Power supply enterprise electric energy metering device and health prediction method

Abstract

The invention relates to the technical field of electric energy metering, in particular to an electric energy metering device and a health prediction method for a power supply enterprise, and the device comprises a current transformer, a voltage transformer, an electric energy meter, a first temperature monitoring unit and a second temperature monitoring unit, the data processing module is used for calculating an upper limit value of a dynamic base line based on the screened data set; the state judgment module is used for judging the state based on the upper limit value of the dynamic base line and the working temperature of the current current transformer and the voltage transformer obtained by the first temperature monitoring unit; and the early warning module is used for generating and outputting health state early warning information for the current transformer and the voltage transformer if the current working temperature exceeds the upper limit value of the dynamic baseline. According to the invention, an alarm line is customized for each device and each working state, so that the interference of non-fault factors is eliminated, an early warning signal truly points to a potential device fault, and the accuracy is greatly improved.

Description

Technical Field

[0001] This invention relates to the field of electricity metering technology, and in particular to an electricity metering device and a health prediction method for power supply companies. Background Technology

[0002] In the operation system of power supply companies, electricity metering devices play a crucial role. They are the core basis for electricity trading; accurate metering of users' electricity consumption directly affects the economic benefits of power supply companies and the vital interests of users. Simultaneously, electricity metering data is also a vital foundation for power grid planning, operation scheduling, and electricity market analysis, playing an irreplaceable role in ensuring the safe, stable, and economical operation of the power system. During use, electricity metering devices typically require related data monitoring. Existing monitoring systems lack effective utilization and analysis of historical data, and cannot establish dynamic relationship models between transformer operating temperature, ambient temperature, and load. This results in a lack of scientific and reasonable basis for judging whether transformers are operating normally, making it difficult to predict potential transformer failures. Summary of the Invention

[0003] In view of this, the purpose of this invention is to propose an energy metering device and a health prediction method for power supply enterprises, so as to solve the problem that the existing monitoring system lacks effective utilization and analysis of historical data, making it difficult to predict the possible failure of the current transformer when judging whether the current transformer is working properly.

[0004] To achieve the above objectives, the present invention provides an energy metering device for power supply enterprises, comprising: a current transformer, a voltage transformer, and an energy meter. The current transformer is connected to the current terminal of the energy meter, and the voltage transformer is connected to the voltage terminal of the energy meter. The energy metering device further includes a first temperature monitoring unit for monitoring the operating temperature of the current transformer and the voltage transformer, a second temperature monitoring unit for detecting the ambient temperature, a historical database of the operating temperatures of the current transformer and the voltage transformer under different loads at different ambient temperatures established based on historical normal data, a data filtering module for matching the current ambient temperature obtained by the second temperature monitoring unit with the current load obtained by the energy meter and the historical database to obtain a filtered data set, a data processing module for calculating a dynamic baseline upper limit value based on the filtered data set, a status judgment module for judging the status based on the dynamic baseline upper limit value and the current operating temperature of the current transformer and the voltage transformer obtained by the first temperature monitoring unit, and an early warning module for generating and outputting health status warning information for the current transformer and the voltage transformer if the current operating temperature exceeds the dynamic baseline upper limit value.

[0005] Optionally, the matching method of the filtering module includes filtering historical data from the historical database that are in the same time period and whose load parameters are in the same load range, based on the current ambient temperature obtained by the second temperature monitoring unit and the current load obtained by the electricity meter.

[0006] Optionally, the same time period is a predetermined time tolerance range centered on the current time.

[0007] Optionally, the method for determining whether the load parameters are in the same load range is as follows: the range of load parameters is divided into several consecutive intervals, and the current load parameters and historical load parameters falling into the same interval are considered to be in the same load range.

[0008] Optionally, the calculation method of the data processing module includes: calculating the mean and standard deviation of the historical data set, and generating a dynamic baseline upper limit value based on the mean and standard deviation, wherein the dynamic baseline upper limit value is the mean plus N times the standard deviation, and N is a real number greater than 2.

[0009] Optionally, the value of N is 3.

[0010] Optionally, the data processing module further includes continuously acquiring temperature data of the operating temperature of the current transformer and voltage transformer at a predetermined sampling frequency, and calculating the temperature change slope of the current stage based on the latest acquired temperature data sequence. The state determination module further includes comparing the calculated temperature change slope with a predetermined slope threshold for determination. The early warning module also includes generating and outputting a predictive early warning message if the slope of the temperature change exceeds the predetermined slope threshold. The predictive early warning message is used to indicate that the device is at risk of overheating in the future due to accelerated temperature changes.

[0011] By continuously calculating and analyzing the slope of temperature changes, a sudden increase in the slope of the predicted value (accelerated temperature rise) is an extremely high-risk signal. The system can issue a predictive warning in advance when the temperature has not yet reached the dangerous threshold but has already shown an abnormal accelerated upward trend, which means that the fault may have changed from quantitative to qualitative change. This provides maintenance personnel with a much longer response and intervention time window than static warnings, achieving "early detection and early handling".

[0012] Optionally, both the current transformer and the voltage transformer are equipped with a data acquisition module on their secondary sides. Based on the current and voltage data obtained by the data acquisition module, the dielectric loss tangent is calculated. The device also includes a fault analysis generation module. When the fault analysis generation module detects that the current operating temperature exceeds the upper limit of the dynamic temperature baseline established for it, it obtains the real-time load current value of the device through the energy meter and compares the real-time load current value with the rated value. If it exceeds the rated value, it generates a first diagnostic conclusion that the temperature abnormality is caused by overload. If the real-time load current value does not exceed the rated value, it determines whether the dielectric loss tangent exceeds a predetermined value. If it does, it generates a second diagnostic conclusion that the temperature abnormality is caused by internal insulation deterioration of the equipment.

[0013] The secondary side of the current transformer and voltage transformer is equipped with a data acquisition module, which can acquire current and voltage data and calculate the dielectric loss tangent. When the monitored current operating temperature exceeds the upper limit of the established dynamic temperature baseline, the fault analysis generation module obtains the real-time load current value of the device through the energy meter and compares it with the rated value. If it exceeds the rated value, a first diagnostic conclusion is generated, i.e., the temperature abnormality is caused by overload. If it does not exceed the rated value, it is determined whether the dielectric loss tangent exceeds a predetermined value. If it does, a second diagnostic conclusion is generated, i.e., the temperature abnormality is caused by internal insulation degradation of the equipment. By comprehensively analyzing the real-time load current and dielectric loss tangent, the cause of the temperature abnormality can be determined, providing maintenance personnel with detailed fault information, which helps to quickly locate the problem and take targeted maintenance measures, thereby improving maintenance efficiency and equipment reliability.

[0014] Optionally, the device further includes a backup heat dissipation mechanism. If the dielectric loss tangent does not exceed a predetermined value, the device acquires the current operating temperature data of nearby similar devices. If the current operating temperature of the nearby similar devices all exceeds the upper limit of the dynamic temperature baseline, a third diagnostic conclusion is generated that the temperature abnormality is caused by shared environmental factors, and the backup heat dissipation mechanism is activated.

[0015] Based on the same invention, this invention also provides a method for predicting the health of power metering devices in power supply companies, the method comprising: Based on historical normal data, a historical database of the operating temperatures of current transformers and voltage transformers under different loads at different ambient temperatures was established. Based on the current ambient temperature obtained by the second temperature monitoring unit, the current load obtained by the electricity meter is matched with the historical database to obtain a filtered data set; The upper limit of the dynamic baseline is calculated based on the filtered dataset; The status is determined based on the upper limit of the dynamic baseline and the current operating temperatures of the current transformer and voltage transformer obtained by the first temperature monitoring unit. If the current operating temperature exceeds the upper limit of the dynamic baseline, a health status warning message for the current transformer and voltage transformer will be generated and output.

[0016] This energy metering device includes current transformers, voltage transformers, and an energy meter, which are interconnected to achieve basic energy metering functions. Simultaneously, a first temperature monitoring unit monitors the operating temperatures of the current and voltage transformers, while a second temperature monitoring unit detects the ambient temperature. A historical database of transformer operating temperatures under different ambient temperatures and loads is established based on historical normal data. A data filtering module filters matching data from the historical database based on the current ambient temperature and the current load obtained from the energy meter, resulting in a filtered data set. A data processing module calculates the dynamic baseline upper limit based on the filtered data set. A status judgment module compares the current transformer operating temperature with the dynamic baseline upper limit to determine the status. If the current operating temperature exceeds the upper limit, an early warning module generates and outputs a health status warning message.

[0017] This invention establishes a dynamic baseline that considers ambient temperature and load current. The system can automatically identify the normal temperature range of equipment under specific operating conditions. An alarm is only triggered when the equipment temperature deviates from its historical normal performance under the same environment and load. This is equivalent to "tailor-making" an alarm line for each piece of equipment and each operating state, thereby eliminating interference from non-faulty factors and ensuring that the alarm signal truly points to potential equipment faults, greatly improving accuracy. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only for this invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 This is a block diagram of the device system according to an embodiment of the present invention. Detailed Implementation

[0020] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to specific embodiments.

[0021] It should be noted that, unless otherwise defined, the technical or scientific terms used in this invention should have the ordinary meaning understood by one of ordinary skill in the art to which this invention pertains. The terms "first," "second," and similar terms used in this invention do not indicate any order, quantity, or importance, but are merely used to distinguish different components. Terms such as "comprising" or "including" mean that the element or object preceding the word encompasses the elements or objects listed following the word and their equivalents, without excluding other elements or objects. Terms such as "connected" or "linked" are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. Terms such as "upper," "lower," "left," and "right" are used only to indicate relative positional relationships; when the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0022] like Figure 1 As shown, a power metering device for a power supply company includes: a current transformer, a voltage transformer, and a power meter. The current transformer is connected to the current terminal of the power meter, and the voltage transformer is connected to the voltage terminal of the power meter. The power metering device also includes a first temperature monitoring unit for monitoring the operating temperature of the current transformer and the voltage transformer, a second temperature monitoring unit for detecting the ambient temperature, a data filtering module for matching the current ambient temperature obtained by the second temperature monitoring unit with the current load obtained by the power meter and the historical database to obtain a filtered data set, a data processing module for calculating a dynamic baseline upper limit value based on the filtered data set, a status judgment module for judging the status based on the dynamic baseline upper limit value and the current operating temperature of the current transformer and the voltage transformer obtained by the first temperature monitoring unit, and an early warning module for generating and outputting a health status warning information for the current transformer and the voltage transformer if the current operating temperature exceeds the dynamic baseline upper limit value.

[0023] This energy metering device includes current transformers, voltage transformers, and an energy meter, which are interconnected to achieve basic energy metering functions. Simultaneously, a first temperature monitoring unit monitors the operating temperatures of the current and voltage transformers, while a second temperature monitoring unit detects the ambient temperature. A historical database of transformer operating temperatures under different ambient temperatures and loads is established based on historical normal data. A data filtering module filters matching data from the historical database based on the current ambient temperature and the current load obtained from the energy meter, resulting in a filtered data set. A data processing module calculates the dynamic baseline upper limit based on the filtered data set. A status judgment module compares the current transformer operating temperature with the dynamic baseline upper limit to determine the status. If the current operating temperature exceeds the upper limit, an early warning module generates and outputs a health status warning message.

[0024] The power metering device for power supply companies provided by this invention, by introducing multi-parameter sensing and dynamic baseline analysis technology, produces the following significant advantages compared to traditional fixed threshold alarm systems: 1. It greatly improves the accuracy and reliability of early warning, and effectively reduces false alarms and missed alarms.

[0025] Traditional methods use fixed temperature thresholds for alarms, leading to frequent false alarms in summer or under high loads, and potential missed alarms in winter. This invention establishes a dynamic baseline that considers ambient temperature and load current, enabling the system to automatically identify the normal temperature range of the equipment under specific operating conditions. An alarm is only triggered when the equipment temperature deviates from its historical normal performance under the same environment and load. This is equivalent to "tailor-making" an alarm threshold for each piece of equipment and each operating state, thus eliminating interference from non-fault-related factors and ensuring that the alarm signal truly points to potential equipment faults, greatly improving accuracy.

[0026] 2. It enables early and predictive diagnosis of equipment health status, transforming "post-event maintenance" into "pre-event early warning".

[0027] Traditional methods typically only trigger alarms after equipment temperature has reached dangerous levels or a malfunction has occurred (such as smoke or burnout), allowing only reactive repairs after damage has already taken place. The advantages of this invention: The dynamic baseline, based on historical normal data, can sensitively detect subtle abnormal temperature changes in equipment. For example, when equipment begins to slowly heat up due to poor internal contact, its temperature may not yet have reached an absolutely dangerous level, but it is already significantly higher than its normal level under similar conditions. The system can issue early warnings at the early stages of a fault, providing maintenance personnel with a valuable intervention window, thus preventing the fault from escalating and enabling predictive maintenance. Current transformers and voltage transformers are key devices for electricity metering and grid protection; their failures can lead to inaccurate metering or malfunctioning / failed protection, affecting grid safety. This invention ensures the continuous and stable operation of these devices by detecting and warning of potential defects in advance, thereby avoiding power outages or safety accidents caused by metering device failures and improving the reliability and security of the entire distribution network.

[0028] In some embodiments, the matching method of the filtering module includes filtering historical data from the historical database that are in the same time period and whose load parameters are in the same load range, based on the current ambient temperature obtained by the second temperature monitoring unit and the current load obtained by the electricity meter.

[0029] When matching data, the filtering module uses the current ambient temperature obtained by the second temperature monitoring unit and the current load obtained by the energy meter to filter historical data from the historical database that are the same as the current time period and whose load parameters are within the same load range. This matching method can more accurately filter historical data similar to the current operating conditions, making the filtered data set more valuable for reference, thereby improving the accuracy of the dynamic baseline upper limit calculation and thus enhancing the reliability of the status judgment.

[0030] In some embodiments, the same time period is a predetermined time tolerance range centered on the current time. Defining the same time period as a predetermined time tolerance range centered on the current time, such as a certain time interval before and after the current time, takes into account the fluctuations and changes in time during actual operation, avoiding insufficient matching data due to strict time consistency, and ensuring that the selected data better reflects the normal situation under the current operating conditions, thereby enhancing the representativeness and usability of the data.

[0031] In some embodiments, the method for determining whether the load parameters are in the same load range is as follows: the range of load parameters is divided into several consecutive intervals, and the current load parameters and historical load parameters falling into the same interval are considered to be in the same load range.

[0032] The load parameter range is divided into several continuous intervals, for example, dividing the load parameters from low to high into multiple smaller intervals. When determining whether the current load parameter and historical load parameters are in the same load range, they are considered to be in the same load range if they fall into the same predefined smaller interval. This simplifies the comparison of load parameters, avoids precise matching of load parameters, improves the efficiency and operability of data filtering, and can better reflect the impact of the load on the operating temperature of the current transformer.

[0033] In some embodiments, the calculation method of the data processing module includes: calculating the mean and standard deviation of the historical data set, and generating a dynamic baseline upper limit value based on the mean and standard deviation, wherein the dynamic baseline upper limit value is the mean plus N times the standard deviation, and N is a real number greater than 2.

[0034] The data processing module calculates the mean and standard deviation of the filtered historical data set, and then generates a dynamic baseline upper limit based on the mean and standard deviation. The dynamic baseline upper limit is the mean plus N times the standard deviation, where N is a real number greater than 2. The mean and standard deviation reflect the central tendency and dispersion of the data. Calculating the dynamic baseline upper limit in this way can accommodate the normal fluctuation range of the transformer's operating temperature under different operating conditions, and more scientifically and rationally determine the warning threshold.

[0035] Optionally, the value of N is 3. In statistics, approximately 99.7% of the data will fall within the range of the mean plus or minus 3 standard deviations. Choosing N = 3 can better cover the normal operating temperature range, while also having high sensitivity to abnormal temperatures, effectively balancing false alarms and false negatives.

[0036] In some embodiments, the data processing module further includes continuously acquiring temperature data of the operating temperatures of the current transformer and voltage transformer at a predetermined sampling frequency, and calculating the temperature change slope of the current stage based on the latest acquired temperature data sequence. The state determination module further includes comparing the calculated temperature change slope with a predetermined slope threshold for determination. The early warning module also includes generating and outputting a predictive early warning message if the slope of the temperature change exceeds the predetermined slope threshold. The predictive early warning message is used to indicate that the device is at risk of overheating in the future due to accelerated temperature changes.

[0037] The data processing module continuously acquires temperature data of the current transformer and voltage transformer at a predetermined sampling frequency. Based on the latest acquired temperature data sequence, it calculates the temperature change slope for the current stage. The status judgment module compares the calculated temperature change slope with a predetermined slope threshold. If the temperature change slope exceeds the predetermined slope threshold, the early warning module generates and outputs a predictive early warning, indicating that the equipment is at risk of overheating due to accelerated temperature changes. By continuously calculating and analyzing the temperature change slope, a sudden increase in the predicted slope (accelerated temperature rise) is a signal of extremely high risk. The system can issue a predictive early warning when the temperature has not yet reached the danger threshold but has already shown an abnormal accelerated upward trend, meaning that the fault may have progressed from quantitative to qualitative change. This provides maintenance personnel with a much longer response and intervention time window than static early warnings, achieving "early detection and early handling."

[0038] In some embodiments, the secondary sides of the current transformer and voltage transformer are each equipped with a data acquisition module. The dielectric loss tangent is calculated based on the current and voltage data obtained by the data acquisition module. The device also includes a fault analysis generation module. When the fault analysis generation module detects that the current operating temperature exceeds the upper limit of the dynamic temperature baseline established for it, it obtains the real-time load current value of the device through the energy meter and compares the real-time load current value with the rated value. If it exceeds the rated value, it generates a first diagnostic conclusion that the temperature abnormality is caused by overload. If the real-time load current value does not exceed the rated value, it determines whether the dielectric loss tangent exceeds a predetermined value. If it does, it generates a second diagnostic conclusion that the temperature abnormality is caused by the internal insulation deterioration of the equipment.

[0039] The secondary side of the current transformer and voltage transformer is equipped with a data acquisition module, which can acquire current and voltage data and calculate the dielectric loss tangent. When the monitored current operating temperature exceeds the upper limit of the established dynamic temperature baseline, the fault analysis generation module obtains the real-time load current value of the device through the energy meter and compares it with the rated value. If it exceeds the rated value, a first diagnostic conclusion is generated, i.e., the temperature abnormality is caused by overload. If it does not exceed the rated value, it is determined whether the dielectric loss tangent exceeds a predetermined value. If it does, a second diagnostic conclusion is generated, i.e., the temperature abnormality is caused by internal insulation degradation of the equipment. By comprehensively analyzing the real-time load current and dielectric loss tangent, the cause of the temperature abnormality can be determined, providing maintenance personnel with detailed fault information, which helps to quickly locate the problem and take targeted maintenance measures, thereby improving maintenance efficiency and equipment reliability.

[0040] In some embodiments, the device further includes a backup heat dissipation mechanism. If the dielectric loss tangent does not exceed a predetermined value, the device acquires the current operating temperature data of neighboring similar devices. If the current operating temperature of the neighboring similar devices all exceeds the upper limit of the dynamic temperature baseline, a third diagnostic conclusion is generated that the temperature abnormality is caused by shared environmental factors, and the backup heat dissipation mechanism is activated.

[0041] When the dielectric loss tangent does not exceed a predetermined value, the device acquires the current operating temperature data of nearby similar equipment. If the current operating temperature of all nearby similar equipment exceeds the upper limit of the dynamic temperature baseline, the fault analysis generation module generates a third diagnostic conclusion, namely that the temperature anomaly is caused by shared environmental factors, and activates the backup cooling mechanism. This further eliminates temperature anomalies caused by the equipment itself, accurately determines that the problem is caused by shared environmental factors, and promptly activates the backup cooling mechanism to improve the equipment's working environment, ensure normal equipment operation, and avoid equipment failure due to environmental factors.

[0042] The present invention also provides a method for predicting the health of power metering devices in power supply companies, the method comprising: Based on historical normal data, a historical database of the operating temperatures of current transformers and voltage transformers under different loads at different ambient temperatures was established. Based on the current ambient temperature obtained by the second temperature monitoring unit, the current load obtained by the electricity meter is matched with the historical database to obtain a filtered data set; The upper limit of the dynamic baseline is calculated based on the filtered dataset; The status is determined based on the upper limit of the dynamic baseline and the current operating temperatures of the current transformer and voltage transformer obtained by the first temperature monitoring unit. If the current operating temperature exceeds the upper limit of the dynamic baseline, a health status warning message for the current transformer and voltage transformer will be generated and output.

[0043] This method establishes a dynamic baseline that considers ambient temperature and load current, enabling the system to automatically identify the normal temperature range of equipment under specific operating conditions. An alarm is only triggered when the equipment temperature deviates from its historical normal performance under the same environment and load. This is equivalent to "tailor-making" an alarm threshold for each piece of equipment and each operating state, thereby eliminating interference from non-faulty factors and ensuring that the alarm signal truly points to potential equipment failures, greatly improving accuracy.

[0044] Those skilled in the art should understand that the discussion of any of the above embodiments is merely exemplary and is not intended to imply that the scope of the invention (including the claims) is limited to these examples; within the framework of the invention, the technical features of the above embodiments or different embodiments can also be combined, the steps can be implemented in any order, and there are many other variations of the different aspects of the invention as described above, which are not provided in the details for the sake of brevity.

[0045] This invention is intended to cover all such substitutions, modifications, and variations that fall within the broad scope of the appended claims. Therefore, any omissions, modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. An electricity metering device for power supply companies, characterized in that, include: The device includes a current transformer, a voltage transformer, and an energy meter. The current transformer is connected to the current terminal of the energy meter, and the voltage transformer is connected to the voltage terminal of the energy meter. The energy metering device also includes a first temperature monitoring unit for monitoring the operating temperature of the current transformer and voltage transformer, a second temperature monitoring unit for detecting the ambient temperature, a historical database of the operating temperatures of the current transformer and voltage transformer under different loads at different ambient temperatures based on historical normal data, a data filtering module that matches the current ambient temperature obtained by the second temperature monitoring unit with the current load obtained by the energy meter and the historical database to obtain a filtered data set, a data processing module that calculates a dynamic baseline upper limit value based on the filtered data set, a status judgment module that judges the status based on the dynamic baseline upper limit value and the current operating temperature of the current transformer and voltage transformer obtained by the first temperature monitoring unit, and an early warning module that generates and outputs a health status warning information for the current transformer and voltage transformer if the current operating temperature exceeds the dynamic baseline upper limit value.

2. The power metering device for power supply enterprises according to claim 1, characterized in that, The matching method of the filtering module includes filtering historical data from the historical database that are in the same time period and whose load parameters are in the same load range, based on the current ambient temperature obtained by the second temperature monitoring unit and the current load obtained by the electricity meter.

3. The power metering device for power supply enterprises according to claim 1, characterized in that, The same time period is a predetermined time tolerance range centered on the current time.

4. The power metering device for power supply enterprises according to claim 1, characterized in that, The method for determining whether the load parameters are in the same load range is as follows: the range of load parameters is divided into several consecutive intervals, and the current load parameters and historical load parameters falling into the same interval are considered to be in the same load range.

5. The power metering device for power supply enterprises according to claim 1, characterized in that, The calculation method of the data processing module includes: calculating the mean and standard deviation of the historical data set, and generating a dynamic baseline upper limit value based on the mean and standard deviation, wherein the dynamic baseline upper limit value is the mean plus N times the standard deviation, and N is a real number greater than 2.

6. The power metering device for power supply enterprises according to claim 5, characterized in that, The value of N is 3.

7. The power metering device for power supply enterprises according to claim 1, characterized in that, The data processing module also includes continuously acquiring temperature data of the operating temperature of the current transformer and voltage transformer at a predetermined sampling frequency, and calculating the temperature change slope of the current stage based on the latest acquired temperature data sequence. The state determination module further includes comparing the calculated temperature change slope with a predetermined slope threshold for determination. The early warning module also includes generating and outputting a predictive early warning message if the slope of the temperature change exceeds the predetermined slope threshold. The predictive early warning message is used to indicate that the device is at risk of overheating in the future due to accelerated temperature changes.

8. The power metering device for power supply enterprises according to claim 1, characterized in that, Both the current transformer and the voltage transformer are equipped with data acquisition modules on their secondary sides. Based on the current and voltage data obtained by the data acquisition modules, the dielectric loss tangent is calculated. The device also includes a fault analysis generation module. When the fault analysis generation module detects that the current operating temperature exceeds the upper limit of the dynamic temperature baseline established for it, it obtains the real-time load current value of the device through the energy meter and compares the real-time load current value with the rated value. If it exceeds the rated value, it generates a first diagnostic conclusion that the temperature abnormality is caused by overload. If the real-time load current value does not exceed the rated value, it determines whether the dielectric loss tangent exceeds a predetermined value. If it does, it generates a second diagnostic conclusion that the temperature abnormality is caused by the internal insulation deterioration of the equipment.

9. A power metering device for power supply enterprises according to claim 8, characterized in that, The device also includes a backup heat dissipation mechanism. If the dielectric loss tangent does not exceed a predetermined value, the device acquires the current operating temperature data of nearby similar devices. If the current operating temperature of the nearby similar devices all exceeds the upper limit of the dynamic temperature baseline, a third diagnostic conclusion is generated that the temperature abnormality is caused by shared environmental factors, and the backup heat dissipation mechanism is activated.

10. A method for predicting the health of an electricity metering device for a power supply company according to claim 1, characterized in that, The method includes: Based on historical normal data, a historical database of the operating temperatures of current transformers and voltage transformers under different loads at different ambient temperatures was established. Based on the current ambient temperature obtained by the second temperature monitoring unit, the current load obtained by the electricity meter is matched with the historical database to obtain a filtered data set; The upper limit of the dynamic baseline is calculated based on the filtered dataset; The status is determined based on the upper limit of the dynamic baseline and the current operating temperatures of the current transformer and voltage transformer obtained by the first temperature monitoring unit. If the current operating temperature exceeds the upper limit of the dynamic baseline, a health status warning message for the current transformer and voltage transformer will be generated and output.

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