioned infrared camera device. The video duration for each cable control infrared video is preset. The infrared camera device can be any device that captures the infrared video of the corresponding cable control. There is a one-to-one correspondence between the cable controls in the cable control group and the infrared video images of the cable controls in the cable control infrared video group. The cable control infrared video can characterize the infrared status of the cable during operation.

[0055] The second step involves using the pre-deployed anomaly detection model on the target cable handling robot to generate anomaly detection information corresponding to the cable control group based on the infrared video group of the cable control. The anomaly detection model can be a neural network model for detecting abnormal operation. In practice, the anomaly detection model is a neural network model pre-deployed in the target cable handling robot. For example, the anomaly detection model can be a combination of a target detection model and a classification model. The target detection model is used to identify cable-related equipment. Here, the output of the target detection model is the image location of the cable-related equipment. The classification model can be a model that determines whether there is an anomaly in the corresponding location area based on the equipment image location. The output of the classification model can include information indicating the presence of an anomaly and information indicating the absence of an anomaly.

[0056] Optionally, the aforementioned execution entity can generate the aforementioned anomaly detection information based on the aforementioned initial anomaly detection information, including the following steps: The first step involves sending the initial anomaly detection information and the corresponding detection reports for the cable control group sequence to the target handheld terminal for review. Each cable control group in the sequence has a corresponding detection report. The report content includes: the abnormal cable control within the cable control group, the model output results corresponding to the cable control group (i.e., the output results of the anomaly detection model), and the infrared video group of the cable control corresponding to the cable control group.

[0057] Here, the test report is sent to the target handheld terminal so that relevant technical personnel can verify the accuracy of the report content, thereby further ensuring the accuracy of the test.

[0058] The second step is to confirm the approval by identifying each initial anomaly detection information as an individual anomaly detection information.

[0059] The third step is to obtain at least one initial anomaly detection information in response to the determination that the review has failed.

[0060] The fourth step involves obtaining at least one abnormal question input on the target handheld terminal in response to the at least one initial anomaly detection information. There is a one-to-one correspondence between the initial anomaly detection information and the abnormal question. The abnormal question can characterize a problem arising from an anomaly in the cable control corresponding to the initial anomaly detection information. For example, the abnormal question could be a cable short circuit or cable sheath wear. In practice, the abnormal question can be a problem determined by relevant experience and manually inputted by a technician on the target handheld terminal.

[0061] Fifth, the at least one initial anomaly detection information and the at least one anomaly problem are sent to the target cable processing robot to perform anomaly detection on the at least one cable assembly corresponding to the at least one anomaly problem and the at least one initial anomaly detection information, resulting in at least one re-detection information. There is a one-to-one correspondence between the cable assembly in the at least one cable assembly and the re-detection information in the at least one re-detection information. The re-detection information can be the result of performing a re-anomaly detection on the cable assembly.

[0062] Step 7: Send at least one of the above-mentioned re-detection information and at least one corresponding re-detection report to the target handheld terminal for review of the re-detection anomaly information.

[0063] Step 8: In response to determining that at least one re-detection information has passed the review, at least one re-detection information and at least one target initial anomaly detection information are identified as each anomaly detection information, wherein the at least one target initial anomaly detection information is each detection information after removing the at least one initial anomaly detection information from the aforementioned initial anomaly detection information.

[0064] Optionally, the aforementioned execution entity may utilize the pre-deployed anomaly detection model of the aforementioned target cable handling robot to generate initial anomaly detection information corresponding to the aforementioned cable control group based on the aforementioned cable control infrared video group, including the following steps: The first step involves synchronously extracting frames from the infrared video of each cable control within the aforementioned cable control infrared video group to generate a sequence of infrared images of the cable controls. The frame extraction frequency for each cable control infrared video is the same. Synchronous frame extraction can involve extracting frames from images taken at the same time.

[0065] The second step involves inputting each cable control infrared image sequence in the aforementioned cable control infrared image sequence group into the aforementioned anomaly detection model to generate first control anomaly detection information. This first control anomaly detection information characterizes the anomaly detection status of the cable control corresponding to the cable control infrared image sequence.

[0066] The third step involves combining the cable control infrared images within the same frame extraction time from the aforementioned cable control infrared image sequence group to generate a cable control infrared image group sequence. Each cable control infrared image within the cable control infrared image group shares the same frame time.

[0067] The fourth step is to combine the individual cable control infrared images in each cable control infrared image group in the above cable control infrared image group sequence to generate a combined infrared image, thus obtaining a combined infrared image sequence.

[0068] As an example, the aforementioned execution entity can sequentially combine the infrared images of each cable control in each cable control infrared image group according to the order of the actual distance between the controls from small to large, in order to generate a combined infrared image and obtain a combined infrared image sequence.

[0069] Fifth, the combined infrared image sequence is input into the anomaly detection model to generate a second control anomaly detection information group corresponding to the cable control group. There is a one-to-one correspondence between the cable controls in the cable control group and the second control anomaly detection information in the second control anomaly detection information group.

[0070] Step 6: For each cable control in the above cable control group, perform the following generation steps: Sub-step 1: Determine the first control anomaly detection information and the second control anomaly detection information corresponding to the above cable control, and use them as the first target control anomaly detection information and the second target control anomaly detection information, respectively.

[0071] Sub-step 2: In response to determining that there is information indicating that the control is abnormal in the first target control anomaly detection information and the second target control anomaly detection information, control anomaly determination information indicating that the cable control is abnormal is generated.

[0072] Optionally, in response to determining that neither the first target control anomaly detection information nor the second target control anomaly detection information contains information indicating that the control is abnormal, control anomaly determination information indicating that the cable control is not abnormal is generated.

[0073] Step 7: Select the obtained control exception determination information group as the initial exception detection information.

[0074] Optionally, the infrared image sequence of the cable control is input into the anomaly detection model to generate the first control anomaly detection information, including the following steps: The first step is to determine the frame time interval between every two cable control infrared images in the above cable control infrared image sequence. The frame time interval can be the duration of the frame skipping interval.

[0075] The second step is to determine the infrared detection interval. This interval can be a pre-set time for detecting infrared anomalies. By setting the infrared detection interval, precise real-time monitoring can be achieved, ensuring the accuracy of anomaly detection.

[0076] The third step involves grouping the various cable control infrared image sequences within the aforementioned cable control infrared image sequence according to the infrared detection interval duration, to generate a cable control infrared image group sequence. The continuous duration corresponding to each cable control infrared image group is greater than or equal to the aforementioned infrared detection interval duration. The aforementioned infrared detection interval duration is greater than the frame extraction interval duration. Each cable control infrared image group is a consecutive set of images.

[0077] Fourth step: For each cable control infrared image group in the above sequence of cable control infrared image groups, perform the following first information generation step: Sub-step 1: For each cable control infrared image in the above cable control infrared image group, perform the following second information generation step: The first sub-step involves determining a predetermined number of consecutive images preceding and following each other in the infrared image group of the cable control, respectively serving as at least one previous image and at least one next image.

[0078] The second sub-step involves inputting the aforementioned at least one previous image and the aforementioned infrared image of the cable control into a pre-trained anomaly detection model, specifically into an image infrared coherent feature extraction layer, to generate first infrared coherent feature information. This image infrared coherent feature extraction layer may include: an image feature extraction layer based on multiple convolutional layers and a recurrent neural network model. The output of the image feature extraction layer with multiple convolutional layers serves as the input to the recurrent neural network model. The first infrared coherent feature information characterizes the infrared feature changes between at least one previous image and the infrared image of the cable control. It should be noted that the number of images corresponding to at least one previous image is less than a predetermined value.

[0079] As an example, firstly, the aforementioned execution entity can input each of the at least one previous image into the image feature extraction layer to generate previous image feature information, thus obtaining at least one previous image feature information. Then, the at least one previous image feature information is stitched together to obtain first stitched information. Next, the infrared image of the cable control is input into the image feature extraction layer to generate infrared image feature information of the cable control. Finally, the first stitched information and the infrared image feature information of the cable control are input into a recurrent neural network model to generate first infrared coherent feature information.

[0080] The third sub-step involves inputting at least one next image and the aforementioned cable control infrared image together into a pre-trained image infrared coherent feature extraction layer to generate second infrared coherent feature information. This second infrared coherent feature information characterizes the infrared feature changes between at least one next image and the cable control infrared image.

[0081] As an example, firstly, the aforementioned execution entity can input each of at least one next image into an image feature extraction layer to generate next image feature information, thus obtaining at least one next image feature information. Then, the at least one next image feature information is concatenated to obtain second concatenated information. Next, the infrared image of the cable control is input into the image feature extraction layer to generate infrared image feature information of the cable control. Finally, the second concatenated information and the infrared image feature information of the cable control are input into a recurrent neural network model to generate second infrared coherent feature information.

[0082] The fourth sub-step involves inputting the aforementioned first infrared coherent feature information, the aforementioned second infrared coherent feature information, and the aforementioned cable control infrared image feature information into the multi-head attention mechanism layer included in the anomaly detection model to generate a weight matrix set. This weight matrix set may include: a weight matrix corresponding to the aforementioned first infrared coherent feature information, a weight matrix corresponding to the aforementioned second infrared coherent feature information, and a weight matrix corresponding to the aforementioned cable control infrared image feature information. The weight matrix corresponding to the first infrared coherent feature information can characterize the importance of each element in the matrix corresponding to the first infrared coherent feature information. The weight matrix corresponding to the second infrared coherent feature information can characterize the importance of each element in the matrix corresponding to the second infrared coherent feature information. The weight matrix corresponding to the third infrared coherent feature information can characterize the importance of each element in the matrix corresponding to the third infrared coherent feature information.

[0083] The fifth sub-step involves performing a weighted summation of the weight matrices in the aforementioned weight matrix set, the aforementioned first infrared coherent feature information, the aforementioned second infrared coherent feature information, and the aforementioned cable control infrared image feature information to generate weighted feature information.

[0084] Sub-step 2 involves inputting the obtained weighted feature information group into the anomaly detection layer included in the anomaly detection model to generate anomaly detection information.

[0085] The fifth step is to determine the obtained sequence of anomaly detection information as the first control anomaly detection information.

[0086] The aforementioned "steps one through five" constitute another inventive point of this disclosure, addressing another technical problem: "how to accurately generate first control anomaly detection information in the modality of an image sequence." Based on this, this disclosure, firstly, achieves accurate real-time monitoring by setting the infrared detection interval, ensuring the accuracy of anomaly detection. Furthermore, by utilizing the image infrared coherent feature extraction layer, multi-head attention mechanism layer, and anomaly detection layer included in the anomaly detection model, first control anomaly detection information in the modality of an image sequence can be accurately generated.

[0087] Optionally, the above-mentioned substation anomaly monitoring terminal displays the above-mentioned cable anomaly information and generates a maintenance plan through the following steps: The first step is to obtain the model parameter information sent by the target handheld terminal and the terminal device identification code corresponding to the target handheld terminal. The terminal device identification code can be a unique identifier for the target handheld terminal.

[0088] The second step involves detecting that the target thread has acquired the terminal device identification code. The acquired terminal device identification code is then entered into the data statement template for querying device management area information to generate the first data statement. This query for device management area information can be the area information monitored and managed by the device. The first data statement can be an SQL statement. The target thread can be used to detect the acquisition of terminal device information in real time to trigger the generation of the first data statement. The data statement template for querying device management area information can be pre-set.

[0089] Third, in response to the detection that the target thread has detected the generation of the first data statement, the device management area information corresponding to the terminal device identification code is determined from the terminal device information database using the first data statement. The terminal device information database may be a database that stores terminal device information.

[0090] Fourth, in response to the detection that the target thread has detected the generation of the aforementioned device management area information, the acquired device management area information is filled into the data statement template for querying digital twin model parameter information to generate a second data statement. The target thread can also be used to generate device management area information. The data statement template for querying digital twin model parameter information can be pre-set.

[0091] Fifth, in response to the detection that the target thread has detected the generation of the second data statement, the model parameter information corresponding to the device management area information is determined from the model parameter information database using the second data statement, and used as the target model parameter information. The model parameter information database may store the model parameter information corresponding to the digital twin model under the management area of ​​each device.

[0092] Step 6: Determine the differences in model parameters between the target model parameter information and the model parameter information mentioned above. These differences can be the specific variations between the model parameters.

[0093] Step 7: Determine the cable region information corresponding to the differences in the above model parameters, as the differential cable region information. This differential cable region information can be the region information of areas where the model parameters differ.

[0094] Step 8: Identify the above-mentioned differential cable area information and the above-mentioned abnormal model parameters as cable abnormality information.

[0095] Step nine involves generating a scheme generation instruction based on the aforementioned differences in cable area information and model parameter differences. This scheme generation instruction can be a prompt command for generating a maintenance scheme.

[0096] Step 10: Input the above-mentioned scheme generation instructions, the above-mentioned cable anomaly information, and the information on the different cable areas into the large language model to generate the above-mentioned maintenance scheme.

[0097] Optionally, after step 104, the steps further include: The first step, in response to the determination that the number of devices corresponding to the target substation area is higher than the second number and that abnormal information is entered in the second manner, is to perform the following determination steps: Sub-step 1: Determine the location of the target handheld terminal. The second method involves personnel simultaneously holding the target handheld device and recording anomaly information from the corresponding cable control. Specifically, in this second method, anomaly detection information is entered into a pop-up window corresponding to the cable control in the real-time digital twin model after the personnel move to that control. The terminal location can be the current location of the target handheld terminal within the substation area.

[0098] As an example, the aforementioned execution entity can use a positioning system to locate the position of the target handheld terminal in real time.

[0099] Sub-step 2 involves determining the twin sub-model centered on the aforementioned terminal location within the aforementioned real-time digital twin model. The twin sub-model can be a sub-model within the real-time digital twin model. The display center corresponding to the twin sub-model is the terminal location. Alternatively, the twin sub-model can be a sub-model corresponding to a magnified sub-area centered on the terminal location.

[0100] Sub-step 3 involves displaying the aforementioned twin model at the target magnification level. This twin model supports dragging and scaling. The target magnification level is determined based on the size of the corresponding twin model. Magnifying the twin model at the target magnification level allows the user to clearly see the various cable controls within the corresponding area of ​​the twin model, facilitating the recording of the control states of each cable control within that area.

[0101] Sub-step 4 prompts the user to input cable control information or photograph the cable control in the cable control search component corresponding to the aforementioned twin model. The cable control search component can be a component for searching for cable controls. Here, the cable control search component includes a section for photographing cable controls. When clicking the cable control search component in an area other than the area corresponding to the photographed cable control, the user can input the text content corresponding to the cable control. When clicking the cable control search component in an area corresponding to the photographed cable control, the camera is activated to capture the image of the cable control in real time.

[0102] Here, prompts can be displayed in the twin model to indicate that you can enter control search information related to the cable control and take a picture of the control corresponding to the cable control in the cable control search component.

[0103] In sub-step 5, in response to confirming the click on the camera control in the cable control search component, the camera device corresponding to the camera control is activated to capture the current abnormal information input control and obtain the control image.

[0104] Sub-step 6 involves adjusting the content of the twin model based on the control recognition model bound to it and the control image. The model center is adjusted to correspond to the control in the control image, resulting in the adjusted twin model. The control recognition model bound to the twin model is the control recognition model deployed on the target server. The control image can be an image captured by a camera.

[0105] As an example, firstly, the aforementioned execution entity can input the control image into the control recognition model bound to the twin model to obtain the recognition result. Then, it determines the control information corresponding to the recognition result. Next, it adjusts the center display position of the adjusted twin model to the position of the control corresponding to the aforementioned control information (i.e., the control image displayed at the center position of the adjusted twin model corresponds to the cable control).

[0106] Sub-step 7: In response to the twin model clicking the abnormal input control corresponding to the control image above after the above adjustment, an abnormal information input pop-up window will pop up to input the abnormal information corresponding to the above control.

[0107] The second step is to re-execute the above determination steps in response to the confirmation that the data entry is complete, the detection of a change in the location of the target handheld terminal, and the cessation of the location change after a certain period of time.

[0108] The target duration can be a pre-set duration. The target duration can be determined based on the distance between the cable controls and the speed of the driver.

[0109] Here, the aforementioned "first step and second step" serve as another inventive point of this disclosure. Based on the second method, in the scenario of real-time recording of anomaly detection information by handheld target terminal, the real-time changes in terminal position are correlated with the real-time updates of the twin model. This allows the model content of the twin model to be updated in real time while moving, and anomaly detection information can be recorded in real time based on the position of the moved cable control. This avoids the need for manual searching to query the cable control and greatly improves the efficiency of recording the anomaly detection status of the corresponding cable control.

[0110] Step 105: In response to receiving the maintenance request information and maintenance plan for the target cable area, instruct the target cable handling robot to perform cable abnormality maintenance according to the maintenance plan.

[0111] In some embodiments, in response to receiving a maintenance request and maintenance plan for the target cable area, the executing entity may instruct the target cable handling robot to perform cable anomaly repair according to the maintenance plan. The maintenance request may be a request to repair each cable and related equipment in the target cable area that exhibits anomalies. The maintenance plan may be a repair plan for each cable and related equipment exhibiting anomalies. The target cable handling robot may be a robot capable of performing various cable processing tasks. For example, the target cable handling robot may support cable repair, cable inspection, and other processing tasks.

[0112] In some optional implementations of certain embodiments, after step 105, the steps further include: The first step, in response to receiving device query information for cable-related equipment within the clicked area of ​​the aforementioned real-time digital twin model, is to determine the click permissions corresponding to the target handheld terminal. Click permissions can be defined as the target handheld terminal's query permissions for device queries. Here, the query permissions for device queries differ for different target handheld terminals.

[0113] The second step, in response to the aforementioned click permission representation, supports device queries within the clicked area, querying cable identifiers, cable routes, cabinet equipment, and trunking equipment within that area. The clicked area can be a region selected in a real-time digital twin model. Cable-related equipment can include cable equipment and equipment connected to cables. Device query information can include the corresponding identifier and location information of the queryed equipment. Cable routes can represent the distribution and direction of cables.

[0114] The second step is to highlight the retrieved cable identifiers, cable routes, cabinet equipment, and cable tray equipment. This highlighting can be done using target colors and brightness levels.

[0115] The above-described embodiments of this disclosure have the following beneficial effects: Through the transparent cable display method of some embodiments of this disclosure, automated anomaly detection of cables within a target cable area can be achieved in a timely and efficient manner, preventing power accidents. Specifically, the reason for the low efficiency of related anomaly detection is that inspection and maintenance personnel may not have sufficient understanding of the cable layout corresponding to the target substation, making inspection and maintenance more difficult and preventing timely anomaly detection and maintenance. This leads to low inspection and maintenance efficiency and may result in power accidents. Based on this, the transparent cable display method of some embodiments of this disclosure firstly, in response to determining that the current time is the anomaly detection time corresponding to the target substation area, inputs cable query information corresponding to the target substation area into the cable digital twin interface of the target handheld terminal. The cable query information is a query request for model parameter information of the digital twin model corresponding to the target substation area. Here, upon reaching the anomaly detection time, the target handheld terminal requests cable query information to obtain the real-time digital twin model of the target substation area at the current time. Here, by inputting information through the cable digital twin interface, model parameter information can be requested to initially construct the real-time digital twin model based on the model parameter information. Then, the system receives the response information corresponding to the cable inquiry sent by the substation anomaly monitoring terminal, and displays a real-time digital twin model of the target substation area on the target handheld terminal based on the response information. Here, by receiving the response information, a real-time digital twin model representing the layout of the target substation area can be constructed, allowing the personnel at the target handheld terminal to understand the current layout. Next, in response to receiving an anomaly click entry within the target cable area in the real-time digital twin model, the system highlights each cable control within the target cable area in the real-time digital twin model and pops up anomaly information entry pop-ups for each cable control. Here, the anomaly click entry method, the highlighting method, and the generation of anomaly information entry pop-ups allow for timely and efficient entry of anomalies corresponding to each cable control, achieving efficient management of cable control anomaly information. Furthermore, in response to receiving the anomaly detection information entered in each anomaly information entry pop-up window and receiving the save click information corresponding to the real-time digital twin model, the model parameter information of the real-time digital twin model corresponding to the aforementioned target cable area, which includes each anomaly detection information, is sent to the aforementioned substation anomaly monitoring terminal. This allows the display of cable anomaly information corresponding to the target cable area in the target substation based on the aforementioned model parameter information. Each anomaly detection information is determined based on at least one cable anomaly detection method.Here, by sending model parameter information to the substation anomaly monitoring terminal, the terminal can promptly obtain information on cable anomalies in the target substation area, facilitating timely detection of potential hazards and preventing power accidents. Finally, in response to receiving maintenance requests and plans for the target cable area, the target cable handling robot is instructed to perform cable anomaly repairs and display transparent cables according to the plan, significantly improving the efficiency and accuracy of cable anomaly repairs. In summary, through the transmission of model parameter information corresponding to the digital twin model, not only can operators at the target handheld terminal promptly understand the layout of the target substation area, but the substation anomaly monitoring terminal can also promptly obtain information on anomalies. This enables timely and efficient automated detection of cable anomalies within the target cable area, preventing power accidents.

[0116] Further reference Figure 2 As an implementation of the methods shown in the above figures, this disclosure provides some embodiments of a transparent cable display device, which are similar to... Figure 1 Corresponding to the method embodiments shown, this transparent cable display device can be specifically applied to various electronic devices.

[0117] like Figure 2As shown, a transparent cable display device 200 includes: an input unit 201, a receiving unit 202, a highlighting display unit 203, a sending unit 204, and an indicating unit 205. The input unit 201 is configured to input cable inquiry information on the cable digital twin interface of the target handheld terminal in response to an anomaly detection time corresponding to the target substation area. The receiving unit 202 is configured to receive a response from the substation anomaly monitoring terminal in response to the cable inquiry information, and to display a real-time digital twin model of the target substation area on the target handheld terminal based on the response information. The highlighting display unit 203 is configured to, in response to receiving an anomaly entry for the target cable area, highlight each cable control within the target cable area in the real-time digital twin model and pop up an anomaly information entry for each cable control. The system includes a pop-up window for inputting abnormal information; a sending unit 204, configured to, in response to receiving abnormal detection information input in each abnormal information input pop-up window and receiving save click information corresponding to the real-time digital twin model, send the model parameter information for the target cable area in the real-time digital twin model to the substation abnormal monitoring terminal, so as to display the cable abnormal information corresponding to the target cable area according to the model parameter information, wherein each abnormal detection information is determined based on at least one cable abnormal detection method; and an instruction unit 205, configured to, in response to receiving maintenance request information and maintenance plan for the target cable area, instruct the target cable handling robot to perform cable abnormality maintenance and transparent cable display.

[0118] It is understandable that the units described in the transparent cable display device 200 are similar to those in the reference. Figure 1 The steps in the described method correspond to each other. Therefore, the operations, features, and beneficial effects described above for the method also apply to the transparent cable display device 200 and the units contained therein, and will not be repeated here.

[0119] The following is for reference. Figure 3 It shows a schematic diagram of the structure of an electronic device (e.g., an electronic device) 300 suitable for implementing some embodiments of the present disclosure. Figure 3 The electronic device shown is merely an example and should not be construed as limiting the functionality and scope of the embodiments of this disclosure.

[0120] like Figure 3As shown, the electronic device 300 may include a processing unit (e.g., a central processing unit, a graphics processing unit, etc.) 301, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 302 or a program loaded from a storage device 308 into a random access memory (RAM) 303. The RAM 303 also stores various programs and data required for the operation of the electronic device 300. The processing unit 301, ROM 302, and RAM 303 are interconnected via a bus 304. An input / output (I / O) interface 305 is also connected to the bus 304.

[0121] Typically, the following devices can be connected to I / O interface 305: input devices 306 including, for example, touchscreens, touchpads, keyboards, mice, cameras, microphones, accelerometers, gyroscopes, etc.; output devices 307 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; storage devices 308 including, for example, magnetic tapes, hard disks, etc.; and communication devices 309. Communication device 309 allows electronic device 300 to communicate wirelessly or wiredly with other devices to exchange data. Although Figure 3 An electronic device 300 with various devices is shown; however, it should be understood that it is not required to implement or possess all of the devices shown. More or fewer devices may be implemented or possessed alternatively. Figure 3 Each box shown can represent a device or multiple devices as needed.

[0122] In particular, according to some embodiments of this disclosure, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, some embodiments of this disclosure include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication device 309, or installed from storage device 308, or installed from ROM 302. When the computer program is executed by processing device 301, it performs the functions defined in the methods of some embodiments of this disclosure.

[0123] It should be noted that, in some embodiments of this disclosure, the computer-readable medium described above may be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. A computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In some embodiments of this disclosure, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In some embodiments of this disclosure, a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium can be any computer-readable medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to: wires, optical fibers, RF (radio frequency), etc., or any suitable combination thereof.

[0124] In some implementations, clients and servers can communicate using any currently known or future-developed network protocol such as HTTP (Hypertext Transfer Protocol) and can interconnect with digital data communication (e.g., communication networks) of any form or medium. Examples of communication networks include local area networks (“LANs”), wide area networks (“WANs”), the Internet (e.g., the Internet of Things), and peer-to-peer networks (e.g., ad hoc peer-to-peer networks), as well as any currently known or future-developed networks.

[0125] The aforementioned computer-readable medium may be included in the aforementioned electronic device; or it may exist independently and not assembled into the electronic device. The aforementioned computer-readable medium carries one or more programs, which, when executed by the electronic device, cause the electronic device to: respond to the current time being the anomaly detection time corresponding to the target substation area, input cable inquiry information on the cable digital twin interface corresponding to the target handheld terminal; receive response information sent by the substation anomaly monitoring terminal regarding the cable inquiry information, so as to display a real-time digital twin model corresponding to the target substation area on the target handheld terminal based on the response information; and, in response to receiving an anomaly click entry for the target cable area, highlight each cable control within the target cable area in the real-time digital twin model, and display a pop-up message. An abnormal information input pop-up window is generated for each of the aforementioned cable controls; in response to receiving the abnormal detection information entered in each abnormal information input pop-up window and receiving the save click information corresponding to the real-time digital twin model, the model parameter information for the aforementioned target cable area in the real-time digital twin model with added information is sent to the aforementioned substation abnormal monitoring terminal, so as to display the cable abnormal information corresponding to the target cable area according to the aforementioned model parameter information, wherein each abnormal detection information is determined based on at least one cable abnormal detection method; in response to receiving the maintenance request information and maintenance plan for the aforementioned target cable area, the target cable handling robot is instructed to perform cable abnormality maintenance and transparent cable display.

[0126] Computer program code for performing operations of some embodiments of this disclosure can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0127] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0128] The units described in some embodiments of this disclosure can be implemented in software or hardware. The described units can also be housed in a processor; for example, a processor may be described as including an input unit, a receiving unit, a highlighting unit, a sending unit, and an indicating unit. The names of these units do not necessarily limit the specific unit; for example, an indicating unit may be described as "a unit that, in response to receiving a maintenance request and maintenance plan for the aforementioned target cable area, instructs the target cable handling robot to perform cable anomaly repair and transparent cable display."

[0129] The functions described above in this document can be performed at least in part by one or more hardware logic components. For example, exemplary types of hardware logic components that can be used, without limitation, include: field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), system-on-a-chip (SoCs), complex programmable logic devices (CPLDs), and so on.

[0130] The above description is merely a selection of preferred embodiments of this disclosure and an explanation of the technical principles employed. Those skilled in the art should understand that the scope of the invention involved in the embodiments of this disclosure is not limited to technical solutions formed by specific combinations of the above-described technical features, but should also cover other technical solutions formed by arbitrary combinations of the above-described technical features or their equivalents without departing from the above-described inventive concept. For example, technical solutions formed by substituting the above-described features with (but not limited to) technical features with similar functions disclosed in the embodiments of this disclosure.

Claims

1. A method for displaying transparent cables, comprising: In response to the anomaly detection time corresponding to the target substation area at the current time, input cable inquiry information into the cable digital twin interface corresponding to the target handheld terminal; Receive response information from the substation anomaly monitoring terminal regarding the cable inquiry information, and display a real-time digital twin model of the target substation area on the target handheld terminal based on the response information; In response to receiving an abnormal click entry for the target cable area, the real-time digital twin model highlights each cable control within the target cable area and pops up an abnormal information entry pop-up window for each cable control. In response to receiving the anomaly detection information entered in each anomaly information entry pop-up window and receiving the save click information corresponding to the real-time digital twin model, the model parameter information for the target cable area in the real-time digital twin model with added information is sent to the substation anomaly monitoring terminal to display the cable anomaly information corresponding to the target cable area according to the model parameter information, wherein each anomaly detection information is determined based on at least one cable anomaly detection method; In response to receiving a maintenance request and maintenance plan for the target cable area, the target cable handling robot is instructed to perform cable anomaly repair and transparent cable display.

2. The method according to claim 1, wherein, The method further includes: In response to receiving device query information for cable-related equipment within the clicked area of ​​the real-time digital twin model, the click permission corresponding to the target handheld terminal is determined; In response to the click permission representation, the device can be queried in the clicked area, including cable identification, cable routing, cabinet equipment, and trunking equipment within the clicked area; The retrieved cable identification, cable routing, cabinet equipment, and trunking equipment are highlighted.

3. The method according to claim 1, wherein, The anomaly detection information is generated through the following steps: Determine the actual position of the control corresponding to each cable control in the various cable controls; Based on the actual position of the control corresponding to each cable control, determine the actual distance between every two cable controls in each cable control; Based on the actual distance between each pair of cable controls, the cable controls are grouped to obtain a cable control set, wherein the farthest control distance between two cable controls in the cable control set is less than the target distance. Determine the control area position corresponding to each cable control group in the cable control group set; Based on the control area location corresponding to each cable control group, the cable control groups in the cable control group set are sorted in order of distance from nearest to farthest to obtain the cable control group sequence; Based on the order of the cable control groups corresponding to the cable control group sequence, perform anomaly detection for each cable control group to generate initial anomaly detection information, and obtain each initial anomaly detection information. Based on the initial anomaly detection information, the various anomaly detection information are generated.

4. The method according to claim 3, wherein, The process of performing anomaly detection for each cable control group to generate initial anomaly detection information includes: The target cable handling robot is controlled to use the infrared camera device to capture infrared video of the cable control group corresponding to the cable control group, wherein the video duration of each cable control infrared video is preset. Using the pre-deployed anomaly detection model of the target cable handling robot, initial anomaly detection information corresponding to the cable control group is generated based on the infrared video group of the cable control.

5. The method according to claim 3, wherein, The step of generating each anomaly detection information based on each initial anomaly detection information includes: The initial anomaly detection information and the detection report corresponding to the cable control group sequence are sent to the target handheld terminal for review of the anomaly detection information; In response to the confirmation of approval, each initial anomaly detection information is identified as an individual anomaly detection information; In response to determining that the review has failed, at least one initial anomaly detection information for the failed review is obtained; Obtain at least one abnormal question input on the target handheld terminal in response to the at least one initial abnormality detection information; The at least one initial anomaly detection information and the at least one anomaly problem are sent to the target cable handling robot to perform anomaly detection on at least one cable component again for the at least one anomaly problem and the at least one initial anomaly detection information, so as to obtain at least one re-detection information; The at least one re-detection information and the corresponding at least one re-detection report are sent to the target handheld terminal for review of the re-detection anomaly information; In response to determining that the at least one re-detection information has passed the review, the at least one re-detection information and the at least one target initial anomaly detection information are identified as each anomaly detection information, wherein the at least one target initial anomaly detection information is each detection information after removing the at least one initial anomaly detection information from the respective initial anomaly detection information.

6. The method according to claim 4, wherein, The method utilizes the pre-deployed anomaly detection model of the target cable handling robot to generate initial anomaly detection information corresponding to the cable control group based on the infrared video group of the cable control, including: Synchronous frame extraction is performed on each cable control infrared video in the cable control infrared video group to generate a cable control infrared image sequence group. For each cable control infrared image sequence in the cable control infrared image sequence group, the cable control infrared image sequence is input into the anomaly detection model to generate first control anomaly detection information; The cable control infrared images in the cable control infrared image sequence group that are at the same frame extraction time are combined to generate a cable control infrared image group, thus obtaining a cable control infrared image group sequence. The individual cable control infrared images in each cable control infrared image group in the cable control infrared image group sequence are combined to generate a combined infrared image, thus obtaining a combined infrared image sequence. The combined infrared image sequence is input into the anomaly detection model to generate a second control anomaly detection information group corresponding to the cable control group; For each cable control in the cable control group, perform the following generation steps: Determine the first control anomaly detection information and the second control anomaly detection information corresponding to the cable control, and use them as the first target control anomaly detection information and the second target control anomaly detection information, respectively. In response to determining that there is information indicating that the control is abnormal in the first target control anomaly detection information and the second target control anomaly detection information, control anomaly determination information indicating that the cable control is abnormal is generated; The obtained control exception determination information group is selected as the initial exception detection information.

7. The method according to claim 1, wherein, The substation anomaly monitoring terminal displays the cable anomaly information and generates a maintenance plan through the following steps: Obtain the model parameter information sent by the target handheld terminal and the terminal device identification code corresponding to the target handheld terminal; In response to the detection that the target thread has detected the acquisition of the terminal device identification code, the acquired terminal device identification code is filled into the data statement template for querying device management area information to generate the first data statement; In response to detecting that the target thread has detected the generation of the first data statement, the device management area information corresponding to the terminal device identification code is determined from the terminal device information database using the first data statement; In response to the detection that the target thread has detected the generation of the device management area information, the acquired device management area information is filled into the data statement template for querying digital twin model parameter information to generate a second data statement; In response to the detection that the target thread has detected the generation of the second data statement, the model parameter information corresponding to the device management area information is determined from the model parameter information database using the second data statement, and used as the target model parameter information; Determine the model parameter differences between the target model parameter information and the model parameter information; Determine the cable region information corresponding to the differences in the model parameters, and use it as the differential cable region information; The differential cable area information and the abnormal model parameters are identified as cable abnormality information; The generation instruction generates a maintenance plan based on the differential cable area information and the model parameter differences. The solution generation instructions, the cable anomaly information, and the differential cable area information are input into the large language model to generate the maintenance solution.

8. A transparent cable display device, comprising: The input unit is configured to respond to the anomaly detection time corresponding to the target substation area at the current time by inputting cable query information on the cable digital twin interface of the target handheld terminal. The receiving unit is configured to receive a response to the cable inquiry information sent by the substation anomaly monitoring terminal, so as to display a real-time digital twin model of the target substation area in the target handheld terminal based on the response information. The highlight display unit is configured to, in response to receiving an abnormal click entry for a target cable area, highlight each cable control within the target cable area in the real-time digital twin model, and pop up an abnormal information entry pop-up window for each cable control. The sending unit is configured to, in response to receiving anomaly detection information entered in each anomaly information entry pop-up window and receiving save click information corresponding to the real-time digital twin model, send the model parameter information for the target cable area in the real-time digital twin model with added information to the substation anomaly monitoring terminal, so as to display the cable anomaly information corresponding to the target cable area according to the model parameter information, wherein each anomaly detection information is determined based on at least one cable anomaly detection method; The instruction unit is configured to, in response to receiving a maintenance request and maintenance plan for the target cable area, instruct the target cable handling robot to perform cable anomaly repair and transparent cable display.

9. An electronic device, comprising: One or more processors; Storage device, on which one or more programs are stored, When the one or more programs are executed by the one or more processors, the one or more processors implement the method as described in any one of claims 1-7.

10. A computer-readable medium having a computer program stored thereon, wherein, When the program is executed by the processor, it implements the method as described in any one of claims 1-7.

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