A method for detecting the state of an electric energy meter and related equipment

Abstract

The present application provides a method and related equipment for detecting the status of an electric energy meter. In the present application, the server obtains the abnormal judgment standard and abnormal scoring standard of each module of the electric energy meter; generates warning data based on the abnormal judgment standard and the abnormal scoring standard; processes the warning data with the historical warning data to obtain target warning data; receives the detection data of each module of the electric energy meter; processes the detection data sent by the electric energy meter based on the target warning data, outputs detection information; and sends the detection information to the electric energy meter. By measuring the power consumption of the electric energy meter itself in real time and monitoring the working status of each functional module of the electric energy meter in real time. When the working status and power consumption data are found to be abnormal, the location and possible cause of the internal fault of the electric energy meter can be effectively determined, thereby improving the efficiency of troubleshooting the electric energy meter fault.

Description

Technical Field

[0001] The present disclosure relates to the field of data processing technology, and in particular to a method for detecting the status of an electric energy meter and related equipment. Background Art

[0002] Currently, in the production process of electricity meters, after the electricity meter is assembled, it is powered on for hardware self-test. The self-test content includes the power module, metering module, control module, storage module, communication module, and display module. After the self-test of each module is completed, if there is no fault, the electricity meter will directly exit the self-test mode and enter the normal operating mode; if there is a fault in the meter, the meter will display the corresponding error code on the LCD screen, and maintenance personnel can repair it according to the code prompts.

[0003] Changes in the overall power consumption of an electricity meter can reflect its health. A healthy meter's overall power consumption is normal and relatively stable. A faulty meter, on the other hand, often experiences abnormal power consumption, with data significantly deviating from normal values. Traditional electricity meters measure a user's electricity consumption and related parameters, but do not measure the meter's overall power consumption. An electricity meter is composed of multiple functional module circuits. When each module is operating normally, its power consumption is normal and relatively stable. However, when the electronic components that make up each functional module age, experience performance degradation, or malfunction, the power consumption data of the functional module will also become abnormal, leading to abnormal overall power consumption of the meter.

[0004] Existing hardware self-test methods can only test the power module, metering module, control module, storage module, communication module, and display module of the electricity meter's entire hardware, and do not provide complete coverage of the meter's hardware. The meter's infrared channel, RS485 channel, carrier communication interface, built-in switch action, external switch action, alarm switch action, second pulse signal, clock signal, etc. cannot be tested through self-test methods. Existing technology causes untested hardware to flow into the next production link, and these hardware issues are gradually detected during the later debugging process. If any problems are repaired, the test process needs to be returned to the front end for retesting and debugging, affecting product quality and production efficiency.

[0005] It should be noted that the information disclosed in the above background technology section is only used to enhance the understanding of the background of the present disclosure, and therefore may include information that does not constitute prior art known to ordinary technicians in the field. Summary of the Invention

[0006] The purpose of this application is to provide a method and related equipment for detecting the status of an electric energy meter, which at least to a certain extent overcomes the problems existing in the prior art. By measuring the power consumption of the electric energy meter itself in real time and monitoring the working status of each functional module of the electric energy meter in real time, when abnormal working status and power consumption data are found, the location and possible cause of the internal fault of the electric energy meter can be effectively determined, thereby achieving the purpose of improving the efficiency of troubleshooting the electric energy meter fault.

[0007] By visualizing industrial IoT data, it is easier to detect abnormal equipment conditions in a timely manner, thereby improving production efficiency.

[0008] Other features and advantages of the present application will become apparent from the following detailed description, or may be learned in part by practice of the invention.

[0009] According to one aspect of the present application, a method for detecting the status of an electric energy meter is provided, including: obtaining abnormality judgment criteria and abnormality scoring criteria for each module of the electric energy meter; generating early warning data based on the abnormality judgment criteria and the abnormality scoring criteria; processing the early warning data with historical early warning data to obtain target early warning data; receiving detection data from each module of the electric energy meter; processing the detection data sent by the electric energy meter based on the target early warning data and outputting detection information; and sending the detection information to the electric energy meter.

[0010] In one embodiment of the present application, the detection data sent by the electric energy meter is processed based on the target warning data, and the detection information is output, including: processing the detection data of the current module based on the target warning data, and outputting the detection information; if the detection information is abnormal data, the detection information is sent to the abnormality processing platform; if the detection information is normal data, the detection data of other modules are processed.

[0011] In one embodiment of the present application, after sending the detection information to the abnormality processing platform, it includes: processing the detection information based on preset rules and outputting abnormal status data of the electric energy meter; generating abnormal status analysis information based on the abnormal status data.

[0012] In one embodiment of the present application, after generating abnormal state analysis information based on the abnormal state data, it includes: generating abnormal state reminder information based on the abnormal state data; generating abnormal state operation information based on the abnormal state reminder information; and sending the abnormal state reminder information and the abnormal state operation information to the electric energy meter.

[0013] In one embodiment of the present application, the abnormal status reminder information is generated based on the abnormal status data, including: issuing an alarm in response to detecting at least one of the following abnormalities: the power consumption data of the electric energy meter exceeds a first proportion of a first threshold; the total power consumption data of the electric energy meter in a first time period exceeds a second proportion of a second threshold; the power consumption data of the electric energy meter in a second time period continuously increases; the power consumption data of the electric energy meter in a third time period continuously decreases; the fluctuation of the power consumption data of the electric energy meter in a fourth time period exceeds a predetermined range.

[0014] In one embodiment of the present application, the generating of abnormal status reminder information based on the abnormal status data further includes: calculating an abnormal score for the abnormal status data according to the abnormal scoring standard; obtaining the abnormal score of each module; sorting the abnormal score and outputting sorted data; performing fault analysis on the abnormal status data based on the sorted data and outputting abnormal status reminder information.

[0015] Another aspect of the present application is a device for detecting the status of an electric energy meter, characterized in that it includes: a receiving module, configured to obtain abnormal judgment standards and abnormal scoring standards for each module of the electric energy meter; receiving detection data of each module of the electric energy meter; a processing module, configured to generate early warning data based on the abnormal judgment standards and the abnormal scoring standards; processing the early warning data with historical early warning data to obtain target early warning data; processing the detection data sent by the electric energy meter based on the target early warning data, and outputting detection information; and a sending module, configured to send the detection information to the electric energy meter.

[0016] According to another aspect of the present application, an electronic device is provided, characterized in that it includes: a processor; and a memory for storing executable instructions of the processor; wherein the processor is configured to execute the above-mentioned method for detecting the state of an electric energy meter by executing the executable instructions.

[0017] According to another aspect of the present application, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the method for detecting the state of an electric energy meter is implemented.

[0018] According to another aspect of the present application, a computer program product is provided, including a computer program, characterized in that when the computer program is executed by a processor, the computer program implements the above-mentioned method for detecting the state of an electric energy meter.

[0019] The present application provides a method for detecting the status of an electric energy meter, comprising: obtaining abnormal judgment criteria and abnormal scoring criteria for each module of the electric energy meter; generating early warning data based on the abnormal judgment criteria and the abnormal scoring criteria; processing the early warning data with historical early warning data to obtain target early warning data; receiving detection data from each module of the electric energy meter; processing the detection data sent by the electric energy meter based on the target early warning data and outputting detection information; and sending the detection information to the electric energy meter. By measuring the overall power consumption of the electric energy meter itself in real time and monitoring the working status of each functional module of the electric energy meter in real time. When the working status and power consumption data are found to be abnormal, it means that the electric energy meter is in an unhealthy state, and the location and possible cause of the internal fault of the electric energy meter can be effectively determined, thereby improving the efficiency of troubleshooting the electric energy meter fault.

[0020] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] The accompanying drawings are incorporated into and constitute a part of the specification, illustrate embodiments consistent with the present disclosure, and together with the specification, are used to explain the principles of the present disclosure. Obviously, the drawings described below are only some embodiments of the present disclosure, and those skilled in the art can derive other drawings based on these drawings without inventive effort.

[0022] Figure 1 A flow chart showing a method for detecting the status of an electric energy meter provided in one embodiment of the present application is shown;

[0023] Figure 2 Another flowchart showing a method for detecting the status of an electric energy meter provided by an embodiment of the present application;

[0024] Figure 3 Another flowchart showing a method for detecting the status of an electric energy meter provided by an embodiment of the present application;

[0025] Figure 4 A schematic structural diagram of a device for detecting the state of an electric energy meter provided in one embodiment of the present application is shown;

[0026] Figure 5 A schematic structural diagram of an electronic device provided in one embodiment of the present application is shown;

[0027] Figure 6 A schematic diagram of a storage medium provided in an embodiment of the present application is shown. DETAILED DESCRIPTION

[0028] Various exemplary embodiments of the present application will now be described in detail with reference to the accompanying drawings. It should be noted that unless otherwise specifically stated, the relative arrangements of components and steps, numerical expressions and numerical values ​​set forth in these embodiments do not limit the scope of the present application.

[0029] At the same time, it should be understood that for the convenience of description, the sizes of the various parts shown in the drawings are not drawn according to the actual proportional relationship.

[0030] The following description of at least one exemplary embodiment is merely illustrative in nature and is not intended to limit the present disclosure, its application, or uses.

[0031] Technologies, methods, and equipment known to ordinary technicians in the relevant art may not be discussed in detail, but where appropriate, the technologies, methods, and equipment should be considered part of the specification.

[0032] It should be noted that like reference numerals and letters refer to like items in the following figures, and therefore, once an item is defined in one figure, it need not be further discussed in subsequent figures.

[0033] In addition, the technical solutions between the various embodiments of the present application can be combined with each other, but it must be based on the fact that ordinary technicians in this field can implement it. When the combination of technical solutions is mutually contradictory or cannot be implemented, it should be deemed that such a combination of technical solutions does not exist and is not within the scope of protection required by this application.

[0034] It should be noted that those skilled in the art will readily conceive of other embodiments of the present application after considering the specification and practicing the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of the present application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein. The description and examples are to be considered merely as exemplary, and the true scope and spirit of this application are indicated by the claims.

[0035] It should be understood that the present application is not limited to the precise structures described below and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present application is limited only by the appended claims.

[0036] The following combination Figure 1-Figure 2 The following describes a method for detecting the status of an electric energy meter according to an exemplary embodiment of the present application. It should be noted that the following application scenarios are merely provided to facilitate understanding of the spirit and principles of the present application, and the embodiments of the present application are not limited in this respect. Rather, the embodiments of the present application can be applied to any applicable scenario.

[0037] In one embodiment, the present application also proposes a method for detecting the status of an electricity meter. Figure 1 The following schematically shows a flow chart of a method for detecting the status of an electric energy meter according to an embodiment of the present application. Figure 1 As shown, the method is applied to the server and includes:

[0038] S101, obtaining abnormality judgment standards and abnormality scoring standards for each module of the electric energy meter.

[0039] In one embodiment, the server obtains in advance or in real time the voltage, current, and power consumption values ​​required for each module operation set by the administrator. For example, the theoretical voltage value, theoretical current value, rated power consumption initial value Pset, maximum power consumption value Pmax, maximum per-second power consumption data average value Pmsec within 24 hours, and average power consumption data value Phour for the previous hour. Abnormal scoring criteria include, but are not limited to, satisfying that 3-20 consecutive power consumption measurement data are all greater than Pset*3, Phour*3, Pmsec, 0.5Pmax, or that the average power consumption data increases by more than 5% per hour for 3-7 consecutive hours. If the above conditions are met, it is considered an abnormal state.

[0040] S102: Generate early warning data based on the abnormality judgment standard and the abnormality scoring standard.

[0041] In one embodiment, the server obtains in advance or in real time the normal operation time of each business operation input by the management personnel, and then generates an early warning management mechanism to facilitate the management personnel to control the electricity meter.

[0042] In one approach, the server associates preset energy consumption values ​​or conversion rates according to the types of different modules, and triggers an alarm when the energy consumption value exceeds the standard energy consumption value or the conversion rate is less than the theoretical value of the power conversion efficiency.

[0043] S103: Process the warning data and historical warning data to obtain target warning data.

[0044] In one embodiment, the server determines whether the currently acquired warning data is identical to the historical warning data. If so, the server filters the currently acquired data and stores the historical warning data as the target warning data. Otherwise, the currently acquired warning data replaces the historical warning data and uses the currently acquired warning data as the target warning data. This effectively reduces the amount of data transmitted and increases the data transmission speed. Upon receiving the warning data, the server can quickly generate an alarm message and send it to the electricity meter, increasing the server's storage space and reducing storage costs.

[0045] S104: Receive detection data from each module of the electric energy meter.

[0046] In one embodiment, a current sampling device is added to the power supply line of the electric energy meter, and the sampled value is sent to the metering chip. Combined with voltage sampling, the power consumption of the electric energy meter itself is measured.

[0047] S105: Process the detection data sent by the electric energy meter based on the target warning data and output detection information.

[0048] In one implementation, a server receives various operational data from the meter and determines the difference between the measured value and the theoretical design value. If the difference is significant, it infers a device anomaly. By acquiring this data, the server determines the meter's current status, effectively identifying the location and possible cause of internal faults, thereby improving the efficiency of troubleshooting.

[0049] In another embodiment, the server compares the real-time power consumption of the current period with the average power consumption values ​​of different time periods, thereby obtaining an alarm message indicating abnormal power consumption data information.

[0050] S106: Send the detection information to the electric energy meter.

[0051] In one implementation, a server collects test data from each module of the energy meter, ensuring its timeliness and accuracy. This data is then transmitted over a network, ensuring its stability and timeliness. Furthermore, by visualizing this test information through an LCD display or communication command query, managers gain timely insight into the meter's status, assisting them in making informed decisions.

[0052] In this application, the server obtains the abnormality judgment standard and abnormality scoring standard of each module of the electric energy meter; generates warning data based on the abnormality judgment standard and the abnormality scoring standard; processes the warning data with the historical warning data to obtain target warning data; receives the detection data of each module of the electric energy meter; processes the detection data sent by the electric energy meter based on the target warning data and outputs detection information; and sends the detection information to the electric energy meter. By measuring the power consumption of the electric energy meter itself in real time and monitoring the working status of each functional module of the electric energy meter in real time, when the working status and power consumption data are found to be abnormal, the location and possible cause of the internal fault of the electric energy meter can be effectively determined, thereby improving the efficiency of troubleshooting the electric energy meter.

[0053] Optionally, in another embodiment of the above method of the present application, processing the detection data sent by the electric energy meter based on the target early warning data and outputting the detection information includes:

[0054] Process the detection data of the current module based on the target warning data and output the detection information;

[0055] If the detection information is abnormal data, the detection information is sent to the abnormality processing platform;

[0056] If the detection information is normal data, the detection data of other modules are processed.

[0057] In one implementation, a server collects meter power data through a detection module and sends it to a data processing module, which compares and analyzes the data to determine if the circuit power is normal. If the meter is abnormal, the alarm module is notified, which then issues a warning message. This allows for remote identification of meter anomalies and monitoring of meter operating status, eliminating on-site operator intervention, reducing the risk of electric shock, and improving work efficiency.

[0058] In another embodiment, if the total power of the electric energy meter is less than 0, the electric energy meter is judged to be abnormal; if the comparative power deviation between the powers of any two modules of the electric energy meter exceeds 40%, the electric energy meter is judged to be abnormal; otherwise, the electric energy meter is judged to be normal.

[0059] Optionally, in another embodiment of the above method of the present application, after sending the detection information to the exception handling platform, the following steps are included:

[0060] Processing the detection information based on preset rules and outputting abnormal state data of the electric energy meter;

[0061] Abnormal state analysis information is generated based on the abnormal state data.

[0062] In one embodiment, a server acquires energy data from an energy meter, performs meter inspections, and determines the meter's fault type. Based on the fault type, the server assigns a corresponding label to the meter, and the meter is categorized by fault type based on the label. An image acquisition device captures information about the meter during power-on inspection, thereby obtaining the meter's inspection data and results. The meter is then categorized based on the inspection results, enabling automated meter sorting and improving work efficiency. Furthermore, a complete record of inspection data is maintained, facilitating future inquiries.

[0063] In another embodiment, the server determines whether various test data of the electric energy meter meet preset normal values ​​based on the electric energy data. If all test data of the electric energy meter meet the preset normal values, the test result of the electric energy meter is determined to be qualified. If any test data of the electric energy meter does not meet the preset normal values, the fault type of the electric energy meter is determined based on the test data that does not meet the preset normal values, and the fault type is used as the test result of the electric energy meter.

[0064] Optionally, in another embodiment of the above method of the present application, after generating abnormal state analysis information based on the abnormal state data, the method includes:

[0065] generating abnormal state reminder information based on the abnormal state data;

[0066] generating abnormal state operation information based on the abnormal state reminder information;

[0067] The abnormal state reminder information and the abnormal state operation information are sent to the electric energy meter.

[0068] In one embodiment, the administrator can pre-configure (associate with DingTalk ID) emergency contacts on the server. When the server calculates the conversion efficiency of the power supply by measuring the power consumption of the functional module when it is working and the change in the power consumption of the electric energy meter itself at this time, if the calculated value is much smaller than the theoretical value of the power conversion efficiency, it is determined that there may be an abnormality in the power supply module. Among them, the conversion rate of the power supply of the electric energy meter is calculated by dividing the power consumption value of each module of the electric energy meter by the increased power consumption value of the electric energy meter when the module is working. When an abnormality occurs in the power supply module, the first-level responder is triggered, and DingTalk notifies the relevant responsible personnel. By sending the abnormal status reminder information and abnormal status operation information to the corresponding management personnel, the corresponding management personnel view the shutdown details of the corresponding electric energy meter, so that the management personnel can understand the factors that cause the current abnormal data, and then avoid or solve the abnormal problem.

[0069] By adopting the above-mentioned technical solution, the embodiments of the present invention can not only achieve predictive maintenance of electricity meters, but also effectively reduce the downtime rate and maintenance costs of electricity meters, thereby avoiding significant losses. In addition, because fault prediction of electricity meters is performed, there is no need to modify the hardware of the electricity meters or install additional software programs on the electricity meters. When abnormal working status and power consumption data are found, the location and possible cause of the internal fault of the electricity meter can be effectively determined, thereby improving the efficiency of troubleshooting electricity meter faults.

[0070] Optionally, in another embodiment of the above method of the present application, generating abnormal state reminder information based on the abnormal state data includes:

[0071] An alarm is issued in response to detecting at least one of the following anomalies:

[0072] The power consumption data of the electric energy meter exceeds a first ratio of a first threshold;

[0073] a second proportion in which the total amount of power consumption data of the electric energy meter in the first time period exceeds a second threshold;

[0074] The power consumption data of the electric energy meter in the second time period continuously increases;

[0075] The power consumption data of the electric energy meter in the third time period continuously decreases;

[0076] The fluctuation of the power consumption data of the electric energy meter in the fourth time period exceeds a predetermined range.

[0077] In one embodiment, the first threshold can be a predefined threshold based on average energy consumption data obtained from historical energy consumption data that matches the energy meter's normal state. For example, the average energy consumption per unit of output can be calculated based on historical energy consumption values ​​at multiple similar time points (such as various time periods of each day or specific time points of each day of the week) and used as the first threshold. When the value exceeds this first threshold by, for example, 5% or 15%, an abnormality is determined.

[0078] The first threshold may also be a threshold predefined by management personnel based on experience or indicators. This indicator is determined based on the energy consumption target and historical energy consumption data of the electricity meter, and the indicator includes the energy consumption indicator of each functional module within a set time period. For example, the total energy consumption target of the enterprise for a certain output is determined, and the energy consumption indicators that the electricity meters corresponding to each factory, workshop, production line or energy-consuming equipment should meet are determined based on historical energy consumption data, and then the energy consumption indicators that each electricity meter should meet in, for example, each month, each quarter or year are determined. The determination of energy consumption indicators can also be obtained through an energy consumption prediction model based on historical energy consumption data.

[0079] In another embodiment, the second threshold value may be a threshold value predefined based on the total amount of energy consumption data of the electric energy meter in a corresponding time period that matches the output obtained from the historical energy consumption data. For example, based on the total historical energy consumption value of the electric energy meter in multiple similar time periods (similar quarters, similar production cycles, or time periods of the same length under similar production environments), the total amount of energy consumption data of the electric energy meter per unit output in the time period is determined as the second threshold value. When it exceeds, for example, 5% or 10% of the second threshold value, it is determined that an abnormality has occurred. The second threshold value may also be a threshold value predefined by management personnel based on experience or indicators. Similar to the first threshold value, it will not be repeated here.

[0080] In another way, if the energy consumption data of the electric energy meter continuously increases or continuously decreases, this may involve unstable operation of the production line or energy-consuming equipment.

[0081] In another way, the predetermined range can be the range of energy consumption data that matches the output obtained based on the historical energy consumption data of the electricity meter. For example, based on the energy consumption value of the unit output at similar time points, the normal range of energy consumption data is determined by the characteristics of the normal distribution (such as the range determined by the sum and difference of the expected value and three times the standard deviation); or the predetermined range of energy consumption data is determined based on a certain proportion of the maximum or minimum energy consumption value of the unit output at similar time points (for example, 95% of the maximum value, 120% of the minimum value, etc.). Among them, the predetermined range can also be a range pre-defined by the management personnel based on experience or indicators, similar to the first threshold value, which will not be repeated here. In addition, different predetermined ranges can be set, and anomalies with different fluctuation ranges can be determined as anomalies of different levels.

[0082] In some other embodiments, abnormalities in functional modules of other electric energy meters can also be detected, and abnormalities in energy consumption data of functional modules of the same type (for example, electric energy meters of the same type) can also be detected to determine whether there is an abnormality in the functional module of this type.

[0083] In addition, the first to fourth time periods in each anomaly can be the same time period or different time periods. The length and location of the time period can be determined by the administrator based on experience or target strategy. For example, different anomaly detection and alert strategies can be set for different time periods.

[0084] Optionally, in another embodiment of the above method of the present application, generating abnormal state reminder information based on the abnormal state data further includes:

[0085] Calculating anomaly scores for the abnormal state data according to the abnormality scoring standard;

[0086] Get the anomaly score of each module;

[0087] Sorting the abnormal scores and outputting sorted data;

[0088] Perform fault analysis on the abnormal state data based on the sorting data, and output abnormal state reminder information.

[0089] In one embodiment, the server calculates an anomaly score based on pre- or real-time anomaly scoring criteria, then adds the resulting anomaly score to the total score X, which is initially 0. If the current module is normal data, the server continues to test the next module until all modules have been tested. The calculated total score and the corresponding electricity meter are uploaded to the server, which sorts them according to the total score and performs fault analysis in sequence. If the final total score is less than 15, the electricity meter is determined to require no maintenance. If the total score is less than 30 and greater than 15, the electricity meter is determined to be able to operate normally with simple on-site maintenance. If the total score is greater than 30, the problem is determined to be serious and a new electricity meter needs to be replaced.

[0090] In another embodiment, the server may further set an abnormal score threshold Y. When the total score obtained by the server exceeds the set threshold Y, the electric energy meter is directly judged to be faulty, and the electric energy meter directly uploads the total score and fault information.

[0091] In another embodiment, the server may also set abnormality score repair thresholds Z1 and Z2, with Z1 being greater than Z2. When the total score obtained by the server is less than threshold Z2, it is determined that no maintenance is required, and the total score and the judgment result are uploaded to the electricity meter. When the total score obtained by the server is less than threshold Z1 but greater than threshold Z2, it is determined that the problem is minor and maintenance is required, and the total score and the judgment result are uploaded to the electricity meter. When the total score obtained by the server is greater than threshold Z1, it is determined that the problem is severe and replacement is required, and the total score and the judgment result are uploaded to the electricity meter.

[0092] In the present application, the server obtains the abnormal judgment standard and abnormal scoring standard of each module of the electric energy meter; generates early warning data based on the abnormal judgment standard and the abnormal scoring standard; processes the early warning data and historical early warning data to obtain target early warning data; receives the detection data of each module of the electric energy meter; processes the detection data of the current module based on the target early warning data and outputs detection information; if the detection information is abnormal data, the detection information is sent to the abnormality processing platform; processes the detection information based on preset rules and outputs the abnormal status data of the electric energy meter; generates abnormal status analysis information based on the abnormal status data; generates abnormal status reminder information based on the abnormal status data; calculates the abnormal score of the abnormal status data according to the abnormal scoring standard; obtains the abnormal score of each module; sorts the abnormal score and outputs sorted data; performs fault analysis on the abnormal status data based on the sorted data and outputs abnormal status reminder information; generates abnormal status operation information based on the abnormal status reminder information; and sends the abnormal status reminder information and the abnormal status operation information to the electric energy meter. If the detection information is normal, the detection data from other modules is processed and sent to the energy meter. By measuring the energy meter's overall power consumption in real time and monitoring the operating status of each functional module, if abnormal operating status or power consumption data is found, the location and possible cause of the meter's internal fault can be effectively determined, thereby improving the efficiency of troubleshooting the meter.

[0093] In one embodiment, Figure 4 As shown, the present application also provides a device for detecting the state of an electric energy meter, comprising:

[0094] The receiving module 401 is configured to obtain abnormality judgment standards and abnormality scoring standards of each module of the electric energy meter; receive detection data of each module of the electric energy meter;

[0095] The processing module 402 is configured to generate warning data based on the abnormality judgment standard and the abnormality scoring standard; process the warning data with historical warning data to obtain target warning data; process the detection data sent by the electric energy meter based on the target warning data and output detection information;

[0096] The sending module 403 is configured to send the detection information to the electric energy meter.

[0097] In this application, the server obtains the abnormality judgment standard and abnormality scoring standard of each module of the electric energy meter; generates warning data based on the abnormality judgment standard and the abnormality scoring standard; processes the warning data with the historical warning data to obtain target warning data; receives the detection data of each module of the electric energy meter; processes the detection data sent by the electric energy meter based on the target warning data and outputs detection information; and sends the detection information to the electric energy meter. By measuring the power consumption of the electric energy meter itself in real time and monitoring the working status of each functional module of the electric energy meter in real time, when the working status and power consumption data are found to be abnormal, the location and possible cause of the internal fault of the electric energy meter can be effectively determined, thereby improving the efficiency of troubleshooting the electric energy meter.

[0098] In another embodiment of the present application, the processing module 402 is configured to process the detection data sent by the electric energy meter based on the target warning data and output detection information, including:

[0099] Process the detection data of the current module based on the target warning data and output the detection information;

[0100] If the detection information is abnormal data, the detection information is sent to the abnormality processing platform;

[0101] If the detection information is normal data, the detection data of other modules are processed.

[0102] In another embodiment of the present application, the processing module 402 is configured to, after sending the detection information to the exception handling platform, include:

[0103] Processing the detection information based on preset rules and outputting abnormal state data of the electric energy meter;

[0104] Abnormal state analysis information is generated based on the abnormal state data.

[0105] In another embodiment of the present application, the processing module 402 is configured to, after generating the abnormal state analysis information based on the abnormal state data, include:

[0106] generating abnormal state reminder information based on the abnormal state data;

[0107] generating abnormal state operation information based on the abnormal state reminder information;

[0108] The abnormal state reminder information and the abnormal state operation information are sent to the electric energy meter.

[0109] In another embodiment of the present application, the processing module 402 is configured to generate abnormal state reminder information based on the abnormal state data, including:

[0110] An alarm is issued in response to detecting at least one of the following anomalies:

[0111] The power consumption data of the electric energy meter exceeds a first ratio of a first threshold;

[0112] a second proportion in which the total amount of power consumption data of the electric energy meter in the first time period exceeds a second threshold;

[0113] The power consumption data of the electric energy meter in the second time period continuously increases;

[0114] The power consumption data of the electric energy meter in the third time period continuously decreases;

[0115] The fluctuation of the power consumption data of the electric energy meter in the fourth time period exceeds a predetermined range.

[0116] In another embodiment of the present application, the processing module 402 is configured to generate abnormal state reminder information based on the abnormal state data, and further includes:

[0117] Calculating anomaly scores for the abnormal state data according to the abnormality scoring standard;

[0118] Get the anomaly score of each module;

[0119] Sorting the abnormal scores and outputting sorted data;

[0120] Perform fault analysis on the abnormal state data based on the sorting data, and output abnormal state reminder information.

[0121] In the present application, the server obtains the abnormal judgment standard and abnormal scoring standard of each module of the electric energy meter; generates early warning data based on the abnormal judgment standard and the abnormal scoring standard; processes the early warning data and historical early warning data to obtain target early warning data; receives the detection data of each module of the electric energy meter; processes the detection data of the current module based on the target early warning data and outputs detection information; if the detection information is abnormal data, the detection information is sent to the abnormality processing platform; processes the detection information based on preset rules and outputs the abnormal status data of the electric energy meter; generates abnormal status analysis information based on the abnormal status data; generates abnormal status reminder information based on the abnormal status data; calculates the abnormal score of the abnormal status data according to the abnormal scoring standard; obtains the abnormal score of each module; sorts the abnormal score and outputs sorted data; performs fault analysis on the abnormal status data based on the sorted data and outputs abnormal status reminder information; generates abnormal status operation information based on the abnormal status reminder information; and sends the abnormal status reminder information and the abnormal status operation information to the electric energy meter. If the detection information is normal, the detection data from other modules is processed and sent to the energy meter. By measuring the energy meter's overall power consumption in real time and monitoring the operating status of each functional module, if abnormal operating status or power consumption data is found, the location and possible cause of the meter's internal fault can be effectively determined, thereby improving the efficiency of troubleshooting the meter.

[0122] The present application embodiment provides an electronic device, such as Figure 5 As shown, it includes a processor 500, a memory 501, a bus 502 and a communication interface 503, and the processor 500, the communication interface 503 and the memory 501 are connected via the bus 502; the memory 501 stores a computer program that can be run on the processor 500, and when the processor 500 runs the computer program, it executes the method for detecting the status of the electric energy meter provided in any of the aforementioned embodiments of the present application.

[0123] The memory 501 may include high-speed random access memory (RAM) and may also include non-volatile memory, such as at least one disk storage. The system network element and at least one other network element are connected via at least one communication interface 503 (which may be wired or wireless), and may use the Internet, a wide area network, a local area network, a metropolitan area network, or the like.

[0124] The bus 502 may be an ISA bus, a PCI bus, or an EISA bus. The bus may be divided into an address bus, a data bus, a control bus, and the like. The memory 501 is used to store programs, and the processor 500 executes the programs upon receiving execution instructions. The method for detecting the status of an electric energy meter disclosed in any of the aforementioned embodiments of the present application may be applied to or implemented by the processor 500.

[0125] The processor 500 may be an integrated circuit chip with signal processing capabilities. During implementation, each step of the above method can be completed by hardware integrated logic circuits in the processor 500 or by software instructions. The above processor 500 may be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it may also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), an off-the-shelf field programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. It can implement or execute the various methods, steps, and logic block diagrams disclosed in the embodiments of this application. The general-purpose processor may be a microprocessor or any conventional processor. The steps of the method disclosed in conjunction with the embodiments of this application can be implemented and executed by a hardware decoding processor, or by a combination of hardware and software modules in the decoding processor. The software module can be located in a storage medium mature in the art, such as random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, etc. The storage medium is located in the memory 501 , and the processor 500 reads the information in the memory 501 and completes the steps of the above method in combination with its hardware.

[0126] The electronic device provided in the above-mentioned embodiments of the present application and the method for detecting the status of an electric energy meter provided in the embodiments of the present application are based on the same inventive concept and have the same beneficial effects as the methods adopted, run or implemented by the application programs stored therein.

[0127] The present application provides a computer-readable storage medium. Figure 6 As shown, the computer-readable storage medium 601 stores a computer program, and when the computer program is read and executed by the processor 602, the method for detecting the state of the electric energy meter as described above is implemented.

[0128] The technical solution of the embodiments of the present application, or the portion that contributes to the prior art, or all or part of the technical solution, may be embodied in the form of a software product. This computer software product is stored in a storage medium and includes instructions for causing an electronic device (such as an air conditioner, a refrigeration device, a personal computer, a server, or a network device) or a processor to execute all or part of the steps of the method described in the embodiments of the present application. The aforementioned storage medium includes various media that can store program code, such as a USB flash drive, a mobile hard drive, ROM, RAM, a magnetic disk, or an optical disk.

[0129] The computer-readable storage medium provided in the above-mentioned embodiments of the present application and the method for detecting the status of an electric energy meter for a flying weaving alignment system provided in the embodiments of the present application are based on the same inventive concept and have the same beneficial effects as the methods adopted, run or implemented by the application programs stored therein.

[0130] An embodiment of the present application provides a computer program product, including a computer program, wherein the computer program is executed by a processor to implement the method described above.

[0131] The computer program product provided in the above-mentioned embodiments of the present application and the method for detecting the status of an electric energy meter provided in the embodiments of the present application are based on the same inventive concept and have the same beneficial effects as the methods adopted, run or implemented by the application programs stored therein.

[0132] It should be noted that, in this application, relational terms such as first and second, etc. are merely used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply the existence of any such actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article, or device comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or elements inherent to such process, method, article, or device. In the absence of further restrictions, an element defined by the statement "comprising a ..." does not exclude the presence of other identical elements in the process, method, article, or device comprising the element.

[0133] Each embodiment of this application is described in a related manner. Similar portions between the embodiments can be referred to in conjunction with each other. Each embodiment focuses on the differences from other embodiments. In particular, the embodiments of the method, electronic device, electronic device, and readable storage medium for detecting the state of an electric energy meter are generally similar to the above-described embodiment of the method for detecting the state of an electric energy meter, so the description is relatively simple. For related portions, refer to the description of the above-described embodiment of the method for detecting the state of an electric energy meter.

[0134] Although the present application is disclosed as above, the present application is not limited thereto. Any person skilled in the art may make various changes and modifications without departing from the spirit and scope of the present application. Therefore, the scope of protection of the present application shall be based on the scope defined by the claims.

Claims

1. A method for detecting the state of an electric energy meter, characterized in that: include: Obtain abnormality judgment criteria and abnormality scoring criteria for each module of the electric energy meter; Generate early warning data based on the abnormality judgment standard and the abnormality scoring standard; Processing the warning data and the historical warning data to obtain target warning data includes: the server will determine whether the currently obtained warning data is the same as the historical warning data; if they are the same, filtering the currently obtained data and storing the historical warning data as the target warning data; otherwise, replacing the historical warning data with the currently obtained warning data and using the currently obtained warning data as the target warning data; Receiving detection data from each module of the electric energy meter; processing the detection data sent by the electric energy meter based on the target early warning data and outputting detection information; sending the detection information to the electric energy meter; Process the detection information and output the abnormal status data of the electric energy meter; Generate abnormal state analysis information and abnormal state reminder information based on abnormal state data; Generate abnormal state operation information based on the abnormal state reminder information, and issue an alarm in response to detecting at least one of the following abnormalities: The power consumption data of the electric energy meter exceeds a first ratio of a first threshold; The total amount of power consumption data of the electric energy meter in the first time period exceeds a second ratio of the second threshold; The power consumption data of the electric energy meter in the second time period continuously increases; The power consumption data of the electric energy meter in the third time period continuously decreases; The fluctuation of the power consumption data of the electric energy meter in the fourth time period exceeds a predetermined range; Send abnormal status reminder information and abnormal status operation information to the electricity meter.

2. The method for detecting the state of an electric energy meter according to claim 1, characterized in that: The processing of the detection data sent by the electric energy meter based on the target early warning data and outputting detection information includes: Process the detection data of the current module based on the target warning data and output the detection information; If the detection information is abnormal data, the detection information is sent to the abnormality processing platform; If the detection information is normal data, the detection data of other modules are processed.

3. The method for detecting the state of an electric energy meter according to claim 1, wherein: The generating of abnormal state reminder information based on the abnormal state data further includes: Calculating anomaly scores for the abnormal state data according to the abnormality scoring standard; Get the anomaly score of each module; Sorting the abnormal scores and outputting sorted data; Perform fault analysis on the abnormal state data based on the sorting data, and output abnormal state reminder information.

4. A device for detecting the state of an electric energy meter, characterized in that: The method for implementing claim 1 comprises: A receiving module is configured to obtain abnormality judgment standards and abnormality scoring standards of each module of the electric energy meter; receive detection data of each module of the electric energy meter; a processing module configured to generate warning data based on the abnormality judgment standard and the abnormality scoring standard; process the warning data with historical warning data to obtain target warning data; process the detection data sent by the electric energy meter based on the target warning data and output detection information; The sending module is configured to send the detection information to the electric energy meter.

5. An electronic device, characterized in that: include: processor; as well as a memory for storing executable instructions of the processor; The processor is configured to execute the method for detecting the state of an electric energy meter according to any one of claims 1 to 3 by executing the executable instructions.

6. A computer-readable storage medium for storing computer-readable instructions, characterized in that: When the instruction is executed, the operation of the method for detecting the state of an electric energy meter according to any one of claims 1 to 3 is implemented.

7. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the method for detecting the state of an electric energy meter according to any one of claims 1 to 3 is implemented.

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