Whole-process automatic verification method and system for intelligent electric energy meter

Abstract

The invention discloses a whole-process automatic verification method and system for an intelligent electric energy meter, and relates to the technical field of electric power metering equipment verification, and the method comprises the steps: collecting the information and historical verification data of the electric energy meter, connecting the electric energy meter with a verification device, calling corresponding verification parameters and standards from a database, and carrying out the self-inspection and calibration. The method comprises the following steps: carrying out synchronous verification on voltage, current, power and power factors, recording data in real time, adjusting a verification strategy through an algorithm, analyzing error data, adjusting the verification strategy, carrying out functional automatic testing, uploading the verification data, generating a verification report through cloud computing analysis, and carrying out qualification judgment according to a preset standard. And disqualification reasons are analyzed, optimization and marking are carried out, and the electric energy meters are stored in a classified mode according to verification results. According to the invention, the analysis depth of the verification result is improved through intelligent analysis, so that the unqualified electric energy meter can be diagnosed, optimized and marked in time, and the overall quality of the electric energy meter is finally ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of electric power metering equipment verification, and in particular to a method and system for full-process automated verification of smart electric energy meters. Background Art

[0002] With the continuous advancement of my country's smart grid construction, the accuracy and stability of smart energy meters, as an important part of the power grid, are of great significance to the normal operation of the power system; the traditional energy meter calibration method mainly relies on manual operation, the calibration process is cumbersome, inefficient, and easily affected by human factors, resulting in certain errors in the calibration results. In recent years, although some automated calibration technologies have been applied, there are still some technical bottlenecks.

[0003] In the prior art, the automated calibration system for electric energy meters generally has the following deficiencies: first, the information collection and identification links are not intelligent enough, which leads to information entry errors during the calibration process; second, the connection process between the calibration device and the electric energy meter is relatively complicated, and connection failures are prone to occur; third, during the synchronous calibration process, the calibration of voltage, current, power and power factor is not accurate enough, and there is a lack of effective error analysis methods; finally, in the qualification judgment and optimization links, the prior art is often unable to conduct in-depth analysis of unqualified electric energy meters, resulting in inadequate optimization measures, which affects the calibration quality of the electric energy meters. Summary of the invention

[0004] In view of the above existing problems, the present invention provides a method and system for fully automated calibration of smart electric energy meters to solve the problems of information entry errors, connection failures, lack of effective error analysis methods and inadequate optimization measures in the prior art.

[0005] In order to solve the above technical problems, a method for the full process automatic verification of smart electric energy meters is proposed, including:

[0006] Collect the information and historical calibration data of the energy meter, connect the energy meter to the calibration device, and retrieve the corresponding calibration parameters and standards from the database for self-inspection and calibration; perform synchronous calibration of voltage, current, power and power factor, record data in real time, and adjust the calibration strategy through algorithms to analyze error data and adjust the calibration strategy; perform functional automated testing, upload the calibration data, generate a calibration report through cloud computing analysis, and make qualification judgments based on preset standards, analyze the reasons for failure, optimize and mark, and classify and store the energy meters according to the calibration results.

[0007] As a preferred solution of the method for fully automated calibration of smart electric energy meters described in the present invention, the collection of electric energy meter information includes scanning the barcode of the smart electric energy meter and collecting the model, serial number, manufacturing date, rated voltage, rated current, accuracy level, maximum display power and frequency range of the electric energy meter.

[0008] The connection includes the verification station automatically identifying and connecting to the connection port of the electric energy meter, receiving information transmitted by the identification device, and immediately interacting with the verification system database.

[0009] As a preferred solution of the method for full-process automated verification of a smart electric energy meter described in the present invention, the self-inspection and calibration includes retrieving corresponding verification parameters and standards from a database to perform self-inspection and calibration.

[0010] The retrieving corresponding verification parameters and standards includes the CPU matching the verification parameters and standards preset in the corresponding national and international verification specifications for electric energy meters according to the model and serial number of the electric energy meter.

[0011] The self-check and calibration also includes a comprehensive check of the sensors, actuators and data acquisition cards of the verification device, and a connectivity test of the communication interface. After the self-check is completed, the calibration mode is entered, each measurement channel of the verification device is calibrated using a high-precision standard source, and the calibration data is automatically recorded.

[0012] As a preferred solution of the method for fully automated calibration of the smart electric energy meter described in the present invention, the synchronous calibration includes: the calibration device issues a start command, the power supply, signal generator and data acquisition card enter the working state, the calibration device applies standard voltage and current signals to the electric energy meter, simulates the actual working conditions, records the electric energy meter readings, and obtains the voltage, current, active power, reactive power and power factor of the electric energy meter.

[0013] The active power calculation formula is:

[0014]

[0015] The reactive power calculation formula is:

[0016]

[0017] The power factor calculation formula is:

[0018]

[0019] Among them, U is voltage, I is current, is the phase angle between voltage and current, P is the active power, Q is the reactive power, and PF is the power factor.

[0020] As a preferred solution of the method for fully automated calibration of smart electricity meters described in the present invention, the error data analysis includes collecting the difference between the measured value displayed by the electricity meter and the actual value emitted by the standard source, and processing the error data using the least squares method to predict the dynamic error of the electricity meter, and automatically adjusting the calibration parameters according to the error prediction results.

[0021] The automatic adjustment of the calibration parameters includes amplitude adjustment, frequency adjustment and test point adjustment; the amplitude adjustment includes setting the accuracy level of the electric energy meter. At a low amplitude, when the predicted error exceeds 0.5%, it indicates that the amplitude of the test signal needs to be reduced and the test points need to be increased. At a high amplitude, when the predicted error exceeds 1%, it indicates that the amplitude of the test signal needs to be increased. The frequency adjustment includes, for the fundamental frequency, when the predicted error exceeds 0.2%, it indicates that the test signal frequency needs to be adjusted within the fundamental frequency range. For the harmonic frequency, when the predicted error exceeds 0.5%, it indicates that the harmonic frequency needs to be adjusted to the set harmonic frequency within the harmonic frequency range.

[0022] As a preferred solution of the method for full-process automated calibration of smart electric energy meters described in the present invention, the generating of the calibration report includes performing functional automated testing, uploading the calibration data, and generating the calibration report through cloud computing analysis.

[0023] The functional automated test includes retrieving functional test parameters and standards from a database according to the model and serial number of the electric energy meter, and performing automated testing of the remote communication, event recording and time period setting functions of the electric energy meter according to preset test sequences and standards. During the test, the response data and functional status of the electric energy meter are recorded in real time.

[0024] The cloud computing analysis includes uploading the collected test data to a data processing center, transmitting it through a high-speed network. The data processing center receives the uploaded data, performs preprocessing, and performs feature analysis, and automatically generates a calibration report based on the analysis results.

[0025] As a preferred solution of the method for fully automated calibration of smart electric energy meters described in the present invention, the qualification judgment includes calculating the qualification index of the electric energy meter. When the calculation result is unqualified, analyzing the cause of the abnormality, matching the optimization strategy according to the calculation result, marking the unqualified smart meters, and storing the electric energy meters according to the classification results.

[0026] The formula for calculating the qualification index of the electric energy meter is expressed as:

[0027]

[0028] Among them, F is the qualification index of the electric energy meter, Z is the preset standard qualification rate of the electric energy meter, D is the cumulative value of the electric energy meter detection error, T is the error tolerance threshold of the electric energy meter, t is the detection time, α is the voltage deviation coefficient of the electric energy meter, V dev is the actual voltage value of the electric energy meter, V std is the standard voltage value of the electric energy meter, β is the resistance error coefficient of the electric energy meter, R err is the actual resistance value of the energy meter, R std is the standard resistance value of the electric energy meter, S is the correction factor; when F=1, it means that the electric energy meter meets the preset standard and is judged to be qualified. When 0≤F<1, it means that the electric energy meter has an error and is judged to be unqualified. Abnormal detection is performed immediately, the faulty parts are replaced, the parameters are adjusted, and the unqualified electric energy meter is marked.

[0029] Another object of the present invention is to provide a system for fully automated calibration of smart electricity meters. The present invention optimizes the calibration process of electricity meters and realizes full-process automation of electricity meter calibration. The system of the present invention improves calibration efficiency, reduces human errors, realizes the intelligence of the calibration process, reduces operational complexity, improves calibration accuracy, ensures the accuracy and stability of electricity meters, conducts in-depth analysis of unqualified electricity meters, and improves the effectiveness of optimization measures.

[0030] As a preferred solution of the system for full-process automated calibration of smart electricity meters described in the present invention, it is characterized by including an information collection and identification module, an automatic connection and parameter retrieval module, a multi-parameter synchronous calibration and error analysis module, and a qualification judgment and optimization module.

[0031] The information collection and identification module is used to scan the barcode of the smart electric energy meter and collect the model, serial number, manufacturing date, rated voltage, rated current, accuracy level, maximum display power and frequency range information of the electric energy meter.

[0032] The automatic connection and parameter retrieval module is used to connect the electric energy meter to the verification device and retrieve the corresponding verification parameters and standards from the database to perform self-inspection and calibration.

[0033] The multi-parameter synchronous calibration and error analysis module is used to perform synchronous calibration of voltage, current, power and power factor, record data in real time, adjust the calibration strategy through an algorithm to analyze error data, adjust the calibration strategy, perform functional automated testing, upload the calibration data, and generate a calibration report through cloud computing analysis.

[0034] The qualification determination and optimization module is used to make qualification determinations according to preset standards, analyze reasons for non-compliance, perform optimization and marking, and classify and store electric energy meters according to the verification results.

[0035] A computer device comprises a memory and a processor, wherein the memory stores a computer program, and is characterized in that when the processor executes the computer program, the steps of the method described in the full-process automated verification of a smart electric energy meter are implemented.

[0036] A computer-readable storage medium stores a computer program, wherein the computer program, when executed by a processor, implements the steps of the method described in the full-process automated verification of a smart electric energy meter.

[0037] The beneficial effects of the present invention are as follows: by collecting the information and historical calibration data of the electric energy meter, and automatically connecting the electric energy meter with the calibration device, and at the same time retrieving the corresponding calibration parameters and standards from the database for self-inspection and calibration, the automation of the preparatory work before calibration is realized, the manual operation links are significantly reduced, the efficiency and accuracy of the calibration process are improved, the correct connection between the calibration device and the electric energy meter and the accuracy of the calibration parameters and standards are ensured, and a solid foundation is laid for subsequent calibration work. By synchronously calibrating the voltage, current, power and power factor, the data is recorded in real time, and the calibration strategy is dynamically adjusted by the algorithm, and the error data is analyzed, thereby improving the accuracy and flexibility of the calibration process, ensuring that the performance of the electric energy meter under various working conditions meets the standard requirements, and enhancing the reliability of the calibration results; performing functional automated testing, uploading the calibration data to the cloud computing platform for analysis to generate a calibration report, and making a qualification judgment according to the preset standards, the analysis depth of the calibration results is also improved through intelligent analysis, so that unqualified electric energy meters can be timely diagnosed, optimized and marked, and ultimately ensuring the overall quality of the electric energy meter. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative work, among which:

[0039] Figure 1 The present invention provides an overall flow chart of a method for fully automated verification of a smart electric energy meter according to an embodiment of the present invention.

[0040] Figure 2 A schematic diagram of a detection architecture of a method for full-process automated verification of a smart electric energy meter provided by an embodiment of the present invention.

[0041] Figure 3 A system solution flow chart of a smart electric energy meter full-process automated calibration system provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0042] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0043] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0044] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor is it an embodiment that is mutually exclusive with other embodiments, either individually or selectively.

[0045] The present invention is described in detail with reference to schematic diagrams. When describing the embodiments of the present invention, for the sake of convenience, the cross-sectional diagrams showing the device structure will not be partially enlarged according to the general scale, and the schematic diagrams are only examples, which should not limit the scope of protection of the present invention. In addition, in actual production, the three-dimensional dimensions of length, width and depth should be included.

[0046] At the same time, in the description of the present invention, it should be noted that the directions or positional relationships indicated by the terms "upper, lower, inner and outer" are based on the directions or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific direction, be constructed and operated in a specific direction, and therefore cannot be understood as limiting the present invention. In addition, the terms "first, second or third" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance.

[0047] In the present invention, unless otherwise clearly specified and limited, the terms "install, connect, connect" should be understood in a broad sense, for example: it can be a fixed connection, a detachable connection or an integral connection; it can also be a mechanical connection, an electrical connection or a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0048] Example 1, reference Figure 1 and Figure 2, which is the first embodiment of the present invention, provides a method for fully automated verification of a smart electric energy meter, including:

[0049] S1: Collect the energy meter information and historical calibration data, connect the energy meter to the calibration device, and retrieve the corresponding calibration parameters and standards from the database for self-inspection and calibration.

[0050] The collecting of the electric energy meter information includes scanning the barcode of the smart electric energy meter and collecting the model, serial number, manufacturing date, rated voltage, rated current, accuracy level, maximum displayed power and frequency range of the electric energy meter.

[0051] The connection includes the verification station automatically identifying and connecting to the connection port of the electric energy meter, receiving information transmitted by the identification device, and immediately interacting with the verification system database.

[0052] It should be noted that the self-checking and calibration includes retrieving corresponding verification parameters and standards from a database to perform self-checking and calibration.

[0053] The retrieving corresponding verification parameters and standards includes the CPU matching the verification parameters and standards preset in the corresponding national and international verification specifications for electric energy meters according to the model and serial number of the electric energy meter.

[0054] The self-check and calibration also includes a comprehensive check of the sensors, actuators and data acquisition cards of the verification device, and a connectivity test of the communication interface. After the self-check is completed, the calibration mode is entered, each measurement channel of the verification device is calibrated using a high-precision standard source, and the calibration data is automatically recorded.

[0055] S2: Perform synchronous verification of voltage, current, power and power factor, record data in real time, and adjust the verification strategy through algorithm to analyze error data and adjust the verification strategy.

[0056] like Figure 2 The synchronous calibration includes: the calibration device issues a start command, the power supply, signal generator and data acquisition card enter the working state, the calibration device applies standard voltage and current signals to the electric energy meter, simulates the actual working conditions, records the electric energy meter readings, and obtains the voltage, current, active power, reactive power and power factor of the electric energy meter.

[0057] Furthermore, the active power calculation formula is:

[0058]

[0059] The reactive power calculation formula is:

[0060]

[0061] The power factor calculation formula is:

[0062]

[0063] Among them, U is voltage, I is current, is the phase angle between voltage and current, P is the active power, Q is the reactive power, and PF is the power factor.

[0064] Furthermore, the analysis of error data includes collecting the difference between the measured value displayed by the electric energy meter and the actual value emitted by the standard source, and processing the error data using the least squares method to predict the dynamic error of the electric energy meter, and automatically adjusting the calibration parameters according to the error prediction results.

[0065] The formula for calculating the difference is:

[0066]

[0067] Among them, ε is the error value, A is the measured value, and B is the actual value.

[0068] The least squares formula is:

[0069] ^

[0070] ε=(H T H) -1 H T z

[0071] in, is the error prediction result, H is the observation matrix, z is the observation vector, H T is the transpose of the observation vector.

[0072] The automatic adjustment of the calibration parameters includes amplitude adjustment, frequency adjustment and test point adjustment; the amplitude adjustment includes setting the accuracy level of the electric energy meter. At a low amplitude, when the predicted error exceeds 0.5%, it indicates that the amplitude of the test signal needs to be reduced and the test points need to be increased. At a high amplitude, when the predicted error exceeds 1%, it indicates that the amplitude of the test signal needs to be increased. The frequency adjustment includes, for the fundamental frequency, when the predicted error exceeds 0.2%, it indicates that the test signal frequency needs to be adjusted within the fundamental frequency range. For the harmonic frequency, when the predicted error exceeds 0.5%, it indicates that the harmonic frequency needs to be adjusted to the set harmonic frequency within the harmonic frequency range.

[0073] S3: Perform functional automated testing, upload the calibration data, generate a calibration report through cloud computing analysis, make qualification determinations based on preset standards, analyze reasons for failure, optimize and mark, and classify and store the energy meters according to the calibration results.

[0074] Furthermore, generating the verification report includes performing functional automated testing, uploading verification data, and generating the verification report through cloud computing analysis.

[0075] The functional automated test includes retrieving functional test parameters and standards from a database according to the model and serial number of the electric energy meter, and performing automated testing of the remote communication, event recording and time period setting functions of the electric energy meter according to preset test sequences and standards. During the test, the response data and functional status of the electric energy meter are recorded in real time.

[0076] The cloud computing analysis includes uploading the collected test data to a data processing center, transmitting it through a high-speed network. The data processing center receives the uploaded data, performs preprocessing, and performs feature analysis, and automatically generates a calibration report based on the analysis results.

[0077] Furthermore, the qualification determination includes calculating the qualification index of the electric energy meter. When the calculation result is unqualified, analyzing the cause of the abnormality, matching the optimization strategy according to the calculation result, marking the unqualified smart meter, and classifying and storing the electric energy meter according to the inspection result.

[0078] The formula for calculating the qualification index of the electric energy meter is expressed as:

[0079]

[0080] Among them, F is the qualification index of the electric energy meter, Z is the preset standard qualification rate of the electric energy meter, D is the cumulative value of the electric energy meter detection error, T is the error tolerance threshold of the electric energy meter, t is the detection time, α is the voltage deviation coefficient of the electric energy meter, V dev is the actual voltage value of the electric energy meter, V std is the standard voltage value of the electric energy meter, β is the resistance error coefficient of the electric energy meter, R err is the actual resistance value of the energy meter, R std is the standard resistance value of the electric energy meter, S is the correction factor; when F=1, it means that the electric energy meter meets the preset standard and is judged to be qualified. When 0≤F<1, it means that the electric energy meter has an error and is judged to be unqualified. Abnormal detection is performed immediately, the faulty parts are replaced, the parameters are adjusted, and the unqualified electric energy meter is marked.

[0081] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

[0082] Example 2, reference Figure 3, which is the second embodiment of the present invention, provides a system for fully automated calibration of smart electricity meters, including an information collection and identification module 100, an automatic connection and parameter retrieval module 200, a multi-parameter synchronous calibration and error analysis module 300, and a qualification judgment and optimization module 400.

[0083] The information collection and identification module 100 is used to scan the barcode of the smart electric energy meter and collect the electric energy meter's model, serial number, manufacturing date, rated voltage, rated current, accuracy level, maximum display power and frequency range information.

[0084] The automatic connection and parameter retrieval module 200 is used to connect the electric energy meter to the verification device and retrieve the corresponding verification parameters and standards from the database to perform self-inspection and calibration.

[0085] The multi-parameter synchronous calibration and error analysis module 300 is used to perform synchronous calibration of voltage, current, power and power factor, record data in real time, adjust the calibration strategy through an algorithm to analyze error data, adjust the calibration strategy, perform functional automated testing, upload the calibration data, and generate a calibration report through cloud computing analysis.

[0086] The qualification determination and optimization module 400 is used to perform qualification determination according to preset standards, analyze the reasons for non-compliance, perform optimization and marking, and classify and store the electric energy meters according to the verification results.

[0087] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

[0088] Embodiment 3, the third embodiment of the present invention, is different from the first two embodiments in that:

[0089] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, and other media that can store program codes.

[0090] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.

[0091] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering or, if necessary, processing in another suitable manner, and then stored in a computer memory.

[0092] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, a plurality of steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

Claims

1. A method for fully automated verification of a smart electric energy meter, characterized in that: include, Collect the energy meter information and historical verification data, connect the energy meter to the verification device, and retrieve the corresponding verification parameters and standards from the database for self-inspection and calibration; Perform synchronous verification of voltage, current, power and power factor, record data in real time, and adjust verification strategy through algorithm to analyze error data and adjust verification strategy; Conduct functional automated testing, upload the calibration data, generate a calibration report through cloud computing analysis, make qualification judgments based on preset standards, analyze the reasons for failure, optimize and mark, and classify and store the electricity meters according to the calibration results.

2. The method for fully automated verification of a smart electric energy meter according to claim 1, characterized in that: The collecting of the electric energy meter information includes scanning the barcode of the smart electric energy meter to collect the model, serial number, manufacturing date, rated voltage, rated current, accuracy level, maximum displayed power and frequency range of the electric energy meter; The connection includes the verification station automatically identifying and connecting to the connection port of the electric energy meter, receiving information transmitted by the identification device, and immediately interacting with the verification system database.

3. The method for fully automated verification of a smart electric energy meter as claimed in claim 2, characterized in that: The self-checking and calibration comprises retrieving corresponding verification parameters and standards from a database to perform self-checking and calibration; The retrieving corresponding verification parameters and standards includes the CPU matching the verification parameters and standards preset in the corresponding national and international verification specifications for electric energy meters according to the model and serial number of the electric energy meter; The self-check and calibration also includes a comprehensive check of the sensors, actuators and data acquisition cards of the verification device, and a connectivity test of the communication interface. After the self-check is completed, the calibration mode is entered, each measurement channel of the verification device is calibrated using a high-precision standard source, and the calibration data is automatically recorded.

4. The method for fully automated verification of a smart electric energy meter as claimed in claim 3, characterized in that: The synchronous verification includes: the verification device issues a start command, the power supply, signal generator and data acquisition card enter the working state, the verification device applies standard voltage and current signals to the electric energy meter, simulates the actual working conditions, records the electric energy meter readings, and obtains the voltage, current, active power, reactive power and power factor of the electric energy meter; The active power calculation formula is: The reactive power calculation formula is: The power factor calculation formula is: Among them, U is voltage, I is current, is the phase angle between voltage and current, P is the active power, Q is the reactive power, and PF is the power factor.

5. The method for fully automated verification of a smart electric energy meter as claimed in claim 4, characterized in that: The analyzing error data includes collecting the difference between the measured value displayed by the electric energy meter and the actual value emitted by the standard source, and processing the error data using the least square method to predict the dynamic error of the electric energy meter, and automatically adjusting the verification parameters according to the error prediction result; The automatic adjustment of the verification parameters includes amplitude adjustment, frequency adjustment and test point adjustment; the amplitude adjustment includes setting the accuracy level of the electric energy meter. At a low amplitude, when the prediction error exceeds 0.5%, it means that the amplitude of the test signal should be reduced and the test points should be increased. At a high amplitude, when the prediction error exceeds 1%, it means that the amplitude of the test signal should be increased. The frequency adjustment includes, for the fundamental frequency, when the prediction error exceeds 0.2%, it means that the test signal frequency needs to be adjusted within the fundamental frequency range; for the harmonic frequency, when the prediction error exceeds 0.5%, it means that the test signal frequency needs to be adjusted to the set harmonic frequency within the harmonic frequency range.

6. The method for fully automated verification of a smart electric energy meter as claimed in claim 5, characterized in that: Generating the verification report includes performing functional automated testing, uploading verification data, and generating the verification report through cloud computing analysis; The functional automated test includes retrieving functional test parameters and standards from a database according to the model and serial number of the electric energy meter, and performing automated tests on the remote communication, event recording and time period setting functions of the electric energy meter according to the preset test sequence and standards. During the test, the response data and functional status of the electric energy meter are recorded in real time; The cloud computing analysis includes uploading the collected test data to a data processing center, transmitting it through a high-speed network. The data processing center receives the uploaded data, performs preprocessing, and performs feature analysis, and automatically generates a calibration report based on the analysis results.

7. The method for fully automated verification of a smart electric energy meter according to claim 6, characterized in that: The qualification determination includes calculating the qualification index of the electric energy meter, and when the calculation result is unqualified, analyzing the abnormal cause, matching the optimization strategy according to the calculation result, marking the unqualified smart meter, and storing the electric energy meter by category according to the verification result; The formula for calculating the qualification index of the electric energy meter is expressed as: Among them, F is the qualification index of the electric energy meter, Z is the preset standard qualification rate of the electric energy meter, D is the cumulative value of the electric energy meter detection error, T is the error tolerance threshold of the electric energy meter, t is the detection time, α is the voltage deviation coefficient of the electric energy meter, V dev is the actual voltage value of the electric energy meter, V std is the standard voltage value of the electric energy meter, β is the resistance error coefficient of the electric energy meter, R err is the actual resistance value of the energy meter, R std is the standard resistance value of the electric energy meter, S is the correction factor; when F=1, it means that the electric energy meter meets the preset standard and is judged to be qualified. When 0≤F<1, it means that the electric energy meter has an error and is judged to be unqualified. Abnormal detection is performed immediately, the faulty parts are replaced, the parameters are adjusted, and the unqualified electric energy meter is marked.

8. A system using the method for full-process automated verification of a smart electric energy meter as claimed in any one of claims 1 to 7, characterized in that: It includes information collection and identification module, automatic connection and parameter retrieval module, multi-parameter synchronous verification and error analysis module, and qualification judgment and optimization module; The information collection and identification module is used to scan the barcode of the smart energy meter and collect the model, serial number, manufacturing date, rated voltage, rated current, accuracy level, maximum display power and frequency range information of the energy meter; The automatic connection and parameter retrieval module is used to connect the electric energy meter to the verification device and retrieve the corresponding verification parameters and standards from the database to perform self-test and calibration; The multi-parameter synchronous verification and error analysis module is used to perform synchronous verification of voltage, current, power and power factor, record data in real time, and adjust the verification strategy through algorithms to analyze error data, adjust the verification strategy, and perform functional automated testing, upload the verification data, and generate a verification report through cloud computing analysis; The qualification determination and optimization module is used to make qualification determinations according to preset standards, analyze reasons for non-compliance, perform optimization and marking, and classify and store electric energy meters according to the verification results.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method for full-process automated verification of a smart electric energy meter according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method for full-process automated verification of a smart electric energy meter according to any one of claims 1 to 7 are implemented.

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