Network distribution defect file automatic supervision method and device, electronic equipment and storage medium

Abstract

The application discloses a kind of network defect file automatic supervision method, device, electronic equipment and storage medium.Its features include: requesting defect data file to power grid management platform;At least one defect data file issued by the defect management module of power grid management platform is received;The defect data file is analyzed and supervised, and the problem reason of the target problem file is output.The automatic supervision analysis of defect data file is realized, and the manpower and material resources are effectively saved by automatically filtering and checking the defect data file one by one, not only improve the efficiency of supervision, but also avoid the mistake of manual inspection, improve the supervision accuracy of defect data file.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of distribution network file processing, and in particular to a distribution network defect file automatic supervision method and device, electronic equipment and a storage medium. BACKGROUND

[0002] As the most critical part of distribution network management, interconnection informationization enables distribution network staff to informationize defect data file information of distribution network defects through Internet communication, and interconnect and intercommunicate with the power grid management platform through mobile devices, so that the defect data file can be uploaded and continuously tracked in the first time. After the elimination of the distribution network defects is completed, a continuous and complete defect data file is generated on the power grid management platform, and the power grid management platform needs to check the defect data file completed by the staff to prevent false information and information falsification in the defect data file. In the prior art, an automatic error correction mechanism in the power grid management platform is usually used to record error information in the filling process, and then the staff manually supervises the error information, but the manual supervision is low in efficiency and easy to miss. SUMMARY

[0003] The present application provides a distribution network defect file automatic supervision method, device, electronic equipment and storage medium to realize automatic supervision of the distribution network defect file and improve the investigation efficiency and accuracy of the distribution network defect registration file.

[0004] According to an aspect of the present application, a distribution network defect file automatic supervision method is provided, comprising:

[0005] requesting a defect data file from a power grid management platform;

[0006] receiving at least one defect data file issued by a defect management module of the power grid management platform;

[0007] performing defect analysis supervision on the defect data file, determining a target problem file, and outputting a problem reason of the target problem file.

[0008] According to another aspect of the present application, a distribution network defect file automatic supervision device is provided, comprising:

[0009] a data request module configured to request a defect data file from a power grid management platform;

[0010] a data receiving module configured to receive at least one defect data file issued by a defect management module of the power grid management platform;

[0011] an automatic supervision module configured to perform defect analysis supervision on the defect data file, determine a target problem file, and output a problem reason of the target problem file.

[0012] According to another aspect of the present application, there is provided an electronic device comprising:

[0013] at least one processor; and

[0014] a memory communicatively connected to the at least one processor; wherein

[0015] the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor to enable the at least one processor to perform the method for automatic supervision of distribution network defect files according to any one of the embodiments of the present application.

[0016] According to another aspect of the present application, there is provided a computer readable storage medium storing computer instructions for enabling a processor to implement the method for automatic supervision of distribution network defect files according to any one of the embodiments of the present application when executed by the processor.

[0017] The technical solution of the embodiments of the present application requests a defect data file from a power grid management platform, receives at least one defect data file issued by a defect management module of the power grid management platform, directly obtains the defect data file by connecting the power grid management platform, does not need manual data transmission, reduces the risk of data tampering, improves the efficiency of obtaining the defect data file, and further improves the efficiency of automatic supervision. The defect data file is analyzed and supervised, the target problem file is determined, and the cause of the target problem file is output. Through comprehensive defect analysis and supervision of the defect data file, the efficiency and accuracy of supervision can be effectively improved, and after the target problem file is determined, the causes of the defects can be output in sequence, effectively improving the effectiveness of supervision. The present application solves the problem that the defect data file filled by the distribution network staff cannot be quickly and accurately supervised in the prior art, realizes automatic supervision and analysis of the defect data file, effectively saves manpower and resources through automatic filtering and checking of the defect data file, improves the efficiency of supervision, avoids the mistakes of manual checking, and improves the accuracy of supervision of the defect data file.

[0018] It should be understood that the content described in this part is not intended to identify key or important features of the embodiments of the present application, nor to limit the scope of the present application. Other features of the present application will become apparent through the following description. BRIEF DESCRIPTION OF DRAWINGS

[0019] In order to make the technical solutions in the embodiments of the present application clearer, the following will briefly introduce the drawings needed in the embodiment description. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without any creative effort on the basis of these drawings.

[0020] Figure 1 is a flow chart of a power distribution network defect file automatic supervision method provided by the first embodiment of the present application;

[0021] Figure 2 is a flow chart of another power distribution network defect file automatic supervision method provided by the second embodiment of the present application;

[0022] Figure 3 is a structural schematic diagram of a power distribution network defect file automatic supervision device provided by the third embodiment of the present application;

[0023] Figure 4 is a structural schematic diagram of an electronic device for implementing the power distribution network defect file automatic supervision method of the embodiments of the present application. DETAILED DESCRIPTION

[0024] In order to make the technical solutions in the embodiments of the present application clearer, the following will briefly introduce the drawings needed in the embodiment description. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without any creative effort on the basis of these drawings.

[0025] Embodiment One

[0026] Figure 1 is a flow chart of a power distribution network defect file automatic supervision method provided by the first embodiment of the present application, and the present embodiment can be applied to automatically check the defect data file of the power grid management platform. The method can be executed by a power distribution network defect file automatic supervision device, which can be realized in the form of hardware and / or software, and the power distribution network defect file automatic supervision device can be configured in an electronic device. As shown in the figure, the method comprises the following steps. Figure 1

[0027] S110, requesting a defect data file from the power grid management platform.

[0028] ​The power grid management platform can be a power grid management platform asset domain; the power grid management platform asset domain can connect multiple different types of power grid businesses in series, mathematically connect various businesses, enable horizontal collaboration of various businesses, enable data flow and sharing of the power distribution network in various business modules, and provide a business data sharing service through the power grid management platform.

[0029] The defect data file can be a defect single file recorded by a worker during a power distribution process.

[0030] Optionally, in the embodiment of the present application, each defect data file includes a device list, a defect list, a defect elimination list, an acceptance list, an attachment list, and a process tracking list. The device list records detailed information of a power distribution network device with defects, such as device model, device classification, device location, device category, device identification, device defect phenomenon, device defect level, device management power grid, device defect type, and defect discovery time. The defect list records specific analysis information of the defect, such as the worker who discovered the defect, the time of reporting the defect, and a specific description of the defect. The defect elimination list records information of a worker eliminating a defect of a power distribution network device, such as the defect elimination worker, the specific time of defect elimination, the defect cause, the defect device part, the defect elimination treatment measure, the defect elimination situation description, and the defect elimination result. The acceptance list records specific information of a worker reporting an acceptance after eliminating a defect of a power distribution network device, such as the acceptance worker, the acceptance department, the acceptance time, the acceptance result, and the acceptance opinion. The attachment list can be an image attachment uploaded by the worker, such as a defect original image uploaded during defect registration, a defect elimination image uploaded during defect elimination registration, an acceptance image uploaded during acceptance registration, and an image of the power distribution network device before defect transmission. The process tracking list can record process information of each list, such as the execution time and the executor of each process.

[0031] Optionally, in the embodiment of the present application, the power grid worker checks the power distribution network equipment and each part of the power distribution network equipment in the cruising route one by one according to the cruising route by the unmanned aerial vehicle, and records the images of the power distribution network equipment. When defects are found in the power distribution network equipment, the power grid worker registers the defects of the power distribution network equipment according to the defects, generates a device list and a defect list, and takes defect images by the unmanned aerial vehicle. The defect treatment worker processes the defects of the power distribution network equipment according to the device list and the defect list, and then uploads the defect treatment list and the treatment defect image. The acceptance worker fills in the acceptance list and takes the corresponding acceptance image. The power grid management platform saves all the images in the attachment list, and generates a corresponding process tracking list according to the entire defect discovery to acceptance process.

[0032] Specifically, a data request is submitted through a data sharing mode provided by the power grid management platform, and a defect data file in the power grid management platform is requested.

[0033] S120, receiving at least one defect data file issued by the defect management module of the power grid management platform.

[0034] The defect management module can be a business module set in the asset domain of the power grid management platform. In the power grid management platform, the data between each business module can be circulated and shared, and the defect data file can be directly issued by the defect management module.

[0035] Optionally, in the embodiment of the present application, the defect management module is used for managing the defect data files registered in the power distribution network. The defect management module provides a defect data file reporting page for the worker. For the same defect data file, the defect data filled and reported by the worker at different times is received in sequence according to the file identification number of the defect data file, and the defect data is stored in the same data storage space according to the file identification number. Each defect data file is identified according to the file identification number.

[0036] Optionally, the power distribution network in each region is managed in the power grid management platform, and a large number of defect data files exist in the defect management module. When the data request is received by the defect management module, a plurality of defect data files can be issued in sequence according to the data transmission capacity.

[0037] Specifically, after the power grid management platform receives the request for the defect data file, the request is circulated to the defect management module, the defect data file is issued through the defect management module, and then a plurality of defect data files issued by the power grid management platform through the defect management model are received.

[0038] S130, defect analysis supervision is performed on the defect data file, a target problem file is determined, and the problem reason of the target problem file is output.

[0039] The defect analysis supervisor can detect all the lists in the defect data file, determine whether the content in each list file exists a violation phenomenon, and determine the defect data file as a target problem file if the violation phenomenon exists in each list in the defect data file. For example, the defect data file includes a device list, a defect list, a defect elimination list, an acceptance list, an attachment list, and a process tracking list. The device type in the device list is inconsistent with the device defect phenomenon. The defect description in the defect list is inconsistent with the defect device. The defect elimination processing measure in the defect elimination list is inconsistent with the ideal defect processing measure. The original defect image in the attachment list is inconsistent with the device in the processed defect image. The execution node in the process tracking list is inconsistent with the execution time. If the violation phenomenon exists in any list file in the defect data file, the defect file is determined as the target problem file.

[0040] The problem cause can be a description of the problem detected in the defect analysis supervisor in the defect data file. Optionally, after defect analysis supervision of the defect data file, the problem cause corresponding to the problem existing in each list file in the defect data file is output.

[0041] Optionally, before defect analysis supervision of the defect data file, the problem cause is set in advance according to all possible problems existing in the defect data file. The problem cause list is established, and the problem cause corresponding to each problem is set in sequence. When the defect data file exists a problem, the corresponding output problem cause is obtained according to the problem cause list, and the corresponding problem cause is output. It should be noted that the defect data file can have more than one problem, and the problem cause is output in sequence according to all the problems existing in the defect data file.

[0042] Specifically, for the received defect data file, defect analysis supervision is performed for each defect data file. If the defect data file exists a problem, the defect data file is determined as a target problem file, and the problem cause of the target problem file is output. If the defect data file does not exist a problem, it is considered that the defect data file passes the defect analysis supervision.

[0043] The technical scheme of the embodiment of the present application requests a defect data file from a power grid management platform; receives at least one defect data file issued by a defect management module of the power grid management platform, directly obtains the defect data file by connecting the power grid management platform, does not need manual data transmission, reduces the risk of data tampering, improves the efficiency of obtaining the defect data file, and further improves the efficiency of automatic supervision; performs defect analysis supervision on the defect data file, determines a target problem file, and outputs a problem cause of the target problem file, can effectively improve the efficiency and accuracy of supervision by automatically performing comprehensive defect analysis supervision on the defect data file, and can sequentially output the causes of defects after determining the target problem file, effectively improving the effectiveness of supervision. The present application solves the problem that the defect data file filled by the distribution network staff cannot be quickly and accurately supervised in the prior art, realizes automatic supervision and analysis of the defect data file, effectively saves manpower and material resources by automatically filtering and checking the defect data file, not only improves the efficiency of supervision, but also avoids the mistakes of manual checking, and improves the accuracy of supervision of the defect data file.

[0044] Embodiment two

[0045] Figure 2 is a flowchart of another distribution network defect file automatic supervision method provided by the embodiment two of the present application, and the relationship between the present embodiment and the above-mentioned embodiments is a specific method of defect analysis supervision on the defect data file. As shown in Figure 2 , the distribution network defect file automatic supervision method comprises:

[0046] S210, requesting a defect data file from a power grid management platform.

[0047] S220, receiving at least one defect data file issued by a defect management module of the power grid management platform.

[0048] S230, analyzing the defect data file to obtain an execution node, an executor and a defect registration file and a defect elimination registration file of the defect data file.

[0049] The execution node and the execution person can be the node and the execution person when each list in the process tracking list is filled in. For example, in the process tracking list in the defect data file, the filling execution time and the execution person of the equipment list, the defect list, the defect elimination list and the acceptance list are recorded in real time. In a complete defect data file, the equipment list is filled in at 9 o'clock in the morning, the execution node of the equipment list is completed, and the execution person is recorded as A. The defect list is filled in at 11 o'clock in the morning, the execution node of the defect list is completed, and the execution person is recorded as B. The defect elimination list is filled in at 13 o'clock in the afternoon, the execution node of the defect elimination list is completed, and the execution person is recorded as B. The acceptance list is filled in at 17 o'clock in the afternoon, the execution node of the acceptance list is completed, and the execution person is recorded as C, thereby completing the recording of the process tracking list of the entire defect data file.

[0050] The defect registration file can include the equipment list and the defect list in the defect data file; and the defect elimination registration file can include the defect elimination list and the acceptance list in the defect data file. It should be noted that during the registration and filling of the equipment list, the defect list, the defect elimination list and the acceptance list, corresponding images can be photographed and recorded in the attachment list. Therefore, when the equipment list, the defect list, the defect elimination list and the acceptance list are obtained, the stored images in the attachment list can be directly obtained.

[0051] Specifically, when the defect data file is analyzed and supervised, in order to improve the efficiency of defect analysis and supervision, the defect data file is parsed, the defect data file is divided into execution nodes and execution persons, defect registration files and defect elimination registration files, and the data is shunted and supervised to improve the efficiency of defect analysis and supervision.

[0052] S240, respectively, the execution node, the execution person, the defect registration file and the defect elimination registration file of the defect data file are analyzed and supervised, and the target problem file is determined.

[0053] Optionally, in another optional embodiment of the present application, the defect analysis and supervision of the execution node, the execution person, the defect registration file and the defect elimination registration file of the defect data file includes:

[0054] The execution time corresponding to the execution node is obtained, and the execution time is analyzed and supervised for defects;

[0055] The number of execution persons corresponding to the execution person is obtained, and the number of execution persons is analyzed and supervised for defects;

[0056] The original defect image and the defect attribute corresponding to the defect registration file are obtained, and the defect attribute is analyzed and supervised for defects according to the original defect image; wherein the defect attribute includes equipment category, equipment defect phenomenon, equipment defect level, equipment defect type and equipment management unit;

[0057] Obtain the processing defect elimination image and defect elimination attribute corresponding to the defect elimination registration file, and perform defect analysis supervision on the processing defect elimination image and defect elimination attribute in sequence; wherein the defect elimination attribute includes defect reason, defect equipment position and defect elimination treatment measure.

[0058] Wherein, the execution time can be the submission time point after completing the registration and filling of any one of the equipment list, the defect list, the defect elimination list and the acceptance list in the process tracking list; for example, after completing the registration and filling of the equipment list by the executor A at 9 o'clock in the morning, the process tracking list records the equipment list-9 o'clock in the morning-A.

[0059] Wherein, the number of executors can be the number of the names of the executors appearing in the process tracking list of the defect data file; for example: recording the filling of the equipment list at 9 o'clock in the morning, completing the equipment list execution node and recording the executor as A, recording the filling of the defect list at 11 o'clock in the morning, completing the defect list execution node and recording the executor as B, recording the filling of the defect elimination list at 13 o'clock in the afternoon, completing the defect elimination list execution node and recording the executor as B, recording the filling of the acceptance list at 17 o'clock in the afternoon, completing the acceptance list execution node and recording the executor as C; in the above defect data file, the number of executors is 3. Recording the filling of the equipment list at 9 o'clock in the morning, completing the equipment list execution node and recording the executor as A, recording the filling of the defect list at 11 o'clock in the morning, completing the defect list execution node and recording the executor as B, recording the filling of the defect elimination list at 13 o'clock in the afternoon, completing the defect elimination list execution node and recording the executor as D, recording the filling of the acceptance list at 17 o'clock in the afternoon, completing the acceptance list execution node and recording the executor as C; in the above defect data file, the number of executors is 4.

[0060] Optionally, in another optional embodiment of the present application, the defect analysis supervision on the execution time includes: in the case that there is an execution time error in the execution time, determining the defect data file as the target problem file.

[0061] Optionally, in the flow tracking list of the defect data file, the execution time of each execution node should follow a time rule, the execution node corresponding to the equipment list is earlier than the execution node corresponding to other lists, the execution node corresponding to the defect list is later than the execution node corresponding to the equipment list, earlier than the execution node corresponding to other lists, the execution node corresponding to the defect list is earlier than the execution node corresponding to the acceptance list, later than the execution node corresponding to other lists, and the execution node corresponding to the acceptance list is later than the execution node corresponding to other lists. On the basis of the above-mentioned time rule, if the execution time of an execution node does not follow the time rule, it is considered that the defect data file has an execution time error; for example, if the execution node corresponding to the acceptance list is earlier than the execution node corresponding to any other list, it is considered that the execution time of the defect data file has an execution time error, and the defect data file is determined as the target problem file, and the problem reason is that the execution time of the execution node has an error.

[0062] Optionally, when recording each execution node in the flow tracking list, due to the influence of the working environment, part of the defect corresponding list file cannot be timely registered, and the execution time of the execution node is allowed not to follow the time rule, so as to prevent the situation that the defect cannot be eliminated in time due to poor communication signal, causing significant economic loss. Therefore, the embodiment of the present application also provides a pre-defect elimination button function in the flow tracking list, if the pre-defect elimination button function is in an open state, in the case that the defect data file has an execution time error, the defect data file is also considered to pass the defect analysis supervision.

[0063] Optionally, in another optional embodiment of the present application, the defect analysis supervision on the number of execution persons includes:

[0064] In the case that the number of execution persons is less than the preset person threshold, the defect data file is determined as the target problem file.

[0065] The preset person threshold can be a preset defect analysis supervision rule, which stipulates that the number of execution persons of the defect data file cannot be less than the preset person threshold.

[0066] Optionally, in the defect data file, ideally, each execution node should correspond to different executors; usually, in order to improve the defect elimination efficiency and reduce the number of staff, the executor data in a defect data file is preset to be not less than a preset number threshold. If the number of executors is less than the preset number threshold, the defect data file is considered as a target problem file, and the problem reason is output: the number of executors does not meet the regulation. For example, the preset number threshold can be set to 2 workers, it is found that the equipment list and the acceptance list registered by the defect correspond to the same worker, and the worker who determines the defect specific condition and eliminates the defect is the same worker, and the number of executors in the process tracking list is 2, which is not less than the preset number threshold; if it is found that the executors of each execution node in the process tracking list are the same person, and the number of executors is less than the preset number threshold, the defect data file is determined as the target problem file.

[0067] Optionally, in another optional embodiment of the present application, the defect analysis supervision on the defect attribute according to the original defect image comprises:

[0068] determining an ideal equipment category, an ideal defect appearance and an ideal defect grade according to the original defect image; determining an ideal defect type and an ideal tube adjusting unit according to the ideal equipment category, the ideal defect appearance and the ideal defect grade; and determining the defect data file as the target problem file in the case that the ideal equipment category, the ideal defect appearance, the ideal defect grade, the ideal defect type and the ideal tube adjusting unit are different from the equipment category, the equipment defect phenomenon, the equipment defect grade, the equipment defect type and the equipment tube adjusting unit.

[0069] The original defect image can be an equipment image photographed when it is found that the power distribution network equipment has a defect. Optionally, when the unmanned aerial vehicle is cruising, the original defect image corresponding to the power distribution network equipment is photographed and recorded by the unmanned aerial vehicle camera when it is found that the power distribution network equipment has a defect.

[0070] The defect attribute can be attribute information corresponding to each list in the defect registration file. It should be noted that the attribute information is pre-set in each list file for a staff to fill in. The defect attribute includes at least one of a device category, a device defect phenomenon, a device defect level, a device defect type, and a device management unit. Optionally, the device category can be a category to which a power distribution network device belongs, for example, the device category can be a power distribution transformer. The device defect phenomenon can be a phenomenon corresponding to a defect of a power distribution network device, for example, the device defect phenomenon can be that a device joint is heated and red and discolored. The device defect level can be the urgency of the defect, for example, the device defect registration can be urgent, general, and other. The device defect type can be a type determined according to the device defect phenomenon, for example, if the device defect phenomenon is that a device joint is heated and red and discolored, the device defect type is joint heating. The device management unit can be a management unit corresponding to the device.

[0071] The defect attribute can be attribute information corresponding to each list in the defect registration file. It should be noted that the attribute information is pre-set in each list file for a staff to fill in. The defect attribute includes at least one of a device category, a device defect phenomenon, a device defect level, a device defect type, and a device management unit. Optionally, the device category can be a category to which a power distribution network device belongs, for example, the device category can be a power distribution transformer. The device defect phenomenon can be a phenomenon corresponding to a defect of a power distribution network device, for example, the device defect phenomenon can be that a device joint is heated and red and discolored. The device defect level can be the urgency of the defect, for example, the device defect registration can be urgent, general, and other. The device defect type can be a type determined according to the device defect phenomenon, for example, if the device defect phenomenon is that a device joint is heated and red and discolored, the device defect type is joint heating. The device management unit can be a management unit corresponding to the device.

[0072] The ideal device category can be a device category obtained by image recognition on the original defect image. The ideal defect appearance can be a defect appearance obtained by image recognition on the original defect image. The ideal defect can be a defect obtained by image recognition on the original defect image.

[0073] Optionally, the original defect image is obtained from the accessory list, image recognition is performed on the original defect image, the device in the original defect image is recognized, the device category corresponding to the device is determined, and the defect recognition model is used to extract the defect to determine the ideal defect appearance and the ideal defect of the device defect in the original defect image. The defect recognition model can be an image recognition model trained based on a neural network. The neural network model is obtained by deep learning algorithm training based on automatic learning of existing defect sample images and automatic simulation of defects existing in the power distribution network device as defect sample images. The defect recognition model can recognize the defect appearance of the device in the image and determine the device defect corresponding to the defect appearance.

[0074] The ideal defect type can be obtained by defect category identification and extraction analysis of the original defect image; and the ideal regulating tube unit can be obtained by regulating tube unit identification and extraction analysis of the original defect image. Optionally, in the embodiment of the present application, a device classification list is stored in the power grid management platform, and after the ideal device category, ideal defect appearance, and ideal defect registration are obtained, the device classification list is queried from the power grid management platform according to the ideal device category, ideal defect appearance, and ideal defect registration, and the power grid management platform returns the type defect category and ideal regulating tube unit through the device classification list.

[0075] Optionally, after the ideal device category, ideal defect appearance, ideal defect level, ideal defect type, and ideal regulating tube unit are obtained, the ideal device category and the device category are compared, the ideal defect appearance and the device defect appearance are compared, the ideal defect type and the device defect type are compared, the ideal defect level and the device defect are compared, and the ideal regulating tube unit and the device regulating tube unit are compared, to determine whether each item of ideal information and registration information is the same. If any comparison is not the same, the defect data file is determined as the target problem file, and the problem reason is output as: registration information error.

[0076] Optionally, in another optional embodiment of the present application, the defect analysis supervision on the processing defect image and the defect data includes:

[0077] At least one ideal defect treatment measure is determined according to the defect reason and the defect device part, and the image recording identifier of the processing defect image and the image recording identifier of the original defect image are obtained respectively; wherein the image recording identifier includes image shooting position and image annotation information; when any of the following conditions exists, the defect data file is determined as the target problem file: the defect treatment measure is not the same as any of the ideal defect treatment measures; the image recording identifier of the processing defect image is not the same as the image recording identifier of the original defect image; and the processing defect image is not the same as the preset standard defect image.

[0078] The ideal defect treatment measure can be a defect treatment measure output by the power grid management platform according to the defect reason and the defect device part through a large model. Optionally, a defect treatment language model is trained through a large amount of data and computing resources in the power grid management platform, and the defect treatment measures in the massive defect data files in the power grid management platform are used as a large corpus to train the defect treatment measures, so as to obtain the defect treatment language model. Then, the defect reason and the defect device level are uploaded to the defect treatment language model, and at least one ideal defect treatment measure is output by the defect treatment language model according to the defect reason and the defect device level.

[0079] The image recording identifier can be identification information corresponding to the obtained image, and the image recording identifier can effectively determine the image shooting information. The image recording identifier includes an image shooting position and image annotation information. The image shooting position can be the position when the power distribution network equipment is shot, and can be used to determine the position information of the power distribution network equipment. The image annotation information can be information of the shot power distribution network equipment in the image. The image annotation information can include at least one of the power distribution network equipment name, the power distribution network equipment shooting time, the power distribution network equipment type, the shooting angle, and the shooting equipment identifier.

[0080] Optionally, in the embodiment of the present application, the staff shoots according to the fixed cruise route by the unmanned aerial vehicle, and then the image shooting position when the unmanned aerial vehicle camera shoots the power distribution network equipment can be determined by the positioning system and the cruise route identifier of the unmanned aerial vehicle, and the position information of the power distribution network equipment can be determined, and the image annotation information can be automatically annotated to the shot image. For example, the power distribution network equipment can be transformer No. 12 in B Street, A City. The unmanned aerial vehicle flies to the air above transformer No. 12 in B Street, A City according to the fixed cruise route, adjusts the shooting equipment carried by the unmanned aerial vehicle to shoot the power distribution network equipment to obtain an image, and records transformer No. 12 in B Street, A City. At the same time, the unmanned aerial vehicle obtains the shooting angle of the shooting equipment, and annotates in the obtained image: transformer No. 12 in B Street, A City, high-angle shooting, angle 150 degrees, shooting at 10 o'clock in the morning, and unmanned aerial vehicle identifier. The unmanned aerial vehicle identifier can be an identifier number pre-set by the power grid management platform.

[0081] Optionally, the defect processing measure and the at least one ideal defect processing measure are compared. If the defect processing measure is not successfully compared with any one of the ideal defect processing measures, it is considered that the defect processing measure in the defect data file has an improper operation problem, the defect data file is determined as a target problem file, and the problem reason is that the defect operation is improper.

[0082] Optionally, after the defect elimination is completed, the defect elimination worker performs image shooting on the power distribution network equipment after defect elimination, obtains a processed defect elimination image, determines the image shooting position and image annotation information for the processed defect elimination image, determines the address and equipment style corresponding to the power distribution network equipment subjected to defect elimination through the image shooting position and image annotation information of the processed defect elimination image, and then compares the address and equipment style of the power distribution network equipment obtained from the original defect image with the address and equipment style of the processed defect elimination image. If the comparison fails, it is considered that the power distribution network equipment subjected to defect elimination in the defect data file does not match, the defect data file is determined as a target problem file, and the problem reason is output as: defect elimination equipment mismatch. When the equipment style is compared, since the shooting angle of the processed defect elimination image shot by the defect elimination worker is different from the shooting angle of the original defect image, the defect processing language model can be used to identify the two images respectively to determine the equipment style corresponding to the processed defect elimination image and the original defect image, thereby realizing the comparison of the equipment style.

[0083] Optionally, in another optional embodiment of the present application, after the defect elimination worker completes the defect elimination, the unmanned aerial vehicle can shoot the power distribution network equipment at the same shooting position and shooting angle according to the original defect image according to the cruising route, update the image obtained to the processed defect elimination image as a new processed defect elimination image, and compare the processed defect elimination image and the original defect elimination image through pixel matching to realize the comparison of the equipment style.

[0084] The technical scheme of the embodiment of the present application requests a defect data file from a power grid management platform, receives at least one defect data file issued by a defect management module of the power grid management platform, directly obtains the defect data file by connecting the power grid management platform, does not need manual data transmission, reduces the risk of data tampering, improves the efficiency of obtaining the defect data file, and further improves the efficiency of automatic supervision. The defect data file is subjected to defect analysis supervision, a target problem file is determined, and the problem reason of the target problem file is output. Through automatic comprehensive defect analysis supervision of the defect data file, the efficiency and accuracy of supervision can be effectively improved, and after the target problem file is determined, the reasons for the defects can be sequentially output, effectively improving the effectiveness of supervision. The present application solves the problem that the defect data file filled by the power distribution network worker cannot be quickly and accurately supervised in the prior art, realizes automatic supervision and analysis of the defect data file, effectively saves manpower and resources through automatic filtering and checking of the defect data file, improves the efficiency of supervision, avoids the mistakes of manual checking, and improves the accuracy of supervision of the defect data file.

[0085] Embodiment three

[0086] Figure 3is a structural schematic diagram of an automatic supervision device for a distribution network defect file provided by Embodiment Four of the present application. As shown in Figure 3 The device comprises a data request module 310, a data receiving module 320 and an automatic supervision module 330, wherein,

[0087] The data request module 310 is configured to request a defect data file from a power grid management platform.

[0088] The data receiving module 320 is configured to receive at least one defect data file issued by a defect management module of the power grid management platform.

[0089] The automatic supervision module 330 is configured to perform defect analysis supervision on the defect data file, determine a target problem file, and output a problem cause of the target problem file.

[0090] The technical solution of the present application can request a defect data file from a power grid management platform, receive at least one defect data file issued by a defect management module of the power grid management platform, directly obtain the defect data file by connecting the power grid management platform, without manual data transmission, reduce the risk of data tampering, improve the efficiency of obtaining the defect data file, and thus improve the efficiency of automatic supervision. By performing comprehensive defect analysis supervision on the defect data file, the efficiency and accuracy of supervision can be effectively improved, and after determining the target problem file, the reasons for the defects can be output in sequence, effectively improving the effectiveness of supervision. The present application solves the problem that the defect data file filled by the distribution network staff cannot be quickly and accurately supervised in the prior art, realizes automatic supervision and analysis of the defect data file, effectively saves manpower and resources through automatic filtering and checking of the defect data file, improves the efficiency of supervision, avoids errors in manual checking, and improves the accuracy of supervision of the defect data file.

[0091] Optionally, the automatic supervision module is specifically configured to:

[0092] analyze the defect data file to obtain an execution node, an executor and a defect registration file and a defect elimination registration file of the defect data file;

[0093] perform defect analysis supervision on the execution node, the executor, the defect registration file and the defect elimination registration file of the defect data file respectively to determine the target problem file.

[0094] Optionally, the automatic supervision module is specifically further configured to:

[0095] obtain an execution time corresponding to the execution node, and perform defect analysis supervision on the execution time.

[0096] obtaining an execution person quantity corresponding to the execution person, and performing defect analysis supervision on the execution person quantity;

[0097] obtaining an original defect image and a defect attribute corresponding to the defect registration file, and performing defect analysis supervision on the defect attribute according to the original defect image; wherein the defect attribute includes a device category, a device defect phenomenon, a device defect level, a device defect type, and a device management unit;

[0098] obtaining a processing defect image and a defect attribute corresponding to the defect registration file, and sequentially performing defect analysis supervision on the processing defect image and the defect attribute; wherein the defect attribute includes a defect reason, a defect device part, and a defect processing measure.

[0099] Optionally, the automatic supervision module is further configured to:

[0100] in a case where the execution time is incorrect, determining the defect data file as the target problem file.

[0101] Optionally, the automatic supervision module is further configured to:

[0102] in a case where the execution person quantity is less than a preset person quantity threshold, determining the defect data file as the target problem file.

[0103] Optionally, the automatic supervision module is further configured to:

[0104] determining an ideal device category, an ideal defect appearance, and an ideal defect level according to the original defect image;

[0105] determining an ideal defect type and an ideal management unit according to the ideal device category, the ideal defect appearance, and the ideal defect level;

[0106] in a case where the ideal device category, the ideal defect appearance, the ideal defect level, the ideal defect type, and the ideal management unit are different from the device category, the device defect phenomenon, the device defect level, the device defect type, and the device management unit, determining the defect data file as the target problem file.

[0107] Optionally, the automatic supervision module is further configured to:

[0108] determining at least one ideal defect processing measure according to the defect reason and the defect device part, and respectively obtaining an image record identifier of the processing defect image and an image record identifier of the original defect image; wherein the image record identifier includes an image shooting position and image annotation information;

[0109] The defect data file is determined as the target problem file when any of the following conditions exists:

[0110] The defect data processing measure and any of the ideal defect processing measures are different;

[0111] The image record identifier of the processed defect image and the image record identifier of the original defect image are different.

[0112] The network distribution defect file automatic supervision device provided by the embodiments of the present application can execute the network distribution defect file automatic supervision method provided by any of the embodiments of the present application, and has the corresponding function modules and beneficial effects of the execution method.

[0113] Embodiment four

[0114] Figure 4 A structural schematic diagram of an electronic device 10 that can be used to implement embodiments of the present application is shown. The electronic device is intended to represent various forms of digital computers, such as laptops, desktops, tablets, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular telephones, smart phones, wearable devices (e.g., headsets, glasses, watches, etc.), and other similar computing devices. The components shown here, their connections and relationships, and their functions, are meant to be examples only, and are not meant to limit implementations of the present application described and / or claimed in this document.

[0115] As shown in Figure 4 The electronic device 10 includes at least one processor 11, and a memory, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., which is communicatively connected to the at least one processor 11, wherein the memory stores a computer program that can be executed by the at least one processor. The processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 into the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0116] A plurality of components in the electronic device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a magnetic disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices through a computer network, such as the Internet, and / or various telecommunication networks.

[0117] The processor 11 can be various general and / or special purpose processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 11 performs various methods and processes described above, such as the automatic supervision method of commissioning defect files.

[0118] In some embodiments, the automatic supervision method of commissioning defect files can be implemented as a computer program tangibly embodied in a computer readable storage medium, such as the storage unit 18. In some embodiments, part or all of the computer program can be loaded and / or installed onto the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded onto the RAM 13 and executed by the processor 11, one or more steps of the automatic supervision method of commissioning defect files described above can be performed. Alternatively, in other embodiments, the processor 11 can be configured to perform the automatic supervision method of commissioning defect files by any other appropriate means, such as by means of firmware.

[0119] Various implementations of the systems and techniques described above can be realized in digital electronic circuitry, integrated circuitry, a field programmable gate array (FPGA), an application specific integrated circuit (ASIC), a system on a chip (SOC), a programmable logic device (CPLD), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include implementation in one or more computer programs that are executable and / or interpretable on a programmable system including at least one programmable processor, which can be special or general purpose, coupled to receive data and instructions from, and to transmit data and instructions to, a storage system, at least one input device, and at least one output device.

[0120] Computer programs for implementing the methods of the present application can be written in any combination of one or more programming languages. These computer programs can be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the computer program, when executed, enables the functions / acts specified in the flowcharts and / or block diagrams to be implemented. The computer program can be executed entirely on a machine, partially on a machine, partially on a machine as a standalone software package and partially on a remote machine or entirely on a remote machine or server.

[0121] In the context of the present application, a computer-readable storage medium can be a tangible medium that can contain or store a computer program for use by or in connection with an instruction execution system, apparatus, or device. A computer-readable storage medium can include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium can be a machine-readable signal medium. More specific examples of a machine-readable storage medium will include one or more lines of electrical connections, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0122] To provide for interaction with a user, the systems and techniques described here can be implemented on an electronic device having a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user and a keyboard and a pointing device (e.g., a mouse or a trackball) by which the user can provide input to the electronic device. Other kinds of devices can be used to provide for interaction with a user as well; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form, including acoustic, speech, or tactile input.

[0123] The systems and techniques described herein can be implemented in a computing system that includes a back end component, e.g., as a data server, or that includes a middleware component, e.g., an application server, or that includes a front end component, e.g., a user computer having a graphical user interface or a Web browser through which a user can interact with an implementation of the systems and techniques described herein, or any combination of such back end, middleware, or front end components. The components of the system can be interconnected by any form or medium of digital data communication, e.g., a communication network. Examples of communication networks include a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0124] The computing system can include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. A server can be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system, to solve the defects of large management difficulty and weak business scalability in traditional physical host and VPS service.

[0125] It should be understood that the various forms of flow shown above can be reordered, added to, or deleted from without departing from the scope of the present application. For example, the steps described in the present application can be executed in parallel, in sequence, or in a different order, as long as the desired results of the technical solutions of the present application can be achieved, and the present application is not limited herein.

[0126] Embodiment five

[0127] The embodiment provides a computer readable storage medium, and a computer program is stored on the computer readable storage medium. The computer program is executed by a processor to implement a method for automatically supervising a defect file in network distribution provided by any embodiment of the present application. The method comprises the following steps.

[0128] Requesting a defect data file from a power grid management platform;

[0129] Receiving at least one defect data file issued by a defect management module of the power grid management platform;

[0130] Performing defect analysis supervision on the defect data file, determining a target problem file, and outputting a problem reason of the target problem file.

[0131] The computer storage medium of the embodiments of the present application can adopt any combination of one or more computer readable media. The computer readable medium can be a computer readable signal medium or a computer readable storage medium. The computer readable storage medium may, for example, but is not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or apparatus, or any combination thereof. More specific examples (non-exhaustive list) of the computer readable storage medium include an electrical connection having one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this document, the computer readable storage medium can be any tangible medium that contains or stores a program that can be used by or in connection with an instruction execution system, apparatus or device.

[0132] The computer readable signal medium can include a data signal propagated in baseband or propagated as a carrier wave, in which computer readable program code is embodied. Such propagated data signals can take a wide variety of forms, including but not limited to electro-magnetic signals, optical signals, or any suitable combination thereof. Computer readable signal medium can also be any computer readable medium that is not a storage medium, that is capable of storing the program code for use by or in connection with an instruction execution system, apparatus or device.

[0133] The program code embodied on the computer readable medium can be transmitted using any appropriate medium, including but not limited to wireless, wire line, optical fiber cable, RF, etc., or any suitable combination of the above.

[0134] Computer program code for carrying out operations of the present application can be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C++ or the like, and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code can execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection can be made to an external computer (for example, through the Internet using an Internet Service Provider). In some embodiments of the present application, electronic mail (email) can be utilized as the

[0135] Those skilled in the art should understand that the modules or steps of the present application described above can be implemented by general computing devices, which can be centralized on a single computing device or distributed on a network composed of multiple computing devices. Alternatively, they can be implemented by computer-executable program codes, which can be stored in storage devices and executed by computing devices, or they can be implemented by individual integrated circuit modules or a plurality of modules or steps of them can be implemented by a single integrated circuit module.

[0136] It should be understood that the steps shown above can be reordered, added, or deleted. For example, the steps described in the present application can be executed in parallel, sequentially, or in different orders, as long as the desired results of the technical solutions of the present application can be achieved, and the present application is not limited herein.

[0137] The specific embodiments described above do not constitute a limitation of the protection scope of the present application. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent replacements, and improvements made within the spirit and principles of the present application shall be included in the protection scope of the present application.

Claims

1. A method for automatically supervising a network configuration defect file, characterized by, The method comprises the following steps: requesting a defect data file from a power grid management platform; receiving at least one defect data file issued by a defect management module of the power grid management platform; automatically performing defect analysis supervision on the defect data file, determining a target problem file, and outputting a problem cause of the target problem file; the defect analysis supervision on the defect data file and the determination of the target problem file comprise the following steps: parsing the defect data file to obtain an execution node, an executor, a defect registration file and a defect elimination registration file of the defect data file; respectively performing defect analysis supervision on the execution node, the executor, the defect registration file and the defect elimination registration file of the defect data file to determine the target problem file; the defect analysis supervision on the execution node, the executor, the defect registration file and the defect elimination registration file of the defect data file comprises the following steps: obtaining an original defect image and defect attributes corresponding to the defect registration file, and performing defect analysis supervision on the defect attributes according to the original defect image; wherein the defect attributes comprise a device category, a device defect phenomenon, a device defect level, a device defect type and a device management unit; obtaining a processing defect elimination image and defect elimination attributes corresponding to the defect elimination registration file, and sequentially performing defect analysis supervision on the processing defect elimination image and the defect elimination attributes; wherein the defect elimination attributes comprise a defect cause, a defect device part and a defect elimination treatment measure; the defect analysis supervision on the defect attributes according to the original defect image comprises the following steps: determining an ideal device category, an ideal defect appearance and an ideal defect level according to the original defect image; determining an ideal defect type and an ideal management unit according to the ideal device category, the ideal defect appearance and the ideal defect level; in the case that the ideal device category, the ideal defect appearance, the ideal defect level, the ideal defect type and the ideal management unit are different from the device category, the device defect phenomenon, the device defect level, the device defect type and the device management unit, the defect data file is determined as the target problem file; the defect analysis supervision on the processing defect elimination image and the defect elimination data comprises the following steps: determining at least one ideal defect treatment measure according to the defect cause and the defect device part, and respectively obtaining an image recording identifier of the processing defect elimination image and an image recording identifier of the original defect image; wherein the image recording identifier comprises an image shooting position and image annotation information; in the case that any of the following conditions exists, the defect data file is determined as the target problem file: the defect elimination treatment measure is different from any ideal defect treatment measure; the image recording identifier of the processing defect elimination image is different from the image recording identifier of the original defect image; the defect analysis supervision on the execution node, the executor, the defect registration file and the defect elimination registration file of the defect data file further comprises the following steps: obtaining an execution time corresponding to the execution node, and performing defect analysis supervision on the execution time; Obtaining the number of executors corresponding to the executor, and performing defect analysis supervision on the number of executors; The defect analysis supervision on the number of executors comprises: In the case that the number of executors is less than a preset number threshold, the defect data file is determined as the target problem file; The execution time is the time point of submission after completing the registration and reporting of any one list; The number of executors is the number of executor names appearing in the defect data file.

2. The method of claim 1, wherein The defect analysis supervision on the execution time comprises: In the case that the execution time is incorrect, the defect data file is determined as the target problem file.

3. An automatic supervision device for network configuration defect files, characterized in that, Comprise: A data request module for requesting a defect data file from a power grid management platform; A data receiving module for receiving at least one defect data file issued by a defect management module of the power grid management platform; An automatic supervision module for automatically performing defect analysis supervision on the defect data file, determining a target problem file, and outputting the problem reason of the target problem file; The automatic supervision module is specifically used for: Parsing the defect data file to obtain the execution node, executor, defect registration file and defect elimination registration file of the defect data file; Respectively performing defect analysis supervision on the execution node, executor, defect registration file and defect elimination registration file of the defect data file to determine the target problem file; The automatic supervision module is specifically used for: Obtaining the original defect image and defect attribute corresponding to the defect registration file, and performing defect analysis supervision on the defect attribute according to the original defect image; wherein the defect attribute comprises device category, device defect phenomenon, device defect level, device defect type and device management unit; Obtaining the processing defect elimination image and defect elimination attribute corresponding to the defect elimination registration file, and sequentially performing defect analysis supervision on the processing defect elimination image and defect elimination attribute; wherein the defect elimination attribute comprises defect reason, defect device part and defect elimination treatment measure; The automatic supervision module is specifically used for: Determining the ideal device category, ideal defect appearance and ideal defect level according to the original defect image; Determining the ideal defect type and ideal management unit according to the ideal device category, ideal defect appearance and ideal defect level; In the case that the ideal device category, the ideal defect appearance, the ideal defect level, the ideal defect type and the ideal management unit are not the same as the device category, the device defect phenomenon, the device defect level, the device defect type and the device management unit, the defect data file is determined as the target problem file; The automatic supervision module is specifically used for: Determining at least one ideal defect treatment measure according to the defect reason and the defect device part, and respectively obtaining the image recording identifier of the processing defect elimination image and the image recording identifier of the original defect image; wherein the image recording identifier comprises image shooting position and image annotation information; In the case that any of the following conditions exists, the defect data file is determined as the target problem file: The defect elimination processing measure is different from any ideal defect processing measure; An image record identifier of the processed defect elimination image is different from an image record identifier of the original defect image; The automatic supervision module is further configured to: obtain an execution time corresponding to the execution node, and perform defect analysis supervision on the execution time; obtain an execution person quantity corresponding to the execution person, and perform defect analysis supervision on the execution person quantity; The automatic supervision module is further configured to: in a case where the execution person quantity is less than a preset person quantity threshold, determine the defect data file as the target problem file; The execution time is a time point of submission after registration and reporting of any one list is completed. The execution person quantity is a quantity of execution person names appearing in the defect data file.

4. An electronic device, comprising: The electronic device comprises: at least one processor; and a memory connected with the at least one processor in communication; wherein The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor to enable the at least one processor to execute the network defect file automatic supervision method of any one of claims 1-2.

5. A computer readable storage medium, characterized in that, The computer readable storage medium stores computer instructions for enabling the processor to execute the network defect file automatic supervision method of any one of claims 1-2 when executed.

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