Intelligent electric energy meter with high protection level

Abstract

The invention provides a high-protection-level intelligent electric energy meter, and relates to the technical field of electric energy meter protection. The electric energy meter is configured to obtain historical dustproof big data of electric meters of the same type to form dustproof performance feature data; acquiring historical waterproof big data of the same type of electricity meters to form waterproof performance characteristic data; acquiring historical comprehensive protection big data of the same type of electricity meters, and performing comprehensive correlation analysis in combination with the dustproof performance feature data and the waterproof performance feature data to form comprehensive protection performance feature data; and collecting real-time protection information, and performing real-time protection monitoring analysis in combination with the comprehensive protection performance characteristic data to form real-time protection monitoring result data. According to the intelligent electric energy meter, a close relationship between periodic maintenance and operation parameter change of the intelligent electric energy meter is established through dustproof and waterproof intelligent meter maintenance big data, so that the intelligent electric energy meter is timely and efficiently protected, and long-term stable and efficient operation of the intelligent electric energy meter is effectively ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of electric energy meter protection, and in particular to an intelligent electric energy meter with a high protection level. Background Art

[0002] Smart meters are equipped with various data collection and processing units for collecting electricity usage information. These functional units also require a suitable environment to ensure efficient and sustained operation. Dust and water resistance are important parameters for evaluating the protection performance of smart meters. After all, the accumulation of dust, moisture, and even water can significantly affect the operation of smart meters and the accuracy of data collection and analysis.

[0003] Currently, most smart meters are dust- and water-resistant by implementing strict sealing techniques and regular cleaning and maintenance on the meter housing. However, the housing seal degrades over time due to aging, and improper cleaning and maintenance can significantly impact the efficiency of smart meters.

[0004] Therefore, designing a smart electricity meter with a high protection level, establishing a close relationship between periodic maintenance and changes in the operating parameters of the smart electricity meter through smart meter maintenance big data based on dustproof and waterproof properties, and achieving timely and efficient protection of the smart electricity meter, effectively ensuring that the smart electricity meter can operate stably and efficiently in the long term, is an urgent problem to be solved. Summary of the Invention

[0005] The purpose of the present invention is to provide a smart electricity meter with a high protection level. By acquiring dust removal big data, the characteristic relationship between the operating parameters affected by protection factors and the dust removal change amount of the smart electricity meter under periodic operation is established. At the same time, the water removal big data is also acquired to establish the characteristic relationship between the operating parameters affected by protection factors and the water removal change amount of the smart electricity meter under periodic operation, and the comprehensive big data of dust removal and water removal are analyzed and processed. On the basis of combining the dust removal performance characteristic data and the water removal performance characteristic data, basic reference data for dust removal and water removal protection analysis is formed. Then, when real-time monitoring data is obtained, reasonable dust removal and water removal information can be determined according to the changes in the operating performance of the smart electricity meter. In this way, periodic maintenance of the smart electricity meter can be achieved while minimizing ineffective dust removal and water removal treatments, ensuring efficient protection of the smart electricity meter, and enabling the smart electricity meter to operate efficiently and stably for a long time.

[0006] In a first aspect, the present invention provides a high-protection-level smart electricity meter, which is configured to: obtain historical dust-proof big data of the same type of electricity meter, perform dust-proof feature analysis based on a single factor, and form dust-proof performance feature data; obtain historical waterproof big data of the same type of electricity meter, perform waterproof feature analysis based on a single factor, and form waterproof performance feature data; obtain historical comprehensive protection big data of the same type of electricity meter, and combine the dust-proof performance feature data and the waterproof performance feature data to perform comprehensive correlation analysis to form comprehensive protection performance feature data; collect real-time protection information, and perform real-time protection monitoring analysis in combination with the comprehensive protection performance feature data to form real-time protection monitoring result data.

[0007] In the present invention, the electric energy meter obtains dust removal big data to establish the characteristic relationship between the operating parameters affected by protection factors and the dust removal change amount under the periodic operation of the smart electric energy meter, and also obtains water removal big data to establish the characteristic relationship between the operating parameters affected by protection factors and the water removal change amount under the periodic operation of the smart electric energy meter, and analyzes and processes the comprehensive big data of dust removal and water removal. On the basis of combining the dust removal performance characteristic data and the water removal performance characteristic data, basic reference data for dust removal and water removal protection analysis is formed, and then, when real-time monitoring data is obtained, reasonable dust removal and water removal information can be determined based on the changes in the operating performance of the smart electric energy meter. In this way, periodic maintenance of the smart electric energy meter can be achieved while minimizing ineffective dust removal and water removal treatments, ensuring efficient protection of the smart electric energy meter, and thus enabling the smart electric energy meter to operate efficiently and stably for a long time.

[0008] As a possible implementation method, historical dust protection big data of the same type of electric meters is obtained, and dust protection feature analysis based on a single factor is performed to form dust protection performance feature data, including: determining protection analysis operating parameters and setting the minimum impact correlation D min Based on historical dust prevention big data, determine the changes in different protection analysis operating parameters before and after completing dust prevention maintenance in each protection cycle And determine the corresponding periodic dust protection correlation D k , n represents the number of different protection analysis running parameters, k represents the number of different protection cycles, α n Represents the dust protection correlation factor of different protection analysis operating parameters; according to the minimum impact correlation D min Correlation between periodic dust protection and different protection periods D k , determine D k >D min The protection period is calibrated as the dust impact protection period, and the operation characteristic information of the dust impact protection period based on dust prevention processing is extracted to form dust prevention performance characteristic data.

[0009] In the present invention, when extracting and analyzing dust-proof performance characteristic data, not all dust-proof data can be used for feature information extraction for historical dust-proof big data. Data with significant changes in protection analysis operating parameters before and after dust removal are required to analyze and extract reasonable and accurate feature information. Therefore, before analyzing and extracting dust-proof performance characteristic data, it is necessary to reasonably screen and extract the dust-proof big data to ensure that the feature information obtained during subsequent feature analysis and extraction is more accurate and reasonable. Here, considering that the effect of dust removal will affect multiple different operating parameters on the smart electric energy meter, the relative change values ​​of these operating parameters before and after dust removal are used as a reference, a comprehensive correlation analysis is performed to determine whether the corresponding dust removal operation can achieve a significant dust removal protection effect and improve the operating efficiency and analysis and processing accuracy of the smart electric energy meter. It's important to note that different operating parameters are affected differently by dust accumulation. That is, the degree of significant improvement in different operating parameters after dust removal varies, but all are positive and effective improvements. Therefore, a minimum impact correlation can be used for comparison to evaluate and determine whether dust removal has been effective. This allows for accurate and reasonable screening of dust prevention big data with significant characteristic information. The minimum impact correlation can be set based on actual needs or determined based on correlation-based big data analysis. Of course, for dust prevention data, the operating status of smart meters is also a significant factor in dust accumulation. From a macro perspective, the operating status of smart meters varies regularly depending on the power consumption habits of consumers on the power supply line. Therefore, the effectiveness of dust removal varies at different stages of this regular change. Therefore, the data in dust prevention big data also uses this regular change to determine the dust prevention cycle, making the dust prevention data within that cycle more characteristic. Each protection cycle in the big data contains rich dust removal information and corresponding operating parameter change information. By extracting characteristic information from this big data within each protection cycle, reasonable and accurate dust prevention feature information can be obtained.

[0010] As a possible implementation method, the dust protection effect protection period is subjected to the dust protection treatment-based operation characteristic information extraction to form the dust protection performance characteristic data, including: determining the dust accumulation amount G corresponding to the dust protection maintenance in each dust protection effect protection period. m and dust removal capacity C m , and form the corresponding dust protection level value E m ,in, m represents the number of different dust protection protection cycles; set the dust protection maintenance level to affect the stage quantity, and according to different dust protection maintenance level values ​​E m, cluster the dust impact protection cycle into different stages to form different dust impact stage cycle sets; for different dust impact stage cycle sets, the change of different protection analysis operating parameters under each dust impact protection cycle is analyzed. And dust protection level value Establish the following periodic dust protection formula: Where y is the number of the different dust impact stage period set, x is the number of the different dust impact protection period corresponding to the dust impact stage period set numbered y, i is the number of power terms and i ≥ 1, It represents the power constant corresponding to different protection analysis operation parameters of different dust protection periods under different dust protection stage cycle sets, It represents the power value of different protection analysis operation parameters of different dust protection periods under different dust protection stage cycle sets. It represents the dustproof constant term of the dustproof protection period numbered x corresponding to the dustproof impact stage period set numbered y; according to the different periodic dustproof formulas in the dustproof impact stage period set, the periodic dustproof characteristic formula corresponding to the dustproof impact stage period set is determined: Among them, E y Indicates the characteristic dust protection maintenance degree value corresponding to the dust protection impact stage cycle set numbered y, It represents the power value of the protection analysis operation parameter numbered n corresponding to the dust protection impact stage cycle set numbered y, raised to the power of i. It represents the characteristic power value of the protection analysis operation parameter numbered n under the dust protection impact stage cycle set numbered y, and the power item number i corresponds to it. It represents the characteristic dustproof constant corresponding to the dustproof impact stage period set numbered y; the periodic dustproof characteristic formulas corresponding to all dustproof impact stage period sets are collected to form the dustproof performance characteristic data.

[0011] In the present invention, after filtering out the dust-proof big data with obvious dust removal effect, the main thing is how to reasonably extract the dust-proof feature information. Considering the dust-proof data obtained under different periods, although the connection between the operating parameter changes and the dust removal information can be directly established based on the operating parameters, there are two considerations. On the one hand, the dust removal amount and the dust removal effect under the same regular period will actually have a certain deviation. Therefore, by expanding the dust-proof formula based on the power, it can be avoided to a certain extent that although the dust-proof formula belongs to the same dust-proof influence stage period set, it cannot achieve effective and accurate comprehensive fitting. Therefore, the selection of the power term can be based on the largest power term corresponding to the dust-proof influence stage period set. The expansion is based on the Taylor series to form a unified power feature formula, and then form a dust-proof feature formula corresponding only to the dust-proof influence stage period set. Here, for the feature formulas corresponding to different protection periods under the same dust-proof influence stage period set, the final periodic dust-proof feature formula can be formed by mutual function fitting, or the periodic dust-proof feature formula can be formed by extracting the limit boundary. In addition, the dust prevention characteristic data is mainly based on the change of the operating parameters before and after dust removal, so the dust prevention characteristic formula is determined by the relative dust removal percentage.

[0012] As a possible implementation method, historical waterproof big data of the same type of electric meters is obtained, and waterproof feature analysis based on a single factor is performed to form waterproof performance feature data, including: based on historical waterproof big data, determining the change in different protection analysis operating parameters before and after completing waterproof maintenance in each protection cycle And determine the corresponding periodic waterproof correlation W k , n represents the number of different protection analysis running parameters, k represents the number of different protection cycles, γ n Represents the waterproof correlation factor of different protection analysis operating parameters; according to the minimum impact correlation D min Correlation between different protection periods and waterproof period W k , determine W k >D min The protection period is calibrated as the waterproof impact protection period, and the operation characteristic information of the waterproof impact protection period based on the waterproof treatment is extracted to form the waterproof performance characteristic data.

[0013] In the present invention, similarly, when extracting waterproof performance characteristic information from large data sets that have only undergone waterproofing treatment over a period of time, screening is performed based on the minimum impact correlation to identify waterproofing large data sets with significant and effective characteristic information. It is understandable that for the minimum impact correlation, operating parameters may be consistent between dustproofing and waterproofing treatments, i.e., the operating parameters affected by dustproofing and waterproofing are the same. Therefore, the minimum impact correlation can be the same when extracting and analyzing characteristic information for dustproofing and waterproofing, or it can be further refined based on the differences in protection, thereby improving the rationality and accuracy of the large data screening process.

[0014] As a possible implementation method, the operation characteristic information of the waterproofing protection cycle is extracted based on the waterproofing treatment to form waterproofing performance characteristic data, including: determining the amount of accumulated water S corresponding to each waterproofing protection cycle when waterproofing maintenance is performed m and water removal J m , and form the corresponding waterproof maintenance level value R m ,in, m represents the number of different waterproof protection cycles; set the waterproof maintenance level to affect the stage quantity, and according to different waterproof maintenance level values ​​R m , cluster the impact stages of the waterproof impact protection cycle to form different waterproof impact stage cycle sets; the change amount of different protection analysis operation parameters under each waterproof impact protection cycle in different waterproof impact stage cycle sets And waterproof protection level Establish the following cycle waterproofing formula: Where z is the number of different waterproof impact stage cycle sets, t is the number of different waterproof impact protection periods corresponding to the waterproof impact stage cycle set numbered z, e is the number of power terms and e≥1, Indicates the power constant corresponding to different protection analysis operation parameters of different waterproof impact protection periods under different waterproof impact stage cycle sets, It represents the power value of different protection analysis operation parameters of different waterproof impact protection periods under different waterproof impact stage cycle sets, It represents the waterproof constant term of the waterproof protection period numbered t corresponding to the waterproof impact stage period set numbered z; according to the different periodic waterproof formulas in the waterproof impact stage period set, the periodic waterproof characteristic formula corresponding to the waterproof impact stage period set is determined: Among them, E z Indicates the characteristic waterproof maintenance degree value corresponding to the waterproof impact stage cycle set numbered z, It represents the power value of the protection analysis operation parameter numbered n corresponding to the waterproof impact stage cycle set numbered z, with the next power term numbered e. It represents the characteristic power value of the protection analysis operation parameter numbered n under the waterproof impact stage cycle set numbered z, with the power term number e corresponding to it. Represents the characteristic waterproof constant corresponding to the waterproof impact stage cycle set numbered z; collects the periodic waterproof characteristic formulas corresponding to all waterproof impact stage cycle sets to form waterproof performance characteristic data.

[0015] In the present invention, the extraction and analysis of the characteristic data of the waterproof performance is also carried out in periods based on the regular changes of the smart electric energy meter. The characteristic formulas corresponding to all protection periods under the same waterproof impact stage period set have close correlation and consistency of relationship, so after processing and analysis, the characteristic formula under the corresponding waterproof impact stage period can be formed, so that the characteristic formula has obvious and accurate representativeness. Here, when dividing the waterproof impact stage period set, the stage quantity of the waterproof maintenance degree can be determined according to the actual situation, or it can be determined based on big data analysis. Similarly, the stage quantity of the dustproof maintenance degree can be determined according to the actual situation, or it can be determined based on big data analysis.

[0016] As a possible implementation method, the historical comprehensive protection big data of the same type of electric meters is obtained, and the dustproof performance characteristic data and waterproof performance characteristic data are combined to perform a comprehensive correlation analysis to form comprehensive protection performance characteristic data, including: determining the comprehensive dustproof maintenance degree value P before and after each comprehensive protection based on the historical comprehensive protection big data u , Comprehensive waterproof protection level value Q u And the comprehensive changes corresponding to different protection analysis operating parameters u represents the number of different comprehensive protection maintenance cycles; according to the comprehensive dust protection maintenance level value P u , determine the corresponding periodic dustproof characteristic formula, and calibrate it as the comprehensive protection potential dustproof characteristic formula According to the comprehensive waterproof maintenance value Q u , determine the corresponding periodic waterproof characteristic formula, and calibrate it as the comprehensive protection potential waterproof characteristic formula For each comprehensive protection maintenance cycle, the comprehensive changes corresponding to the operating parameters of different protection analysis are analyzed Comprehensive protection potential dustproof feature And comprehensive protection potential waterproof feature Conduct comprehensive protection feature analysis to form corresponding comprehensive protection feature information.

[0017] In the present invention, of course, protective treatment applies not only to cases where only dust removal or only water removal is performed, but also to cases where both dust removal and water removal are performed simultaneously. Regarding operating parameters, the combined effect of dust removal and water removal is not necessarily a linear combination of the characteristic information corresponding to the dust removal and water removal processes performed independently. Therefore, it is necessary to extract and analyze characteristic information for comprehensive protective performance. This analysis ensures that the extracted comprehensive protective characteristic information has wide applicability, covering both cases where individual protective treatments are performed independently and cases where protective treatments are combined.

[0018] As a possible implementation method, for each comprehensive protection maintenance cycle, the comprehensive change corresponding to different protection analysis operating parameters is combined Comprehensive protection potential dustproof feature And comprehensive protection potential waterproof feature Conduct comprehensive protection feature analysis to form corresponding comprehensive protection feature information, including: if there are different comprehensive dust protection constants for all comprehensive maintenance protection cycles and comprehensive waterproof constant Make the comprehensive changes corresponding to different protection analysis operating parameters Introducing comprehensive protection potential dustproof feature And comprehensive protection potential waterproof feature After that, Eq. If the dustproof performance characteristic data and waterproof performance characteristic data are combined to form comprehensive protection characteristic information, if for all comprehensive protection maintenance cycles: there are comprehensive protection maintenance cycles that cannot meet the requirements of the determined comprehensive dustproof constant. and comprehensive waterproof constant Make the comprehensive changes corresponding to different protection analysis operating parameters Introducing comprehensive protection potential dustproof feature And comprehensive protection potential waterproof feature After that, Eq. If it is established, the deviation L corresponding to the comprehensive protection maintenance cycle is determined u ,in, And set the deviation threshold to make the following analysis and judgment: When L u If both do not exceed the deviation threshold, the dustproof performance characteristic data and waterproof performance characteristic data are collected to form comprehensive protection characteristic information; when there is L u When the deviation threshold is exceeded, comprehensive protection independent feature analysis is performed to form comprehensive protection feature information.

[0019] In the present invention, the key to obtaining comprehensive protection feature information is determining whether the effects of individual protection treatments are linearly superimposed on the overall protection. Therefore, when extracting comprehensive protection feature information, the power characteristics of the characteristic formula can more intuitively determine whether the comprehensive protection treatment is a linear superposition of individual feature information. In cases where there is no constant that allows the superposition of individual feature information to form comprehensive feature information, the necessity of extracting supplementary feature information is determined by determining the difference resulting from this superposition.

[0020] As a possible implementation method, when there is L u When the deviation threshold is exceeded, the independent feature analysis of comprehensive protection is performed to form comprehensive protection feature information, including: for different comprehensive protection maintenance cycles: according to the comprehensive dust protection maintenance degree value P u , Comprehensive waterproof protection level value Q u , the comprehensive changes corresponding to different protection analysis operating parameters And the corresponding comprehensive protection potential dustproof characteristic formula and comprehensive protection potential waterproof characteristic formula Establish the following characteristic formula:

[0021] in, It represents the periodic comprehensive supplementary characteristic formula corresponding to the comprehensive protection maintenance cycle numbered u, v represents the comprehensive supplementary power number and v≥1, The power constant representing the comprehensive change of the protection analysis operating parameter numbered n under the comprehensive protection maintenance cycle numbered u when the next power is v. It represents the power value of the protection analysis operation parameter numbered n in the comprehensive protection maintenance cycle numbered u. Indicates the periodic comprehensive supplement constant corresponding to the comprehensive protection and maintenance cycle numbered u; the periodic comprehensive supplement characteristic formula corresponding to different comprehensive protection and maintenance cycles is Perform homogenization fitting to form a comprehensive supplementary characteristic formula Collects dustproof performance characteristic data, waterproof performance characteristic data and all comprehensive supplementary characteristic formulas Form comprehensive protection feature information.

[0022] In the present invention, when single protection feature information cannot be linearly superimposed to form comprehensive protection feature information, the feature information can be directly used to extract and analyze supplementary feature information. This can intuitively show the difference between comprehensive protection and single protection processing, and on the other hand, it can also quickly and directly determine reasonable comprehensive supplementary feature information.

[0023] As a possible implementation method, real-time protection information is collected, and real-time protection monitoring and analysis is performed in combination with comprehensive protection performance characteristic data to form real-time protection monitoring result data, including: obtaining the real-time operating range of different protection analysis operating parameters and periodically collecting the corresponding real-time operating values; determining the corresponding real-time change amount based on the real-time operating values ​​of different protection analysis operating parameters and the corresponding real-time operating range; determining the real-time dust removal reference amount and the real-time water removal reference amount based on the real-time change amount of different protection analysis operating parameters and the comprehensive protection characteristic information.

[0024] In the present invention, of course, after obtaining the comprehensive protection feature information, the dust removal amount and water removal amount can be determined quickly and efficiently in combination with real-time monitoring data, thereby avoiding the situation where multiple maintenances are ineffective and cause increased maintenance costs and reduced working efficiency of smart electricity meters.

[0025] As a possible implementation method, the real-time dust removal reference amount and the real-time water removal reference amount are determined based on the real-time changes in different protection analysis operating parameters and the comprehensive protection characteristic information, including: applying different protection analysis operating parameters to different periodic dust prevention characteristic formulas and periodic water prevention characteristic formulas, and determining different real-time dust removal amount and real-time water removal amount combinations based on the real-time dust accumulation amount and the real-time water accumulation amount, and determining the combination with the smallest sum of the real-time dust removal amount and the real-time water removal amount as the corresponding real-time dust removal reference amount and real-time water removal reference amount.

[0026] In the present invention, it is understood that it is necessary for a smart energy meter to be able to maintain its current operating state without performing protective processing. Therefore, the protective processing of the smart energy meter can be performed or used as a reference with a minimum protective processing amount. After all, the minimum protective processing amount can greatly shorten the protection time, improve the effective working market of the smart energy meter, and ensure that the smart energy meter has a significant improvement in operation after the protective processing.

[0027] The beneficial effects of the high protection level smart electric energy meter provided by the present invention are as follows:

[0028] The electric energy meter obtains dust removal big data to establish the characteristic relationship between the operating parameters affected by protection factors and the dust removal changes under the periodic operation of the smart electric energy meter. At the same time, it also obtains water removal big data to establish the characteristic relationship between the operating parameters affected by protection factors and the water removal changes under the periodic operation of the smart electric energy meter, and analyzes and processes the comprehensive big data of dust removal and water removal. On the basis of combining the dust removal performance characteristic data and the water removal performance characteristic data, basic reference data for dust removal and water removal protection analysis is formed. Then, when real-time monitoring data is obtained, reasonable dust removal and water removal information can be determined according to the changes in the operating performance of the smart electric energy meter. In this way, periodic maintenance of the smart electric energy meter can be achieved while minimizing ineffective dust removal and water removal treatments, ensuring efficient protection of the smart electric energy meter, and thus enabling the smart electric energy meter to operate efficiently and stably for a long time. 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 high-protection-level smart energy meter 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] Smart meters are equipped with various data collection and processing units for collecting electricity usage information. These functional units also require a suitable environment to ensure efficient and sustained operation. Dust and water resistance are important parameters for evaluating the protection performance of smart meters. After all, the accumulation of dust, moisture, and even water can significantly affect the operation of smart meters and the accuracy of data collection and analysis.

[0033] Currently, most smart meters are dust- and water-resistant by implementing strict sealing techniques and regular cleaning and maintenance on the meter housing. However, the housing seal degrades over time due to aging, and improper cleaning and maintenance can significantly impact the efficiency of smart meters.

[0034] refer to Figure 1An embodiment of the present invention provides a high-protection-level smart energy meter, which establishes a characteristic relationship between the operating parameters affected by protection factors and the dust removal change amount under the periodic operation of the smart energy meter by acquiring dust removal big data, and also acquires water removal big data to establish a characteristic relationship between the operating parameters affected by protection factors and the water removal change amount under the periodic operation of the smart energy meter, and analyzes and processes the comprehensive big data of dust removal and water removal, and forms basic reference data for dust removal and water removal protection analysis based on the combination of dust removal performance characteristic data and water removal performance characteristic data, and then, when real-time monitoring data is obtained, reasonable dust removal and water removal information can be determined based on the change in the operating performance of the smart energy meter, so that periodic maintenance of the smart energy meter can be achieved while minimizing ineffective dust removal and water removal treatment, ensuring efficient protection of the smart energy meter, and thus enabling the smart energy meter to operate efficiently and stably for a long time.

[0035] The high protection level smart energy meter is specifically configured as follows:

[0036] S1: Obtain historical dust prevention big data of the same type of electricity meters, perform dust prevention feature analysis based on a single factor, and form dust prevention performance feature data.

[0037] Obtain historical dust protection big data of the same type of electric meters, conduct dust protection feature analysis based on a single factor, and form dust protection performance feature data, including: determining protection analysis operating parameters and setting the minimum impact correlation D min Based on historical dust prevention big data, determine the changes in different protection analysis operating parameters before and after completing dust prevention maintenance in each protection cycle And determine the corresponding periodic dust protection correlation D k , n represents the number of different protection analysis running parameters, k represents the number of different protection cycles, α n Represents the dust protection correlation factor of different protection analysis operating parameters; according to the minimum impact correlation D min Correlation between periodic dust protection and different protection periods D k , determine D k >D min The protection period is calibrated as the dust impact protection period, and the operation characteristic information of the dust impact protection period based on dust prevention processing is extracted to form dust prevention performance characteristic data.

[0038] When extracting and analyzing dust prevention performance characteristic data, not all dust prevention data can be used for feature information extraction for historical dust prevention big data. Data with significant changes in protection analysis operating parameters before and after dust removal are required to analyze and extract reasonable and accurate feature information. Therefore, before analyzing and extracting dust prevention performance characteristic data, it is necessary to reasonably screen and extract the dust prevention big data to ensure that the feature information obtained in subsequent feature analysis and extraction is more accurate and reasonable. Here, considering that the effect of dust removal will affect multiple different operating parameters on the smart energy meter, the relative change values ​​of these operating parameters before and after dust removal are used as a reference to conduct a comprehensive correlation analysis to determine whether the corresponding dust removal operation can achieve a significant dust removal protection effect and improve the operating efficiency and analysis and processing accuracy of the smart energy meter. It's important to note that different operating parameters are affected differently by dust accumulation. That is, the degree of significant improvement in different operating parameters after dust removal varies, but all are positive and effective improvements. Therefore, a minimum impact correlation can be used for comparison to evaluate and determine whether dust removal has been effective. This allows for accurate and reasonable screening of dust prevention big data with significant characteristic information. The minimum impact correlation can be set based on actual needs or determined based on correlation-based big data analysis. Of course, for dust prevention data, the operating status of smart meters is also a significant factor in dust accumulation. From a macro perspective, the operating status of smart meters varies regularly depending on the power consumption habits of consumers on the power supply line. Therefore, the effectiveness of dust removal varies at different stages of this regular change. Therefore, the data in dust prevention big data also uses this regular change to determine the dust prevention cycle, making the dust prevention data within that cycle more characteristic. Each protection cycle in the big data contains rich dust removal information and corresponding operating parameter change information. By extracting characteristic information from this big data within each protection cycle, reasonable and accurate dust prevention feature information can be obtained.

[0039] Extract the operational characteristic information based on dust prevention processing for the dust prevention protection cycle to form dust prevention performance characteristic data, including: determining the amount of dust accumulated during each dust prevention protection cycle corresponding to the dust prevention maintenance G m and dust removal capacity C m , and form the corresponding dust protection level value E m ,in, m represents the number of different dust protection protection cycles; set the dust protection maintenance level to affect the stage quantity, and according to different dust protection maintenance level values ​​E m , cluster the dust impact protection cycle into different stages to form different dust impact stage cycle sets; for different dust impact stage cycle sets, the change of different protection analysis operating parameters under each dust impact protection cycle is analyzed. And dust protection level value Establish the following periodic dust protection formula: Where y is the number of the different dust impact stage period set, x is the number of the different dust impact protection period corresponding to the dust impact stage period set numbered y, i is the number of power terms and i ≥ 1, It represents the power constant corresponding to different protection analysis operation parameters of different dust protection periods under different dust protection stage cycle sets, It represents the power value of different protection analysis operation parameters of different dust protection periods under different dust protection stage cycle sets. It represents the dustproof constant term of the dustproof protection period numbered x corresponding to the dustproof impact stage period set numbered y; according to the different periodic dustproof formulas in the dustproof impact stage period set, the periodic dustproof characteristic formula corresponding to the dustproof impact stage period set is determined: Among them, E y Indicates the characteristic dust protection maintenance degree value corresponding to the dust protection impact stage cycle set numbered y, It represents the power value of the protection analysis operation parameter numbered n corresponding to the dust protection impact stage cycle set numbered y, raised to the power of i. It represents the characteristic power value of the protection analysis operation parameter numbered n under the dust protection impact stage cycle set numbered y, and the power item number i corresponds to it. It represents the characteristic dustproof constant corresponding to the dustproof impact stage period set numbered y; the periodic dustproof characteristic formulas corresponding to all dustproof impact stage period sets are collected to form the dustproof performance characteristic data.

[0040] After selecting dust prevention big data with significant dust removal effects, the main issue is how to properly extract dust prevention feature information. Considering the dust prevention data acquired during different periods, while operating parameter changes can be directly linked to dust removal information based on operating parameters, there are two considerations. First, the actual dust removal amount and dust removal effect within the same regular period will vary. Therefore, expanding the dust prevention formula based on powers can, to a certain extent, avoid the situation where dust prevention formulas belonging to the same dust prevention impact period set cannot achieve an effective and accurate comprehensive fit. Therefore, the power terms can be selected based on the Taylor series expansion of the largest power term corresponding to the dust prevention impact period set to form a unified power feature formula, thereby forming a dust prevention feature formula corresponding only to the dust prevention impact period set. Here, for the feature formulas corresponding to different protection periods within the same dust prevention impact period set, the final periodic dust prevention feature formula can be formed through function fitting between them, or by extracting the limiting boundary to form the periodic dust prevention feature formula. In addition, the dust prevention characteristic data is mainly based on the change of the operating parameters before and after dust removal, so the dust prevention characteristic formula is determined by the relative dust removal percentage.

[0041] S2: Obtain historical waterproof big data of the same type of electricity meters, conduct waterproof feature analysis based on a single factor, and form waterproof performance feature data.

[0042] Obtain historical waterproof big data of the same type of electric meters, conduct waterproof feature analysis based on a single factor, and form waterproof performance feature data, including: Based on historical waterproof big data, determine the change in different protection analysis operating parameters before and after completing waterproof maintenance in each protection cycle And determine the corresponding periodic waterproof correlation W k , n represents the number of different protection analysis running parameters, k represents the number of different protection cycles, γ n Represents the waterproof correlation factor of different protection analysis operating parameters; according to the minimum impact correlation D min Correlation between different protection periods and waterproof period W k , determine W k >D min The protection period is calibrated as the waterproof impact protection period, and the operation characteristic information of the waterproof impact protection period based on the waterproof treatment is extracted to form the waterproof performance characteristic data.

[0043] Similarly, when extracting waterproof performance feature information from large data sets that have only undergone waterproofing treatment over a certain period, screening is performed based on the minimum impact correlation to identify waterproof big data with significant and effective feature information. It is understandable that for the minimum impact correlation, operating parameters may be consistent between dustproofing and waterproofing treatments, meaning that the operating parameters affected by dustproofing and waterproofing are the same. Therefore, the minimum impact correlation can be the same when extracting and analyzing feature information for dustproofing and waterproofing, or it can be further refined based on the differences in protection, thereby improving the rationality and accuracy of the large data screening process.

[0044] Extract the operational characteristic information based on waterproof treatment for the waterproof impact protection cycle to form waterproof performance characteristic data, including: determining the amount of accumulated water S corresponding to waterproof maintenance in each waterproof impact protection cycle m and water removal J m , and form the corresponding waterproof maintenance level value R m ,in, m represents the number of different waterproof protection cycles; set the waterproof maintenance level to affect the stage quantity, and according to different waterproof maintenance level values ​​R m , cluster the impact stages of the waterproof impact protection cycle to form different waterproof impact stage cycle sets; the change amount of different protection analysis operation parameters under each waterproof impact protection cycle in different waterproof impact stage cycle sets And waterproof protection level Establish the following cycle waterproofing formula: Where z is the number of different waterproof impact stage cycle sets, t is the number of different waterproof impact protection periods corresponding to the waterproof impact stage cycle set numbered z, e is the number of power terms and e≥1, Indicates the power constant corresponding to different protection analysis operation parameters of different waterproof impact protection periods under different waterproof impact stage cycle sets, It represents the power value of different protection analysis operation parameters of different waterproof impact protection periods under different waterproof impact stage cycle sets, It represents the waterproof constant term of the waterproof protection period numbered t corresponding to the waterproof impact stage period set numbered z; according to the different periodic waterproof formulas in the waterproof impact stage period set, the periodic waterproof characteristic formula corresponding to the waterproof impact stage period set is determined: Among them, E z Indicates the characteristic waterproof maintenance degree value corresponding to the waterproof impact stage cycle set numbered z, It represents the power value of the protection analysis operation parameter numbered n corresponding to the waterproof impact stage cycle set numbered z, with the next power term numbered e. It represents the characteristic power value of the protection analysis operation parameter numbered n under the waterproof impact stage cycle set numbered z, with the power term number e corresponding to it. Represents the characteristic waterproof constant corresponding to the waterproof impact stage cycle set numbered z; collects the periodic waterproof characteristic formulas corresponding to all waterproof impact stage cycle sets to form waterproof performance characteristic data.

[0045] The extraction and analysis of waterproof performance characteristic data is also conducted periodically based on the regular changes in the smart energy meter. The characteristic formulas corresponding to all protection periods under the same waterproof impact stage period set have close correlation and relationship consistency. Therefore, after processing and analysis, the characteristic formula under the corresponding waterproof impact stage period can be formed, making the characteristic formula clearly and accurately representative. Here, when dividing the waterproof impact stage period set, the stage quantity of waterproof maintenance degree can be determined based on actual conditions or based on big data analysis. Similarly, the stage quantity of dustproof maintenance degree can be determined based on actual conditions or based on big data analysis.

[0046] S3: Obtain historical comprehensive protection big data of the same type of electricity meters, and combine it with the dustproof performance characteristic data and waterproof performance characteristic data to conduct comprehensive correlation analysis to form comprehensive protection performance characteristic data.

[0047] Obtain historical comprehensive protection big data of the same type of electric meters, and combine it with dustproof performance characteristic data and waterproof performance characteristic data to conduct comprehensive correlation analysis to form comprehensive protection performance characteristic data, including: Based on the historical comprehensive protection big data, determine the comprehensive dustproof maintenance degree value P before and after each comprehensive protection u , comprehensive waterproof maintenance value Q and comprehensive changes corresponding to different protection analysis operating parameters u represents the number of different comprehensive protection maintenance cycles; according to the comprehensive dust protection maintenance level value P u , determine the corresponding periodic dustproof characteristic formula, and calibrate it as the comprehensive protection potential dustproof characteristic formula According to the comprehensive waterproof maintenance value Q u , determine the corresponding periodic waterproof characteristic formula, and calibrate it as the comprehensive protection potential waterproof characteristic formula For each comprehensive protection maintenance cycle, the comprehensive changes corresponding to the operating parameters of different protection analysis are analyzed Comprehensive protection potential dustproof feature And comprehensive protection potential waterproof feature Conduct comprehensive protection feature analysis to form corresponding comprehensive protection feature information.

[0048] Of course, protective treatment applies not only to cases where only dust removal or water removal is performed, but also to cases where both dust removal and water removal are performed simultaneously. As for operating parameters, the combined effect of dust removal and water removal is not necessarily a linear combination of the characteristic information corresponding to the two treatments performed separately. Therefore, it is necessary to extract and analyze the characteristic information of the comprehensive protective performance. This analysis ensures that the extracted comprehensive protective characteristic information has wide applicability and can cover the cases where single protective treatments are performed independently as well as the cases where protective treatments are combined.

[0049] For each comprehensive protection maintenance cycle, the comprehensive changes corresponding to the operating parameters of different protection analysis are analyzed Comprehensive protection potential dustproof feature And comprehensive protection potential waterproof feature Conduct comprehensive protection feature analysis to form corresponding comprehensive protection feature information, including: if there are different comprehensive dust protection constants for all comprehensive maintenance protection cycles and comprehensive waterproof constant Make the comprehensive changes corresponding to different protection analysis operating parameters Introducing comprehensive protection potential dustproof feature And comprehensive protection potential waterproof feature After that, Eq. If the dustproof performance characteristic data and waterproof performance characteristic data are combined to form comprehensive protection characteristic information, if for all comprehensive protection maintenance cycles: there are comprehensive protection maintenance cycles that cannot meet the requirements of the determined comprehensive dustproof constant. and comprehensive waterproof constant Make the comprehensive changes corresponding to different protection analysis operating parameters Introducing comprehensive protection potential dustproof feature And comprehensive protection potential waterproof feature After that, Eq. If it is established, the deviation L corresponding to the comprehensive protection maintenance cycle is determined u ,in, And set the deviation threshold to make the following analysis and judgment: When L u If both do not exceed the deviation threshold, the dustproof performance characteristic data and waterproof performance characteristic data are collected to form comprehensive protection characteristic information; when there is L u When the deviation threshold is exceeded, comprehensive protection independent feature analysis is performed to form comprehensive protection feature information.

[0050] The key to obtaining comprehensive protection feature information is determining whether the effects of a single protection treatment are linearly superimposed on the overall protection. Therefore, the power characteristics of the characteristic formula can be used to more intuitively determine whether the comprehensive protection treatment is a linear superposition of single feature information when extracting comprehensive protection feature information. In cases where there is no constant that allows the superposition of single feature information to form comprehensive feature information, the necessity of extracting supplementary feature information is determined by determining the difference generated by this superposition.

[0051] When there is L u When the deviation threshold is exceeded, the comprehensive protection independent feature analysis is performed to form comprehensive protection feature information, including: for different comprehensive protection maintenance cycles: according to the comprehensive dust protection maintenance degree value P u , Comprehensive waterproof protection level value Q u , the comprehensive changes corresponding to different protection analysis operating parameters And the corresponding comprehensive protection potential dustproof characteristic formula and comprehensive protection potential waterproof feature formula Establish the following characteristic formula:

[0052] in, It represents the periodic comprehensive supplementary characteristic formula corresponding to the comprehensive protection maintenance cycle numbered u, v represents the comprehensive supplementary power number and v≥1, The power constant representing the comprehensive change of the protection analysis operating parameter numbered n under the comprehensive protection maintenance cycle numbered u when the next power is v. It represents the power value of the protection analysis operation parameter numbered n in the comprehensive protection maintenance cycle numbered u. Indicates the periodic comprehensive supplement constant corresponding to the comprehensive protection and maintenance cycle numbered u; the periodic comprehensive supplement characteristic formula corresponding to different comprehensive protection and maintenance cycles is Perform homogenization fitting to form a comprehensive supplementary characteristic formula Collects dustproof performance characteristic data, waterproof performance characteristic data and all comprehensive supplementary characteristic formulas Form comprehensive protection feature information.

[0053] When single protection feature information cannot be linearly superimposed to form comprehensive protection feature information, the feature information can be directly used to extract and analyze supplementary feature information. This can intuitively show the difference between comprehensive protection and single protection treatment, and on the other hand, it can also quickly and directly determine reasonable comprehensive supplementary feature information.

[0054] S4: Collect real-time protection information and conduct real-time protection monitoring and analysis in combination with comprehensive protection performance characteristic data to form real-time protection monitoring result data.

[0055] Collect real-time protection information, and conduct real-time protection monitoring and analysis in combination with comprehensive protection performance characteristic data to form real-time protection monitoring result data, including: obtaining the real-time operating range of different protection analysis operating parameters and periodically collecting the corresponding real-time operating values; determining the corresponding real-time change amount based on the real-time operating values ​​of different protection analysis operating parameters and the corresponding real-time operating range; determining the real-time dust removal reference amount and the real-time water removal reference amount based on the real-time change amount of different protection analysis operating parameters and the comprehensive protection characteristic information.

[0056] Of course, after obtaining the comprehensive protection feature information, the dust removal and water removal amounts can be determined quickly and efficiently in combination with real-time monitoring data, avoiding the situation where multiple maintenances are ineffective, resulting in increased maintenance costs and reduced working efficiency of smart electricity meters.

[0057] According to the real-time changes in different protection analysis operating parameters and the comprehensive protection characteristic information, the real-time dust removal reference amount and the real-time water removal reference amount are determined, including: applying different protection analysis operating parameters to different periodic dust prevention characteristic formulas and periodic water prevention characteristic formulas, and determining different real-time dust removal amount and real-time water removal amount combinations according to the real-time dust accumulation amount and the real-time water accumulation amount, and determining the combination with the smallest sum of the real-time dust removal amount and the real-time water removal amount as the corresponding real-time dust removal reference amount and real-time water removal reference amount.

[0058] It is understandable that it is necessary for smart energy meters to be able to maintain their current operating status without protective processing. Therefore, the protective processing of smart energy meters can be performed or used as a reference with the minimum protective processing amount. After all, the minimum protective processing amount can greatly shorten the protection time, improve the effective working market of the smart energy meter, and ensure that the smart energy meter has a significant improvement in operation after the protective processing.

[0059] In summary, the beneficial effects of the high protection level smart energy meter provided by the embodiment of the present invention are:

[0060] The electric energy meter obtains dust removal big data to establish the characteristic relationship between the operating parameters affected by protection factors and the dust removal changes under the periodic operation of the smart electric energy meter. At the same time, it also obtains water removal big data to establish the characteristic relationship between the operating parameters affected by protection factors and the water removal changes under the periodic operation of the smart electric energy meter, and analyzes and processes the comprehensive big data of dust removal and water removal. On the basis of combining the dust removal performance characteristic data and the water removal performance characteristic data, basic reference data for dust removal and water removal protection analysis is formed. Then, when real-time monitoring data is obtained, reasonable dust removal and water removal information can be determined according to the changes in the operating performance of the smart electric energy meter. In this way, periodic maintenance of the smart electric energy meter can be achieved while minimizing ineffective dust removal and water removal treatments, ensuring efficient protection of the smart electric energy meter, and thus enabling the smart electric energy meter to operate efficiently and stably for a long time.

[0061] 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.

[0062] 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.

[0063] 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.

[0064] "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.

[0065] 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.

[0066] 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.

[0067] In the description of the embodiments of the present application, unless otherwise specified, " / " indicates that the objects associated with each other are in an "or" relationship. For example, A / B can represent A or B. "And / or" in the embodiments of the present application is only a description of the association relationship of the associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. A and B can be singular or plural. In addition, in the description of the embodiments of the present application, unless otherwise specified, "multiple" refers to two or more than two. "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 represent: a, b, c, ab, ac, bc, or abc, where a, b, and c can be single or multiple. In addition, in order to facilitate the clear description of the technical solutions of the embodiments of the present application, in the embodiments of the present application, words such as "first" and "second" are used to distinguish between identical or similar items with basically the same functions and effects. 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.

[0068] It should be understood that the processor in the embodiments of the present application may be a central processing unit (CPU), and the processor 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.

[0069] 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 synchronous dynamic random access memory (DDR SDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link DRAM (SLDRAM), and direct rambus RAM (DR RAM).

[0070] The above embodiments can be implemented in whole or in part by software, hardware (such as circuits), firmware or any other combination. 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 includes one or more computer instructions or computer programs. When the computer instructions or computer program are loaded or executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. 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 computer-readable storage medium. 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 a wired (such as infrared, wireless, microwave, etc.) method. The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or data center that contains one or more available media sets. The available medium can be a magnetic medium (for example, a floppy disk, a hard disk, a tape), an optical medium (for example, a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state drive.

[0071] 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.

[0072] 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.

[0073] 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.

[0074] 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.

[0075] 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.

[0076] 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.

[0077] 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.

[0078] 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.

[0079] 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, a server, or a 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 codes, 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.

[0080] 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 high protection level smart energy meter, characterized in that: Configured to: Obtain historical dust prevention big data for similar electricity meters, conduct dust prevention feature analysis based on a single factor, and generate dust prevention performance feature data; Obtain historical waterproof big data of the same type of electricity meters, conduct waterproof feature analysis based on a single factor, and generate waterproof performance feature data; Obtain historical comprehensive protection big data of the same type of electric meters, and combine the dustproof performance characteristic data and the waterproof performance characteristic data to perform comprehensive correlation analysis to form comprehensive protection performance characteristic data; Collect real-time protection information, and conduct real-time protection monitoring and analysis in combination with the comprehensive protection performance characteristic data to form real-time protection monitoring result data.

2. The high protection level smart energy meter according to claim 1, characterized in that: The acquisition of historical dust prevention big data of the same type of electric meters, performing dust prevention feature analysis based on a single factor, and forming dust prevention performance feature data includes: Determine the protection analysis operation parameters and set the minimum impact correlation D min ; Based on the historical dust prevention big data, determine the changes in the protection analysis operating parameters before and after the completion of dust prevention maintenance in each protection cycle And determine the corresponding periodic dust protection correlation D k , n represents the number of different protection analysis running parameters, k represents the number of different protection cycles, α n Dust protection correlation factors representing different protection analysis operating parameters; According to the minimum impact correlation D min The dust protection correlation degree D corresponding to the different protection periods k , determine D k >D min The protection period is calibrated as the dust impact protection period, and the operation characteristic information of the dust impact protection period is extracted based on the dust prevention processing to form dust prevention performance characteristic data.

3. The high protection level smart energy meter according to claim 2, characterized in that: The step of extracting operational characteristic information based on dust prevention processing from the dust prevention protection period to form dust prevention performance characteristic data includes: Determine the dust accumulation amount G during each dust protection period corresponding to the dust protection maintenance m and dust removal capacity C m , and form the corresponding dust protection level value E m ,in, m represents the number of the different dust protection protection periods; Set the dust protection level to affect the stage amount, and according to the different dust protection level values ​​E m , clustering the dust protection impact protection period according to the impact stage to form different dust protection impact stage period sets; The variation of the protection analysis operating parameters under each dust protection period in different dust protection period concentrations And dust protection level value Establish the following periodic dust protection formula: Wherein, y is the number of the different dust impact stage period sets, x is the number of the different dust impact protection period corresponding to the dust impact stage period set numbered y, i is the number of power terms and i≥1, represents the power constant corresponding to different protection analysis operation parameters of different dust prevention protection periods under different dust prevention stage period sets, represents the power values ​​of different protection analysis operation parameters of different dust impact protection periods under different dust impact stage cycle sets, The dustproof constant term representing the dustproof impact protection period numbered x corresponding to the dustproof impact stage period set numbered y; According to the different periodic dust prevention formulas in the dust prevention impact stage period set, the periodic dust prevention characteristic formula corresponding to the dust prevention impact stage period set is determined: Among them, E y Indicates the characteristic dust protection maintenance degree value corresponding to the dust protection impact stage cycle set numbered y, represents the power value of the protection analysis operation parameter numbered n corresponding to the dust protection impact stage period set numbered y, raised to the power of i. Indicates the characteristic power value of the power term number i corresponding to the protection analysis operating parameter numbered n under the dust protection impact stage cycle set numbered y, The characteristic dust protection constant corresponding to the dust protection impact stage period set numbered y; The periodic dustproof characteristic formulas corresponding to all the dustproof impact stage period sets are collected to form the dustproof performance characteristic data.

4. The high protection level smart energy meter according to claim 3, characterized in that: The acquisition of historical waterproof big data of the same type of electric meters, and the analysis of waterproof characteristics based on a single factor to form waterproof performance characteristic data include: Based on the historical waterproof big data, determine the changes in the different protection analysis operating parameters before and after the completion of waterproof maintenance in each protection cycle And determine the corresponding periodic waterproof correlation W k , n represents the number of different protection analysis running parameters, k represents the number of different protection cycles, γ n A waterproof correlation factor representing different protection analysis operation parameters; According to the minimum impact correlation D min The waterproof correlation degree W corresponding to the different protection periods k , determine W k >D min The protection period is calibrated as a waterproof impact protection period, and the operation characteristic information of the waterproof impact protection period based on waterproof processing is extracted to form waterproof performance characteristic data.

5. The high protection level smart energy meter according to claim 4, characterized in that: The step of extracting operational characteristic information based on waterproofing treatment from the waterproofing protection period to form waterproofing performance characteristic data includes: Determine the amount of accumulated water S during each waterproof protection period corresponding to waterproof maintenance m and water removal J m , and form the corresponding waterproof maintenance level value R m ,in, m represents the number of the different waterproof protection periods; Set the waterproof maintenance level to affect the stage amount, and according to the different waterproof maintenance level values ​​R m , clustering the waterproof impact protection cycle according to the impact stage to form different waterproof impact stage cycle sets; The change amount of different protection analysis operation parameters under each waterproof impact protection cycle in different waterproof impact stage cycles And waterproof protection level Establish the following cycle waterproofing formula: Wherein, z is the number of the different waterproof impact stage period sets, t is the number of the different waterproof impact protection periods corresponding to the waterproof impact stage period set numbered z, e is the number of power terms and e≥1, represents the power constant corresponding to different protection analysis operation parameters of different waterproof impact protection periods under different waterproof impact stage period sets, represents the power values ​​of different protection analysis operation parameters of different waterproof impact protection periods under different waterproof impact stage cycle sets, The waterproof constant term representing the waterproof impact protection period numbered t corresponding to the waterproof impact stage period set numbered z; According to the different periodic waterproofing formulas in the waterproofing impact stage period set, the periodic waterproofing characteristic formula corresponding to the waterproofing impact stage period set is determined: Among them, E z represents the characteristic waterproof maintenance degree value corresponding to the waterproof impact stage cycle set numbered z, represents the power value of the protection analysis operation parameter numbered n corresponding to the waterproof impact stage cycle set numbered z, raised to the power of e. Indicates the characteristic power value of the protection analysis operation parameter numbered n under the waterproof impact stage cycle set numbered z, corresponding to the power term number e, The characteristic waterproof constant corresponding to the waterproof impact stage period set numbered z; The periodic waterproof characteristic formulas corresponding to all the waterproof impact stage period sets are collected to form the waterproof performance characteristic data.

6. The high protection level smart energy meter according to claim 5, characterized in that: The acquisition of historical comprehensive protection big data of the same type of electric meters and combining the dustproof performance characteristic data and the waterproof performance characteristic data to perform comprehensive correlation analysis to form comprehensive protection performance characteristic data include: According to the historical comprehensive protection big data, the comprehensive dust protection maintenance degree value P before and after each comprehensive protection is determined. u , Comprehensive waterproof protection level value Q u And the comprehensive changes corresponding to the different protection analysis operating parameters u represents the number of different comprehensive protection maintenance cycles; According to the comprehensive dust protection level value P u , determine the corresponding periodic dustproof characteristic formula, and calibrate it as the comprehensive protection potential dustproof characteristic formula According to the comprehensive waterproof maintenance level value Q u , determine the corresponding periodic waterproof characteristic formula, and calibrate it as the comprehensive protection potential waterproof characteristic formula For each comprehensive protection maintenance cycle, the comprehensive change corresponding to the different protection analysis operation parameters is calculated. The comprehensive protection potential dustproof characteristic formula And the comprehensive protection potential waterproof characteristic formula Conduct comprehensive protection feature analysis to form corresponding comprehensive protection feature information.

7. The high protection level smart energy meter according to claim 6, characterized in that: For each comprehensive protection maintenance cycle, the comprehensive change amount corresponding to different protection analysis operation parameters is The comprehensive protection potential dustproof characteristic formula And the comprehensive protection potential waterproof characteristic formula Conduct comprehensive protection feature analysis to form corresponding comprehensive protection feature information, including: If for all the comprehensive maintenance protection cycles: there are different comprehensive dust protection constants and comprehensive waterproof constant The comprehensive changes corresponding to the different protection analysis operating parameters are Introducing the comprehensive protection potential dustproof feature formula And the comprehensive protection potential waterproof characteristic formula After that, Eq. If yes, the dustproof performance characteristic data and the waterproof performance characteristic data are combined to form the comprehensive protection characteristic information; If for all the comprehensive protection maintenance cycles: there is a comprehensive protection maintenance cycle that cannot meet the determined comprehensive dust prevention constant and comprehensive waterproof constant The comprehensive changes corresponding to the different protection analysis operating parameters are Introducing the comprehensive protection potential dustproof feature formula And the comprehensive protection potential waterproof characteristic formula After that, Eq. If the deviation L corresponding to the comprehensive protection maintenance cycle is established, the deviation L corresponding to the comprehensive protection maintenance cycle is determined. u ,in, And set the deviation threshold to perform the following analysis and judgment: When L u If both do not exceed the deviation threshold, the dustproof performance characteristic data and the waterproof performance characteristic data are combined to form the comprehensive protection characteristic information; When there is L u When the deviation threshold is exceeded, comprehensive protection independent feature analysis is performed to form the comprehensive protection feature information.

8. The high protection level smart energy meter according to claim 7, characterized in that: When there is L u When the deviation threshold is exceeded, a comprehensive protection independent feature analysis is performed to form the comprehensive protection feature information, including: For different comprehensive protection maintenance cycles: According to the comprehensive dust protection level value P u , the comprehensive waterproof protection level value Q u , the comprehensive changes corresponding to the different protection analysis operating parameters And the corresponding comprehensive protection potential dustproof characteristic formula and the comprehensive protection potential waterproof characteristic formula Establish the following characteristic formula: in, represents the periodic comprehensive supplementary characteristic formula corresponding to the comprehensive protection and maintenance period numbered u, v represents the comprehensive supplementary power number and v≥1, The power constant representing the power of the comprehensive change of the protection analysis operating parameter numbered n under the comprehensive protection maintenance cycle numbered u when the next power is v, represents the power value of the protection analysis operation parameter numbered n in the comprehensive protection maintenance cycle numbered u, Indicates the periodic comprehensive supplement constant corresponding to the comprehensive protection and maintenance period numbered u; The period comprehensive supplementary characteristic formula corresponding to different comprehensive protection maintenance cycles Perform homogenization fitting to form a comprehensive supplementary characteristic formula Collect the dustproof performance characteristic data, waterproof performance characteristic data and all the comprehensive supplementary characteristic formulas The comprehensive protection feature information is formed.

9. The high protection level smart energy meter according to claim 8, characterized in that: The real-time protection information is collected and combined with the comprehensive protection performance characteristic data to perform real-time protection monitoring and analysis to form real-time protection monitoring result data, including: Obtaining the real-time operating ranges of different protection analysis operating parameters and periodically collecting corresponding real-time operating values; Determining corresponding real-time changes according to the real-time operating values ​​and corresponding real-time operating ranges of different protection analysis operating parameters; According to the real-time changes of the different protection analysis operating parameters and the comprehensive protection feature information, a real-time dust removal reference amount and a real-time water removal reference amount are determined.

10. The high protection level smart energy meter according to claim 9, characterized in that: The determining of the real-time dust removal reference amount and the real-time water removal reference amount according to the real-time changes in the protection analysis operating parameters and the comprehensive protection feature information includes: Different protection analysis operating parameters are applied to different periodic dust prevention characteristic formulas and periodic water resistance characteristic formulas, and different real-time dust removal and real-time water removal combinations are determined based on the real-time dust accumulation and real-time water accumulation. The combination with the smallest sum of the real-time dust removal and real-time water removal is determined as the corresponding real-time dust removal reference amount and real-time water removal reference amount.

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