Device data collection method, system, terminal device and storage medium

Abstract

The present application relates to the field of operation, inspection, and control technology, and in particular to a device data acquisition method, system, terminal device, and storage medium, the method comprising obtaining a target acquisition item; obtaining corresponding acquisition data according to the type of the target acquisition item; judging whether the acquisition data meets the preset operation standard; if the acquisition data meets the preset operation standard, verifying the acquisition data according to the preset verification rules, and generating verification items as data acquisition reports; if the acquisition data does not meet the preset operation standard, obtaining corresponding abnormal acquisition data, and processing the abnormal acquisition data according to the preset tracing rules, and generating tracing items as the data acquisition report; analyzing the data acquisition report, and generating corresponding data acquisition results. The device data acquisition method, system, terminal device, and storage medium provided in the present application have the effect of improving the detection of power grid equipment.

Description

Technical Field

[0001] The present application relates to the field of operation, inspection, and control technology, and in particular to a method, system, terminal device, and storage medium for collecting equipment data. Background Art

[0002] As the construction of power grids progresses, both power grid companies and electricity users have established a considerable scale of power grid equipment. The operation, maintenance, inspection, commissioning, and transformation and replacement of power grid equipment play a vital role in the safe operation of power grid equipment.

[0003] At present, power grid equipment is usually inspected using an operation and maintenance control system, which usually requires relevant operation and maintenance personnel to upload and export the collected data of the power grid equipment. However, due to the errors between the actual operation of the power grid equipment and the corresponding collected and uploaded data, and the operation and maintenance personnel fail to update the relevant collected data in a timely manner, the data collection results of the power grid equipment will be greatly different from the actual situation. Summary of the Invention

[0004] In order to improve the detection effect of power grid equipment, the present application provides a device data acquisition method, system, terminal device and storage medium.

[0005] The present application provides a device data collection method, comprising the following steps:

[0006] Obtain target collection items;

[0007] Acquire corresponding collection data according to the type of the target collection item;

[0008] Determining whether the collected data meets the preset operating standards;

[0009] If the collected data meets the preset operating standards, the collected data is verified according to the preset verification rules, and verification items are generated as a data collection report;

[0010] If the collected data does not meet the preset operating standards, the corresponding abnormal collected data is obtained, and the abnormal collected data is processed according to the preset tracing rules to generate a tracing item as the data collection report;

[0011] Analyze the data collection report and generate corresponding data collection results.

[0012] By adopting the above technical solution, it is determined whether the acquired collected data meets the corresponding preset operating standards, and the collected data that meets the preset operating standards is further verified according to the preset verification rules to generate corresponding verification items. The abnormal collected data that does not meet the preset operating standards is processed according to the preset traceability rules to generate corresponding verification items. Then, a comprehensive analysis is performed on the verification items and traceability items in the data collection report to generate a data collection report corresponding to the relevant power grid equipment in the target collection project. The specific analysis of the collected data by the verification items and traceability items in the data collection report can actually reflect the operating status of the power grid equipment, thereby improving the detection effect of the power grid equipment.

[0013] Optionally, if the collected data meets the preset operating standard, verifying the collected data according to preset verification rules and generating verification items as a data collection report includes the following steps:

[0014] If the collected data meets the preset operating standard, obtaining the collected historical data corresponding to the collected data according to the preset verification rule;

[0015] Obtaining corresponding data differences based on the collected data and the collected historical data;

[0016] Determining whether the data difference meets a preset difference standard;

[0017] If the data difference does not meet the preset difference standard, obtaining and generating the verification item as the data collection report based on the corresponding abnormal difference data;

[0018] If the data difference meets the preset difference standard, then obtain the data fluctuation range corresponding to the collected historical data within the preset time period;

[0019] Determining whether the data fluctuation range exceeds a preset operating threshold;

[0020] If the data fluctuation range exceeds the preset operating threshold, the verification item is obtained and generated as the data collection report based on the corresponding abnormal fluctuation data.

[0021] By adopting the above technical solution, it is possible to determine whether the data difference meets the corresponding preset difference standard, further generate corresponding verification items based on the abnormal difference data that does not meet the preset difference standard, and determine whether the data fluctuation range that meets the preset difference standard exceeds the corresponding preset operating threshold, further generate corresponding verification items based on the abnormal fluctuation data that exceeds the preset operating threshold. Through the verification items, the collected historical data corresponding to the collected data can be further analyzed, thereby better reflecting the actual operating status of the power grid equipment.

[0022] Optionally, if the data fluctuation range exceeds the preset operating threshold, obtaining and generating the verification item as the data collection report based on the corresponding abnormal fluctuation data includes the following steps:

[0023] If the data fluctuation range exceeds the preset operating threshold, obtaining the corresponding abnormal fluctuation frequency according to the abnormal fluctuation data;

[0024] Determining whether the abnormal fluctuation frequency exceeds a preset frequency standard;

[0025] If the frequency of the abnormal fluctuation exceeds the preset frequency standard, the corresponding inducing factors are obtained according to the abnormal fluctuation data, and the verification items are generated as the data collection report according to the inducing factors.

[0026] By adopting the above technical solution, it is possible to determine whether the frequency of abnormal fluctuations exceeds the corresponding preset frequency standard, and further obtain the corresponding inducing factors, so as to facilitate the acquisition of the actual reasons affecting the normal operation of the power grid equipment based on the inducing factors.

[0027] Optionally, after obtaining the historical data corresponding to the collected data according to the preset verification rule if the collected data meets the preset operating standard, the following steps are further included:

[0028] Reading the collected data to obtain the corresponding data collection time point;

[0029] According to the preset verification rule, obtaining the verification time point associated with the data collection time point;

[0030] According to the associated verification time point, obtaining corresponding verification data;

[0031] Determining whether the verification data meets the preset warning standards;

[0032] If the verification data meets the preset warning standard, corresponding prompt information is generated according to the verification data.

[0033] By adopting the above technical solution, it is possible to determine whether the verification data corresponding to the associated verification time point meets the corresponding preset warning standards, thereby improving the verification scope of data collected outside the normal data collection time point, and further providing early warning prompts before abnormalities occur in the verification data.

[0034] Optionally, if the collected data does not meet the preset operating standard, obtaining corresponding abnormal collected data, processing the abnormal collected data according to preset tracing rules, and generating tracing items as the data collection report includes the following steps:

[0035] If the collected data does not meet the preset operating standard, obtaining a corresponding target device area based on the abnormal collected data;

[0036] According to the target device area, obtain a corresponding data collection list;

[0037] Read the data collection list according to the preset tracing rules and generate a corresponding collection update progress;

[0038] Determining whether the acquisition and update progress meets the preset update standard;

[0039] If the collection and update progress does not meet the preset update standard, the collection and update progress is marked, and the corresponding collection personnel information is associated to generate the traceability item as the data collection report.

[0040] By adopting the above technical solution, it is possible to determine whether the collection update progress in the data collection list corresponding to the target device area meets the preset update standards, and further calibrate and associate the collection update progress that does not meet the preset update standards with the corresponding collection personnel, and generate corresponding traceability items. Therefore, through the traceability items, it is possible to clearly understand the actual collection progress of the current collection data and the traceability of the relevant collection personnel, thereby improving the tracing of problems with abnormal collection data.

[0041] Optionally, after acquiring the corresponding target device area according to the abnormal collected data if the collected data does not meet the preset operating standard, the method further includes the following steps:

[0042] According to the target device area, obtaining the corresponding collection personnel information;

[0043] According to the collection personnel information, obtain the corresponding collection task list;

[0044] Determine whether the collected information in the collection task list meets the preset task standards;

[0045] If the collection information in the collection task list does not meet the preset task standard, obtaining the associated device area of ​​the target device area;

[0046] Acquire corresponding associated personnel according to the associated device area;

[0047] Granting the collection authority of the collected information to the associated personnel.

[0048] By adopting the above technical solution, the collection authority of the target equipment area is granted to the associated personnel in the associated equipment area, thereby reducing the occurrence of the situation where the collected data is inconsistent with the actual operation status of the power grid equipment due to the collection personnel's failure to complete the collection task in a timely manner.

[0049] Optionally, analyzing the data collection report to generate corresponding data collection results includes the following steps:

[0050] Calculating target weights of the verification items and the traceability items;

[0051] Determining whether the target weight of the traceability item is greater than the target weight of the verification item;

[0052] If the target weight of the traceability item is less than or equal to the target weight of the verification item, generating the data collection result according to the target weight of the verification item and the target weight of the traceability item;

[0053] If the target weight of the traceable item is greater than the target weight of the verification item, obtaining historical record information of the traceable item;

[0054] Obtaining the number of times the same type of traceable item is recorded in the historical record information;

[0055] Determining whether the number of recorded times meets a preset alarm standard;

[0056] If the number of recordings meets the preset alarm standard, corresponding alarm information is generated according to the tracing item as the data collection result.

[0057] By adopting the above technical solution, the target weights of the verification item and the traceability item are calculated, and it is further determined whether the target weight of the verification item is greater than the target weight of the verification item. If it is greater, the historical record information of the traceability item is obtained, and then it is determined whether the number of records of similar traceability items in the historical record information meets the preset alarm standard, and then the traceability items that meet the preset alarm standard are alarmed, thereby improving the analysis and investigation effect of frequent problems in the traceability items.

[0058] In a second aspect, the present application provides a device data acquisition system, comprising:

[0059] A first acquisition module is used to acquire target collection items;

[0060] A second acquisition module is used to acquire corresponding collection data according to the type of the target collection item;

[0061] A judgment module, used to judge whether the collected data meets the preset operating standards;

[0062] A verification module, if the collected data meets the preset operating standards, the verification module is used to verify the collected data according to preset verification rules and generate verification items as a data collection report;

[0063] The tracing module is used to obtain the corresponding abnormal collected data if the collected data does not meet the preset operating standards, and process the abnormal collected data according to the preset tracing rules to generate a tracing item as the data collection report.

[0064] The generating module is used to analyze the data collection report and generate corresponding data collection results.

[0065] The judgment module determines whether the acquired collected data meets the corresponding preset operating standards. The collected data that meets the preset operating standards is further verified according to the preset verification rules of the verification module to generate corresponding verification items. The traceability module processes the abnormal collected data that does not meet the preset operating standards according to the preset traceability rules. The generation module generates corresponding verification items, and then comprehensively analyzes the verification items and traceability items in the data collection report to generate the data collection report corresponding to the relevant power grid equipment in the target collection project. The specific analysis of the collected data by the verification items and traceability items in the data collection report can actually reflect the operating status of the power grid equipment, thereby improving the detection effect of the power grid equipment.

[0066] In a third aspect, the present application provides a terminal device that adopts the following technical solution:

[0067] A terminal device includes a memory and a processor, wherein the memory stores computer instructions that can be run on the processor, and when the processor loads and executes the computer instructions, the above-mentioned device data collection method is adopted.

[0068] By adopting the above technical solution, the above-mentioned device data collection method is generated into computer instructions and stored in the memory to be loaded and executed by the processor, thereby making a terminal device based on the memory and the processor for easy use.

[0069] In a fourth aspect, the present application provides a computer-readable storage medium, which adopts the following technical solution:

[0070] A computer-readable storage medium stores computer instructions. When the computer instructions are loaded and executed by a processor, the above-mentioned device data acquisition method is adopted.

[0071] By adopting the above technical solution, the above-mentioned device data acquisition method is generated into computer instructions and stored in a computer-readable storage medium so as to be loaded and executed by a processor. The computer-readable storage medium facilitates the reading and storage of computer instructions.

[0072] To sum up, the present application includes at least one of the following beneficial technical effects: judging whether the acquired collected data meets the corresponding preset operating standards, further verifying the collected data that meets the preset operating standards according to the preset verification rules, generating corresponding verification items, processing the abnormal collected data that does not meet the preset operating standards according to the preset traceability rules, generating corresponding verification items, and then comprehensively analyzing the verification items and traceability items in the data collection report to generate a data collection report corresponding to the relevant power grid equipment in the target collection project; through the specific analysis of the collected data by the verification items and traceability items in the data collection report, the operating status of the power grid equipment can be actually reflected, thereby improving the detection effect of the power grid equipment. BRIEF DESCRIPTION OF THE DRAWINGS

[0073] Figure 1 This is a flow chart of steps S101 to S106 in a device data collection method of the present application.

[0074] Figure 2 This is a flow chart of steps S201 to S207 in a device data collection method of the present application.

[0075] Figure 3 This is a flow chart of steps S301 to S303 in a device data collection method of the present application.

[0076] Figure 4 This is a flow chart of steps S401 to S405 in a device data collection method of the present application.

[0077] Figure 5 This is a flow chart of steps S501 to S505 in a device data collection method of the present application.

[0078] Figure 6 This is a flow chart of steps S601 to S605 in a device data collection method of the present application.

[0079] Figure 7 This is a flow chart of steps S701 to S707 in a device data collection method of the present application.

[0080] Figure 8 This is a module diagram of a device data acquisition system of the present application.

[0081] Description of reference numerals:

[0082] 1. First acquisition module; 2. Second acquisition module; 3. Judgment module; 4. Verification module; 5. Tracing module; 6. Generation module. DETAILED DESCRIPTION

[0083] The following is combined with Figure 1-8 This application is described in further detail.

[0084] In order to facilitate the explanation of this solution, the operation and maintenance of power grid equipment is taken as an example.

[0085] Previously, power industry personnel had to perform periodic power outages to inspect and repair power facilities and equipment, causing great inconvenience to residents' production and life. To meet the relevant needs of Chinese residents, more and more power departments have begun to use live detection methods to maintain power grid equipment.

[0086] Electricity is an essential energy source for people's daily lives and production, and plays a vital role. Therefore, the operation and maintenance of power grid equipment is particularly important. Live detection technology, a new type of power detection technology, involves power industry personnel using portable detection equipment to conduct on-site inspections of relevant power facilities while power equipment is operating normally. This involves conducting live detection in a short period of time.

[0087] With the development of data collection technology for power grid equipment, the collected data of power grid equipment and facilities is generally controlled through the operation and inspection control system. The operation and inspection control system has built-in multiple management modules such as task planning and dispatching management, drone data collection management, inspection results management, fault elimination management, statistics and early warning management, transmission line ledger management, drone equipment management, and drone operation online monitoring.

[0088] Among them, task management: specify weekly, monthly, and quarterly inspection plans and related task plans; drone inspection management: for various types of drone inspections, various types of data and defects and hidden dangers collected on-site are uploaded to the platform in real time through handheld terminals; defect elimination management: obtain defect information on-site, and update the status in real time after the defect elimination is completed; manual inspection management: upload various types of data collected on-site during manual inspections to the platform in real time through handheld terminals; power grid resource management: ledger management of transmission lines, substations, etc.; inventory management: daily equipment and tool management; equipment management: daily management of drone equipment (drones, cameras, batteries, etc.); statistical reports: statistics and output of various types of defects, inspection tasks, equipment, operation and maintenance work, etc. Statistical reports; drone operation monitoring: built-in map, which can monitor drone flight inspections in real time.

[0089] Integrate the various separate links in traditional transmission line operation and maintenance, such as task planning, inspection data collection, data analysis and storage, and fault elimination, into one system, realize the interconnection of internal and external operations and front-end and back-end data in operation and maintenance work, and form a complete closed loop of transmission line operation and maintenance work, thereby realizing the refined, systematic, intelligent, visual, and full-process management of transmission line operation and maintenance, and effectively improving the scientific management level of power line operation and maintenance.

[0090] The present application embodiment discloses a device data collection method, such as Figure 1As shown, the following steps are included:

[0091] S101, obtaining target collection items;

[0092] S102. Acquire corresponding collection data according to the type of target collection item;

[0093] S103, determining whether the collected data meets the preset operating standards;

[0094] S104. If the collected data meets the preset operating standards, the collected data is verified according to the preset verification rules, and verification items are generated as a data collection report;

[0095] S105: If the collected data does not meet the preset operating standards, the corresponding abnormal collected data is obtained, and the abnormal collected data is processed according to the preset traceability rules to generate a traceability item as a data collection report;

[0096] S106: Analyze the data collection report and generate corresponding data collection results.

[0097] The target collection items in step S101 to step S102 refer to the detection items of the operation status of the power grid equipment, and the collected data refer to the power grid equipment operation detection data corresponding to the target collection items.

[0098] For example, the detection items corresponding to the target collection items include 10KV line equipment detection items and 0.4KV line equipment detection items.

[0099] Among them, according to the 10KV line equipment detection items, the corresponding collection data is obtained, including the line list page, equipment summary page, equipment list page and equipment details editing page.

[0100] On the line list page, you can view the number of lines under your jurisdiction and the line names, as well as local caching for specific lines, view the optical cable status, search for line names, and perform other operations; on the equipment summary page, you can view the progress of various types of equipment; on the equipment list page, you can view the completion status of equipment inspections, add new equipment, and search for equipment names; on the equipment details editing page, you can operate on multiple dimensions such as equipment properties, ledger information, adding additional equipment, uploading photos, saving locally, and uploading local information.

[0101] According to the line equipment detection items under 0.4KV, the corresponding collection data is obtained, including the line list page, transformer list page, equipment collection map page and equipment details editing page.

[0102] On the line list page, you can view the number of lines under your jurisdiction, line names, and survey completion status, and you can search for line names; on the transformer list page, you can view the number and names of transformers on the selected line, support searching for device names, and click on a specific device name to enter the device collection map page; on the device collection map page, you can select a transformer and add branch box, distribution room, and tower data, correct the device position, and edit and save the collected device details locally; on the device details editing page, you can edit multiple dimensions such as device properties, whether to attach a user access point, upload photos, and save locally.

[0103] Among them, the specific equipment data collected for the 0.4KV line equipment inspection items include: equipment information table data: transformer, feeder, equipment name, longitude, latitude, pole height, material, voltage level, whether a user access point is mounted, access line length, connection type, model, length, whether high and low voltage are on the same pole, superior equipment, updater, update time, whether deleted, whether completed, unique identification, and photos.

[0104] Line information table data: feeder ID, line name, operation number, voltage level, installation method, overhead line length (km), cable line length (km), total line length (km), starting power station, outgoing line switch, outgoing line switch type, outgoing line interval, starting point equipment, starting point equipment name, affiliated city, operation and maintenance unit, maintenance team, affiliated city name, operation and maintenance unit name, maintenance team name, release status including, operation status, maintenance line length, equipment owner, commissioning date, power supply area, equipment code, total number of line equipment, number of completed line equipment, number of completed optical cables, number of mounted optical cables.

[0105] The preset operating standards in steps S103 to S105 refer to the standards that the collected data corresponding to the target collection project should comply with. The preset verification rules refer to the verification rules for the collected data and data related to the collected data. The verification items refer to the collection items formed after the collected data is verified according to the preset verification rules. Abnormal collected data refers to the data that the collected data corresponding to the target collection project does not comply with the corresponding preset operating standards. The preset traceability rules refer to the traceability rules for problems corresponding to abnormal collected data in the collected data. The traceability items refer to the collection items formed after the abnormal collected data is processed according to the preset traceability rules.

[0106] For example, the equipment list page is the collected data in the above-mentioned 10KV line equipment data detection item. The preset operating standard corresponding to the equipment list page is that the updated data of the newly added equipment should be consistent with the actual equipment situation. According to the actual equipment situation, a new cable branch box A is added to the 10KV line. Further, the updated data of the cable branch box A is displayed on the equipment list page. It can be determined that the collected data on the equipment list page meets the corresponding preset operating standard.

[0107] The actual connection status of the cable branch box A is further verified according to the preset verification rules corresponding to the data collected on the equipment list page. The connection status of the cable branch box A can be collected by drone to obtain image information, and then the corresponding cable branch box A verification items are generated as a data collection report.

[0108] For another example, according to the actual equipment situation, a new cable branch box A is added to the 10KV line. At this time, the updated data of the cable branch box A is not displayed on the device list page. It can be determined that the collected data on the device list page does not meet the corresponding preset operating standards.

[0109] Further obtain the abnormal collection data corresponding to the data collected on the device list page, and trace the abnormal collection data according to the corresponding preset tracing rules. The preset tracing rules can be tracing the entry system of cable branch box A, and then forming the corresponding cable branch box A tracing item as a data collection report.

[0110] The data collection report in step S106 refers to an analysis report on the relevant verification items and traceability items, and the data collection results refer to the detection results of the target collection items corresponding to the power grid equipment in the verification items and traceability items.

[0111] The device data collection method provided in this embodiment determines whether the acquired collected data meets the corresponding preset operating standards, further verifies the collected data that meets the preset operating standards according to preset verification rules, generates corresponding verification items, processes abnormal collected data that does not meet the preset operating standards according to preset traceability rules, generates corresponding verification items, then comprehensively analyzes the verification items and traceability items in the data collection report to generate a data collection report corresponding to the relevant power grid equipment in the target collection project. The specific analysis of the collected data by the verification items and traceability items in the data collection report can actually reflect the operating status of the power grid equipment, thereby improving the detection effect of the power grid equipment.

[0112] In one implementation of this embodiment, Figure 2 As shown, step S104, i.e., if the collected data meets the preset operating standards, the collected data is verified according to the preset verification rules, and the verification items are generated as a data collection report, including the following steps:

[0113] S201. If the collected data meets the preset operating standard, obtain the collected historical data corresponding to the collected data according to the preset verification rules;

[0114] S202: Obtain corresponding data differences based on the collected data and the collected historical data;

[0115] S203, determining whether the data difference meets the preset difference standard;

[0116] S204: If the data difference does not meet the preset difference standard, obtain and generate verification items as a data collection report based on the corresponding abnormal difference data;

[0117] S205: If the data difference meets the preset difference standard, obtain the data fluctuation range corresponding to the historical data collected within the preset time period;

[0118] S206: Determine whether the data fluctuation range exceeds a preset operating threshold;

[0119] S207: If the data fluctuation range exceeds the preset operating threshold, obtain and generate verification items as a data collection report based on the corresponding abnormal fluctuation data.

[0120] The collected historical data in step S201 to step S202 refers to the historical operation data corresponding to the collected data, and the data difference refers to the data difference between the current collected data and the collected historical data.

[0121] For example, it is necessary to collect the operating data of the operating voltage of the 0.4KV line every day. The corresponding collection time points are 9 am and 3 pm. According to the preset verification rules, it is necessary to conduct a random check on the operating voltage of the 0.4KV line within 1 hour before 9 am and 3 pm on the same day. The operating voltage of the 0.4KV line within 1 hour before 9 am and 3 pm on the same day is the collection historical data corresponding to the operating voltage of the 0.4KV line.

[0122] At 9 a.m., the operating voltage of the 0.4KV line was collected to be 300V. The corresponding historical data showed that the operating voltage randomly collected from the 0.4KV line within 1 hour before 9 a.m. was 320V. Further, based on the operating voltage of the 0.4KV line being 300V at 9 a.m. and the operating voltage randomly collected from the 0.4KV line within 1 hour before 9 a.m. being 320V, the corresponding data difference is 20V.

[0123] The preset difference standard in steps S203 to S205 refers to the difference value standard that should be met between the collected data and its collected historical data. Abnormal difference data refers to the relevant data that does not meet the corresponding preset difference standard. The preset time length refers to the pre-set data collection time period. The data fluctuation range refers to the range between the maximum and minimum values ​​of the collected historical data within the preset time length.

[0124] For example, according to the preset difference standard, the voltage difference between the collected data of the operating voltage of the 0.4KV line and its corresponding collected historical data shall not exceed 30V. Here, the voltage difference is the data difference indicated above.

[0125] At 9 a.m., the operating voltage of the 0.4KV line was collected to be 300V. The corresponding historical data showed that the operating voltage randomly collected from the 0.4KV line within 1 hour before 9 a.m. was 350V. It can be determined that the data difference of the operating voltage does not meet the corresponding preset difference standard. The voltage difference value of 50V is further obtained to generate the above-mentioned abnormal difference data as the corresponding verification item.

[0126] For another example, the operating voltage of the 0.4KV line collected at 9 a.m. is 300V. The corresponding historical data collection shows that the operating voltage randomly collected from the 0.4KV line within 1 hour before 9 a.m. is 310V. It can be determined that the data difference of the operating voltage meets the corresponding preset difference standard, and the data fluctuation range corresponding to the randomly collected operating voltage of 310V from the 0.4KV line within the preset time period is further obtained.

[0127] According to the preset duration, the data collection period is 10 minutes before and after the time point when the operating voltage of 310V is collected. The corresponding maximum operating voltage within the preset duration is 315V, and the minimum operating voltage is 300V. The corresponding data fluctuation range is 15V.

[0128] The preset operating threshold in steps S206 to S207 refers to the fluctuation threshold that the data fluctuation range corresponding to the collected historical data should meet, and abnormal fluctuation data refers to abnormal data corresponding to the data fluctuation range of the collected historical data exceeding the corresponding preset operating threshold.

[0129] For example, the data fluctuation range corresponding to the historical data collected for the 0.4KV line is 15V. According to the corresponding preset operating threshold, the fluctuation threshold of the data fluctuation range corresponding to the historical data collected is 10V. It can be determined that the data fluctuation range corresponding to the historical data collected for the 0.4KV line does not meet the corresponding preset operating threshold. Further, abnormal fluctuation data with a fluctuation range of 15V in the historical data is obtained, and corresponding verification items are generated as data collection reports.

[0130] For another example, if the data fluctuation range corresponding to the historical data collected for the 0.4KV line is 8V, it can be determined that the data fluctuation range corresponding to the historical data collected for the 0.4KV line meets the corresponding preset operating threshold, and the fluctuation of the historical data collected for the 0.4KV line will continue to be monitored.

[0131] The device data collection method provided in this embodiment determines whether the data difference meets the corresponding preset difference standard, further generates corresponding verification items based on the abnormal difference data that does not meet the preset difference standard, and determines whether the data fluctuation range that meets the preset difference standard exceeds the corresponding preset operating threshold, and further generates corresponding verification items based on the abnormal fluctuation data that exceeds the preset operating threshold. The collection historical data corresponding to the collected data can be further analyzed through the verification items, thereby better reflecting the actual operating status of the power grid equipment.

[0132] In one implementation of this embodiment, Figure 3 As shown, step S207, i.e., if the data fluctuation range exceeds the preset operating threshold, obtaining and generating verification items as a data collection report based on the corresponding abnormal fluctuation data, includes the following steps:

[0133] S301. If the data fluctuation range exceeds the preset operating threshold, obtain the corresponding abnormal fluctuation frequency based on the abnormal fluctuation data;

[0134] S302, determining whether the frequency of abnormal fluctuations exceeds a preset frequency standard;

[0135] S303. If the frequency of abnormal fluctuations exceeds the preset frequency standard, the corresponding inducing factors are obtained according to the abnormal fluctuation data, and verification items are generated according to the inducing factors as a data collection report.

[0136] The abnormal fluctuation frequency in step S301 to step S303 refers to the number of times abnormal fluctuation data occurs, the preset frequency standard refers to the safe number standard for the occurrence of abnormal fluctuation data, and the inducing factor refers to the reason for the occurrence of abnormal fluctuation data.

[0137] For example, the data fluctuation range corresponding to the historical data collected by the 0.4KV line is 15V. According to its corresponding preset operating threshold, the fluctuation threshold of the data fluctuation range corresponding to the historical data collected is 10V. It can be determined that the data fluctuation range corresponding to the historical data collected by the 0.4KV line does not meet the corresponding preset operating threshold, and further abnormal fluctuation data with a fluctuation range of 15V of the historical data collected is obtained.

[0138] After system query, the abnormal fluctuation frequency of 15V abnormal fluctuation data is 5 times. According to the preset frequency standard corresponding to the abnormal fluctuation frequency, it can be determined that the abnormal fluctuation frequency exceeds the corresponding preset frequency standard. The inducing factor of the abnormal fluctuation frequency is obtained to be lightning strike, and the corresponding verification item is generated as a data collection report based on the inducing factor of the lightning strike.

[0139] The device data collection method provided in this embodiment determines whether the frequency of abnormal fluctuations exceeds the corresponding preset frequency standard, and further obtains the corresponding inducing factors, so as to facilitate the acquisition of the actual reasons affecting the normal operation of the power grid equipment based on the inducing factors.

[0140] In one implementation of this embodiment, Figure 4 As shown, in step S104, if the collected data meets the preset operating standards, the collected data is checked according to the preset checking rules, and the check items are generated as a data collection report, and the following steps are also included:

[0141] S401, read the collected data and obtain the corresponding data collection time point;

[0142] S402. Obtaining a verification time point associated with a data collection time point according to a preset verification rule;

[0143] S403. Obtain corresponding verification data according to the associated verification time point;

[0144] S404: Determine whether the verification data meets the preset warning standards;

[0145] S405: If the verification data meets the preset warning standard, a corresponding prompt message is generated based on the verification data.

[0146] The data collection time point in step S401 to step S402 refers to the collection time point of the collected data, the preset verification rule refers to the collection data verification rule other than the pre-specified data collection time point, and the associated verification time point refers to the pre-set verification time point related to the collection data association.

[0147] For example, the operating data of the operating voltage of the 0.4KV line needs to be collected once on the 1st and 15th of each month. The 1st and 15th of each month here are the data collection time points expressed above. According to the preset verification rules, the associated verification time point of the above data collection time point is obtained as the last day of each month. Here, the last day of each month is the associated verification time point expressed above.

[0148] The verification data in step S403 to step S405 refers to the verification data of the power grid equipment within the associated verification time point, and the preset warning standard refers to the verification data reaching the warning standard.

[0149] For example, the associated verification time point is the last day of March. The verification data of the operating voltage of the 0.4KV line collected on the last day of March is 310V. According to the preset early warning standard, a corresponding early warning will be issued when the operating voltage of the 0.4KV line exceeds 305V. At this time, it can be determined that the verification data does not meet the corresponding preset early warning standard, and the corresponding prompt information is generated according to the 310V operating voltage verification data.

[0150] For example, on the last day of March, the verification data of the operating voltage of the 0.4KV line was collected to be 300V. At this time, it can be determined that the verification data meets the corresponding preset warning standard, and the verification system does not take any action.

[0151] The device data collection method provided in this embodiment determines whether the verification data corresponding to the associated verification time point meets the corresponding preset warning standards, thereby improving the verification scope of data collected outside the normal data collection time point, and further providing a warning prompt before the verification data becomes abnormal.

[0152] In one implementation of this embodiment, Figure 5 As shown, step S105, i.e., if the collected data does not meet the preset operating standard, then the corresponding abnormal collected data is obtained, and the abnormal collected data is processed according to the preset tracing rules to generate the tracing items as the data collection report, includes the following steps:

[0153] S501. If the collected data does not meet the preset operating standard, obtain the corresponding target device area based on the abnormal collected data;

[0154] S502: Obtain a corresponding data collection list according to the target device area;

[0155] S503: Read the data collection list according to the preset tracing rules and generate the corresponding collection update progress;

[0156] S504: Determine whether the collection update progress meets the preset update standard;

[0157] S505: If the collection update progress does not meet the preset update standard, the collection update progress is calibrated, and the corresponding collection personnel information is associated to generate a traceability item as a data collection report.

[0158] The target device area in step S501 to step S502 refers to the area corresponding to the data collected by the collection device, and the data collection list refers to the collection list of the collected data.

[0159] For example, if the collected data of the equipment information table corresponding to the line equipment under 0.4KV does not meet the corresponding preset operating standards, the target equipment area corresponding to the equipment obtained according to the equipment information table is area A. Further, a data collection list of the corresponding equipment in area A can be obtained. The data collection list includes the equipment information table. The data that needs to be collected in the equipment information table include: the transformer to which it belongs, the large feeder to which it belongs, the equipment name, longitude, latitude, connection model, update personnel, and update time.

[0160] The collection update progress in step S503 to step S505 refers to the update progress of the collected data in the data collection list, the preset update standard refers to the update standard that the collection update progress should comply with, and the collection personnel information refers to the data collection personnel corresponding to the collected data.

[0161] For example, the data collection list is read according to the preset traceability rules to generate the collection update progress corresponding to the equipment information table, where the collection update progress of the transformer and the large feeder is 80%, and the update progress of the equipment name, longitude, latitude, and connection model is 95%. According to the preset update standard, the update progress of each collection data in the equipment information table must reach more than 90%. At this time, it can be determined that the collection update progress of the transformer and the large feeder in the equipment information table does not meet the corresponding preset update standard. The collection update progress of 80% of the transformer and the large feeder is calibrated, and the corresponding collection personnel information is associated to generate the corresponding traceability item as a data collection report.

[0162] For another example, if the update progress of the transformer, large feeder, device name, longitude, latitude, and connection model in the device information table is 95%, it can be determined that the collected data in the device information table meets the corresponding preset update standard, and the update progress of the collected data in the device information table will continue to be updated in real time.

[0163] The device data collection method provided in this embodiment determines whether the collection update progress in the data collection list corresponding to the target device area meets the preset update standards, further calibrates and associates the collection update progress that does not meet the preset update standards with the corresponding collection personnel, and generates corresponding traceability items. Therefore, through the traceability items, the actual collection progress of the current collection data can be clearly understood, as well as the traceability of the relevant collection personnel, thereby improving the tracing of problems with abnormal collection data.

[0164] In one implementation of this embodiment, Figure 6 As shown, in step S501, that is, if the collected data does not meet the preset operating standard, the following steps are further included after obtaining the corresponding target device area according to the abnormal collected data:

[0165] S601. Obtain corresponding collection personnel information according to the target device area;

[0166] S602: Obtain a corresponding collection task list based on the collection personnel information;

[0167] S603: Determine whether the collected information in the collection task list meets the preset task standards;

[0168] S604: If the collection information in the collection task list does not meet the preset task standard, obtain the associated device area of ​​the target device area;

[0169] S605. Obtain the corresponding associated personnel according to the associated device area;

[0170] S606: Granting the collection authority of the collected information to the related personnel.

[0171] The collection task list in step S601 to step S602 refers to the collection tasks corresponding to the collection personnel information.

[0172] For example, based on area A, the corresponding data collector Wang Wu is obtained, and Wang Wu's personal information is further obtained. Here, Wang Wu's personal information is the collection personnel information corresponding to area A. Further, based on Wang Wu's personal information, the corresponding collection task list is obtained, which is the collection task items of the corresponding transformer, the corresponding large feeder, the equipment name, longitude, latitude, connection model, update personnel, and update time.

[0173] The collection information in steps S603 to 604 refers to the collection information corresponding to the collection task in the collection task list, the preset task standard refers to the standard that the collection information in the collection task list should complete, and the associated device area refers to the area adjacent to the target device area.

[0174] For example, the collection information in the collection task list is the collection information of the transformer, the large feeder, the equipment name, longitude, latitude, connection model, update personnel, and update time. According to the preset task standard, the update progress of each collection information in the collection task list is more than 95%. Further, the update progress of the transformer and the large feeder is 90%, and the update progress of the equipment name, longitude, latitude, connection model, update personnel, and update time collection information is 98%. It can be determined that the update progress of the transformer and the large feeder does not meet the corresponding preset task standard, and the associated equipment area of ​​the target equipment area where the transformer and the large feeder are located is obtained. Among them, the area where the transformer and the large feeder are located is area A, and area B is the adjacent area of ​​area A. Then area B is the associated equipment area of ​​area A.

[0175] For example, if the update progress of the collection information of the transformer, large feeder, equipment name, longitude, latitude, connection model, update personnel, and update time in the collection task list is 98%, it can be determined that all the collection information in the collection task list meets the corresponding preset task standards, and the system displays the update progress of the collection information in the collection task list in real time.

[0176] The associated personnel in step S605 to step S606 are data collectors corresponding to the associated device area, and the collection authority refers to the authority to collect information of the target device area.

[0177] In actual use, because the associated device area is close to the target device area, when there is a vacancy in the data collection personnel in the target device area or the data is not updated in time, the data collection personnel in the associated device area can conveniently view the actual situation of the equipment in the target device area and collect data from the equipment in the target device area. The data collection permissions corresponding to the relevant areas are set to ensure the security of the equipment data.

[0178] For example, if Wang Wu, the collector in Area A, fails to meet the corresponding preset task standards due to untimely update of the collected information, the associated equipment area of ​​Area B adjacent to Area A is obtained, and the corresponding associated personnel Zhang San is obtained based on the associated equipment area of ​​Area B. Wang Wu's collection authority to collect information from Area A is further granted to Zhang San, and Zhang San collects the information from Area A.

[0179] The device data collection method provided in this embodiment grants the collection authority of the target device area to the associated personnel in the associated device area, thereby reducing the occurrence of the situation where the collected data is inconsistent with the actual operation status of the power grid equipment due to the collection personnel's failure to complete the collection task in a timely manner.

[0180] In one implementation of this embodiment, Figure 7 As shown, step S106 is analyzing the data collection report and generating corresponding data collection results, which includes the following steps:

[0181] S701. Calculate target weights for verification items and traceability items;

[0182] S702: Determine whether the target weight of the traceability item is greater than the target weight of the verification item;

[0183] S703. If the target weight of the traceability item is less than or equal to the target weight of the verification item, generate a data collection result based on the target weight of the verification item and the target weight of the traceability item;

[0184] S704: If the target weight of the traceability item is greater than the target weight of the verification item, obtain historical record information of the traceability item;

[0185] S705, obtaining the number of times the same type of traceability item is recorded in the historical record information;

[0186] S706, determining whether the number of recorded times meets the preset alarm standard;

[0187] S707: If the number of recorded times meets the preset alarm standard, corresponding alarm information is generated according to the traceability item as the data collection result.

[0188] The target weights in steps S701 to S703 refer to the percentages of the verification and traceability items in the overall data. For example, if the target weight for the verification item is 60% and the target weight for the traceability item is 40%, then the target weight for the traceability item is determined to be less than or equal to the target weight for the verification item. The corresponding data collection results are then generated based on the 60% target weight for the verification item and the 40% target weight for the traceability item.

[0189] The historical record information in step S704 refers to the historical storage record information related to the traceability item in the operation and inspection system. For example, if the target weight of the verification item is 40% and the target weight of the traceability item is 60%, it can be determined that the target weight of the traceability item is greater than the target weight of the verification item. In this case, the historical record information of the traceability item in the operation and inspection system is obtained based on the current traceability item.

[0190] The number of recording times in step S705 to step S707 refers to the number of times the same type of traceability item is recorded in the historical recording information, and the preset alarm standard refers to the standard that the traceability item meets the alarm.

[0191] For example, according to the tracing item, abnormal collection data of data collector Wang Wu not updating data in time is obtained, wherein the historical record information records abnormal collection data of data collector Wang Wu not updating data in time 5 times. According to the preset alarm standard, it can be obtained that the alarm information is triggered when the number of times the data collector fails to update data in time exceeds 3 times. It can be determined that the number of records corresponding to the abnormal collection data of data collector Wang Wu not updating data in time in the tracing item meets the corresponding preset alarm standard. Then, the corresponding alarm information is generated according to the tracing item corresponding to the data collector Wang Wu, and used as the data collection result.

[0192] For another example, if the historical record information contains two abnormal collection data in which the data collector Wang Wu did not update the data in a timely manner, it can be determined that the number of records corresponding to the abnormal collection data in which the data collector Wang Wu did not update the data in a timely manner in the traceability item does not meet the corresponding preset alarm standard, and the system does not take any action.

[0193] The device data collection method provided in this embodiment calculates the target weights of the verification item and the traceability item, and further determines whether the target weight of the verification item is greater than the target weight of the verification item. If so, the historical record information of the traceability item is obtained, and then the number of records of similar traceability items in the historical record information is determined to meet the preset alarm standard. Then, the traceability items that meet the preset alarm standard are alarmed, thereby improving the analysis and troubleshooting effect of frequent problems in the traceability items.

[0194] This application also discloses a device data acquisition system, such as Figure 8 Shown, including:

[0195] The first acquisition module 1 is used to acquire target collection items;

[0196] The second acquisition module 2 is used to acquire corresponding collection data according to the type of the target collection item;

[0197] Judgment module 3, used to judge whether the collected data meets the preset operating standards;

[0198] Verification module 4, if the collected data meets the preset operating standards, the verification module 4 is used to verify the collected data according to the preset verification rules and generate verification items as a data collection report;

[0199] Tracing module 5, if the collected data does not meet the preset operating standards, tracing module 5 is used to obtain the corresponding abnormal collected data, and process the abnormal collected data according to the preset tracing rules to generate tracing items as data collection reports;

[0200] The generating module 6 is used to analyze the data collection report and generate corresponding data collection results.

[0201] The equipment data acquisition system provided in this embodiment determines whether the acquired collected data meets the corresponding preset operating standards through the judgment module 3, further verifies the collected data that meets the preset operating standards according to the preset verification rules of the verification module 4, and generates corresponding verification items. The abnormal collected data that does not meet the preset operating standards is processed by the tracing module 5 according to the preset tracing rules, and the corresponding verification items are generated by the generation module 6. The verification items and tracing items in the data collection report are then comprehensively analyzed to generate a data collection report corresponding to the relevant power grid equipment in the target collection project. The specific analysis of the collected data through the verification items and tracing items in the data collection report can actually reflect the operating status of the power grid equipment, thereby improving the detection effect of the power grid equipment.

[0202] It should be noted that the device data acquisition system provided in the embodiment of the present application also includes various modules and / or corresponding sub-modules corresponding to the logical functions or logical steps of any of the above-mentioned device data acquisition methods, to achieve the same effects as each logical function or logical step, and the details will not be repeated here.

[0203] An embodiment of the present application also discloses a terminal device, including a memory, a processor, and computer instructions stored in the memory and capable of running on the processor, wherein when the processor executes the computer instructions, any one of the device data collection methods in the above embodiments is adopted.

[0204] Among them, the terminal device can be a computer device such as a desktop computer, a laptop computer or a cloud server, and the terminal device includes but is not limited to a processor and a memory. For example, the terminal device can also include input and output devices, network access devices and buses, etc.

[0205] Among them, the processor can adopt a central processing unit (CPU). Of course, according to actual usage, other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. can also be adopted. The general-purpose processor can adopt a microprocessor or any conventional processor, etc., and this application does not impose any restrictions on this.

[0206] Among them, the memory can be an internal storage unit of the terminal device, such as the hard disk or memory of the terminal device, or it can be an external storage device of the terminal device, such as a plug-in hard disk, smart memory card (SMC), secure digital card (SD) or flash memory card (FC) equipped on the terminal device, etc., and the memory can also be a combination of the internal storage unit and the external storage device of the terminal device. The memory is used to store computer instructions and other instructions and data required by the terminal device. The memory can also be used to temporarily store data that has been output or is to be output. This application does not impose any restrictions on this.

[0207] Among them, through this terminal device, any one of the device data collection methods in the above embodiments is stored in the memory of the terminal device, and is loaded and executed on the processor of the terminal device for easy use.

[0208] An embodiment of the present application further discloses a computer-readable storage medium, and the computer-readable storage medium stores computer instructions, wherein when the computer instructions are executed by a processor, any one of the device data collection methods in the above embodiments is adopted.

[0209] Among them, computer instructions can be stored in computer-readable media, computer instructions include computer instruction codes, computer instruction codes can be in source code form, object code form, executable files or certain middleware forms, etc. Computer-readable media include any entity or device that can carry computer instruction codes, recording media, USB flash drives, mobile hard drives, magnetic disks, optical disks, computer memories, read-only memories (ROMs), random access memories (RAMs), electrical carrier signals, telecommunication signals, and software distribution media, etc. It should be noted that computer-readable media include but are not limited to the above-mentioned components.

[0210] Among them, through this computer-readable storage medium, any one of the device data collection methods in the above embodiments is stored in the computer-readable storage medium, and is loaded and executed on the processor to facilitate the storage and application of the above method.

[0211] The above are all preferred embodiments of the present application, and are not intended to limit the scope of protection of the present application. Therefore, any equivalent changes made based on the structure, shape, and principle of the present application should be included in the scope of protection of the present application.

Claims

1. A device data collection method, characterized in that: The following steps are involved: Obtain target collection items; Acquire corresponding collection data according to the type of the target collection item; Determining whether the collected data meets the preset operating standards; If the collected data meets the preset operating standard, the collected historical data corresponding to the collected data is obtained according to the preset verification rules; Calculating data differences based on the collected data and the collected historical data; If the data difference does not meet the preset difference standard, abnormal difference data is generated as a verification item; If the data difference meets the preset difference standard, the data fluctuation range within the preset time period is obtained, and when the data fluctuation range exceeds the preset operating threshold, abnormal fluctuation data is generated as a verification item; Generate data collection reports; If the collected data does not meet the preset operating standard, the corresponding abnormal collected data is obtained, and the target device area is determined according to the abnormal collected data; a data collection list is obtained according to the target device area, and a collection update schedule is generated; If the collection and update progress does not meet the preset update standard, the collection personnel information is associated to generate a traceability item; Analyze the traceability items and the verification items in the data collection report to generate corresponding data collection results.

2. The device data collection method according to claim 1, characterized in that: generating abnormal fluctuation data as a verification item when the data fluctuation range exceeds a preset operating threshold; Generating a data collection report involves the following steps: If the data fluctuation range exceeds the preset operating threshold, obtaining the corresponding abnormal fluctuation frequency according to the abnormal fluctuation data; Determining whether the abnormal fluctuation frequency exceeds a preset frequency standard; If the frequency of the abnormal fluctuation exceeds the preset frequency standard, the corresponding inducing factors are obtained according to the abnormal fluctuation data, and the verification items are generated as the data collection report according to the inducing factors.

3. The device data collection method according to claim 1, characterized in that: If the collected data meets the preset operating standard, the method further includes the following steps after obtaining the collected historical data corresponding to the collected data according to the preset verification rule: Reading the collected data to obtain the corresponding data collection time point; According to the preset verification rule, obtaining the verification time point associated with the data collection time point; According to the associated verification time point, obtaining corresponding verification data; Determining whether the verification data meets the preset warning standards; If the verification data meets the preset warning standard, corresponding prompt information is generated according to the verification data.

4. The device data collection method according to claim 1, characterized in that: After determining the target device area according to the abnormal collected data, the method further includes the following steps: According to the target device area, obtaining the corresponding collection personnel information; According to the collection personnel information, obtain the corresponding collection task list; Determine whether the collected information in the collection task list meets the preset task standards; If the collection information in the collection task list does not meet the preset task standard, obtaining the associated device area of ​​the target device area; Acquire corresponding associated personnel according to the associated device area; Granting the collection authority of the collected information to the associated personnel.

5. The device data collection method according to claim 1, characterized in that: Analyzing the traceability items and the verification items in the data collection report to generate corresponding data collection results includes the following steps: Calculating target weights of the verification items and the traceability items; Determining whether the target weight of the traceability item is greater than the target weight of the verification item; If the target weight of the traceability item is less than or equal to the target weight of the verification item, generating the data collection result according to the target weight of the verification item and the target weight of the traceability item; If the target weight of the traceable item is greater than the target weight of the verification item, obtaining historical record information of the traceable item; Obtaining the number of times the same type of traceable item is recorded in the historical record information; Determining whether the number of recorded times meets a preset alarm standard; If the number of recordings meets the preset alarm standard, corresponding alarm information is generated according to the tracing item as the data collection result.

6. A device data acquisition system, characterized in that: include: A first acquisition module (1) is used to acquire target collection items; A second acquisition module (2) is used to acquire corresponding collection data according to the type of the target collection item; A judgment module (3) is used to judge whether the collected data meets the preset operating standards; A verification module (4), if the collected data meets the preset operating standard, the verification module (4) is used to obtain the collected historical data corresponding to the collected data according to the preset verification rules; calculate the data difference based on the collected data and the collected historical data; if the data difference does not meet the preset difference standard, generate abnormal difference data as a verification item; If the data difference meets the preset difference standard, the data fluctuation range within the preset time period is obtained, and when the data fluctuation range exceeds the preset operating threshold, abnormal fluctuation data is generated as a verification item; Generate data collection reports; A tracing module (5) is used to obtain corresponding abnormal collected data if the collected data does not meet the preset operating standard, and determine the target device area based on the abnormal collected data; obtain a data collection list based on the target device area, and generate a collection update progress; if the collection update progress does not meet the preset update standard, associate the collection personnel information to generate a tracing item; Analyze the traceability items and the verification items in the data collection report to generate corresponding data collection results; A generation module (6) is used to analyze the traceability items and the verification items in the data collection report to generate corresponding data collection results.

7. A terminal device comprising a memory and a processor, characterized in that: The memory stores computer instructions that can be run on the processor. When the processor loads and executes the computer instructions, the device data acquisition method according to any one of claims 1 to 5 is adopted.

8. A computer-readable storage medium storing computer instructions, characterized in that: When the computer instructions are loaded and executed by the processor, the device data collection method according to any one of claims 1 to 5 is adopted.

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