Smart meter monitoring method, device, equipment and storage medium

Abstract

The present disclosure provides a smart meter monitoring method, device, equipment and storage medium. The method includes: sending a basic information text to a distributed file system, downloading the basic information text from the distributed file system to a data warehouse; creating a basic information table of the meter in the original data layer, loading the content in the basic information text into the basic information table of the meter, and then using the cleaning data layer to clean the basic information table of the meter to obtain a cleaned basic information table of the meter; using the summary data layer to summarize the cleaned basic information table of the meter to obtain a summary table of meter information of different statistical dimensions; using the report platform to query the table in the application data layer to obtain the target meter information, based on the target meter information to develop a report to obtain an assessment report, and based on the assessment report to monitor the fault and energy consumption of the smart meter. The present disclosure realizes the intelligent monitoring of the meter, which can improve the energy utilization rate and the level of accurate energy management.

Description

Technical Field

[0001] The present disclosure relates to the field of data processing technology, and in particular to a smart meter monitoring method, device, equipment and storage medium. Background Art

[0002] With the vigorous development of the national power grid, the construction of smart grids has provided opportunities for smart meters. New smart meters have been widely promoted and popularized. my country's electric energy meter industry is in the stage of smart meter replacement. The measurement data and collection system of smart meters presents the characteristics of large scale, high collection frequency, long data storage time, diversified data and dense distribution of measurement points.

[0003] In the prior art, for the collection of meter data, the smart meter information is usually collected in the form of on-site verification. The traditional method is to manually record the meter usage and meter base number, which requires a lot of manpower and material resources. In addition, due to the poor real-time performance of data collection, completing a large number of data collection and transmission tasks will inevitably greatly affect the data collection rate, resulting in the inability to quickly obtain the meter usage and meter base number. At the same time, due to the relatively poor inspection cycle, the smart meter failure cannot be discovered in time. The existing smart meter monitoring and management method, the analysis results of meter data are affected by human subjectivity, the energy information visibility is poor, the data processing efficiency is low, the resource management level is low, and the intelligent monitoring of the meter cannot be realized, which is not conducive to improving energy utilization and accurate energy management. Summary of the invention

[0004] In view of this, the embodiments of the present disclosure provide a smart meter monitoring method, device, equipment and storage medium to solve the problems of low data processing efficiency in the prior art, inability to realize smart monitoring of the meter, which is not conducive to improving energy utilization and accurate management of energy.

[0005] In a first aspect of an embodiment of the present disclosure, a smart meter monitoring method is provided, comprising: obtaining basic information text uploaded by a user, and sending the basic information text to a distributed file system of a big data cluster, wherein the basic information text contains basic information related to the meter; adding a timestamp to each basic information text according to the current time, and downloading the basic information text with the timestamp added from the distributed file system to a pre-configured data warehouse; creating an electric meter basic information table in the original data layer of the data warehouse, and loading the content in the basic information text into the electric meter basic information table, and then transferring the electric meter basic information table containing the basic information to the cleaned data warehouse. Layer, use the cleaning data layer to perform data cleaning operations on the basic information table of the electric meter to obtain the cleaned basic information table of the electric meter; transfer the cleaned basic information table of the electric meter to the summary data layer, use the summary data layer to summarize the data in the cleaned basic information table of the electric meter according to the preset statistical dimensions of different levels, and obtain the summary table of electric meter information of different statistical dimensions; transfer the electric meter information summary table to the application data layer, use the query engine in the report platform to perform query operations on the table in the application data layer to obtain the target electric meter information, develop reports based on the target electric meter information in the report platform to obtain assessment reports, and monitor the faults and energy consumption of the smart meters based on the assessment reports.

[0006] According to a second aspect of the embodiments of the present disclosure, there is provided a smart meter monitoring device, comprising: an acquisition module, configured to acquire basic information text uploaded by a user, and send the basic information text to a distributed file system of a big data cluster, wherein the basic information text contains basic information related to the meter; a download module, configured to add a timestamp to each basic information text according to the current time, and download the basic information text with the timestamp added from the distributed file system to a pre-configured data warehouse; a cleaning module, configured to create an electric meter basic information table in the original data layer of the data warehouse, and load the content in the basic information text into the electric meter basic information table, and then transfer the electric meter basic information table containing the basic information to A cleaning data layer is used to perform data cleaning operations on the basic information table of the electric meter using the cleaning data layer to obtain the cleaned basic information table of the electric meter; a summary module is configured to transfer the cleaned basic information table of the electric meter to the summary data layer, and use the summary data layer to summarize the data in the cleaned basic information table of the electric meter according to preset statistical dimensions of different levels to obtain a summary table of electric meter information of different statistical dimensions; a development module is configured to transfer the summary table of the electric meter information to the application data layer, and use the query engine in the report platform to perform query operations on the tables in the application data layer to obtain target electric meter information, and develop reports based on the target electric meter information in the report platform to obtain assessment reports, and monitor the faults and energy consumption of the smart meters based on the assessment reports.

[0007] At least one of the above technical solutions adopted in the embodiments of the present disclosure can achieve the following beneficial effects:

[0008] The basic information text uploaded by the user is obtained and sent to the distributed file system of the big data cluster, wherein the basic information text contains basic information related to the electric meter; a timestamp is added to each basic information text according to the current time, and the basic information text with the timestamp is downloaded from the distributed file system to a pre-configured data warehouse; an electric meter basic information table is created in the original data layer of the data warehouse, and the content in the basic information text is loaded into the electric meter basic information table, and then the electric meter basic information table containing the basic information is transferred to the cleaning data layer, and the cleaning data layer is used to perform data cleaning operations on the electric meter basic information table to obtain the cleaned electric meter basic information table; the cleaned electric meter basic information table is transferred to the summary data layer, and the summary data layer is used to summarize the data in the cleaned electric meter basic information table according to the preset statistical dimensions of different levels to obtain the electric meter information summary table of different statistical dimensions; the electric meter information summary table is transferred to the application data layer, and the query engine in the report platform is used to perform query operations on the table in the application data layer to obtain the target electric meter information, and a report is developed based on the target electric meter information in the report platform to obtain an assessment report, and the fault and energy consumption of the smart meter are monitored based on the assessment report. The present invention discloses an assessment report based on the development to realize energy consumption monitoring of electric meter data, and can timely discover electric meter failures based on the data in the assessment report to avoid problems caused by electric meter failures, thereby realizing intelligent monitoring of electric meters, which can improve energy utilization and the level of accurate energy management. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] In order to more clearly illustrate the technical solutions in the embodiments of the present disclosure, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present disclosure. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0010] Figure 1 It is a flowchart of a smart meter monitoring method provided by an embodiment of the present disclosure;

[0011] Figure 2 is a structural diagram of a smart meter monitoring device provided by an embodiment of the present disclosure;

[0012] Figure 3 It is a schematic diagram of the structure of an electronic device provided by an embodiment of the present disclosure. DETAILED DESCRIPTION

[0013] In the following description, specific details such as specific system structures and technologies are provided for the purpose of illustration rather than limitation, so as to provide a thorough understanding of the embodiments of the present disclosure. However, it should be clear to those skilled in the art that the present disclosure may be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to avoid obstructing the description of the present disclosure with unnecessary details.

[0014] As mentioned above, with the vigorous advocacy of the State Grid, the construction of smart grids has provided opportunities for smart meters. New smart meters have been widely promoted and popularized. my country's electric energy meter industry is in the stage of smart energy meter replacement. Now, most of the rural and urban areas no longer use electricians to read meters on site. They are replaced by smart meters with various functions and remote automatic meter reading. Smart meters are actually smart grid data terminals. In the past, regardless of the type of electricity consumption, meters could only record the amount of electricity that had been used. The measurement data and collection system of smart meters presents the characteristics of large scale, high collection frequency, long data storage time, diversified data and dense distribution of measurement points. In addition to the most basic calculation of electricity consumption, it can also calculate the electricity consumption of smart grids and photovoltaic systems separately, as well as other intelligent functions.

[0015] The traditional method is to collect smart meter information in the form of on-site verification. At the same time, due to the relatively poor inspection cycle, smart meter failures cannot be discovered in time. In addition, the traditional method is to manually record the meter usage and meter base number, which requires a lot of manpower and material resources. The real-time performance of data collection in enterprises is relatively poor. Completing a large amount of data collection and transmission tasks will inevitably greatly affect the data collection rate, resulting in the inability to quickly obtain the meter usage and meter base number.

[0016] Therefore, existing enterprises cannot obtain important information such as the meter serial number, name, usage mark, gateway location, meter location, meter address, multiple, hourly (0:00 to 23:00), weekly (Monday to Sunday), daily (1st to 31st), and monthly (January to December) meter base number and usage number. Due to the lack of data support, it is impossible to fully understand the meter usage and meter base number, and thus it is impossible to make appropriate decisions. In addition, with the intelligentization of meters, operational failures have the characteristics of suddenness and complexity. Once a meter fails and causes meter data loss or delay, it cannot be discovered and solved in a timely and rapid manner, resulting in unnecessary problems.

[0017] Figure 1 It is a flowchart of the resource management method provided by the embodiment of the present disclosure. Figure 1 The resource management method can be executed by the server. Figure 1 As shown, the resource management method may specifically include:

[0018] S101, obtaining a basic information text uploaded by a user, and sending the basic information text to a distributed file system of a big data cluster, wherein the basic information text includes basic information related to the electric meter;

[0019] S102, adding a timestamp to each basic information text according to the current time, and downloading the basic information text with the timestamp added from the distributed file system to a pre-configured data warehouse;

[0020] S103, creating an electric meter basic information table in the original data layer of the data warehouse, and loading the content in the basic information text into the electric meter basic information table, and then transferring the electric meter basic information table containing the basic information to the cleaned data layer, and performing a data cleansing operation on the electric meter basic information table using the cleaned data layer to obtain a cleaned electric meter basic information table;

[0021] S104, transferring the cleaned electric meter basic information table to the summary data layer, and using the summary data layer to summarize the data in the cleaned electric meter basic information table according to preset statistical dimensions of different levels to obtain electric meter information summary tables of different statistical dimensions;

[0022] S105, transfer the meter information summary table to the application data layer, use the query engine in the report platform to perform query operations on the table in the application data layer to obtain the target meter information, develop reports based on the target meter information in the report platform, obtain assessment reports, and monitor the faults and energy consumption of the smart meters based on the assessment reports.

[0023] Specifically, the data warehouse (DW) is obtained by systematically processing, summarizing and organizing the original scattered database data after extraction and cleaning. The purpose of data warehouse construction is to provide functional analysis and decision support as a basis for front-end query and analysis. The embodiment of the present disclosure adopts the Hive data warehouse, which is mainly used to process structured data. The Hive data warehouse is generally divided into 4 levels, namely the ODS layer, DWD layer, DWS layer and ADS layer, and each level is used to store different types of tables.

[0024] Furthermore, the big data cluster of the disclosed embodiment adopts the Hadoop big data software platform. Hadoop realizes distributed computing of massive data in a cluster composed of a large number of computers. Hadoop implements a distributed file system, wherein one component of the distributed file system is HDFS. HDFS is a distributed file system that stores very large files in a streaming data access mode and stores data in blocks on different machines in a commercial hardware cluster.

[0025] In some embodiments, before obtaining the basic information text uploaded by the user, the method also includes: the user collects basic information of the electrical equipment and the electric meter corresponding to the electrical equipment, and writes the basic information of the electric meter corresponding to the electrical equipment into the basic information text, the basic information text includes information related to the user, information related to the electric meter, and information related to the equipment, wherein the user is a corporate user.

[0026] Specifically, the electric meter used by the electric equipment of the enterprise user will generate power consumption data at every moment, and the basic information of the electric meter of each electric equipment is not exactly the same. In actual applications, the smart meter reports its own information and the generated data to the enterprise user, and the enterprise user writes the basic information of the electric meter of the electric equipment into the basic information text. For example, an external enterprise hand-writes the basic information of the electric meter corresponding to the electric equipment in the enterprise into a text document (file suffix is ​​.txt), such as the enterprise's serial number, name, usage mark, gateway location, electric meter location, electric meter address, multiplier, system code, indicator code, equipment code and other information.

[0027] In some embodiments, a data cleaning operation is performed on the electric meter basic information table using a cleaning data layer to obtain a cleaned electric meter basic information table, including: cleaning null values ​​and dirty data in the electric meter basic information table in the cleaning data layer, desensitizing the cleaned electric meter basic information table, and lightly summarizing the cleaned electric meter basic information table according to key fields in the electric meter basic information table to obtain a lightly summarized electric meter basic information table.

[0028] Specifically, after uploading the basic information text to the distributed file system HDFS, the Hive data warehouse uses the ETL data processing method to synchronize the basic information text in HDFS to the Hive data warehouse. After being synchronized to the Hive data warehouse, the basic information text is first loaded into the meter basic information table in the original data layer, and then the meter basic information table is transferred to the cleansing data layer. In the cleansing data layer, the information in the meter basic information table is cleansed, including removing null values ​​and dirty data; and the cleaned meter basic information table is desensitized, and then the cleaned meter basic information table is lightly summarized according to the key fields in the meter basic information table to obtain a lightly summarized meter basic information table. ETL is equivalent to a bridge that transfers data from the distributed file system to the data warehouse.

[0029] In some embodiments, the data in the cleaned basic information table of the electric meter is summarized to obtain electric meter information summary tables of different statistical dimensions, including: summarizing the data in the cleaned basic information table of the electric meter according to statistical dimensions of different levels to obtain electric meter information summary tables corresponding to different statistical dimensions, and the electric meter information summary table of each statistical dimension contains the data of the statistical dimension, wherein the statistical dimension includes the time statistical dimension.

[0030] Specifically, the cleaned electric meter basic information table is transferred from the cleaned data layer to the summary data layer, and the data in the cleaned electric meter basic information table is summarized in the summary data layer according to the preset statistical dimensions of different levels to obtain the electric meter information summary table of different statistical dimensions. In practical applications, the statistical dimension can adopt the time statistical dimension, for example, it can be a daily statistical dimension, a monthly statistical dimension and a yearly statistical dimension.

[0031] Furthermore, the electric meter information summary table of each statistical dimension only includes data summarized using the statistical dimension. For example, the electric meter information summary table according to the daily statistical dimension includes electric meter related information partitioned by day.

[0032] In some embodiments, a query engine in a reporting platform is used to perform query operations on tables in an application data layer to obtain target meter information, and a report is developed in the reporting platform based on the target meter information, including: based on a query engine pre-configured in the reporting platform, a query data set in the query engine is used to perform data query operations on the application data layer of the data warehouse, so as to collect target meter information from the application data layer, and an assessment report is developed using the target meter information, wherein the query engine contains a pre-developed query data set, and the query engine adopts the Presto query engine.

[0033] Specifically, the table data stored in the Hive application data layer is just a row of data, which is not displayed in the report. In addition, not all fields in the HIVE table are necessarily used when developing reports. Therefore, the Presto query engine is used in the report platform to perform query operations on the tables in the application data layer. The Presto query engine contains a pre-configured query data set, which can query the target meter information. In actual applications, the Presto query engine actually uses a SQL script for data query (i.e., data query script) to query data, that is, by adding a SQL script in the Presto query engine of the report platform, the SQL script is used to query the target meter information from the application data layer.

[0034] Furthermore, after obtaining the target meter information through the Presto query engine of the report platform, the report platform develops the assessment report based on the target meter information using the preset report configuration. When developing the report, the report configuration and the target meter information are used to automatically develop and generate an assessment report that matches the report configuration. In actual applications, the report configuration is a report configuration created based on a preset report style. Report developers can design report styles according to user needs, so the style of the assessment report finally developed can also meet the user's display needs.

[0035] In some embodiments, the data warehouse is a Hive data warehouse, the original data layer corresponds to the ODS layer in the Hive data warehouse, the cleaned data layer corresponds to the DWD layer in the Hive data warehouse, the summary data layer corresponds to the DWS layer in the Hive data warehouse, and the application data layer corresponds to the ADS layer in the Hive data warehouse.

[0036] Specifically, Hive's ODS (Operation Data Store) is the original data layer, which is used to store the original data. The basic information table of the electric meter is obtained by directly loading the original log and the original data. The data in the basic information table of the electric meter remains original without being processed; Hive's DWD (Data Warehouse Detail) is the cleaning data layer, which is used to clean the data in the ODS layer (for example, remove null values ​​and dirty data) and desensitize the data, that is, to perform light aggregation on the data; Hive's DWS (Data Warehouse Service) is used to aggregate and process according to various business topics; Hive's ADS (Application Data Store) is used to provide data for various statistical reports.

[0037] The following is a detailed description of the specific contents of the assessment report developed using the report platform in conjunction with a specific embodiment. The report is developed on the Pan-Energy Report Platform, and the final statistical report can have 12 reports, including:

[0038] (1) Assessment form_Daily report: including serial number, name, 0 o'clock, 1 o'clock, 2 o'clock, 3 o'clock, 4 o'clock, 5 o'clock, 6 o'clock, 7 o'clock, 8 o'clock, 9 o'clock, 10 o'clock, 11 o'clock, 12 o'clock, 13 o'clock, 14 o'clock, 15 o'clock, 16 o'clock, 17 o'clock, 18 o'clock, 19 o'clock, 20 o'clock, 21 o'clock, 22 o'clock, 23 o'clock, total and other information.

[0039] (2) Assessment Form_Weekly Report: including serial number, name, electricity consumption on Thursday, electricity consumption on Friday, electricity consumption on Saturday, electricity consumption on Sunday, electricity consumption on Monday, electricity consumption on Tuesday, electricity consumption on Wednesday, weekly total, etc.

[0040] (3) Assessment table_monthly report: including serial number, name, table usage on the 25th of last month, table usage on the 26th of last month, table usage on the 27th of last month, table usage on the 28th of last month, table usage on the 29th of last month, table usage on the 30th of last month, table usage on the 31st of last month, table usage on the 1st of this month, table usage on the 2nd of this month, table usage on the 3rd of this month, table usage on the 4th of this month, table usage on the 5th of this month, table usage on the 6th of this month, table usage on the 7th of this month, table usage on the 8th of this month, table usage on the 9th of this month Daily meter usage, meter usage on the 10th of this month, meter usage on the 11th of this month, meter usage on the 12th of this month, meter usage on the 13th of this month, meter usage on the 14th of this month, meter usage on the 15th of this month, meter usage on the 16th of this month, meter usage on the 17th of this month, meter usage on the 18th of this month, meter usage on the 19th of this month, meter usage on the 20th of this month, meter usage on the 21st of this month, meter usage on the 22nd of this month, meter usage on the 23rd of this month, meter usage on the 24th of this month, total electricity usage and other information.

[0041] (4) Assessment Form_Annual Report: including serial number, name, January, February, March, April, May, June, July, August, September, October, November, December and other information.

[0042] (5) Daily report_meter base number: including serial number, name, usage mark, gateway location, meter location, meter address, multiplier, 0 o'clock meter base number, 1 o'clock meter base number, 2 o'clock meter base number, 3 o'clock meter base number, 4 o'clock meter base number, 5 o'clock meter base number, 6 o'clock meter base number, 7 o'clock meter base number, 8 o'clock meter base number, 9 o'clock meter base number, 10 o'clock meter base number, 11 o'clock meter base number, 12 o'clock meter base number, 13 o'clock meter base number, 14 o'clock meter base number, 15 o'clock meter base number, 16 o'clock meter base number, 17 o'clock meter base number, 18 o'clock meter base number, 19 o'clock meter base number, 20 o'clock meter base number, 21 o'clock meter base number, 22 o'clock meter base number, 23 o'clock meter base number and other information.

[0043] (6) Daily report_usage: including serial number, name, usage mark, gateway location, meter location, meter address, multiplier, usage at 0 o'clock, usage at 1 o'clock, usage at 2 o'clock, usage at 3 o'clock, usage at 4 o'clock, usage at 5 o'clock, usage at 6 o'clock, usage at 7 o'clock, usage at 8 o'clock, usage at 9 o'clock, usage at 10 o'clock, usage at 11 o'clock, usage at 12 o'clock, usage at 13 o'clock, usage at 14 o'clock, usage at 15 o'clock, usage at 16 o'clock, usage at 17 o'clock, usage at 18 o'clock, usage at 19 o'clock, usage at 20 o'clock, usage at 21 o'clock, usage at 22 o'clock and usage at 23 o'clock.

[0044] (7) Weekly report_meter base number: including serial number, name, usage mark, gateway location, meter location, meter address, multiplier, Thursday meter base number, Friday meter base number, Saturday meter base number, Sunday meter base number, Monday meter base number, Tuesday meter base number, Wednesday meter base number and other information.

[0045] (8) Weekly report_usage: including serial number, name, usage mark, gateway location, meter location, meter address, multiplier, electricity consumption on Thursday, electricity consumption on Friday, electricity consumption on Saturday, electricity consumption on Sunday, electricity consumption on Monday, electricity consumption on Tuesday, electricity consumption on Wednesday, etc.

[0046] (9) Monthly report_meter base number: including serial number, name, usage mark, gateway location, meter location, meter address, multiplier, meter base number on the 25th of last month, meter base number on the 26th of last month, meter base number on the 27th of last month, meter base number on the 28th of last month, meter base number on the 29th of last month, meter base number on the 30th of last month, meter base number on the 31st of last month, meter base number on the 1st of this month, meter base number on the 2nd of this month, meter base number on the 3rd of this month, meter base number on the 4th of this month, meter base number on the 5th of this month, meter base number on the 6th of this month, meter base number on the 7th of this month Base number, base number on the 8th of this month, base number on the 9th of this month, base number on the 10th of this month, base number on the 11th of this month, base number on the 12th of this month, base number on the 13th of this month, base number on the 14th of this month, base number on the 15th of this month, base number on the 16th of this month, base number on the 17th of this month, base number on the 18th of this month, base number on the 19th of this month, base number on the 20th of this month, base number on the 21st of this month, base number on the 22nd of this month, base number on the 23rd of this month, base number on the 24th of this month and other information.

[0047] (10) Monthly report_usage: including serial number, name, usage mark, gateway location, meter location, meter address, multiplier, meter usage on the 25th of last month, meter usage on the 26th of last month, meter usage on the 27th of last month, meter usage on the 28th of last month, meter usage on the 29th of last month, meter usage on the 30th of last month, meter usage on the 31st of last month, meter usage on the 1st of this month, meter usage on the 2nd of this month, meter usage on the 3rd of this month, meter usage on the 4th of this month, meter usage on the 5th of this month, meter usage on the 6th of this month, meter usage on the 7th of this month meter usage on the 8th of this month, meter usage on the 9th of this month, meter usage on the 10th of this month, meter usage on the 11th of this month, meter usage on the 12th of this month, meter usage on the 13th of this month, meter usage on the 14th of this month, meter usage on the 15th of this month, meter usage on the 16th of this month, meter usage on the 17th of this month, meter usage on the 18th of this month, meter usage on the 19th of this month, meter usage on the 20th of this month, meter usage on the 21st of this month, meter usage on the 22nd of this month, meter usage on the 23rd of this month, meter usage on the 24th of this month and other information.

[0048] (11) Annual report_meter base data: including serial number, name, usage mark, gateway location, meter location, meter address, multiplier, meter base data for January, meter base data for February, meter base data for March, meter base data for April, meter base data for May, meter base data for June, meter base data for July, meter base data for August, meter base data for September, meter base data for October, meter base data for November, meter base data for December, etc.

[0049] (12) Annual report_usage: including serial number, name, usage mark, gateway location, meter location, meter address, multiplier, usage in January, usage in February, usage in March, usage in April, usage in May, usage in June, usage in July, usage in August, usage in September, usage in October, usage in November, usage in December, etc.

[0050] Furthermore, from the above report, we can get the basic information of each meter, including the serial number, name, usage mark, gateway location, meter location, meter address, multiplier and other information of each meter, so that the basic information of each meter is more accurate. Once the meter value is found to be abnormal from Monday to Sunday, every hour, every day, every month and every year, it can be checked and solved more accurately. According to the data displayed in the report, we can conduct targeted statistical analysis based on the results, which can be used for large-screen display and is also convenient for data statistical analysis or leadership decision-making.

[0051] According to the technical solution provided by the embodiment of the present disclosure, the serial number, name, usage mark, gateway location, meter location, meter address, and rate information of the electric meter can be obtained through the report display results. By viewing the report data, meaningful fault information and rules can be obtained to achieve the purpose of monitoring the operation faults of the smart meter.

[0052] When monitoring the faults of smart meters based on the above report, the method of obtaining fault information and the fault diagnosis process based on the report data are as follows:

[0053] ① If it is Assessment Table_Daily, Daily_Meter Base Number, Daily_Usage Number, then you need to check the data of the report 3 hours ago. If the report has a value, it means that the meter data is normal; if the report has no value, it means that the meter is abnormal;

[0054] ② If it is Assessment Table_Weekly Report, Weekly Report_Meter Base Number, Weekly Report_Usage Number, the results displayed in the report are the meter base number and usage number of last Thursday, last Friday, last Saturday, last Sunday, this Monday, this Tuesday, this Wednesday, etc., then you need to check the data of the report yesterday and before yesterday. If the report has a value, it means that the meter data is normal; if the report has no value, it means that the meter is abnormal;

[0055] ③ If it is Assessment Table_Monthly Report, Monthly Report_Table Base Number, Monthly Report_Usage Number, then you need to check the data of today and before today. If the report has a value, it means that the meter data is normal; if the report has no value, it means that the meter is abnormal;

[0056] ④ If it is Assessment Table_Annual Report, Annual Report_Table Base Number, Annual Report_Usage Number, then you need to check the data of this month and before this month. If the report has a value, it means that the meter data is normal; if the report has no value, it means that the meter is abnormal;

[0057] Since each row of data in the report contains information such as the serial number, name, usage mark, gateway location, meter location, meter address, multiplier, meter base number, and meter usage corresponding to each meter, it is possible to know which meters have faults and problems. Through this fault diagnosis process, the specific fault information of the meter can be obtained.

[0058] The disclosed embodiment can collect, centralize, uniformly manage and analyze the energy consumption of the electric meter in real time, and provide a basis for decision-making, that is, through the report display results, the meter base number and usage number of the electric meter per hour (0:00 to 23:00), per week (Monday to Sunday), per day (1st to 31st), and per month (January to December) can be obtained. By checking the report data, once the data is lost or delayed, the fault data must be processed, that is, the processing of the electric meter monitoring data and diagnosis results is completed, and the operation fault diagnosis of the smart meter is realized.

[0059] The processing process of the meter fault data is as follows: diagnose the fault according to the above diagnostic process and obtain specific fault information. If a problem is found in the meter, the data warehouse development engineer will start to troubleshoot the problem to see which step in the middle caused the report to have no data. According to the upstream and downstream relationship of the underlying data in the report, check whether there is data layer by layer. If it is a problem with the data warehouse data processing logic, then the logic can be modified; if there is no data in the table at the upstream layer of the data warehouse (Hive), then the meter itself has a fault and no data is generated, resulting in the failure of IoT to collect the original data, and ultimately resulting in no data in the report. If the meter fails, then a dedicated person will investigate and solve the meter failure (the reason may be: through investigation and monitoring, it is found that the distribution room is unattended, resulting in theft, illegal intrusion, causing failure or accident, or seasonal environmental changes and bad weather causing changes in the ambient temperature and humidity of the distribution room, resulting in meter failure, or other reasons, which need to be specifically investigated.

[0060] The following are embodiments of the device disclosed herein, which can be used to execute the method embodiments disclosed herein. For details not disclosed in the device embodiments disclosed herein, please refer to the method embodiments disclosed herein.

[0061] Figure 2 Schematic diagram of the structure of the smart meter monitoring device provided by the embodiment of the present disclosure. Figure 2 As shown, the smart meter monitoring device includes:

[0062] The acquisition module 201 is configured to acquire the basic information text uploaded by the user and send the basic information text to the distributed file system of the big data cluster, wherein the basic information text includes basic information related to the electric meter;

[0063] The download module 202 is configured to add a timestamp to each basic information text according to the current time, and download the basic information text with the timestamp added from the distributed file system to a pre-configured data warehouse;

[0064] The cleaning module 203 is configured to create an electric meter basic information table in the original data layer of the data warehouse, and load the content in the basic information text into the electric meter basic information table, and then transfer the electric meter basic information table containing the basic information to the cleaning data layer, and perform data cleaning operations on the electric meter basic information table using the cleaning data layer to obtain a cleaned electric meter basic information table;

[0065] The summary module 204 is configured to transfer the cleaned electric meter basic information table to the summary data layer, and use the summary data layer to summarize the data in the cleaned electric meter basic information table according to preset statistical dimensions of different levels to obtain electric meter information summary tables of different statistical dimensions;

[0066] The development module 205 is configured to transfer the meter information summary table to the application data layer, use the query engine in the report platform to perform query operations on the table in the application data layer to obtain the target meter information, develop reports based on the target meter information in the report platform, obtain assessment reports, and monitor the faults and energy consumption of the smart meters based on the assessment reports.

[0067] In some embodiments, Figure 2 Before obtaining the basic information text uploaded by the user, the acquisition module 201 collects basic information of the electric equipment and the electric meter corresponding to the electric equipment, and writes the basic information of the electric meter corresponding to the electric equipment into the basic information text. The basic information text contains information related to the user, information related to the electric meter, and information related to the equipment, wherein the user is an enterprise user.

[0068] In some embodiments, Figure 2 The cleaning module 203 cleans the null values ​​and dirty data in the electric meter basic information table in the cleaning data layer, desensitizes the cleaned electric meter basic information table, and lightly summarizes the cleaned electric meter basic information table according to the key fields in the electric meter basic information table to obtain a lightly summarized electric meter basic information table.

[0069] In some embodiments, Figure 2 The summary module 204 summarizes the data in the cleaned electric meter basic information table according to statistical dimensions of different levels, and obtains electric meter information summary tables corresponding to different statistical dimensions. The electric meter information summary table of each statistical dimension contains the data of the statistical dimension, wherein the statistical dimension includes the time statistical dimension.

[0070] In some embodiments, Figure 2 The development module 205 is based on a query engine pre-configured on the report platform, and uses the query data set in the query engine to perform data query operations on the application data layer of the data warehouse, so as to collect target meter information from the application data layer, and use the target meter information to develop an assessment report, wherein the query engine contains a pre-developed query data set, and the query engine adopts the Presto query engine.

[0071] In some embodiments, Figure 2 The development module 205 monitors the faults of the smart meter according to the report data in the preset historical section corresponding to the assessment report. When data loss or data delay occurs in the report data in the preset historical section, it indicates that the smart meter has a fault. When the report data in the assessment report is normal but the smart meter has a fault, it is determined based on the table data in the original data layer in the data warehouse whether the meter itself has a fault or there is a problem with the processing logic of the data warehouse.

[0072] It should be understood that the size of the serial numbers of the steps in the above embodiments does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present disclosure.

[0073] Figure 3 Schematic diagram of the structure of the electronic device 3 provided in the embodiment of the present disclosure. Figure 3 As shown, the electronic device 3 of this embodiment includes: a processor 301, a memory 302, and a computer program 303 stored in the memory 302 and executable on the processor 301. When the processor 301 executes the computer program 303, the steps in the above-mentioned method embodiments are implemented. Alternatively, when the processor 301 executes the computer program 303, the functions of the modules / units in the above-mentioned device embodiments are implemented.

[0074] Exemplarily, the computer program 303 may be divided into one or more modules / units, which are stored in the memory 302 and executed by the processor 301 to complete the present disclosure. The one or more modules / units may be a series of computer program instruction segments capable of completing specific functions, which are used to describe the execution process of the computer program 303 in the electronic device 3.

[0075] The electronic device 3 may be a desktop computer, a notebook, a PDA, a cloud server, or other electronic device. The electronic device 3 may include, but is not limited to, a processor 301 and a memory 302. Those skilled in the art will appreciate that Figure 3It is only an example of the electronic device 3 and does not constitute a limitation of the electronic device 3. It may include more or fewer components than shown in the figure, or a combination of certain components, or different components. For example, the electronic device may also include input and output devices, network access devices, buses, etc.

[0076] The processor 301 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or the processor may be any conventional processor, etc.

[0077] The memory 302 may be an internal storage unit of the electronic device 3, for example, a hard disk or memory of the electronic device 3. The memory 302 may also be an external storage device of the electronic device 3, for example, a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. equipped on the electronic device 3. Further, the memory 302 may also include both an internal storage unit and an external storage device of the electronic device 3. The memory 302 is used to store computer programs and other programs and data required by the electronic device. The memory 302 may also be used to temporarily store data that has been output or is to be output.

[0078] The technicians in the relevant field can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In practical applications, the above-mentioned function allocation can be completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiment can be integrated in a processing unit, or each unit can exist physically separately, or two or more units can be integrated in one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application. The specific working process of the units and modules in the above-mentioned system can refer to the corresponding process in the aforementioned method embodiment, which will not be repeated here.

[0079] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0080] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this disclosure.

[0081] In the embodiments provided in the present disclosure, it should be understood that the disclosed apparatus / computer equipment and methods can be implemented in other ways. For example, the apparatus / computer equipment embodiments described above are merely schematic. For example, the division of modules or units is only a logical function division. There may be other division methods in actual implementation. Multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed may be through some interfaces, indirect coupling or communication connection of the apparatus or unit, which may be electrical, mechanical or other forms.

[0082] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0083] In addition, each functional unit in each embodiment of the present disclosure may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0084] If the integrated module / unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present disclosure implements all or part of the processes in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and the computer program can implement the steps of the above-mentioned various method embodiments when executed by the processor. The computer program may include computer program code, and the computer program code may be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may include: any entity or device capable of carrying computer program code, recording medium, U disk, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electric carrier signal, telecommunication signal and software distribution medium. It should be noted that the content contained in the computer-readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, the computer-readable medium does not include electric carrier signals and telecommunication signals.

[0085] The above embodiments are only used to illustrate the technical solutions of the present disclosure, rather than to limit them. Although the present disclosure has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present disclosure, and should all be included in the protection scope of the present disclosure.

Claims

1. A smart meter monitoring method, characterized in that: include: Obtaining basic information text uploaded by a user, and sending the basic information text to a distributed file system of a big data cluster, wherein the basic information text includes basic information related to the electric meter; Adding a timestamp to each of the basic information texts according to the current time, and downloading the basic information texts with the timestamp added from the distributed file system to a pre-configured data warehouse; Creating an electric meter basic information table in the original data layer of the data warehouse, and loading the content of the basic information text into the electric meter basic information table, then transferring the electric meter basic information table containing the basic information to the cleaned data layer, and performing a data cleansing operation on the electric meter basic information table using the cleaned data layer to obtain a cleaned electric meter basic information table; The cleaned electric meter basic information table is transferred to the summary data layer, and the summary data layer is used to summarize the data in the cleaned electric meter basic information table according to preset statistical dimensions of different levels to obtain electric meter information summary tables of different statistical dimensions; The meter information summary table is transferred to the application data layer, and the query engine in the report platform is used to perform query operations on the table in the application data layer to obtain the target meter information. Reports are developed based on the target meter information in the report platform to obtain assessment reports, and faults and energy consumption of smart meters are monitored based on the assessment reports.

2. The method according to claim 1, characterized in that Before obtaining the basic information text uploaded by the user, the method further includes: The user collects basic information of the electrical equipment and the electric meter corresponding to the electrical equipment, and writes the basic information of the electric meter corresponding to the electrical equipment into the basic information text, wherein the basic information text includes information related to the user, information related to the electric meter, and information related to the equipment, wherein the user is an enterprise user.

3. The method according to claim 1, characterized in that The step of performing a data cleaning operation on the electric meter basic information table by using the cleaning data layer to obtain a cleaned electric meter basic information table includes: In the cleaning data layer, the empty values ​​and dirty data in the electric meter basic information table are cleaned, and the cleaned electric meter basic information table is desensitized. The cleaned electric meter basic information table is lightly summarized according to the key fields in the electric meter basic information table to obtain a lightly summarized electric meter basic information table.

4. The method according to claim 1, characterized in that: The data in the cleaned electric meter basic information table is summarized to obtain an electric meter information summary table of different statistical dimensions, including: The data in the cleaned electric meter basic information table is summarized according to the statistical dimensions of different levels to obtain electric meter information summary tables corresponding to the different statistical dimensions, and the electric meter information summary table of each statistical dimension contains the data of the statistical dimension, wherein the statistical dimension includes a time statistical dimension.

5. The method according to claim 1, characterized in that The step of using a query engine in the report platform to perform a query operation on a table in the application data layer to obtain target electric meter information, and developing a report based on the target electric meter information in the report platform includes: Based on a query engine pre-configured in the reporting platform, a data query operation is performed on the application data layer of the data warehouse using the query data set in the query engine, so as to collect target electricity meter information from the application data layer, and use the target electricity meter information to develop an assessment report, wherein the query engine contains a pre-developed query data set, and the query engine adopts the Presto query engine.

6. The method according to claim 1, characterized in that The monitoring of the fault and energy consumption of the smart meter based on the assessment report includes: The smart meter is monitored for faults based on the report data in the preset historical segment corresponding to the assessment report. When data loss or data delay occurs in the report data in the preset historical segment, it indicates that the smart meter is faulty. When the report data in the assessment report is normal but the smart meter is faulty, it is determined based on the table data in the original data layer in the data warehouse whether the meter itself is faulty or there is a problem with the processing logic of the data warehouse.

7. The method according to any one of claims 1 to 6, characterized in that The data warehouse is a Hive data warehouse, the original data layer corresponds to the ODS layer in the Hive data warehouse, the cleaned data layer corresponds to the DWD layer in the Hive data warehouse, the summary data layer corresponds to the DWS layer in the Hive data warehouse, and the application data layer corresponds to the ADS layer in the Hive data warehouse.

8. A smart meter monitoring device, characterized in that: include: An acquisition module is configured to acquire a basic information text uploaded by a user and send the basic information text to a distributed file system of a big data cluster, wherein the basic information text includes basic information related to the electric meter; A download module is configured to add a timestamp to each of the basic information texts according to the current time, and download the basic information texts with the timestamp added from the distributed file system to a pre-configured data warehouse; a cleaning module configured to create an electric meter basic information table in the original data layer of the data warehouse, load the content of the basic information text into the electric meter basic information table, then transfer the electric meter basic information table containing the basic information to the cleaning data layer, perform data cleaning operations on the electric meter basic information table using the cleaning data layer, and obtain a cleaned electric meter basic information table; A summary module is configured to transfer the cleaned electric meter basic information table to a summary data layer, and use the summary data layer to summarize the data in the cleaned electric meter basic information table according to preset statistical dimensions of different levels to obtain electric meter information summary tables of different statistical dimensions; The development module is configured to transfer the meter information summary table to the application data layer, use the query engine in the report platform to perform query operations on the table in the application data layer to obtain target meter information, develop reports based on the target meter information in the report platform to obtain assessment reports, and monitor the faults and energy consumption of smart meters based on the assessment reports.

9. An electronic device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the method according to any one of claims 1 to 7 when executing the program.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

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