A system and method for improving the reliability of operation of a power supply module of an electric energy meter

Abstract

The application provides a system and method for improving the operation reliability of a power module of an electric energy meter, and relates to the technical field of smart electric energy meters.The system comprises an impedance acquisition unit for acquiring an ESR measured value of an electrolytic capacitor in the power module;an influence analysis unit for obtaining environmental influence quantity distribution data based on the ESR measured value, circuit influence quantity and environmental influence parameters;an index evaluation unit for determining a current viscosity index of the electrolytic capacitor according to the environmental influence quantity distribution data; a switching prediction unit for predicting a path switching timing according to the environmental influence quantity distribution data and the current viscosity index; and a switching control unit for controlling the switching of the power module to a backup power source through the path switching timing to replace the electrolytic capacitor on the power module in time.The system and method provided by the application can realize the timely replacement of the electrolytic capacitor and effectively improve the operation reliability of the power module of the electric energy meter.

Description

Technical Field

[0001] This invention relates to the field of smart energy meter technology, and in particular to a system and method for improving the operational reliability of energy meter power supply modules. Background Technology

[0002] The ESR (Equivalent Series Resistance) value of a capacitor refers to the resistance exhibited by the capacitor in an AC circuit. It includes the resistive effect caused by various factors, such as the capacitor's internal parasitic resistance. In high-frequency circuits, the ESR value of a capacitor significantly affects its filtering performance. For example, in the high-frequency filtering circuit of an electricity meter power module, if the ESR value is too high, it will lead to increased output voltage ripple. This noise can interfere with the precision metering chip, resulting in measurement errors.

[0003] During operation, the electrolytic capacitors in existing electricity meters can dry out and fail due to environmental factors such as high temperature, high humidity, and vibration. This not only alters the ESR value but also increases output ripple, leading to metering errors and affecting measurement accuracy. Furthermore, this type of electrolytic capacitor failure cannot be accurately predicted, causing the power module to be unable to respond quickly and switch to backup power in time when a fault occurs, significantly reducing the reliability of the power module. Summary of the Invention

[0004] This invention provides a system and method for improving the operational reliability of power supply modules in electricity meters. It addresses the problem in existing technologies where the electrolyte in electrolytic capacitors is consumed and dries out due to environmental factors, leading to changes in ESR values, increased output ripple, metering errors, and compromised metering performance. Furthermore, the resulting electrolytic capacitor failure cannot be accurately predicted, hindering the power supply module's ability to respond quickly and switch to backup power in a timely manner when a fault occurs.

[0005] To achieve the above and other related objectives, this invention provides a system for improving the operational reliability of an electricity meter power module, comprising: a resistance acquisition unit for acquiring the measured ESR value of the electrolytic capacitor in the power module; an impact analysis unit for performing environmental impact analysis based on the measured ESR value, circuit influence quantities, and environmental impact parameters to obtain the distribution data of the environmental impact quantities of each environmental impact parameter on the electrolytic capacitor; an index evaluation unit for determining the current viscosity index of the electrolytic capacitor based on the environmental impact quantity distribution data; a switching prediction unit for predicting the path switching timing of the power module based on the environmental impact quantity distribution data and the current viscosity index; and a switching control unit for controlling the switching of the power module to a backup power source based on the path switching timing, so as to replace the electrolytic capacitor on the power module in a timely manner and improve the operational reliability of the electricity meter power module.

[0006] In one embodiment of the present invention, the impact analysis unit includes: a duration calculation subunit, used to obtain the circuit impact duration based on the measured ESR value and the initial operating time when the power module is put into use; a circuit impact calculation subunit, used to obtain the circuit impact amount based on the circuit impact duration and the circuit impact increment per unit time; and an environmental impact calculation subunit, used to obtain the total environmental impact of all environmental impact parameters on the electrolytic capacitor based on the measured ESR value, the initial ESR value, and the circuit impact amount, wherein the formula for calculating the total environmental impact is: ,in, Indicates the total environmental impact. This represents the measured ESR value. Indicates the initial value of ESR. It represents the circuit impact quantity; and the parameter classification subunit is used to perform environmental impact analysis based on the total environmental impact and environmental impact parameters, and obtain the distribution data of the environmental impact quantity of each environmental impact parameter on the electrolytic capacitor.

[0007] In one embodiment of the present invention, the circuit impact calculation subunit includes: a power grid monitoring module for monitoring the power grid voltage fluctuation value after the power module is put into use; a first incremental output module for obtaining a first unit-time circuit impact increment when the power grid voltage fluctuation value is less than a fluctuation threshold; a second incremental output module for obtaining the circuit impact level based on the fluctuation difference between the power grid voltage fluctuation value and the fluctuation threshold when the power grid voltage fluctuation value is greater than the fluctuation threshold, and obtaining a second unit-time circuit impact increment corresponding to each circuit impact level based on the circuit impact level; and a circuit impact synthesis module for obtaining the circuit impact quantity based on the circuit impact duration, the first unit-time circuit impact increment, and the second unit-time circuit impact increment; the calculation formula for the circuit impact quantity is: ,in, Indicates the influence of the circuit. This indicates the increment of the circuit's influence in the first unit of time. Indicates the duration of the circuit's influence. Indicates the measurement time. Indicates the initial running time. Indicates the duration of the circuit's influence. The second unit time circuit influence increment corresponding to the influence level of each circuit.

[0008] In one embodiment of the present invention, the parameter classification subunit includes: a parameter detection module, used to perform corresponding parameter threshold detection on each environmental impact parameter, extract the corresponding environmental impact parameters that are greater than the parameter threshold, and form an environmental impact parameter set, the environmental impact parameter set including absolute impact parameters and relative impact parameters; a first impact calculation module, used to obtain first environmental impact quantity distribution data based on the absolute impact parameters and the first parameter impact factor corresponding to the absolute impact parameters; a second impact calculation module, used to obtain the first component corresponding to the second environmental impact quantity distribution data based on the relative impact parameters and the second parameter impact factor corresponding to the relative impact parameters; and a residual impact output module, used to obtain the relative impact parameters based on the total environmental impact, the first parameter impact factor, and the first component. The system includes: a total remaining impact; an impact monitoring module for monitoring the impact threshold of the total remaining impact; a coefficient determination module for combining the impact of relative impact parameters and their relative durations when the total remaining impact exceeds the impact threshold, to obtain the impact level coefficient of each relative impact parameter on the total remaining impact; a third impact calculation module for obtaining the second component corresponding to the second environmental impact distribution data based on the relative impact parameters and their corresponding impact level coefficients; and an environmental impact integration module for obtaining the environmental impact distribution data of each environmental impact parameter on the electrolytic capacitor based on the first environmental impact distribution data, the first component corresponding to the second environmental impact distribution data, and the second component corresponding to the second environmental impact distribution data.

[0009] In one embodiment of the present invention, the formula for calculating the distribution data of environmental impact is as follows: ,in, Indicates the absolute influence parameter. This represents the threshold value of the first parameter corresponding to the parameter with absolute influence. This indicates the number of factors influencing the first parameter; Indicates the relative influence parameter. This represents the threshold value of the second parameter corresponding to the relative influence parameter. This indicates the influence factor of the second parameter. This represents the distribution data of environmental impact. This represents the distribution data of the first environmental impact. This indicates the first environmental impact distribution data. The first environmental influence quantum term, Indicates the first component. Indicates the first component The first component sub-item Indicates the second component, Indicates the second component The second component item.

[0010] In one embodiment of the present invention, the coefficient determination module includes: a parameter combination submodule, used to randomly combine relative influence parameters to obtain influence parameter combinations; a coefficient estimation submodule, used to calculate the estimated total influence corresponding to different coefficient combinations by combining different calibrated influence level coefficients corresponding to each target relative influence parameter according to the influence parameter combinations, the additional influence increment of each target relative influence parameter in the influence parameter combinations, and the relative effect duration of the target relative influence parameters; an influence comparison submodule, used to compare the estimated total influence with the remaining total influence to obtain the target estimated total influence that is closest to the remaining total influence; and a coefficient extraction submodule, used to extract each calibrated influence level coefficient from the coefficient combinations corresponding to the target estimated total influence as the influence level coefficient of each relative influence parameter on the remaining total influence.

[0011] In one embodiment of the present invention, the formula for calculating the estimated total impact is as follows: ,in, This indicates the estimated total impact. This represents the calibrated influence level coefficient corresponding to each target's relative influence parameter. This represents the incremental additional impact of each objective relative to the influencing parameters. This indicates the relative duration of the effect of the target relative to the parameters. This indicates the number of coefficients that define the level of influence in each coefficient combination.

[0012] In one embodiment of the present invention, the environmental impact parameters include absolute impact parameters and relative impact parameters, and the environmental impact quantity distribution data includes first environmental impact quantity distribution data corresponding to the absolute impact parameters, and first and second components of second environmental impact quantity distribution data corresponding to the relative impact parameters; the index evaluation unit includes: a first index calculation subunit, used to obtain a first viscosity index based on the first environmental impact quantity distribution data and a first viscosity influence factor corresponding to each first environmental impact quantity distribution data; a second index calculation subunit, used to obtain a second viscosity index based on the first component and a second viscosity influence factor corresponding to each first component; a third index calculation subunit, used to obtain a third viscosity index based on the second component and a third viscosity influence factor corresponding to each second component; and an index synthesis subunit, used to determine the current viscosity index of the electrolytic capacitor based on the first viscosity index, the second viscosity index, and the third viscosity index.

[0013] In one embodiment of the present invention, the environmental impact parameters include absolute impact parameters and relative impact parameters, and the environmental impact quantity distribution data includes first environmental impact quantity distribution data corresponding to the absolute impact parameters, and first and second components of second environmental impact quantity distribution data corresponding to the relative impact parameters; the switching prediction unit includes: a feature query subunit, used to obtain the impact features corresponding to the second component of the power module formation based on the impact level coefficient corresponding to the second component; a first curve prediction subunit, used to obtain the first environmental impact quantity distribution curve corresponding to each absolute impact parameter based on the first environmental impact quantity distribution data corresponding to different times, and to obtain a first prediction curve based on the first environmental impact quantity distribution curve and the predicted environmental parameters; and a second curve prediction subunit, used to obtain the first component corresponding to each absolute impact parameter based on the first component corresponding to different times. The system comprises the following components: a quantity curve, a second prediction curve (derived from the first component curve and predicted environmental parameters); a third curve prediction subunit (predicted based on changes in the impact level coefficient, yielding the predicted level coefficient, and a second component prediction based on the predicted level coefficient and predicted environmental parameters, yielding the third prediction curve); a curve overlay subunit (overlaying the first, second, and third prediction curves to obtain the environmental impact quantity prediction curve); an increment prediction subunit (predicting viscosity trends based on the environmental impact quantity prediction curve to obtain the viscosity index prediction increment); and a switching timing conversion subunit (predicting the viscosity index based on the current viscosity index and the viscosity index prediction increment to obtain the viscosity prediction index, and outputting in real time the time corresponding to when the viscosity prediction index exceeds the index threshold, serving as the path switching timing for the power module).

[0014] To achieve the above and other related objectives, the present invention also provides a method for improving the operational reliability of an electricity meter power module, comprising: acquiring the measured ESR value of the electrolytic capacitor in the power module through a resistance acquisition unit; performing environmental impact analysis based on the measured ESR value, circuit influence quantities, and environmental impact parameters through an impact analysis unit to obtain the distribution data of the environmental impact quantities of each environmental impact parameter on the electrolytic capacitor; determining the current viscosity index of the electrolytic capacitor based on the environmental impact quantity distribution data through an index evaluation unit; predicting the path switching timing of the power module based on the environmental impact quantity distribution data and the current viscosity index through a switching prediction unit; and controlling the switching of the power module to a backup power source through a switching control unit to promptly replace the electrolytic capacitor on the power module, thereby improving the operational reliability of the electricity meter power module.

[0015] The beneficial effects of this invention: This invention proposes a system and method for improving the operational reliability of an electricity meter power module. It obtains the measured ESR value of the electrolytic capacitor in the power module, and then uses this measured ESR value, combined with circuit influence factors and environmental influence parameters, to determine the distribution data of the environmental impact of each environmental influence parameter on the electrolytic capacitor after removing the circuit influence factors from the measured ESR value. In this way, the impact of each environmental influence parameter on the measured ESR value can be accurately determined, allowing for a better assessment of the viscosity impact on the electrolytic capacitor based on the influence of each environmental influence parameter on the measured ESR value. In other words, the current viscosity index of the electrolytic capacitor is evaluated using the environmental influence distribution data. Subsequently, by utilizing the obtained environmental impact distribution data and current viscosity index, and combining it with predictive environmental parameters for future forecasting, the path switching timing of the power module can be predicted. This allows for timely replacement of the electrolytic capacitors on the power module before the viscosity index of the electrolytic capacitors exceeds the standard, i.e., before the electrolytic capacitors dry out. Based on this path switching timing, the power module can be switched to the backup power supply, thus preventing damage to the electrolytic capacitors from increasing output ripple (or noise) and significantly reducing the filtering effect. Therefore, timely replacement of the electrolytic capacitors can effectively improve the operational reliability of the power meter's power module. Attached Figure Description

[0016] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application. It is obvious that the drawings described below are merely some embodiments of this application, and those skilled in the art can obtain other drawings based on these drawings without any inventive effort.

[0017] In the attached diagram:

[0018] Figure 1 This is a structural block diagram of a system for improving the operational reliability of a power meter power module, provided in an embodiment of the present invention.

[0019] Figure 2 The diagram shows a flowchart illustrating a method for improving the operational reliability of a power meter power module according to an embodiment of the present invention.

[0020] The attached figures are labeled as follows:

[0021] Resistance value acquisition unit 111; impact analysis unit 112; index evaluation unit 113; switching prediction unit 114; switching control unit 115. Detailed Implementation

[0022] The following specific examples illustrate the implementation of the present invention. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments. Various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention. In the absence of conflict, the following embodiments and features in the embodiments can be combined with each other.

[0023] It should be noted that the illustrations provided in the following embodiments are only schematic representations of the basic concept of the present invention. The drawings only show the components related to the present invention and are not drawn according to the actual number, shape and size of the components in the actual implementation. In the actual implementation, the form, quantity and proportion of each component can be arbitrarily changed, and the layout of the components may also be more complex.

[0024] In the following description, numerous details are explored to provide a more thorough explanation of embodiments of the invention. However, it will be apparent to those skilled in the art that embodiments of the invention may be practiced without these specific details. In other embodiments, well-known structures and devices are shown in block diagram form rather than in detail to avoid obscuring embodiments of the invention.

[0025] Please see Figure 1 This invention provides a system for improving the operational reliability of an electricity meter power module, comprising: a resistance acquisition unit 111 for acquiring the measured ESR value of the electrolytic capacitor in the power module; an impact analysis unit 112 for performing environmental impact analysis based on the measured ESR value, circuit influence quantities, and environmental impact parameters, and obtaining the distribution data of the environmental impact quantities of each environmental impact parameter on the electrolytic capacitor; an index evaluation unit 113 for determining the current viscosity index of the electrolytic capacitor based on the environmental impact quantity distribution data; a switching prediction unit 114 for predicting the path switching timing of the power module based on the environmental impact quantity distribution data and the current viscosity index; and a switching control unit 115 for controlling the switching of the power module to a backup power source through the path switching timing, so as to replace the electrolytic capacitor on the power module in a timely manner and improve the operational reliability of the electricity meter power module.

[0026] As can be seen from the above, in the system of the present invention, the measured ESR value of the electrolytic capacitor in the power module can be obtained through the resistance acquisition unit 111. This measured ESR value can be a real-time resistance value calculated by measuring the voltage and current values ​​of the electrolytic capacitor's ESR (Equivalent Series Resistance). After obtaining the measured ESR value, the influence analysis unit 112 can use the measured ESR value, combined with circuit influence quantities and environmental influence parameters, to determine the distribution data of the environmental influence quantity formed by each environmental influence parameter on the electrolytic capacitor after removing the circuit influence quantity from the measured ESR value. In this way, the influence of each environmental influence parameter on the measured ESR value can be accurately determined, so as to better determine the viscosity influence on the electrolytic capacitor based on the influence of each environmental influence parameter on the measured ESR value. That is, the index evaluation unit 113 uses the environmental influence quantity distribution data to evaluate the current viscosity index of the electrolytic capacitor. Subsequently, the switching prediction unit 114 can utilize the obtained environmental impact distribution data and current viscosity index, and combine them with the predicted environmental parameters for future forecasting, to predict the path switching timing of the power module. This allows for timely replacement of the electrolytic capacitors on the power module before the viscosity index of the electrolytic capacitors exceeds the standard, i.e., before the electrolytic capacitors dry out. Based on this path switching timing, the switching control unit 115 controls the switching of the power module to the backup power supply, thereby preventing damage to the electrolytic capacitors from increasing output ripple (or noise) and significantly reducing the filtering effect. Therefore, timely replacement of the electrolytic capacitors can effectively improve the operational reliability of the power meter's power module.

[0027] In the system of this invention, the impact analysis unit 112 includes: a duration calculation subunit, used to obtain the circuit impact duration based on the measurement time of the ESR measured value and the initial operating time when the power module is put into use; a circuit impact calculation subunit, used to obtain the circuit impact amount based on the circuit impact duration and the circuit impact increment per unit time; and an environmental impact calculation subunit, used to obtain the total environmental impact of all environmental impact parameters on the electrolytic capacitor based on the ESR measured value, the initial ESR value, and the circuit impact amount. The formula for calculating the total environmental impact is: ,in, Indicates the total environmental impact. This represents the measured ESR value. Indicates the initial value of ESR. It represents the circuit impact quantity; and the parameter classification subunit is used to perform environmental impact analysis based on the total environmental impact and environmental impact parameters, and obtain the distribution data of the environmental impact quantity of each environmental impact parameter on the electrolytic capacitor.

[0028] When analyzing and calculating the distribution data of environmental impact, the impact analysis unit 112 can use the duration calculation subunit to calculate the difference between the measurement time corresponding to each ESR measurement value and the initial operating time when the power module is put into use or after the electrolytic capacitor is replaced. This difference is then used as the circuit impact duration. Based on this circuit impact duration, the circuit impact calculation subunit calculates the estimated value of the change in the measured ESR value of the electrolytic capacitor caused by the circuit impact, i.e., the corresponding circuit impact quantity, by combining the circuit impact increment per unit time. Then, the environmental impact calculation subunit calculates the difference between the measured ESR value, the initial ESR value, and the circuit impact quantity to obtain another estimated value of the change in the measured ESR value of the electrolytic capacitor caused by environmental impacts other than the circuit impact, i.e., the total environmental impact. Furthermore, after obtaining the total environmental impact, the parameter classification subunit can use this total environmental impact to perform environmental impact classification analysis in conjunction with each environmental impact parameter. This allows for the precise division of the ESR resistance impact of each environmental impact parameter, obtaining the distribution data of the environmental impact of each parameter on the electrolytic capacitor. This distribution data can then be used to accurately assess the viscosity impact of each environmental impact parameter on the electrolytic capacitor, determine the current degree of dryness of the electrolytic capacitor, predict the timing of power module switching, and replace the power module or the corresponding electrolytic capacitor within it. This prevents the problem of increased output ripple (or noise) and significantly reduced filtering effect of the electrolytic capacitor during the operation of the power meter's power module.

[0029] The circuit impact calculation subunit includes: a power grid monitoring module for monitoring power grid voltage fluctuations after the power module is put into use; a first incremental output module for obtaining a first unit-time circuit impact increment when the power grid voltage fluctuation is less than a fluctuation threshold; a second incremental output module for obtaining the circuit impact level based on the fluctuation difference between the power grid voltage fluctuation and the fluctuation threshold when the power grid voltage fluctuation is greater than the fluctuation threshold, and obtaining a second unit-time circuit impact increment corresponding to each circuit impact level; and a circuit impact synthesis module for obtaining the circuit impact quantity based on the circuit impact duration, the first unit-time circuit impact increment, and the second unit-time circuit impact increment.

[0030] In calculating the ESR resistance change of electrolytic capacitors caused by circuit influence factors using the circuit influence calculation subunit, the grid voltage fluctuation value after the power module is put into use can be monitored by the grid monitoring module. This grid voltage fluctuation value can be a voltage sensor installed at the front end of the power module to collect grid voltage fluctuation values ​​at any time and send them to the grid monitoring module. When the monitored grid voltage fluctuation value is less than the fluctuation threshold, the basic quantity of the circuit influence quantity can be calculated using a manually set first unit time circuit influence increment. When the grid voltage fluctuation value is greater than the fluctuation threshold, while calculating the basic quantity of the first unit time circuit influence increment, the circuit influence level formed by the grid voltage fluctuation value can be further determined by the fluctuation difference between the grid voltage fluctuation value and the fluctuation threshold. Specifically, a correspondence table between the fluctuation difference and the circuit influence level can be manually established in advance, and then the corresponding circuit level can be directly found based on the fluctuation difference. After obtaining the circuit level, the corresponding second unit time circuit influence increment can be derived based on the circuit influence level. Each circuit impact level corresponds to a different second unit time circuit impact increment. Therefore, the corresponding second unit time circuit impact increment can be queried by the circuit impact level. Finally, the circuit impact synthesis module calculates the corresponding circuit impact quantity based on the circuit impact duration, the first unit time circuit impact increment, and the second unit time circuit impact increment, using the circuit impact quantity calculation formula. This allows the difference between the measured ESR value and the initial ESR value to be processed using the calculated circuit impact quantity, thereby removing the influence of grid voltage fluctuation value on the parameters when calculating the environmental impact quantity distribution data.

[0031] Specifically, the formula for calculating the circuit influence is: ,in, Indicates the influence of the circuit. This indicates the increment of the circuit's influence in the first unit of time. Indicates the duration of the circuit's influence. Indicates the measurement time. Indicates the initial running time. Indicates the duration of the circuit's influence. The second unit time circuit influence increment corresponding to the influence level of each circuit.

[0032] In the calculation of circuit influence, if there is only an increment in circuit influence within the first unit time, then the circuit influence can be calculated solely through... The calculation yields the result. However, when the grid voltage fluctuation exceeds the fluctuation threshold, there will be an additional increment, representing the duration of the circuit's impact. The second unit time circuit influence increment corresponding to each circuit influence level can be obtained by integrating the second unit time circuit influence increment with the circuit influence duration, and adding the increase of the first unit time circuit influence increment under the circuit influence duration.

[0033] In the system of this invention, the parameter classification subunit includes: a parameter detection module, used to perform corresponding parameter threshold detection on each environmental impact parameter, extract the corresponding environmental impact parameters that are greater than the parameter threshold, and form an environmental impact parameter set, the environmental impact parameter set including absolute impact parameters and relative impact parameters; a first impact calculation module, used to obtain first environmental impact quantity distribution data based on the absolute impact parameters and the first parameter impact factor corresponding to the absolute impact parameters; a second impact calculation module, used to obtain the first component corresponding to the second environmental impact quantity distribution data based on the relative impact parameters and the second parameter impact factor corresponding to the relative impact parameters; and a residual impact output module, used to obtain the relative impact parameter pair based on the total environmental impact, the first parameter impact factor, and the first component. The system comprises: a residual total impact; an impact monitoring module for monitoring the impact threshold of the residual total impact; a coefficient determination module for combining the impacts of relative impact parameters and their relative durations when the residual total impact exceeds the impact threshold, to obtain the impact level coefficient of each relative impact parameter on the residual total impact; a third impact calculation module for obtaining the second component corresponding to the second environmental impact distribution data based on the relative impact parameters and their corresponding impact level coefficients; and an environmental impact integration module for obtaining the environmental impact distribution data of each environmental impact parameter on the electrolytic capacitor based on the first environmental impact distribution data, the first component corresponding to the second environmental impact distribution data, and the second component corresponding to the second environmental impact distribution data.

[0034] When classifying the environmental impact distribution data corresponding to each environmental impact parameter through the parameter classification subunit, the impact of smaller environmental impact parameters on the measured ESR value is relatively small. Therefore, the parameter detection module can extract corresponding environmental impact parameters greater than the parameter threshold, such as temperature, humidity, vibration, and magnetic parameters, to form an environmental impact parameter set. After obtaining the environmental impact parameter set, the corresponding environmental impact parameters can be divided into absolute impact parameters and relative impact parameters. It is worth noting that absolute impact parameters can be magnetic parameters, etc., which will not further increase the viscosity of the electrolytic capacitors in the power meter module due to factors such as sealing failure, thus accelerating drying. Relative impact parameters can be parameters such as temperature and humidity. When the power module experiences factors such as sealing failure, the relative impact parameter will further accelerate the drying of the electrolytic capacitors due to sealing failure. Therefore, the absolute impact parameter can be regarded as a component, that is, the first impact calculation module can use each absolute impact parameter and its corresponding first parameter impact factor to perform a product operation to calculate the first environmental impact distribution data corresponding to each absolute impact parameter. Then, the second impact calculation module uses the relative impact parameter and its corresponding second parameter impact factor to perform a product operation to calculate the first component of the second environmental impact distribution data for each relative impact parameter. Since the degree of sealing failure varies, the impact of parameters such as temperature and humidity on the measured ESR value will also differ. Therefore, the residual impact output module can first calculate the residual impact corresponding to the relative impact parameter by using the difference between the total environmental impact and all first parameter impact factors and all first components. The impact monitoring module monitors whether the residual impact exceeds the impact threshold. When it does, the coefficient determination module uses the relative impact parameter and its relative duration of action to freely combine the relative impact parameters, thereby finding the relative impact parameters that can determine the residual impact and their corresponding impact level coefficients. Then, the third impact calculation module combines the impact level coefficients with the additional impact increment of the corresponding relative impact parameter to accurately determine the impact of sealing failure and other impact characteristics on the degree of drying of the electrolytic capacitor, thus forming the impact on the measured ESR value. Therefore, after determining the first component corresponding to the first environmental impact quantity distribution data, the second component corresponding to the second environmental impact quantity distribution data, and the second component corresponding to the second environmental impact quantity distribution data, the second component is superimposed onto the first component of the corresponding relative impact parameter through the environmental impact integration module. Then, combined with the first environmental impact quantity distribution data, the environmental impact quantity distribution data of each environmental impact parameter on the electrolytic capacitor is accurately determined. The environmental impact parameters may include absolute impact parameters and relative impact parameters.

[0035] The formula for calculating the distribution data of environmental impact is as follows:

[0036] ,

[0037] in, Indicates the absolute influence parameter. This represents the threshold value of the first parameter corresponding to the parameter with absolute influence. This indicates the number of factors influencing the first parameter; Indicates the relative influence parameter. This represents the threshold value of the second parameter corresponding to the relative influence parameter. This indicates the influence factor of the second parameter. This represents the distribution data of environmental impact. This represents the distribution data of the first environmental impact. This indicates the first environmental impact distribution data. The first environmental influence quantum term, Indicates the first component. Indicates the first component The first component sub-item Indicates the second component, Indicates the second component The second component is a sub-item. The first parameter influence factor and the second parameter influence factor can be the influence factors on the measured ESR value of each absolute influence parameter and relative influence parameter, which are artificially calibrated in advance based on experience.

[0038] In addition, the coefficient determination module includes: a parameter combination submodule, used to randomly combine relative impact parameters to obtain impact parameter combinations; a coefficient estimation submodule, used to calculate the estimated total impact corresponding to different coefficient combinations by combining different calibrated impact level coefficients corresponding to each target relative impact parameter based on the impact parameter combinations, the additional impact increment of each target relative impact parameter in the impact parameter combinations, and the relative effect duration of the target relative impact parameters; an impact comparison submodule, used to compare the estimated total impact with the remaining total impact to obtain the target estimated total impact that is closest to the remaining total impact; and a coefficient extraction submodule, used to extract each calibrated impact level coefficient from the coefficient combinations corresponding to the target estimated total impact as the impact level coefficient of each relative impact parameter on the remaining total impact.

[0039] In determining the impact level coefficients, the coefficient determination module first uses a parameter combination submodule to randomly combine various relative impact parameters exceeding a parameter threshold, thus forming impact parameter combinations. Then, the coefficient estimation submodule, based on the target relative impact parameter in each impact parameter combination, finds the corresponding additional impact increment. Combining this with the relative effect duration of each relative impact parameter (i.e., the relative effect duration of the target relative impact parameter), and adjusting the calibration impact level coefficients based on the integral calculation of the additional impact increment and relative effect duration, the estimated total impact corresponding to different coefficient combinations is calculated. After obtaining multiple estimated total impacts, the impact comparison submodule compares these estimated total impacts with the remaining total impact, finding the target estimated total impact closest to the remaining total impact. This forms the calibration impact level coefficient corresponding to this target estimated total impact. The coefficient extraction submodule then extracts the coefficients to serve as the impact level coefficients of each relative impact parameter on the remaining total impact. These impact level coefficients effectively reflect the severity of current impact characteristics, such as sealing failure. These calibration impact level coefficients can be set integers or other specific values.

[0040] Preferably, the formula for calculating the estimated total impact is:

[0041] ,

[0042] in, This indicates the estimated total impact. This represents the calibrated influence level coefficient corresponding to each target's relative influence parameter. This represents the incremental additional impact of each objective relative to the influencing parameters. This indicates the relative duration of the effect of the target relative to the parameters. This indicates the number of calibrated influence level coefficients in each coefficient combination. When calculating the estimated total impact, this refers to the calibrated influence level coefficient corresponding to each target's relative influence parameter. They can be different, depending on the relative duration of the relative influence parameters on the target. Within, the additional influence increment of each target relative to the influence parameter at different times. They can be different. Specifically, they can be set in advance by humans based on the different effects of each relative action parameter on the ESR resistance under conditions such as seal failure.

[0043] Therefore, preferably, the environmental impact parameters include absolute impact parameters and relative impact parameters, and the environmental impact quantity distribution data includes the first environmental impact quantity distribution data corresponding to the absolute impact parameters, and the first and second components of the second environmental impact quantity distribution data corresponding to the relative impact parameters.

[0044] In the system of the present invention, the index evaluation unit 113 includes: a first index calculation subunit, used to obtain a first viscosity index based on the first environmental impact quantity distribution data and the first viscosity influence factor corresponding to each first environmental impact quantity distribution data; a second index calculation subunit, used to obtain a second viscosity index based on the first component and the second viscosity influence factor corresponding to each first component; a third index calculation subunit, used to obtain a third viscosity index based on the second component and the third viscosity influence factor corresponding to each second component; and an index synthesis subunit, used to determine the current viscosity index of the electrolytic capacitor based on the first viscosity index, the second viscosity index, and the third viscosity index.

[0045] After acquiring the measured ESR value of each electrolytic capacitor, the index evaluation unit 113 further evaluates the current viscosity index of the electrolytic capacitor based on the measured ESR value. Specifically, the first index calculation subunit can use the calculated first environmental impact quantity distribution data, combined with the first viscosity influence factor corresponding to each first environmental impact quantity distribution data (i.e., the first viscosity influence factor of the absolute influence parameter), to calculate the influence of the absolute influence parameter on the viscosity of the electrolytic capacitor, i.e., the first viscosity index. Similarly, the second index calculation subunit can combine the first component with the relative influence parameter (i.e., the second viscosity influence factor corresponding to each first component) to calculate the second viscosity index. Furthermore, for the second component, the third index calculation subunit can combine the corresponding third viscosity influence factor to calculate the third viscosity index. Finally, the index synthesis subunit is used to superimpose all viscosity indices—the first, second, and third viscosity indices—to accurately calculate the point viscosity effect of all influencing parameters on the electrolytic capacitor, i.e., the current viscosity index. The first and second viscosity influencing factors are pre-calibrated manually based on the influence of absolute and relative influencing parameters on the viscosity index, respectively. The third viscosity influencing factor can be manually calibrated based on relative influencing parameters under influencing characteristics such as different degrees of seal failure.

[0046] In the system of the present invention, the switching prediction unit 114 includes: a feature query subunit, used to obtain the influence features corresponding to the second component of the power module formation based on the influence level coefficient corresponding to the second component; a first curve prediction subunit, used to obtain the first environmental influence quantity distribution curve corresponding to each absolute influence parameter based on the first environmental influence quantity distribution data corresponding to different times, and to obtain a first prediction curve based on the first environmental influence quantity distribution curve and the predicted environmental parameters; a second curve prediction subunit, used to obtain the first component curve corresponding to each absolute influence parameter based on the first component corresponding to different times, and to obtain a second prediction curve based on the first component curve and the predicted environmental parameters; and a third curve prediction subunit, used to obtain the first component curve corresponding to each absolute influence parameter based on the first component at different times, and to obtain a second prediction curve based on the first component curve and the predicted environmental parameters; and a third curve prediction subunit, used to obtain the first component curve corresponding to each absolute influence parameter based on the first component curve and the predicted environmental parameters. The system uses data on changes in the influence level coefficient to predict the level coefficient, obtains the predicted level coefficient, and then uses the predicted level coefficient and predicted environmental parameters to predict the second component, resulting in the third predicted curve. A curve overlay subunit is used to overlay the first, second, and third predicted curves to obtain the environmental impact quantity prediction curve. An incremental prediction subunit is used to predict the viscosity trend based on the environmental impact quantity prediction curve, obtaining the viscosity index prediction increment. Finally, a switching timing conversion subunit is used to obtain the viscosity prediction index based on the current viscosity index and the viscosity index prediction increment, and outputs the time corresponding to when the viscosity prediction index exceeds the index threshold in real time, serving as the path switching timing for the power module.

[0047] When determining the timing of switching the power module to the backup power supply, the switching prediction unit 114 can first use the feature query subunit to detect that the influence level coefficient is not zero. Then, based on the relative influence parameter corresponding to the influence level coefficient, the influence level coefficient, relative influence parameter and influence feature correspondence table can find each influence feature corresponding to the total amount of remaining influence that exceeds the influence threshold. The influence feature can be a situation such as sealing failure or welding loosening. The degree of sealing failure and welding loosening can be used as the corresponding influence level coefficient.

[0048] Furthermore, after determining the impact characteristics, the first environmental impact distribution curves corresponding to each absolute impact parameter can be plotted using the first curve prediction subunit based on the first environmental impact distribution data at different times. Then, based on the plotted first environmental impact distribution curves and the predicted environmental parameters, a first prediction curve is further predicted based on the current measured ESR value, i.e., the first environmental impact distribution curve. Specifically, when the predicted environmental parameter is an absolute impact parameter, the predicted distribution data of each first environmental impact parameter can be calculated based on its difference from the corresponding first parameter threshold, combined with the corresponding first parameter influence factor, to form the first prediction curve.

[0049] Similarly, the second curve prediction subunit can use the first component corresponding to different times to draw the first component curve corresponding to each absolute influence parameter, and based on the first component curve and the prediction environment parameter, the second prediction curve can be further predicted. Specifically, when the prediction environment parameter is a relative influence parameter, the first component can be calculated based on the difference between it and the corresponding second parameter threshold, and combined with the corresponding second parameter influence factor, to form the third prediction curve.

[0050] As the measured ESR values ​​increase, the total residual impact grows, leading to a continuous deterioration in the impact level coefficients corresponding to the impact features. Therefore, the third curve prediction subunit can predict the level coefficients based on changes in the impact level coefficients. For example, the historical level coefficient curves corresponding to the impact features can be searched using the data on changes in the impact level coefficients to find the most similar historical level coefficient curve, and this historical level coefficient curve, based on the historical level coefficient after the corresponding impact level coefficient, can be used as the predicted level coefficient. Alternatively, the least squares method can be used to directly predict the stage-wise predicted level coefficients after the changes in the impact level coefficient data. Then, after obtaining the predicted level coefficients, based on the predicted future duration and the additional impact increment corresponding to each impact feature, the formula can be used to predict the level coefficients. This is used to predict the corresponding second prediction component and form the third prediction curve, where... Indicates the second predicted component. Indicates the predicted duration of the future.

[0051] After obtaining the first, second, and third prediction curves, the curve overlay subunit can overlay all the prediction curves to generate the final overall prediction result, namely the environmental impact prediction curve. Then, the incremental prediction subunit, based on each component of the environmental impact prediction curve, performs viscosity conversion using the corresponding first, second, and third viscosity influence factors to determine the predicted increment of the viscosity index after the measured ESR value. Subsequently, the switching timing conversion subunit sums the predicted viscosity index increment with the already calculated current viscosity index to obtain the viscosity prediction index. This allows for the rapid and accurate identification of the time when the viscosity prediction index exceeds the index threshold, serving as the path switching timing for the power module. After switching the power module to the backup power supply, the electrolytic capacitors of the power module can be replaced or repaired to improve the operational reliability of the power module when it is switched back into use.

[0052] Please see Figure 2 The present invention also provides a method for improving the operational reliability of a power meter power module, comprising:

[0053] Step S10: Obtain the measured ESR value of the electrolytic capacitor in the power module through the resistance acquisition unit 111;

[0054] Step S20: Based on the measured ESR value, circuit influence quantity and environmental influence parameters, the influence analysis unit 112 performs environmental influence analysis to obtain the distribution data of the environmental influence quantity of each environmental influence parameter on the electrolytic capacitor.

[0055] Step S30: Determine the current viscosity index of the electrolytic capacitor based on the environmental impact distribution data through the index evaluation unit 113;

[0056] Step S40: The switching prediction unit 114 predicts the path switching timing of the power module based on the environmental impact distribution data and the current viscosity index.

[0057] Step S50: The switching control unit 115 controls the switching of the power module to the backup power supply through path switching timing, so as to replace the electrolytic capacitor on the power module in a timely manner and improve the operational reliability of the power module of the electricity meter.

[0058] In summary, the system and method disclosed in this invention for improving the operational reliability of an electricity meter power module obtains the measured ESR value of the electrolytic capacitor in the power module. Then, using the measured ESR value, combined with circuit influence parameters and environmental influence parameters, the distribution data of the environmental impact of each environmental influence parameter on the electrolytic capacitor is determined after removing the circuit influence from the measured ESR value. In this way, the impact of each environmental influence parameter on the measured ESR value can be accurately determined, allowing for a better assessment of the viscosity impact on the electrolytic capacitor based on the influence of each environmental influence parameter on the measured ESR value. In other words, the current viscosity index of the electrolytic capacitor is evaluated using the environmental influence distribution data. Subsequently, by utilizing the obtained environmental impact distribution data and current viscosity index, and combining this with predictive environmental parameters for future forecasting, the timing of path switching for the power module can be predicted. This allows for timely replacement of the electrolytic capacitors on the power module before their viscosity index exceeds the limit (i.e., before they dry out), based on the predicted path switching timing. This prevents damage to the electrolytic capacitors, which would otherwise increase output ripple (or noise) and significantly reduce filtering effectiveness. Therefore, timely replacement of the electrolytic capacitors effectively improves the operational reliability of the power meter's power module. Thus, this invention effectively overcomes the various shortcomings of existing technologies and possesses high industrial applicability.

[0059] The above embodiments are merely illustrative of the principles and effects of the present invention and are not intended to limit the invention. Any person skilled in the art can modify or alter the above embodiments without departing from the spirit and scope of the present invention. Therefore, all equivalent modifications or alterations made by those skilled in the art without departing from the spirit and technical concept disclosed in the present invention should still be covered by the claims of the present invention.

Claims

1. A system for improving the operational reliability of a power meter power module, characterized in that, include: The resistance acquisition unit is used to acquire the measured ESR value of the electrolytic capacitor in the power module. The impact analysis unit is used to perform environmental impact analysis based on the measured ESR value, circuit impact quantity and environmental impact parameters, and obtain the distribution data of the environmental impact quantity of each environmental impact parameter on the electrolytic capacitor. The index evaluation unit is used to determine the current viscosity index of the electrolytic capacitor based on the environmental impact distribution data. A switching prediction unit is used to predict the path switching timing of the power module based on the environmental impact distribution data and the current viscosity index. as well as The switching control unit is used to control the switching of the power module to the backup power supply through the path switching timing, so as to replace the electrolytic capacitor on the power module in a timely manner and improve the operational reliability of the power module of the energy meter. The environmental impact parameters include absolute impact parameters and relative impact parameters, and the environmental impact quantity distribution data includes the first environmental impact quantity distribution data corresponding to the absolute impact parameters, and the first and second components of the second environmental impact quantity distribution data corresponding to the relative impact parameters. The indicator evaluation unit includes: The first index calculation subunit is used to obtain the first viscosity index based on the first environmental impact quantity distribution data and the first viscosity impact factor corresponding to each of the first environmental impact quantity distribution data. The second index calculation subunit is used to obtain the second viscosity index based on the first component and the second viscosity influence factor corresponding to each first component. The third index calculation subunit is used to obtain the third viscosity index based on the second component and the third viscosity influence factor corresponding to each second component; and The index synthesis subunit is used to determine the current viscosity index of the electrolytic capacitor based on the first viscosity index, the second viscosity index, and the third viscosity index.

2. The system for improving the operational reliability of the power supply module of an electricity meter according to claim 1, characterized in that, The impact analysis unit includes: The duration calculation subunit is used to obtain the circuit influence duration based on the measurement time of the ESR measured value and the initial running time when the power module is put into use. The circuit influence calculation subunit is used to obtain the circuit influence amount based on the circuit influence duration and the circuit influence increment per unit time. The environmental impact calculation subunit is used to obtain the total environmental impact of all the environmental impact parameters on the electrolytic capacitor based on the measured ESR value, the initial ESR value, and the circuit influence quantity. The formula for calculating the total environmental impact is as follows: ,in, Indicates the total environmental impact. This represents the measured ESR value. Indicates the initial value of ESR. Indicates the influence of the circuit; and The parameter classification subunit is used to perform environmental impact analysis based on the total environmental impact and the environmental impact parameters, and to obtain the distribution data of the environmental impact of each environmental impact parameter on the electrolytic capacitor.

3. The system for improving the operational reliability of the power supply module of an electricity meter according to claim 2, characterized in that, The circuit influence calculation subunit includes: The power grid monitoring module is used to monitor the power grid voltage fluctuation value after the power supply module is put into use; The first incremental output module is used to obtain the first unit time circuit influence increment when the grid voltage fluctuation value is less than the fluctuation threshold. The second incremental output module is used to, when the grid voltage fluctuation value is greater than the fluctuation threshold, obtain the circuit impact level based on the fluctuation difference between the grid voltage fluctuation value and the fluctuation threshold, and obtain the second unit-time circuit impact increment corresponding to each circuit impact level based on the circuit impact level; and The circuit influence synthesis module is used to obtain the circuit influence amount based on the circuit influence duration, the circuit influence increment in the first unit time, and the circuit influence increment in the second unit time. The formula for calculating the influence of the circuit is: ， in, Indicates the influence of the circuit. This indicates the increment of the circuit's influence in the first unit of time. Indicates the duration of the circuit's influence. Indicates the measurement time. Indicates the initial running time. Indicates the duration of the circuit's influence. The second unit time circuit influence increment corresponding to the influence level of each circuit.

4. The system for improving the operational reliability of the power supply module of an electricity meter according to claim 2, characterized in that, The parameter classification subunit includes: The parameter detection module is used to perform corresponding parameter threshold detection on each of the environmental impact parameters, extract the corresponding environmental impact parameters that are greater than the parameter threshold, and form an environmental impact parameter set, which includes absolute impact parameters and relative impact parameters. The first impact calculation module is used to obtain the first environmental impact distribution data based on the absolute impact parameter and the first parameter impact factor corresponding to the absolute impact parameter. The second impact calculation module is used to obtain the first component corresponding to the second environmental impact quantity distribution data based on the relative impact parameter and the second parameter impact factor corresponding to the relative impact parameter; The residual impact output module is used to obtain the total residual impact corresponding to the relative impact parameter based on the total environmental impact, the first parameter impact factor, and the first component. An impact monitoring module is used to monitor the impact threshold of the remaining total impact. The coefficient determination module is used to combine the influence of the relative influence parameters and the relative duration of the relative influence parameters when the total remaining influence is greater than the influence threshold, and obtain the influence level coefficient of each relative influence parameter on the total remaining influence. The third impact calculation module is used to obtain the second component corresponding to the second environmental impact distribution data based on the relative impact parameters and the corresponding impact level coefficients; and The environmental impact comprehensive module is used to obtain the environmental impact distribution data formed by each environmental impact parameter on the electrolytic capacitor based on the first environmental impact distribution data, the first component corresponding to the second environmental impact distribution data, and the second component corresponding to the second environmental impact distribution data.

5. The system for improving the operational reliability of the power supply module of an electricity meter according to claim 4, characterized in that, The formula for calculating the distribution data of the environmental impact is: ， in, Indicates the absolute influence parameter. This represents the threshold value of the first parameter corresponding to the parameter with absolute influence. This indicates the number of factors influencing the first parameter; Indicates the relative influence parameter. This represents the threshold value of the second parameter corresponding to the relative influence parameter. This indicates the influence factor of the second parameter. This represents the distribution data of environmental impact. This represents the distribution data of the first environmental impact. This indicates the first environmental impact distribution data. The first environmental influence quantum term, Indicates the first component. Indicates the first component The first component sub-item Indicates the second component, Indicates the second component The second component item.

6. The system for improving the operational reliability of the power supply module of an electricity meter according to claim 4, characterized in that, The coefficient determination module includes: The parameter combination submodule is used to randomly combine the relative influence parameters to obtain the influence parameter combination. The coefficient calculation submodule is used to calculate the estimated total impact corresponding to different coefficient combinations by combining the combination of the impact parameters, the additional impact increment of each target relative impact parameter in the combination of the impact parameters, and the relative effect duration of the target relative impact parameters through different calibrated impact level coefficients corresponding to each target relative impact parameter. The impact comparison submodule is used to compare the estimated total impact with the remaining total impact to obtain the target estimated total impact that is closest to the remaining total impact; and The coefficient extraction submodule is used to extract each of the calibrated influence level coefficients from the coefficient combinations corresponding to the total estimated influence of the target, as the influence level coefficients of each of the relative influence parameters on the total remaining influence.

7. The system for improving the operational reliability of an electricity meter power supply module according to claim 6, characterized in that, The formula for calculating the estimated total impact is as follows: ， in, This indicates the estimated total impact. This represents the calibrated influence level coefficient corresponding to the relative influence parameter of each target. This represents the incremental additional impact of each objective relative to the influencing parameters. This indicates the relative duration of the effect of the target relative to the parameters. This indicates the number of coefficients that define the level of influence in each coefficient combination.

8. The system for improving the operational reliability of an electricity meter power supply module according to claim 1, characterized in that, The environmental impact parameters include absolute impact parameters and relative impact parameters, and the environmental impact quantity distribution data includes the first environmental impact quantity distribution data corresponding to the absolute impact parameters, and the first and second components of the second environmental impact quantity distribution data corresponding to the relative impact parameters. The handover prediction unit includes: The feature query subunit is used to obtain the influence features of the power module forming the second component based on the influence level coefficient corresponding to the second component. The first curve prediction subunit is used to obtain the first environmental impact distribution curve corresponding to each of the absolute impact parameters based on the first environmental impact distribution data corresponding to different times, and to obtain the first prediction curve based on the first environmental impact distribution curve and the predicted environmental parameters. The second curve prediction subunit is used to obtain the first component curve corresponding to each of the absolute influence parameters based on the first component at different times, and to obtain the second prediction curve based on the first component curve and the prediction environment parameter. The third curve prediction subunit is used to predict the level coefficient based on the change data of the influence level coefficient, obtain the predicted level coefficient, and perform second component prediction based on the predicted level coefficient and the predicted environmental parameters to obtain the third prediction curve. The curve overlay subunit is used to overlay the first prediction curve, the second prediction curve, and the third prediction curve to obtain the environmental impact prediction curve. An incremental prediction subunit is used to predict the viscosity trend based on the environmental impact prediction curve, and obtain the predicted increment of the viscosity index; and The switching timing calculation subunit is used to obtain a viscosity prediction index based on the current viscosity index and the viscosity index prediction increment, and output the time corresponding to when the viscosity prediction index exceeds the index threshold in real time, as the path switching timing of the power module.

9. A method for using a system for improving the operational reliability of a power meter power module as described in any one of claims 1-8, characterized in that, include: The measured ESR value of the electrolytic capacitor in the power module is obtained through the resistance acquisition unit; The environmental impact analysis unit performs environmental impact analysis based on the measured ESR value, circuit impact quantity, and environmental impact parameters to obtain the distribution data of the environmental impact quantity of each environmental impact parameter on the electrolytic capacitor. The current viscosity index of the electrolytic capacitor is determined by the index evaluation unit based on the environmental impact distribution data. The switching prediction unit predicts the path switching timing of the power module based on the environmental impact distribution data and the current viscosity index. By controlling the switching control unit to switch the power module to the backup power source at the path switching timing, the electrolytic capacitor on the power module can be replaced in a timely manner, thereby improving the operational reliability of the power module of the electricity meter.

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