Electric energy meter capable of automatically distinguishing Rogowski coil type and identification method

Abstract

The invention provides an electric energy meter capable of automatically judging the type of a Rogowski coil and an identification method, and relates to the technical field of electric energy meters. The method comprises the following steps: respectively acquiring historical real-time parameter data of electric energy meters of different Rogowski coil types and product parameter data of different Rogowski coil types; according to the historical real-time parameter data, classification identification analysis based on feature information is carried out to form Rogowski coil classification identification reference data; and in combination with the Rogowski coil classification identification parameter data and the product parameter data, performing type identification analysis to form Rogowski coil type identification result data. According to the method, the type of the Rogowski coil in the electric energy meter is accurately confirmed based on big data analysis.

Description

Technical Field

[0001] The present invention relates to the technical field of electric energy meters, and in particular to an electric energy meter capable of automatically distinguishing the type of a Rogowski coil and an identification method thereof. Background Art

[0002] A Rogowski coil, also known as a Rogowski coil, is an AC current sensor. It's a hollow, ring-shaped coil, available in both flexible and rigid configurations, that can be directly applied to the conductor being measured to measure AC current. Because it converts high currents into measurable voltages, it's an ideal measuring component for electricity meters. Converting high currents to a reasonable voltage range allows for wide-ranging measurements while also avoiding the potential risks of directly measuring high currents.

[0003] Currently, since electricity meters are frequently used and most of the time require inspection and secondary use, it is crucial to determine the type of Rogowski coil in the electricity meter when the original data is not available. After all, different types of Rogowski coils are suitable for different measurement ranges to ensure measurement accuracy.

[0004] Therefore, designing an electric energy meter and identification method that can automatically identify the type of Rogowski coil and accurately confirm the type of Rogowski coil in the electric energy meter through big data analysis is an urgent problem to be solved. Summary of the Invention

[0005] The present invention aims to provide a method for automatically distinguishing the type of Rogowski coil. The method obtains historical measurement data of an electric energy meter to establish a rich set of basic data on Rogowski coil measurement parameters, and combines parameters that can characterize the type characteristics of the Rogowski coil to reasonably and accurately classify the Rogowski coils into different types. The obtained Rogowski coil product parameter big data is then compared and confirmed to accurately determine the type of the Rogowski coil in the electric energy meter. This method is accurate and efficient and can quickly provide type identification for the Rogowski coil in the electric energy meter.

[0006] Another object of the present invention is to provide an electric energy meter that can automatically identify the type of Rogowski coil. The system is configured to obtain the measurement parameters of the Rogowski coil of the electric energy meter, and the collected data is classified, identified and analyzed in real time and efficiently to provide classification results that can be used for identification and judgment. At the same time, in conjunction with a system that can collect parameters generated by the type of Rogowski coil, the type of Rogowski coil in the electric energy meter is identified and judged, providing an important material basis for efficient and accurate identification and judgment of the type of Rogowski coil in the electric energy meter.

[0007] In a first aspect, the present invention provides an identification method capable of automatically distinguishing the type of Rogowski coil, comprising obtaining historical real-time parameter data of electric energy meters of different Rogowski coil types and product parameter data of different Rogowski coil types; performing classification and identification analysis based on feature information based on the historical real-time parameter data to form Rogowski coil classification and identification reference data; and performing type identification analysis on the basis of the Rogowski coil classification and identification parameter data and the product parameter data to form Rogowski coil type identification result data.

[0008] In the present invention, the method acquires historical measurement data of the electric energy meter and thereby establishes rich basic data of Rogowski coil measurement parameters, and combines parameters that can characterize the type characteristics of the Rogowski coil to reasonably and accurately identify and classify the Rogowski coil. The acquired Rogowski coil product parameter big data is then compared and confirmed, thereby accurately determining the type of the Rogowski coil in the electric energy meter. This method is accurate and efficient and can quickly provide type identification of the Rogowski coil in the electric energy meter.

[0009] As a possible implementation method, classification and identification analysis based on characteristic information is performed based on historical real-time parameter data to form Rogowski coil classification and identification reference data, including: extracting characteristic parameter data based on historical real-time parameter data to form characteristic parameter data; extracting and analyzing the parameter effective value range based on the characteristic parameter data to form characteristic parameter effective value range data; performing classification analysis based on characteristic information based on the characteristic parameter effective value range data to form characteristic parameter classification and identification data; performing classification verification analysis based on the characteristic information based on the characteristic parameter effective value range data and in combination with the characteristic parameter classification and identification data to form Rogowski coil classification and identification reference data.

[0010] In the present invention, to identify and analyze the type of Rogowski coil in an electricity meter, a key step in utilizing big data analysis and processing is to extract characteristic information about the Rogowski coil type from the big data, perform reasonable analysis and processing based on this characteristic information, and then apply the results of this analysis and processing to identify and determine the type of Rogowski coil in the electricity meter. This characteristic information about the Rogowski coil type is essentially parameter data related to the operation of the Rogowski coil. This parameter data exhibits a range of variations depending on the characteristics of the Rogowski coil's operation. Therefore, by extracting and analyzing the effective range of these characteristic parameters, the type of Rogowski coil in the electricity meter can be accurately identified and confirmed.

[0011] As a possible implementation method, characteristic parameter data is extracted based on historical real-time parameter data to form characteristic parameter data, including: extracting the current input value range corresponding to different electricity meters within the analysis period based on the historical real-time parameter data, and arranging them in chronological order to form a historical current input value range set; extracting the maximum withstand voltage value range corresponding to different electricity meters within the analysis period based on the historical real-time parameter data, and arranging them in chronological order to form a historical maximum withstand voltage value range set; extracting the voltage output value range corresponding to different electricity meters within the analysis period based on the historical real-time parameter data, and arranging them in chronological order to form a historical voltage output value range set.

[0012] In the present invention, for Rogowski coils, characteristic parameters that are closely related to them and exhibit correlation between parameters include the current input value range, voltage output value range, and maximum withstand voltage value range of the coil. These three types of characteristic parameter ranges essentially determine the type characteristics of the Rogowski coil. Therefore, by collecting and analyzing these three types of characteristic parameters, it is possible to reasonably and accurately identify and judge the type of Rogowski coil in the electric energy meter. Of course, it is worth noting that these three types of characteristic parameters are not independent of each other, but are closely related. Therefore, not only can the three types of characteristic parameter data themselves be used, but the relationship between these three types of characteristic parameter data can also be combined to perform analysis and judgment during classification analysis and processing, providing reasonable identification and analysis judgment under another dimension, which can greatly improve the accuracy of identifying and judging the type of Rogowski coil in the electric energy meter.

[0013] As a possible implementation method, based on the characteristic parameter data, the effective value range of the parameter is extracted and analyzed to form the effective value range data of the characteristic parameter, including: for each current input value range in the historical current input value range set, all discrete historical current input values in the range are evenly spaced in order from small to large, and fitted to form a historical current input curve; the slope of the line connecting the minimum value and the maximum value in the historical current input curve is determined to be the effective boundary slope of the historical current input; based on the effective boundary slope of the historical current input, the effective current input value point on the historical current input curve with the slope being the effective boundary slope of the historical current input is defined, and two effective current input points are determined. The maximum and minimum values of the historical current input values defined between the effective current input value points are used to form an effective historical current input value range, and the number of discrete effective historical current input values in the effective historical current input value range is uniformly adjusted; all effective historical current input value ranges are gathered to form an effective historical current input value range set; for each maximum withstand voltage value range in the historical maximum withstand voltage value range set, all discrete historical maximum withstand voltage values in the range are evenly spaced in order from small to large, and fitted to form a historical maximum withstand voltage curve; the slope of the line connecting the minimum value and the maximum value in the historical maximum withstand voltage curve is determined to be the effective boundary slope of the historical maximum withstand voltage; according to The effective boundary slope of the historical maximum withstand voltage defines the effective maximum withstand voltage value point on the historical maximum withstand voltage curve whose slope is the effective boundary slope of the historical maximum withstand voltage, determines the maximum and minimum values of the historical maximum withstand voltage value defined between the two effective maximum withstand voltage value points, forms an effective historical maximum withstand voltage value range, and uniformly adjusts the number of discrete effective historical maximum withstand voltage values in the effective historical maximum withstand voltage value range; gathers all effective historical maximum withstand voltage value ranges to form an effective historical maximum withstand voltage value range set; for each voltage output value range in the historical voltage output value range set, arranges all discrete historical voltage output values in the range in an evenly spaced order from small to large. , and fit to form a historical voltage output curve; determine the slope of the line connecting the minimum value and the maximum value in the historical voltage output curve, and determine it as the historical voltage output effective boundary slope; according to the historical voltage output effective boundary slope, define the effective voltage output value point on the historical voltage output curve with the slope of the historical voltage output effective boundary slope, determine the maximum and minimum values of the historical voltage output value defined between the two effective voltage output value points, form an effective historical voltage output value range, and uniformly adjust the number of discrete effective historical voltage output values in the effective historical voltage output value range; gather all effective historical voltage output value ranges to form an effective historical voltage output value range set.

[0014] In the present invention, data analysis of the three characteristic parameters that determine Rogowski coil types primarily extracts valid data generated during meter operation, thereby accurately determining the different performance of different Rogowski coil types in these three characteristic parameters. Direct historical data collection only captures initial data information. Considering the potential for abnormal deviations or other influences in these parameter data, it is necessary to rationally filter and process this initial data to generate valid parameter data for accurate Rogowski coil classification. It should be noted that the input current ranges vary significantly depending on the type of Rogowski coil, with some receiving a larger range and some receiving a smaller range. Similarly, the corresponding output voltage range and maximum withstand voltage range also vary accordingly. Therefore, when defining the valid data range, the slope of the maximum and minimum values is used. It is understood that the larger the parameter variation range allowed by the Rogowski coil itself, the greater the difference between the maximum and minimum values obtained. Consequently, the larger the slope used for definition, the larger the valid range obtained. This defined range is consistent with the parameter range characteristics of the Rogowski coil itself, making the extracted valid parameter range data more reasonable. In addition, it should be noted that after completing the definition of the valid parameter range, in order to improve the comparability and processability of the valid data range, it is necessary to adjust the number of historical data obtained in the range. The simplest way is to obtain the historical valid current input value range, the historical valid voltage output value range and the historical valid maximum withstand voltage range respectively, and then determine the minimum number of historical data in these ranges, and based on the minimum value, reasonably delete the historical data in all parameter ranges, such as determining the average within the range, and starting to delete the data closest to the average, so as not to affect the characteristics of the range data.

[0015] As a possible implementation method, according to the effective value range data of the characteristic parameter, a classification analysis based on the characteristic information is performed to form characteristic parameter classification identification data, including: for each effective historical current input value range in the effective historical current input value range set, the effective historical current input values are arranged in order of the time dimension, and the change rate between adjacent effective historical current input values is determined respectively. , where n represents the number of the valid historical current input value in the valid historical current input value range; for each valid historical voltage output value range in the valid historical voltage output value range set, the valid historical voltage input values are arranged in time dimension order, and the change rate between adjacent valid historical voltage output values is determined respectively. .

[0016] In this invention, classification and identification analysis primarily utilizes range data to categorize Rogowski coils of the same type. It is understood that Rogowski coils of the same type are typically used in similar environments, which is essentially reflected in the fact that the relative rate of change of parameter data during historical data collection is at the same level. Therefore, extracting the rate of change is essential during classification analysis, providing an important reference for subsequent rationality analysis based on the relationships between parameter data.

[0017] As a possible implementation method, based on the effective value range data of the feature parameters, classification analysis based on feature information is performed to form feature parameter classification recognition data, including: setting the overlap classification threshold and allowable overlap slope range , determine the different valid historical current input value ranges that have an inclusion relationship, and perform the following overlap classification analysis: if the ratio of the included valid historical current input value range to the included valid historical current input value range is not less than the overlap classification threshold , and according to the overlap range of the historical current input value range, the two valid historical voltage output value ranges are both satisfied. , the two valid historical current input value ranges are merged, and the included valid historical current input value range is used as the merged valid historical current input value range; otherwise, no merging is performed; the Rogowski coils of the electric energy meter corresponding to the two merged valid historical current input value ranges are determined to be of the same type.

[0018] In this invention, when classifying Rogowski coils of the same type, the primary analysis and judgment is based on the coil's current input value range and voltage output value range. These two parameters have a strong correspondence, necessitating a comprehensive analysis. Of course, the first step in this analysis is to identify ranges that contain a relationship. After all, this type of range data is most likely to represent Rogowski coils of the same type. However, it is also possible that the included ranges represent a more sensitive type of Rogowski coil, so analysis and confirmation are performed by setting a threshold. This threshold can be determined based on actual conditions or through big data analysis.

[0019] As a possible implementation method, based on the effective value range data of the feature parameters, classification analysis based on feature information is performed to form feature parameter classification identification data, including: setting the non-inclusion overlap classification threshold , for different valid historical current input value ranges with intersecting ranges, the following overlap classification analysis is performed: for two valid historical current input value ranges, the ratio of the intersecting range to the corresponding valid historical current input value range is not less than the non-inclusion overlap classification threshold , and within the two valid historical voltage output value ranges corresponding to the intersection range, both satisfy , the two valid historical current input value ranges are merged, and the intersecting range is used as the merged valid historical current input value range, otherwise, no merging is performed; the Rogowski coils of the electric energy meter corresponding to the two merged valid historical current input value ranges are determined to be of the same type.

[0020] In the present invention, for range data with a certain intersection, when classifying and judging the type of Rogowski coils, it is necessary to consider whether such intersection is formed based on minor differences in the usage environment. Similarly, by setting a reasonable threshold for analysis and judgment, different types of Rogowski coils can be accurately determined, thereby achieving a reasonable and accurate classification of Rogowski coil types.

[0021] As a possible implementation method, according to the effective value range data of the characteristic parameters, classification analysis based on characteristic information is performed to form characteristic parameter classification identification data, including: setting the overlap withstand voltage classification threshold and withstand voltage difference threshold , and perform the following verification analysis on the electric energy meter that is to be overlapped and merged: determine the effective historical maximum withstand voltage value range corresponding to the overlap interval of the effective historical current input value range of the overlapped and merged, and calibrate it as the overlapped and merged maximum withstand voltage value range; if the overlapped and merged maximum withstand voltage value range accounts for the corresponding effective historical maximum withstand voltage value range and is not less than the overlapped withstand voltage classification threshold , and the difference in the average withstand voltage change rate of the valid historical maximum withstand voltage value range corresponding to the two valid historical current input value ranges is less than the withstand voltage difference threshold , then determine that the Rogowski coils of the electric energy meters corresponding to the effective historical current input value range of the coincident merger are of the same type, otherwise the coincident merger is decomposed.

[0022] In the present invention, it is understood that after using the historical effective current input value range and the historical effective voltage output value range for classification and analysis, the voltage withstand characteristics of the Rogowski coils also need to be considered. Voltage withstand characteristics are also important parameters for distinguishing Rogowski coil types. Here, the maximum voltage withstand data is used to sequentially verify and judge the Rogowski coils classified according to the historical effective current input value range and the historical effective voltage output value range, thereby improving the accuracy and rationality of the Rogowski coil type identification and classification. Similarly, a reasonable threshold is set for analysis and determination.

[0023] As a possible implementation method, type identification analysis is performed in combination with Rogowski coil classification identification parameter data and product parameter data to generate Rogowski coil type identification result data, including: for electricity meters classified as the same type of Rogowski coil, the following Rogowski coil type determination is performed based on the product parameter data: if all valid historical current input value ranges corresponding to electricity meters with the same type of Rogowski coil are included in the Rogowski coil current input product range, all valid historical voltage output value ranges corresponding to electricity meters with the same type of Rogowski coil are included in the Rogowski coil voltage output product range, and all valid historical maximum withstand voltage value ranges corresponding to electricity meters with the Rogowski coil are included in the Rogowski coil maximum withstand voltage product range, then the Rogowski coil in the electricity meter is determined to be the Rogowski coil type to which the corresponding product parameters belong.

[0024] In this invention, after classifying the Rogowski coil types in electricity meters using characteristic parameters based on historical big data, it is necessary to determine the specific product type of each Rogowski coil type, thereby fully identifying the Rogowski coil type. It is understandable that the valid range formed by the historical parameter data is essentially part of the allowable range for Rogowski coil products. In other words, the valid range formed is within the allowable range for the product. Therefore, the inclusion relationship used to identify Rogowski coils is accurate and reasonable.

[0025] In a second aspect, the present invention provides an electric energy meter capable of automatically identifying the type of Rogowski coil. The electric energy meter capable of automatically identifying the type of Rogowski coil is configured to: respectively obtain historical real-time parameter data of electric energy meters of different Rogowski coil types and product parameter data of different Rogowski coil types; perform classification and recognition analysis based on feature information based on the historical real-time parameter data to form Rogowski coil classification and recognition reference data; and perform type recognition analysis in combination with the Rogowski coil classification and recognition parameter data and the product parameter data to form Rogowski coil type recognition result data.

[0026] In the present invention, the electric energy meter is configured as an acquisition system capable of acquiring the measurement parameters of the electric energy meter's Rogowski coil, and performs real-time and efficient classification, identification and analysis on the acquired data, providing classification results that can be used for identification and judgment. At the same time, in conjunction with a system capable of acquiring parameters generated by the type of Rogowski coil, the identification and judgment of the type of Rogowski coil in the electric energy meter is completed, providing an important material basis for efficient and accurate identification and judgment of the type of Rogowski coil in the electric energy meter.

[0027] The beneficial effects of the electric energy meter and identification method capable of automatically distinguishing the type of Rogowski coil provided by the present invention are as follows: This method obtains historical measurement data of the electric energy meter to establish rich basic data on Rogowski coil measurement parameters, and combines parameters that can characterize the type characteristics of the Rogowski coil to reasonably and accurately identify and classify the Rogowski coil. The obtained Rogowski coil product parameter big data is then compared and confirmed to accurately determine the type of the Rogowski coil in the electric energy meter. This method is accurate and efficient and can quickly provide type identification of the Rogowski coil in the electric energy meter.

[0028] The electric energy meter is configured as an acquisition system capable of acquiring the measurement parameters of the Rogowski coil of the electric energy meter, and performs real-time and efficient classification, identification and analysis of the acquired data, providing classification results that can be used for identification and judgment. At the same time, it cooperates with a system capable of acquiring parameters generated by the type of Rogowski coil to complete the identification and judgment of the type of Rogowski coil in the electric energy meter, providing an important material basis for efficient and accurate identification and judgment of the type of Rogowski coil in the electric energy meter. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the embodiments of the present invention. It should be understood that the following drawings only illustrate certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other relevant drawings can be obtained based on these drawings without paying any creative work.

[0030] Figure 1 This is a step diagram of a method for automatically identifying the type of Rogowski coil provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0031] The technical solutions in the embodiments of the present invention will be described below with reference to the accompanying drawings in the embodiments of the present invention.

[0032] A Rogowski coil, also known as a Rogowski coil, is an AC current sensor. It's a hollow, ring-shaped coil, available in both flexible and rigid configurations, that can be directly applied to the conductor being measured to measure AC current. Because it converts high currents into measurable voltages, it's an ideal measuring component for electricity meters. Converting high currents to a reasonable voltage range allows for wide-ranging measurements while also avoiding the potential risks of directly measuring high currents.

[0033] Currently, since electricity meters are frequently used and most of the time require inspection and secondary use, it is crucial to determine the type of Rogowski coil in the electricity meter when the original data is not available. After all, different types of Rogowski coils are suitable for different measurement ranges to ensure measurement accuracy.

[0034] refer to Figure 1 An embodiment of the present invention provides an identification method capable of automatically distinguishing the type of Rogowski coil. The method obtains historical measurement data of an electric energy meter to establish a rich set of basic data on Rogowski coil measurement parameters, and combines parameters that can characterize the type characteristics of the Rogowski coil to reasonably and accurately identify and classify the Rogowski coil. The obtained Rogowski coil product parameter big data is then compared and confirmed to accurately determine the type of the Rogowski coil in the electric energy meter. This method is accurate and efficient and can quickly provide type identification for the Rogowski coil in the electric energy meter.

[0035] The identification method capable of automatically distinguishing the type of Rogowski coil specifically includes the following steps: S1: respectively obtain historical real-time parameter data of electric energy meters of different Rogowski coil types and product parameter data of different Rogowski coil types.

[0036] Collecting big data for Rogowski coil type analysis and judgment provides an important data basis for subsequent reasonable and accurate analysis and identification.

[0037] S2: Based on the historical real-time parameter data, classification and identification analysis based on feature information is performed to form Rogowski coil classification and identification reference data.

[0038] Based on the historical real-time parameter data, classification and identification analysis based on characteristic information is performed to form Rogowski coil classification and identification reference data, including: extracting characteristic parameter data based on the historical real-time parameter data to form characteristic parameter data; extracting and analyzing the effective value range of the parameter based on the characteristic parameter data to form characteristic parameter effective value range data; based on the characteristic parameter effective value range data, classification analysis based on characteristic information is performed to form characteristic parameter classification and identification data; based on the characteristic parameter effective value range data and in combination with the characteristic parameter classification and identification data, classification verification analysis based on characteristic information is performed to form Rogowski coil classification and identification reference data.

[0039] To identify and analyze the type of Rogowski coil in an electricity meter, a key step in utilizing big data analysis and processing is to extract characteristic information about the Rogowski coil type from the big data, perform reasonable analysis and processing based on this characteristic information, and then apply the results of this analysis and processing to identify and determine the type of Rogowski coil in the electricity meter. This characteristic information about the Rogowski coil type is essentially parameter data related to the coil's operation. This parameter data exhibits a range of variations depending on the characteristics of the coil's operation. Therefore, by extracting and analyzing the effective range of these characteristic parameters, accurate identification and confirmation of the Rogowski coil type in the electricity meter can be achieved.

[0040] Among them, characteristic parameter data is extracted according to historical real-time parameter data to form characteristic parameter data, including: extracting the current input value range corresponding to different electricity meters within the analysis period according to the historical real-time parameter data, and arranging them in chronological order to form a historical current input value range set; extracting the maximum withstand voltage value range corresponding to different electricity meters within the analysis period according to the historical real-time parameter data, and arranging them in chronological order to form a historical maximum withstand voltage value range set; extracting the voltage output value range corresponding to different electricity meters within the analysis period according to the historical real-time parameter data, and arranging them in chronological order to form a historical voltage output value range set.

[0041] For Rogowski coils, characteristic parameters that are closely related and exhibit correlation include the coil's current input range, voltage output range, and maximum withstand voltage range. These three characteristic parameter ranges fundamentally determine the type of Rogowski coil. Therefore, collecting and analyzing these three types of characteristic parameters allows for reasonable and accurate identification of the type of Rogowski coil in an electricity meter. Of course, it's worth noting that these three types of characteristic parameters are not independent of each other but rather closely related. Therefore, not only can the characteristic parameter data itself be utilized, but the relationships between these three types of characteristic parameter data can also be combined during classification analysis and processing to analyze and judge the type of Rogowski coil in an electricity meter. This provides another dimension for reasonable identification and analysis, significantly improving the accuracy of Rogowski coil identification in electricity meters.

[0042] According to the characteristic parameter data, the effective value range of the parameter is extracted and analyzed to form the effective value range data of the characteristic parameter, including: for each current input value range in the historical current input value range set, all discrete historical current input values in the range are evenly spaced in order from small to large, and fitted to form a historical current input curve; the slope of the line connecting the minimum value and the maximum value in the historical current input curve is determined to be the effective boundary slope of the historical current input; according to the effective boundary slope of the historical current input, the effective current input value point on the historical current input curve with the slope being the effective boundary slope of the historical current input is defined, and the effective current input value point between the two effective current input value points is determined. The maximum and minimum values of the historical current input values defined by the time interval are used to form a valid historical current input value range, and the number of discrete valid historical current input values in the valid historical current input value range is uniformly adjusted; all valid historical current input value ranges are gathered to form a valid historical current input value range set; for each maximum withstand voltage value range in the historical maximum withstand voltage value range set, all discrete historical maximum withstand voltage values in the range are evenly spaced in order from small to large, and fitted to form a historical maximum withstand voltage curve; the slope of the line connecting the minimum value and the maximum value in the historical maximum withstand voltage curve is determined to be the effective boundary slope of the historical maximum withstand voltage; according to the historical maximum withstand voltage The effective boundary slope is used to define the effective maximum withstand voltage value point on the historical maximum withstand voltage curve whose slope is the effective boundary slope of the historical maximum withstand voltage, and the maximum and minimum values of the historical maximum withstand voltage value defined between the two effective maximum withstand voltage value points are determined to form an effective historical maximum withstand voltage value range, and the number of discrete effective historical maximum withstand voltage values in the effective historical maximum withstand voltage value range is uniformly adjusted; all effective historical maximum withstand voltage value ranges are collected to form an effective historical maximum withstand voltage value range set; for each voltage output value range in the historical voltage output value range set, all discrete historical voltage output values in the range are evenly spaced in order from small to large, and a simulation is performed. The historical voltage output curve is formed by combining the minimum value and the maximum value in the historical voltage output curve; the slope of the line connecting the minimum value and the maximum value in the historical voltage output curve is determined to be the effective boundary slope of the historical voltage output; according to the effective boundary slope of the historical voltage output, the effective voltage output value point on the historical voltage output curve with the slope being the effective boundary slope of the historical voltage output is defined, the maximum value and the minimum value of the historical voltage output value defined between the two effective voltage output value points are determined to form an effective historical voltage output value range, and the number of discrete effective historical voltage output values in the effective historical voltage output value range is uniformly adjusted; all effective historical voltage output value ranges are aggregated to form an effective historical voltage output value range set.

[0043] Data analysis of the three characteristic parameters that determine Rogowski coil types primarily aims to extract valid data generated during meter operation, thereby accurately determining the performance of different Rogowski coil types in these three characteristic parameters. Direct historical data collection only captures initial data. Considering the potential for abnormal deviations or other influences in these parameter data, it is necessary to carefully filter and process this initial data to generate valid parameter data for accurate Rogowski coil classification. It should be noted that the input current range varies significantly depending on the type of Rogowski coil, with some receiving a larger range and some receiving a smaller range. Similarly, the corresponding output voltage range and maximum withstand voltage range also vary accordingly. Therefore, the slope of the maximum and minimum values is used to define the valid data range. As can be seen, the larger the range of the Rogowski coil's inherent parameter variation, the greater the difference between the maximum and minimum values obtained. Consequently, the slope used for the definition is larger, resulting in a larger valid range. This allows the defined range to be consistent with the Rogowski coil's inherent parameter range characteristics, making the extracted valid parameter range data more reasonable. In addition, it should be noted that after completing the definition of the valid parameter range, in order to improve the comparability and processability of the valid data range, it is necessary to adjust the number of historical data obtained in the range. The simplest way is to obtain the historical valid current input value range, the historical valid voltage output value range and the historical valid maximum withstand voltage range respectively, and then determine the minimum number of historical data in these ranges, and based on the minimum value, reasonably delete the historical data in all parameter ranges, such as determining the average within the range, and starting to delete the data closest to the average, so as not to affect the characteristics of the range data.

[0044] According to the effective value range data of the characteristic parameters, a classification analysis based on the characteristic information is performed to form characteristic parameter classification identification data, including: for each effective historical current input value range in the effective historical current input value range set, the effective historical current input values are arranged in the order of the time dimension, and the change rate between adjacent effective historical current input values is determined respectively. , where n represents the number of the valid historical current input value in the valid historical current input value range; for each valid historical voltage output value range in the valid historical voltage output value range set, the valid historical voltage input values are arranged in time dimension order, and the change rate between adjacent valid historical voltage output values is determined respectively. .

[0045] Classification and identification analysis primarily utilizes range data to categorize and judge Rogowski coils of the same type. It's understandable that the same type of Rogowski coils are used in similar environments, which is essentially reflected in the same relative rate of change in parameter data during historical data collection. Therefore, when conducting classification analysis, it's essential to first extract the rate of change, providing an important reference for subsequent rationale analysis based on the relationships between parameter data.

[0046] According to the effective value range data of the characteristic parameters, classification analysis based on the characteristic information is performed to form characteristic parameter classification identification data, including: setting the classification threshold including the degree of overlap and allowable overlap slope range , determine the different valid historical current input value ranges that have an inclusion relationship, and perform the following overlap classification analysis: if the ratio of the included valid historical current input value range to the included valid historical current input value range is not less than the overlap classification threshold , and according to the overlap range of the historical current input value range, the two valid historical voltage output value ranges are both satisfied. , the two valid historical current input value ranges are merged, and the included valid historical current input value range is used as the merged valid historical current input value range; otherwise, no merging is performed; the Rogowski coils of the electric energy meter corresponding to the two merged valid historical current input value ranges are determined to be of the same type.

[0047] When classifying Rogowski coils of the same type, the primary analysis is based on their current input and voltage output ranges. These two parameters have a strong correlation, necessitating a comprehensive analysis. Of course, the first step in this analysis is to identify ranges that are inclusive. After all, this type of range data is most likely to represent Rogowski coils of the same type. However, it's possible that the included ranges represent a more sensitive type of Rogowski coil, requiring analysis and confirmation by setting a threshold. This threshold can be determined based on actual conditions or through big data analysis.

[0048] According to the effective value range data of the characteristic parameters, classification analysis based on the characteristic information is performed to form characteristic parameter classification identification data, including: setting the non-inclusion overlap classification threshold , for different valid historical current input value ranges with intersecting ranges, the following overlap classification analysis is performed: for two valid historical current input value ranges, the ratio of the intersecting range to the corresponding valid historical current input value range is not less than the non-inclusion overlap classification threshold , and within the two valid historical voltage output value ranges corresponding to the intersection range, both satisfy , the two valid historical current input value ranges are merged, and the intersecting range is used as the merged valid historical current input value range, otherwise, no merging is performed; the Rogowski coils of the electric energy meter corresponding to the two merged valid historical current input value ranges are determined to be of the same type.

[0049] For range data with a certain intersection, when classifying and judging the type of Rogowski coil, it is necessary to consider whether this intersection is formed based on minor differences in the usage environment. Similarly, by setting reasonable thresholds for analysis and judgment, different types of Rogowski coils can be accurately determined, thereby achieving a reasonable and accurate classification of Rogowski coil types.

[0050] According to the effective value range data of the characteristic parameters, classification analysis based on the characteristic information is performed to form characteristic parameter classification identification data, including: setting the overlap withstand voltage classification threshold And the voltage difference threshold , and perform the following verification analysis on the electric energy meter that is to be overlapped and merged: determine the effective historical maximum withstand voltage value range corresponding to the overlap interval of the effective historical current input value range of the overlapped and merged, and calibrate it as the overlapped and merged maximum withstand voltage value range; if the overlapped and merged maximum withstand voltage value range accounts for the corresponding effective historical maximum withstand voltage value range and is not less than the overlapped withstand voltage classification threshold , and the difference in the average withstand voltage change rate of the valid historical maximum withstand voltage value range corresponding to the two valid historical current input value ranges is less than the withstand voltage difference threshold , then determine that the Rogowski coils of the electric energy meters corresponding to the effective historical current input value range of the coincident merger are of the same type, otherwise the coincident merger is decomposed.

[0051] It is understandable that after using the historical effective current input value range and the historical effective voltage output value range for classification and analysis, the voltage withstand characteristics of the Rogowski coil also need to be considered. Voltage withstand characteristics are also important parameters for distinguishing Rogowski coil types. Here, the maximum voltage withstand data is used to sequentially verify and judge the Rogowski coils classified according to the historical effective current input value range and the historical effective voltage output value range, thereby improving the accuracy and rationality of the Rogowski coil type identification and classification. Similarly, a reasonable threshold is set for analysis and determination.

[0052] S3: Combine the Rogowski coil classification identification parameter data and the product parameter data to perform type identification analysis to form Rogowski coil type identification result data.

[0053] Combining the Rogowski coil classification identification parameter data and the product parameter data, type identification analysis is performed to generate Rogowski coil type identification result data, including: for electric energy meters classified as the same type of Rogowski coil, the following Rogowski coil type determination is performed based on the product parameter data: if all valid historical current input value ranges corresponding to electric energy meters with the same type of Rogowski coil are included in the Rogowski coil current input product range, all valid historical voltage output value ranges corresponding to electric energy meters with the same type of Rogowski coil are included in the Rogowski coil voltage output product range, and all valid historical maximum withstand voltage value ranges corresponding to electric energy meters with the Rogowski coil are included in the Rogowski coil maximum withstand voltage product range, then the Rogowski coil in the electric energy meter is determined to be the Rogowski coil type to which the corresponding product parameters belong.

[0054] After classifying the Rogowski coil types in electricity meters using characteristic parameters based on historical big data, it's necessary to determine the specific product type of each Rogowski coil type, thereby fully identifying the coil type. It's understandable that the valid range formed by the historical parameter data is essentially part of the permitted range for Rogowski coil products. Therefore, using inclusion relationships to identify Rogowski coils is both accurate and reasonable.

[0055] The present invention also provides an electric energy meter capable of automatically distinguishing the type of Rogowski coil. The electric energy meter capable of automatically distinguishing the type of Rogowski coil is configured to: respectively obtain historical real-time parameter data of electric energy meters of different Rogowski coil types and product parameter data of different Rogowski coil types; perform classification and identification analysis based on feature information based on the historical real-time parameter data to form Rogowski coil classification and identification reference data; and perform type identification analysis in combination with the Rogowski coil classification and identification parameter data and the product parameter data to form Rogowski coil type identification result data.

[0056] The electric energy meter is configured as an acquisition system capable of acquiring the measurement parameters of the Rogowski coil of the electric energy meter, and performs real-time and efficient classification, identification and analysis of the acquired data, providing classification results that can be used for identification and judgment. At the same time, it cooperates with a system capable of acquiring parameters generated by the type of Rogowski coil to complete the identification and judgment of the type of Rogowski coil in the electric energy meter, providing an important material basis for efficient and accurate identification and judgment of the type of Rogowski coil in the electric energy meter.

[0057] In summary, the embodiments of the present invention provide an electric energy meter and identification method capable of automatically identifying the type of Rogowski coil, which have the following beneficial effects: This method obtains historical measurement data of the electric energy meter to establish rich basic data on Rogowski coil measurement parameters, and combines parameters that can characterize the type characteristics of the Rogowski coil to reasonably and accurately identify and classify the Rogowski coil. The obtained Rogowski coil product parameter big data is then compared and confirmed to accurately determine the type of the Rogowski coil in the electric energy meter. This method is accurate and efficient and can quickly provide type identification of the Rogowski coil in the electric energy meter.

[0058] The electric energy meter is configured as an acquisition system capable of acquiring the measurement parameters of the Rogowski coil of the electric energy meter, and performs real-time and efficient classification, identification and analysis of the acquired data, providing classification results that can be used for identification and judgment. At the same time, it cooperates with a system capable of acquiring parameters generated by the type of Rogowski coil to complete the identification and judgment of the type of Rogowski coil in the electric energy meter, providing an important material basis for efficient and accurate identification and judgment of the type of Rogowski coil in the electric energy meter.

[0059] In the embodiment of the present application, "indication" may include direct indication and indirect indication, and may also include explicit indication and implicit indication. The information indicated by a certain information is called information to be indicated. In the specific implementation process, there are many ways to indicate the information to be indicated, such as but not limited to, the information to be indicated can be directly indicated, such as the information to be indicated itself or the index of the information to be indicated. The information to be indicated can also be indirectly indicated by indicating other information, wherein there is an association relationship between the other information and the information to be indicated. It is also possible to indicate only a part of the information to be indicated, while the other parts of the information to be indicated are known or agreed in advance. For example, the indication of specific information can also be achieved by means of the arrangement order of each piece of information agreed in advance (such as specified in the protocol), thereby reducing the indication overhead to a certain extent. At the same time, the common parts of each piece of information can also be identified and indicated uniformly to reduce the indication overhead caused by indicating the same information separately.

[0060] In addition, the specific indication method can also be various existing indication methods, such as but not limited to the above-mentioned indication methods and various combinations thereof. The specific details of the various indication methods can be referred to the prior art and will not be repeated herein. As can be seen from the above, for example, when it is necessary to indicate multiple information of the same type, there may be a situation where the indication methods for different information are different. In the specific implementation process, the required indication method can be selected according to specific needs. The embodiment of the present application does not limit the selected indication method. In this way, the indication method involved in the embodiment of the present application should be understood to cover various methods that can enable the party to be indicated to obtain the information to be indicated.

[0061] It should be understood that the information to be indicated can be sent as a whole or divided into multiple sub-information and sent separately, and the sending period and / or sending time of these sub-information can be the same or different. The specific sending method is not limited in the embodiments of this application. The sending period and / or sending time of these sub-information can be predefined, for example, predefined according to a protocol, or can be configured by the transmitting device by sending configuration information to the receiving device.

[0062] "Pre-definition" or "pre-configuration" can be implemented by pre-saving corresponding codes, tables or other methods that can be used to indicate relevant information in the device, and the embodiments of the present application do not limit the specific implementation method. Among them, "saving" can mean saving in one or more memories. The one or more memories can be set separately or integrated in an encoder or decoder, a processor, or a communication device. The one or more memories can also be partially set separately and partially integrated in a decoder, a processor, or a communication device. The type of memory can be any form of storage medium, and the embodiments of the present application do not limit this.

[0063] The "protocol" involved in the embodiments of the present application may refer to a protocol family in the communication field, a standard protocol with a similar protocol family frame structure, or a related protocol used in future communication systems. The embodiments of the present application do not make specific limitations on this.

[0064] In the embodiments of the present application, descriptions such as "when...", "in the case of...", "if" and "if" all mean that the device will perform corresponding processing under certain objective circumstances. It does not limit the time, nor does it require the device to perform judgment actions when implemented, nor does it mean that there are other limitations.

[0065] In the description of the embodiments of this application, unless otherwise specified, " / " indicates that the associated objects are in an "or" relationship. For example, A / B can mean A or B. "And / or" in the embodiments of this application is merely a description of the associated relationship between the associated objects, indicating that three relationships can exist. For example, "A and / or B" can mean: A alone, A and B together, or B alone. A and B can be singular or plural. Furthermore, in the description of the embodiments of this application, unless otherwise specified, "multiple" means two or more. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single or plural items. For example, "at least one of a, b, or c" can mean: a, b, c, ab, ac, bc, or abc, where a, b, and c can be single or plural. Furthermore, to facilitate the clear description of the technical solutions of the embodiments of this application, the terms "first" and "second" are used in the embodiments of this application to distinguish between identical or similar items with substantially the same function or effect. Those skilled in the art will understand that words such as "first" and "second" do not limit the quantity and execution order, and words such as "first" and "second" do not necessarily limit differences. At the same time, in the embodiments of the present application, words such as "exemplary" or "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design described as "exemplary" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or design. Specifically, the use of words such as "exemplary" or "for example" is intended to present related concepts in a concrete way for easy understanding.

[0066] It should be understood that the processor in the embodiments of the present application may be a central processing unit (CPU), but may also be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field programmable gate arrays (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor, etc.

[0067] It should also be understood that the memory in the embodiments of the present application may be a volatile memory or a non-volatile memory, or may include both volatile and non-volatile memories. Among them, the non-volatile memory may be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), or a flash memory. The volatile memory may be a random access memory (RAM), which is used as an external cache. By way of example and not limitation, many forms of random access memory (RAM) are available, such as static RAM (SRAM), dynamic random access memory (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), and direct rambus RAM (DR RAM).

[0068] The above embodiments can be implemented in whole or in part via software, hardware (e.g., circuits), firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product comprises one or more computer instructions or computer programs. When loaded or executed on a computer, the processes or functions described in the embodiments of this application are fully or partially generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired means (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium accessible by a computer or a data storage device such as a server or data center that contains a collection of one or more available media. The available medium can be magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., DVDs), or semiconductor media. The semiconductor media can be a solid-state drive.

[0069] It should be understood that the term "and / or" as used herein simply describes a relationship between associated objects, indicating that three possible relationships exist. For example, "A and / or B" can represent: A alone, A and B together, or B alone. A and B can be singular or plural. Furthermore, the character " / " as used herein generally indicates an "or" relationship between the associated objects, but it may also indicate an "and / or" relationship. For specific understanding, please refer to the context.

[0070] In this application, "at least one" means one or more, and "plurality" means two or more. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single or plural items. For example, "at least one of a, b, or c" can mean: a, b, c, ab, ac, bc, or abc, where a, b, and c can be single or plural.

[0071] It should be understood that in the various embodiments of the present application, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0072] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0073] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0074] In the several embodiments provided in this application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are merely schematic. For example, the division of the units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0075] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0076] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0077] 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 application, 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 and includes several instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the method described in each embodiment 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 disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0078] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of this application. Therefore, the scope of protection of this application should be based on the scope of protection of the claims.

Claims

1. A method for automatically identifying the type of Rogowski coil, characterized in that: include: Obtain historical real-time parameter data of electric energy meters of different Rogowski coil types and product parameter data of different Rogowski coil types; Performing classification and identification analysis based on feature information according to the historical real-time parameter data to form Rogowski coil classification and identification reference data; The Rogowski coil classification identification parameter data and the product parameter data are combined to perform type identification analysis to form Rogowski coil type identification result data.

2. The method for automatically distinguishing the type of Rogowski coil according to claim 1, characterized in that: The method of performing classification and identification analysis based on feature information according to the historical real-time parameter data to form Rogowski coil classification and identification reference data includes: Extracting characteristic parameter data based on the historical real-time parameter data to form characteristic parameter data; Extracting and analyzing the effective value range of the parameter based on the characteristic parameter data to form effective value range data of the characteristic parameter; According to the effective value range data of the characteristic parameters, a classification analysis based on the characteristic information is performed to form characteristic parameter classification identification data; According to the valid value range data of the characteristic parameters and in combination with the characteristic parameter classification identification data, a classification verification analysis based on the characteristic information is performed to form the Rogowski coil classification identification reference data.

3. The method for automatically distinguishing the type of Rogowski coil according to claim 2, characterized in that: The extracting of characteristic parameter data based on the historical real-time parameter data to form characteristic parameter data includes: Extracting current input value ranges corresponding to different electric energy meters within an analysis period based on the historical real-time parameter data, and arranging them in chronological order to form a historical current input value range set; Extracting the maximum withstand voltage value ranges within the analysis period corresponding to different electric energy meters based on the historical real-time parameter data, and arranging them in chronological order to form a historical maximum withstand voltage value range set; According to the historical real-time parameter data, the voltage output value ranges within the analysis period corresponding to different electric energy meters are extracted and arranged in chronological order to form a historical voltage output value range set.

4. The method for automatically distinguishing the type of Rogowski coil according to claim 3, characterized in that: The extracting and analyzing the effective value range of the parameter based on the characteristic parameter data to form the effective value range data of the characteristic parameter includes: For each current input value range in the historical current input value range set, all discrete historical current input values in the range are evenly spaced in ascending order, and fitted to form a historical current input curve; Determine the slope of the line connecting the minimum value and the maximum value in the historical current input curve, and determine it as the effective boundary slope of the historical current input; Based on the historical current input effective boundary slope, defining effective current input value points on the historical current input curve whose slopes are the historical current input effective boundary slopes, determining the maximum and minimum values of the historical current input values defined between two of the effective current input value points to form an effective historical current input value range, and uniformly adjusting the number of discrete effective historical current input values in the effective historical current input value range; Gathering all the valid historical current input value ranges to form a valid historical current input value range set; For each maximum withstand voltage value range in the historical maximum withstand voltage value range set, all discrete historical maximum withstand voltage values in the range are evenly spaced in ascending order, and fitted to form a historical maximum withstand voltage curve; Determine the slope of the line connecting the minimum value and the maximum value in the historical maximum withstand voltage curve, and determine it as the effective boundary slope of the historical maximum withstand voltage; Based on the effective boundary slope of the historical maximum withstand voltage, defining an effective maximum withstand voltage value point on the historical maximum withstand voltage curve whose slope is the effective boundary slope of the historical maximum withstand voltage, determining the maximum and minimum values of the historical maximum withstand voltage value defined between two effective maximum withstand voltage value points to form an effective historical maximum withstand voltage value range, and uniformly adjusting the number of discrete effective historical maximum withstand voltage values in the effective historical maximum withstand voltage value range; Gather all the valid historical maximum withstand voltage value ranges to form a valid historical maximum withstand voltage value range set; For each voltage output value range in the historical voltage output value range set, all discrete historical voltage output values in the range are evenly spaced in ascending order, and fitted to form a historical voltage output curve; Determine the slope of the line connecting the minimum value and the maximum value in the historical voltage output curve, and determine it as the slope of the historical voltage output effective boundary; Based on the historical voltage output effective boundary slope, defining effective voltage output value points on the historical voltage output curve whose slopes are the historical voltage output effective boundary slopes, determining the maximum and minimum values of the historical voltage output values defined between two of the effective voltage output value points to form an effective historical voltage output value range, and uniformly adjusting the number of discrete effective historical voltage output values in the effective historical voltage output value range; All of the valid historical voltage output value ranges are collected to form a valid historical voltage output value range set.

5. The method for automatically distinguishing the type of Rogowski coil according to claim 4, characterized in that: The method of performing classification analysis based on the feature information according to the feature parameter valid value range data to form feature parameter classification identification data includes: For each valid historical current input value range in the valid historical current input value range set, the valid historical current input values are arranged in order of time dimension, and the change rate between adjacent valid historical current input values is determined respectively. , wherein n represents the number of the valid historical current input value in the valid historical current input value range; For each valid historical voltage output value range in the valid historical voltage output value range set, the valid historical voltage input values are arranged in time dimension order, and the change rates between adjacent valid historical voltage output values are determined respectively. .

6. The method for automatically distinguishing the type of Rogowski coil according to claim 5, characterized in that: The method of performing classification analysis based on the feature information according to the feature parameter valid value range data to form feature parameter classification identification data includes: Set the classification threshold including overlap and allowable overlap slope range , determine the different valid historical current input value ranges that have an inclusion relationship, and perform the following overlap classification analysis: If the ratio of the valid historical current input value range included to the valid historical current input value range included is not less than the overlap classification threshold , and within the two valid historical voltage output value ranges corresponding to the overlapping range of the historical current input value range, both satisfy , then the two valid historical current input value ranges are merged, and the valid historical current input value range included is used as the merged valid historical current input value range; otherwise, no merging is performed; The Rogowski coils of the electric energy meter corresponding to the two combined effective historical current input value ranges are determined to be of the same type.

7. The method for automatically distinguishing the type of Rogowski coil according to claim 6, characterized in that: The method of performing classification analysis based on the feature information according to the feature parameter valid value range data to form feature parameter classification identification data includes: Set the non-inclusion overlap classification threshold , for different valid historical current input value ranges that have a range intersection relationship, the following overlap classification analysis is performed: For the two valid historical current input value ranges, the ratio of the intersection range to the corresponding valid historical current input value range is not less than the non-inclusion overlap classification threshold. , and within the two valid historical voltage output value ranges corresponding to the intersection range, both satisfy , merging the two valid historical current input value ranges, and using the intersecting range as the merged valid historical current input value range, otherwise, no merging is performed; The Rogowski coils of the electric energy meter corresponding to the two combined effective historical current input value ranges are determined to be of the same type.

8. The method for automatically distinguishing the type of Rogowski coil according to claim 7, characterized in that: The method of performing classification analysis based on the feature information according to the feature parameter valid value range data to form feature parameter classification identification data includes: Set the overlap withstand voltage classification threshold and withstand voltage difference threshold , and perform the following verification analysis on the electric energy meters that are to be merged and overlapped: Determine the effective historical maximum withstand voltage value range corresponding to the overlap interval of the effective historical current input value range of the overlap merger, and calibrate it as the overlap merger maximum withstand voltage value range; If the proportion of the overlapped combined maximum withstand voltage value range in the corresponding valid historical maximum withstand voltage value range is not less than the overlapped withstand voltage classification threshold , and the difference in the average withstand voltage change rate of the two valid historical current input value ranges corresponding to the valid historical maximum withstand voltage value ranges is less than the withstand voltage difference threshold , it is determined that the Rogowski coils of the electric energy meters corresponding to the valid historical current input value ranges to be overlapped and merged are of the same type, otherwise the Rogowski coils are decomposed, overlapped and merged.

9. The method for automatically distinguishing the type of Rogowski coil according to claim 8, characterized in that: The combining of the Rogowski coil classification identification parameter data and the product parameter data to perform type identification analysis to form Rogowski coil type identification result data includes: For electric energy meters classified as the same type of Rogowski coil, the following Rogowski coil types are determined based on the product parameter data: If all the valid historical current input value ranges corresponding to the energy meter of the same type of Rogowski coil are included in the Rogowski coil current input product range, all the valid historical voltage output value ranges corresponding to the energy meter of the same type of Rogowski coil are included in the Rogowski coil voltage output product range, and all the valid historical maximum withstand voltage value ranges corresponding to the energy meter of the Rogowski coil are included in the Rogowski coil maximum withstand voltage product range, then it is determined that the Rogowski coil in the energy meter is the Rogowski coil type to which the corresponding product parameters belong.

10. An electric energy meter capable of automatically identifying the type of Rogowski coil, characterized in that: The electric energy meter capable of automatically distinguishing the type of Rogowski coil is configured as follows: Obtain historical real-time parameter data of electric energy meters of different Rogowski coil types and product parameter data of different Rogowski coil types; Performing classification and identification analysis based on feature information according to the historical real-time parameter data to form Rogowski coil classification and identification reference data; The Rogowski coil classification identification parameter data and the product parameter data are combined to perform type identification analysis to form Rogowski coil type identification result data.

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