Intelligent electric energy meter and terminal error normal distribution automatic compensation calibration method and system

Abstract

The invention discloses an automatic compensation and calibration method and system for error normal distribution of an intelligent electric energy meter and a terminal. The method comprises the following steps: performing first calibration based on a preset compensation value to obtain first detection error data for verifying an error distribution condition; based on the first detection error data system, calculating and analyzing automatically according to a self-contained calculation tool, and calculating a data trend and preset parameters according to a preset upper and lower limit threshold range; determining an error compensation data value according to a calculation result, and calculating an error compensation value through the upper and lower limit threshold range; and automatically pushing the error compensation value to a compensation bit of a work order meter calibration scheme, and calibrating and checking the intelligent electric energy meter based on the meter calibration scheme after automatic compensation. According to the invention, automatic compensation and calibration of errors are realized through an intelligent algorithm, the problems of inaccurate segmentation compensation value, inaccurate manual adjustment, long time consumption and low efficiency in the prior art are solved, and the calibration precision and the production efficiency of the electric energy meter are remarkably improved.

Description

Technical Field

[0001] The present invention relates to the technical field of smart meters, and more specifically, to a smart electricity meter and an automatic compensation calibration method and system for the normal distribution of terminal errors. Background Art

[0002] The existing calibration technologies for the measurement errors of smart electricity meters and terminals have the following disadvantages: 1. The measurement errors of smart electricity meters and terminals are usually caused by component deviations, environmental factors (temperature, humidity), signal interference, etc. At the same time, under low load or harmonic conditions, non-linear errors occur, and a segmented compensation strategy needs to be designed, but the segmented compensation values are difficult to accurately determine. 2. Bench difference and power deviation: In the prior art, whether it is the error calibration method or the power calibration method, due to the bench difference of the bench body and the deviation of the output power, the error values of each error point are unevenly distributed and have a large discreteness after the measurement error calibration, and the error range is ±0.5% or more. 3. Inaccurate manual adjustment: During the calibration process, it is necessary to continuously manually adjust the calibration scheme to meet the accuracy class requirements. However, the manual adjustment is affected by human factors, and the adjustment values are often inaccurate. The manual adjustment usually requires 3 to 5 times on average, repeating the calibration and inspection errors, consuming a lot of time and energy. 4. Time-consuming and low efficiency: Due to the need for multiple adjustments and verifications, the resulting time cost averages 2 hours each time, with low time and efficiency, affecting the production progress and quality. Summary of the Invention

[0003] The purpose of the present invention is to provide a smart electricity meter and an automatic compensation calibration method and system for the normal distribution of terminal errors. Through a closed-loop compensation algorithm based on statistical process control (SPC), according to the real-time feedback calibration error value, the compensation value is dynamically adjusted through the Cpk parameter, relying on real-time data feedback, automatically calculating the calibration error compensation value, realizing the automatic compensation calibration of errors, solving the problems of inaccurate segmented compensation values, inaccurate manual adjustment, time-consuming, and low efficiency in the prior art, and significantly improving the calibration accuracy and production efficiency of the electricity meter.

[0004] The first aspect of the present invention provides a smart electricity meter and an automatic compensation calibration method for the normal distribution of terminal errors, including the following steps: 1. Error data collection: Conduct the first calibration based on a preset compensation value to obtain the first inspection error data for verifying the error distribution situation; obtain the first inspection error data set of the electricity meter and terminal (sample size ≥ 30 units) in real time through the MES system, and record the error values at each load point (such as light load 5% rated current, rated load 100% rated current, overload 120% rated current). 2. Process capability analysis: Calculate and analyze based on the first inspection error data, where the data trend and preset parameters are calculated according to a preset upper and lower limit threshold range; Calculate the process capability index using the Cpk tool: , where USL / LSL is the upper / lower limit of the error (such as ±0.3%), μ is the error mean, and σ is the standard value. If Cpk < 1.33, trigger the dynamic compensation process; 3. Compensation value generation: Determine the error compensation data value according to the calculation result, and calculate the error compensation value through the upper and lower limit threshold range: Calculate the compensation value according to the deviation between μ and the target value (0%) as $$ \Delta = k \cdot (\mu - 0) $$ (k is the attenuation coefficient, determined by fitting historical data); 4. Closed-loop calibration: Push the error compensation value to the compensation position of the work order meter calibration plan, and calibrate and verify the smart energy meter based on the automatically compensated meter calibration plan: Automatically write Δ into the meter calibration work order, and re-verify after calibration until Cpk ≥ 1.33 and the error distribution passes the Shapiro-Wilk normality test (p > 0.05).

[0005] In this solution, the first inspection error data obtained by performing the first calibration based on the preset compensation value to obtain the inspection error distribution situation specifically includes: Initialize the error compensation value to zero for the first calibration; Record the error data of the smart energy meter at different load points; Analyze and verify the error data to obtain the first inspection error data corresponding to the error discreteness and distribution trend.

[0006] In this solution, the calculation and analysis based on the first inspection error data specifically includes: Extract the first inspection error data and import it into a preset calculation tool, where the calculation tool includes a Cpk calculation tool; Based on the Cpk calculation tool, calculate the calculation result according to the preset upper and lower limit threshold range for the data trend and preset parameters, where the preset parameters include the Cpk value.

[0007] In this solution, the determination of the error compensation data value according to the calculation result specifically includes: When the error compensation data value is not within the upper limit threshold range and / or the lower limit threshold range, calculate the mean error compensation value based on the error compensation data value as the error compensation value; When the error compensation data value is within the upper threshold range and / or the lower threshold range, the compensation value remains unchanged, and the error compensation data value is used as the error compensation value.

[0008] In this solution, based on the error compensation value, it is automatically pushed to the compensation bit of the work order meter calibration plan in the meter calibration system to update the calibration parameters, and the meter calibration plan after automatic compensation is obtained.

[0009] In this solution, calibrating and verifying the smart energy meter based on the meter calibration plan after automatic compensation specifically includes: Real-time monitoring of the measured error data during the calibration process; Performing zero-point normal distribution calibration on the measured error data based on the meter calibration plan; Generating a calibration report based on the normal distribution calibration, and synchronously recording the measured error distribution and the measured calibration parameters in the calibration report.

[0010] The second aspect of the present invention also provides a smart energy meter and a terminal error normal distribution automatic compensation calibration system, including a memory and a processor. The memory includes a smart energy meter and a terminal error normal distribution automatic compensation calibration method program. When the smart energy meter and the terminal error normal distribution automatic compensation calibration method program are executed by the processor, the following steps are implemented: Performing a first calibration based on a preset compensation value to obtain first inspection error data for verifying the error distribution; Performing calculation and analysis based on the first inspection error data, wherein calculating the data trend and preset parameters according to the preset upper and lower threshold ranges; Determining the error compensation data value according to the calculation result, and calculating the error compensation value through the upper and lower threshold ranges; Pushing the error compensation value to the compensation bit of the work order meter calibration plan, and calibrating and verifying the smart energy meter based on the meter calibration plan after automatic compensation.

[0011] In this solution, performing the first calibration based on the preset compensation value to obtain the first inspection error data for verifying the error distribution specifically includes: Initializing the error compensation value to zero for the first calibration; Recording the error data of the smart energy meter at different load points; Analyzing and verifying the error data to obtain the first inspection error data corresponding to the error discreteness and distribution trend.

[0012] In this solution, performing the calculation and analysis based on the first inspection error data specifically includes: Extracting the first inspection error data and importing it into a preset calculation tool, wherein the calculation tool includes a Cpk calculation tool; Based on the Cpk calculation tool, calculate the calculation result according to the preset upper and lower limit threshold ranges for the data trend and preset parameters, where the preset parameters include the Cpk value.

[0013] In this solution, determining the error compensation data value according to the calculation result specifically includes: When the error compensation data value is not within the upper limit threshold range and / or the lower limit threshold range, calculate the mean error compensation value based on the error compensation data value as the error compensation value; When the error compensation data value is within the upper limit threshold range and / or the lower limit threshold range, the compensation value remains unchanged, and the error compensation data value is used as the error compensation value.

[0014] In this solution, automatically push the error compensation value to the compensation position of the work order calibration plan in the meter calibration system to update the calibration parameters to obtain the automatically compensated calibration plan.

[0015] In this solution, calibrating and verifying the smart electric energy meter based on the automatically compensated calibration plan specifically includes: Real-time monitor the measured error data during the calibration process; Perform zero normal distribution calibration on the measured error data based on the calibration plan; Generate a calibration report based on the normal distribution calibration, and the measured error distribution and measured calibration parameters are synchronously recorded in the calibration report.

[0016] The third aspect of the present invention provides a computer-readable storage medium, which includes a program for an intelligent electric energy meter and terminal error normal distribution automatic compensation calibration method of a machine. When the program for the intelligent electric energy meter and terminal error normal distribution automatic compensation calibration method is executed by a processor, the steps of an intelligent electric energy meter and terminal error normal distribution automatic compensation calibration method as described in any one of the above are implemented.

[0017] An intelligent electric energy meter and terminal error normal distribution automatic compensation calibration method and system disclosed by the present invention realize automatic compensation calibration of errors through an intelligent algorithm, solve the problems of inaccurate segmented compensation values, inaccurate manual adjustment, long time consumption, and low efficiency in the prior art, and significantly improve the calibration accuracy and production efficiency of the electric energy meter. The specific beneficial effects are as follows: 1. Automatic compensation calibration: The present invention automatically calculates the error compensation value through a closed-loop compensation algorithm based on statistical process control (SPC), avoiding the inaccuracy of manual adjustment and the problem of multiple repeated verifications, and significantly improving the calibration accuracy and efficiency. 2. Error normal distribution: The automatically compensated error is based on zero normal distribution, ensuring the uniformity and stability of the error distribution and improving the measurement accuracy of the electric energy meter. 3. Improve production efficiency: Through automated error compensation calibration, the time for manual intervention and repeated verification is reduced, significantly improving production efficiency and quality. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 Shows a flowchart of an automatic compensation calibration method for the normal distribution of errors of an intelligent electricity meter and a terminal according to the present invention; Figure 2 Shows a block diagram of an automatic compensation calibration system for the normal distribution of errors of an intelligent electricity meter and a terminal according to the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0019] In order to more clearly understand the above objects, features, and advantages of the present invention, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be noted that, without conflict, the embodiments of the present application and the features in the embodiments may be combined with each other.

[0020] In the following description, many specific details are set forth in order to fully understand the present invention. However, the present invention may be implemented in other ways different from those described herein. Therefore, the protection scope of the present invention is not limited by the specific embodiments disclosed below.

[0021] Figure 1 Shows a flowchart of an automatic compensation calibration method for the normal distribution of errors of an intelligent electricity meter and a terminal according to the present application.

[0022] As Figure 1 shown, the present application discloses an automatic compensation calibration method for the normal distribution of errors of an intelligent electricity meter and a terminal, including the following steps: S102, perform a first calibration based on a preset compensation value to obtain first inspection error data for verifying the error distribution situation; S104, perform calculation and analysis based on the first inspection error data, wherein calculate the data trend and preset parameters according to a preset upper and lower threshold range; S106, determine the error compensation data value according to the calculation result, and calculate the error compensation value through the upper and lower threshold range; S108, push the error compensation value to the compensation position of the work order meter calibration plan, and calibrate and verify the intelligent electricity meter based on the automatically compensated meter calibration plan.

[0023] It should be noted that in this embodiment, automatic compensation and calibration can be achieved by automatically calculating the error compensation value. Among them, the first calibration error compensation value is 0, the error distribution is verified, and then data extraction and calculation are performed. Among them, the first inspection error data is imported into the Cpk calculation tool for calculation and analysis. Specifically, according to the preset upper and lower limit threshold ranges, the data trend and Cpk parameters are calculated to obtain the calculation result.

[0024] Furthermore, determine the error compensation value. Specifically, determine the error compensation data value according to the calculation result, and calculate the appropriate error compensation value through the upper and lower limit ranges. Then, automatically push the error compensation value to the compensation position of the work order meter calibration scheme to update the calibration parameters. Finally, perform automatic compensation and verification. Among them, calibration and verification are performed according to the meter calibration scheme after automatic compensation to achieve a zero normal distribution of errors.

[0025] According to the embodiment of the present invention, the first inspection error data for obtaining the error distribution by performing the first calibration based on the preset compensation value specifically includes: Initialize the error compensation value to zero for the first calibration; Record the error data of the intelligent electric energy meter at different load points; Analyze and verify the error data to obtain the first inspection error data corresponding to the error discreteness and distribution trend.

[0026] It should be noted that in this embodiment, the automatically initialized error compensation value is "0". After the calibration is started, the intelligent electric energy meter starts to work and records the error data at different load points (such as 5% rated current at light load, 100% rated current at rated load, 120% rated current at overload). For example: light load point error: +0.2%, rated load point error: -0.1%, overload point error: +0.3%. Then, error distribution analysis is performed. Among them, it is found that the error distribution discreteness is relatively large and there is a positive deviation phenomenon (such as positive deviation of the light load and overload point errors and negative deviation of the rated load point error).

[0027] According to the embodiment of the present invention, the calculation and analysis based on the first inspection error data specifically includes: Extract the first inspection error data and import it into a preset calculation tool, where the calculation tool includes a Cpk calculation tool; Based on the Cpk calculation tool, calculate the data trend and preset parameters according to the preset upper and lower limit threshold ranges to obtain the calculation result, where the preset parameters include the Cpk value.

[0028] It should be noted that in this embodiment, the Cpk calculation tool is a software or tool used to calculate and evaluate the Process Capability Index (Cpk). In the above embodiment, the light load point error is +0.2%, the rated load point error is -0.1%, and the overload point error is +0.3%. According to the preset upper and lower threshold ranges (for example, the error upper limit is +0.5% and the lower limit is -0.5%), the Cpk value of the error data is calculated. Among them, the Cpk value corresponds to the error compensation data value. Assuming the calculation result is Cpk = 0.8, it indicates that the distribution of the error data is not ideal and exceeds the controllable range.

[0029] According to an embodiment of the present invention, determining the error compensation data value according to the calculation result specifically includes: When the error compensation data value is not within the upper threshold range and / or the lower threshold range, calculate the mean error compensation value based on the error compensation data value as the error compensation value; When the error compensation data value is within the upper threshold range and / or the lower threshold range, the compensation value remains unchanged, and the error compensation data value is used as the error compensation value.

[0030] It should be noted that in this embodiment, it is stated in the above embodiment that Cpk = 0.8. Therefore, it is not within the upper and lower threshold ranges. Calculate the mean of each load point error: (+0.2% + -0.1% + +0.3%) / 3 = +0.13%, so as to determine the error compensation value as "-0.13%", so that the error mean can be adjusted to near zero. If the Cpk value is within the upper and lower threshold ranges, the compensation value remains unchanged.

[0031] According to an embodiment of the present invention, the error compensation value is automatically pushed to the compensation position of the work order calibration scheme in the meter calibration system to update the calibration parameters to obtain the automatically compensated calibration scheme.

[0032] It should be noted that in this embodiment, the calculated error compensation value "-0.13%" is pushed to the compensation position of the work order calibration scheme in the calibration system. After updating the calibration parameters, a new calibration scheme is generated according to the updated compensation value "-0.13%".

[0033] According to an embodiment of the present invention, calibrating and verifying the smart electricity meter based on the automatically compensated calibration scheme specifically includes: Real-time monitor the measured error data during the calibration process; Perform zero normal distribution calibration on the measured error data based on the calibration scheme; Generate a calibration report based on the normal distribution calibration. The measured error distribution and the measured calibration parameters are synchronously recorded in the calibration report.

[0034] It should be noted that in this embodiment, according to the updated meter calibration scheme (the error compensation value is "-0.13%"), the electric energy meter is actually calibrated, and the error data during the calibration process is monitored in real time. For example: light load point error: +0.07% (original +0.2% - compensation value 0.13%); rated load point error: -0.23% (original -0.1% - compensation value 0.13%); overload point error: +0.17% (original +0.3% - compensation value 0.13%).

[0035] Furthermore, the calibrated error data is analyzed. Among them, the light load point error: +0.07% (within the preset range); the rated load point error: -0.23% (within the preset range); the overload point error: +0.17% (within the preset range). Therefore, the calibration is completed and a calibration report is generated, recording the error distribution and calibration parameters. For example, the error distribution before calibration: positively biased, with large discreteness; the error distribution after calibration: approaching a normal distribution around zero, and the error values are all within the range of "±0.5%", and the error data conforms to the preset upper and lower threshold range (±0.5%), and the calibration is completed.

[0036] Figure 2 The block diagram of an automatic compensation calibration system for the normal distribution of errors of an intelligent electric energy meter and a terminal according to the present invention is shown.

[0037] As Figure 2 shown, the present invention discloses an automatic compensation calibration system for the normal distribution of errors of an intelligent electric energy meter and a terminal, including a memory and a processor. The memory includes a program for the automatic compensation calibration method of the normal distribution of errors of the intelligent electric energy meter and the terminal. When the program for the automatic compensation calibration method of the normal distribution of errors of the intelligent electric energy meter and the terminal is executed by the processor, the following steps are implemented: Perform a first calibration based on a preset compensation value to obtain first inspection error data for verifying the error distribution situation; Perform calculation and analysis based on the first inspection error data, wherein the data trend and preset parameters are calculated according to a preset upper and lower threshold range; Determine the error compensation data value according to the calculation result, and calculate the error compensation value through the upper and lower threshold range; Push the error compensation value to the compensation position of the work order meter calibration scheme, and calibrate and verify the intelligent electric energy meter based on the automatically compensated meter calibration scheme.

[0038] It should be noted that in this embodiment, automatic compensation and calibration can be achieved by automatically calculating the error compensation value. Among them, the first calibration error compensation value is 0, the error distribution is verified, and then data extraction and calculation are performed. Among them, the first inspection error data is imported into the Cpk calculation tool for calculation and analysis. Specifically, according to the preset upper and lower limit threshold ranges, the data trend and Cpk parameters are calculated to obtain the calculation results.

[0039] Further, determine the error compensation value. Specifically, determine the error compensation data value according to the calculation results, calculate the appropriate error compensation value through the upper and lower limit ranges, and then automatically push the error compensation value to the compensation position of the work order meter calibration scheme to update the calibration parameters. Finally, perform automatic compensation and verification. Among them, calibration and verification are performed according to the meter calibration scheme after automatic compensation to achieve a zero normal distribution of errors.

[0040] According to the embodiment of the present invention, the first inspection error data for obtaining the error distribution situation by performing the first calibration based on the preset compensation value specifically includes: Initialize the error compensation value to zero for the first calibration; Record the error data of the intelligent electric energy meter at different load points; Analyze and verify the error data to obtain the first inspection error data corresponding to the error discreteness and distribution trend.

[0041] It should be noted that in this embodiment, the automatically initialized error compensation value is "0". After the calibration is started, the intelligent electric energy meter starts to work and records the error data at different load points (such as 5% rated current at light load, 100% rated current at rated load, 120% rated current at overload). For example: light load point error: +0.2%, rated load point error: -0.1%, overload point error: +0.3%. Then, error distribution analysis is performed. Among them, it is found that the error distribution discreteness is relatively large and there is a positive deviation phenomenon (such as positive deviation of the light load and overload point errors and negative deviation of the rated load point error).

[0042] According to the embodiment of the present invention, the calculation and analysis based on the first inspection error data specifically includes: Extract the first inspection error data and import it into a preset calculation tool, where the calculation tool includes a Cpk calculation tool; Based on the Cpk calculation tool, calculate the data trend and preset parameters according to the preset upper and lower limit threshold ranges to obtain the calculation results, where the preset parameters include the Cpk value.

[0043] It should be noted that in this embodiment, the Cpk calculation tool is a software or tool for calculating and evaluating the Process Capability Index (Cpk). In the above embodiment, the light load point error is +0.2%, the rated load point error is -0.1%, and the overload point error is +0.3%. According to the preset upper and lower threshold ranges (such as the error upper limit is +0.5% and the lower limit is -0.5%), the Cpk value of the error data is calculated. Among them, the Cpk value corresponds to the error compensation data value. Assuming the calculation result is Cpk = 0.8, it indicates that the distribution of the error data is not ideal and exceeds the controllable range.

[0044] According to an embodiment of the present invention, the determining the error compensation data value according to the calculation result specifically includes: When the error compensation data value is not within the upper threshold range and / or the lower threshold range, calculate the mean error compensation value based on the error compensation data value as the error compensation value; When the error compensation data value is within the upper threshold range and / or the lower threshold range, the compensation value remains unchanged, and the error compensation data value is used as the error compensation value.

[0045] It should be noted that in this embodiment, in the above embodiment, it is stated that Cpk = 0.8. Therefore, it is not within the upper and lower threshold ranges. Calculate the mean of each load point error: (+0.2% + -0.1% + +0.3%) / 3 = +0.13% to determine the error compensation value as "-0.13%", so as to be able to adjust the error mean to near zero. If the Cpk value is within the upper and lower threshold ranges, the compensation value remains unchanged.

[0046] According to an embodiment of the present invention, based on the error compensation value, it is automatically pushed to the compensation position of the work order meter calibration scheme in the meter calibration system to update the calibration parameters to obtain the automatically compensated meter calibration scheme.

[0047] It should be noted that in this embodiment, the calculated error compensation value "-0.13%" is pushed to the compensation position of the work order meter calibration scheme in the calibration system, and after updating the calibration parameters, a new calibration scheme is generated according to the updated compensation value "-0.13%".

[0048] According to an embodiment of the present invention, the calibrating and verifying the smart electric energy meter based on the automatically compensated meter calibration scheme specifically includes: Real-time monitor the measured error data during the calibration process; Perform zero normal distribution calibration on the measured error data based on the meter calibration scheme; Generate a calibration report based on the normal distribution calibration. The measured error distribution and the measured calibration parameters are synchronously recorded in the calibration report.

[0049] It should be noted that in this embodiment, according to the updated meter calibration scheme (the error compensation value is "-0.13%"), the electric energy meter is actually calibrated, and the error data during the calibration process is monitored in real time. For example: light load point error: +0.07% (original +0.2% - compensation value 0.13%); rated load point error: -0.23% (original -0.1% - compensation value 0.13%); overload point error: +0.17% (original +0.3% - compensation value 0.13%).

[0050] Furthermore, the calibrated error data is analyzed. Among them, the light load point error: +0.07% (within the preset range); the rated load point error: -0.23% (within the preset range); the overload point error: +0.17% (within the preset range). Therefore, the calibration is completed and a calibration report is generated, recording the error distribution and calibration parameters. For example, the error distribution before calibration: positively skewed, with large discreteness; the error distribution after calibration: approaching a normal distribution centered at zero, and the error values are all within the range of "±0.5%", and the error data conforms to the preset upper and lower threshold ranges (±0.5%), and the calibration is completed.

[0051] The third aspect of the present invention provides a computer-readable storage medium, which includes a program for an automatic compensation calibration method for the normal distribution of errors of an intelligent electric energy meter and a terminal. When the program for the automatic compensation calibration method for the normal distribution of errors of the intelligent electric energy meter and the terminal is executed by a processor, the steps of an automatic compensation calibration method for the normal distribution of errors of an intelligent electric energy meter and a terminal as described in any one of the above are realized.

[0052] An automatic compensation calibration method and system for the normal distribution of errors of an intelligent electric energy meter and a terminal disclosed in the present invention realizes automatic compensation calibration of errors through an intelligent algorithm, solves the problems of inaccurate segmented compensation values, inaccurate manual adjustment, long time consumption, and low efficiency in the prior art, and significantly improves the calibration accuracy and production efficiency of the electric energy meter. The specific beneficial effects are as follows: The first is automatic compensation calibration: The present invention automatically calculates the error compensation value through a closed-loop compensation algorithm based on statistical process control (SPC), avoiding the inaccuracy of manual adjustment and the problem of multiple repeated calibrations, and significantly improving the accuracy and efficiency of calibration; The second is normal distribution of errors: The errors after automatic compensation are based on a normal distribution centered at zero, ensuring the uniformity and stability of the error distribution and improving the measurement accuracy of the electric energy meter; The third is to improve production efficiency: Through automated error compensation calibration, the time of manual intervention and repeated calibration is reduced, and the production efficiency and quality are significantly improved.

[0053] In several embodiments provided by the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are merely illustrative. For example, the division of the units is only a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components can be combined, or can be integrated into another system, or some features can be ignored, or not executed. In addition, the couplings between the various components shown or discussed, or direct couplings, or communication connections can be through some interfaces. The indirect couplings or communication connections of devices or units can be electrical, mechanical or other forms.

[0054] The units described above as separate components may or may not be physically separated. The components shown as units may or may not be physical units. They can be located in one place or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0055] In addition, each functional unit in the embodiments of the present invention can be all integrated in a processing unit, or each unit can be separately used as a unit, or two or more units can be integrated in a unit. The above-mentioned integrated units can be implemented in the form of hardware, or in the form of hardware plus software functional units.

[0056] Those of ordinary skill in the art can understand that all or part of the steps to implement the above method embodiments can be completed by hardware related to program instructions. The foregoing program can be stored in a computer-readable storage medium. When the program is executed, it executes the steps including the above method embodiments. The foregoing storage media include various media that can store program codes, such as removable storage devices, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical discs.

[0057] Alternatively, if the above-mentioned integrated units of the present invention are implemented in the form of software functional modules and sold or used as independent products, they can also be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the embodiments of the present invention, in essence, or the part that contributes to the prior art 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 causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the methods described in the various embodiments of the present invention. The foregoing storage media include various media that can store program codes, such as removable storage devices, ROM, RAM, magnetic disks, or optical discs.

Claims

1. A method for automatic compensation calibration of normal distribution of smart electric energy meter and terminal error, characterized in that: The following steps are involved: Performing a first calibration based on a preset compensation value to obtain first inspection error data of a calibration error distribution; Performing calculation and analysis based on the first inspection error data, wherein data trends and preset parameters are calculated according to preset upper and lower threshold ranges; Determine the error compensation data value according to the calculation result, and calculate the error compensation value through the upper and lower limit threshold ranges; The error compensation value is pushed to the compensation position of the work order calibration scheme, and the smart electric energy meter is calibrated and verified based on the calibration scheme after automatic compensation.

2. A method for automatic compensation calibration of normal distribution of smart electric energy meter and terminal error according to claim 1, characterized in that: The first calibration based on the preset compensation value to obtain the first inspection error data of the inspection error distribution specifically includes: Initialize the error compensation value to zero for the first calibration; Record the error data of smart energy meters at different load points; The error data is analyzed and verified to obtain the first-check error data corresponding to the error discrete type and distribution trend.

3. A method for automatic compensation calibration of normal distribution of smart electric energy meter and terminal error according to claim 2, characterized in that: The calculation and analysis based on the first inspection error data specifically includes: Extracting the first inspection error data and importing it into a preset calculation tool, wherein the calculation tool includes a Cpk calculation tool; Based on the Cpk calculation tool, the data trend and preset parameters are calculated according to the preset upper and lower limit threshold ranges to obtain the calculation results, wherein the preset parameters include the Cpk value.

4. A method for automatic compensation calibration of normal distribution of smart electric energy meter and terminal error according to claim 3, characterized in that: Determining the error compensation data value according to the calculation result specifically includes: When the error compensation data value is not within the upper threshold range and / or the lower threshold range, calculating a mean error compensation value based on the error compensation data value as the error compensation value; When the error compensation data value is within the upper threshold range and / or the lower threshold range, the compensation value is not changed and is used as the error compensation value based on the error compensation data value.

5. A method for automatic compensation calibration of normal distribution of smart electric energy meter and terminal error according to claim 4, characterized in that: Based on the error compensation value, the compensation position of the work order calibration plan is automatically pushed to the calibration system to update the calibration parameters to obtain the calibration plan after automatic compensation.

6. A method for automatic compensation calibration of normal distribution of smart electric energy meter and terminal error according to claim 5, characterized in that: The calibration and verification of the smart electric energy meter based on the automatic compensation calibration scheme specifically includes: Real-time monitoring of measured error data during the calibration process, and real-time feedback of calibration error values; Performing zero-point normal distribution calibration on the measured error data based on the calibration scheme; A calibration report is generated after calibration based on normal distribution, in which the measured error distribution and the measured calibration parameters are simultaneously recorded.

7. A smart electric energy meter and terminal error normal distribution automatic compensation calibration system, characterized in that: The invention comprises a memory and a processor, wherein the memory comprises a smart electric energy meter and a terminal error normal distribution automatic compensation calibration method program, and the smart electric energy meter and the terminal error normal distribution automatic compensation calibration method program are executed by the processor to implement the following steps: Performing a first calibration based on a preset compensation value to obtain first inspection error data of a calibration error distribution; Performing calculation and analysis based on the first inspection error data, wherein data trends and preset parameters are calculated according to preset upper and lower threshold ranges; Determine the error compensation data value according to the calculation result, and calculate the error compensation value through the upper and lower limit threshold ranges; The error compensation value is pushed to the compensation position of the work order calibration scheme, and the smart electric energy meter is calibrated and verified based on the calibration scheme after automatic compensation.

8. The intelligent electric energy meter and terminal error normal distribution automatic compensation calibration system according to claim 7, characterized in that: The first calibration based on the preset compensation value to obtain the first inspection error data of the inspection error distribution specifically includes: Initialize the error compensation value to zero for the first calibration; Record the error data of smart energy meters at different load points; The error data is analyzed and verified to obtain the first-check error data corresponding to the error discrete type and distribution trend.

9. The intelligent electric energy meter and terminal error normal distribution automatic compensation calibration system according to claim 8, characterized in that: The calculation and analysis based on the first inspection error data specifically includes: Extracting the first inspection error data and importing it into a preset calculation tool, wherein the calculation tool includes a Cpk calculation tool; Based on the Cpk calculation tool, the data trend and preset parameters are calculated according to the preset upper and lower limit threshold ranges to obtain the calculation results, wherein the preset parameters include the Cpk value.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a program for an automatic compensation calibration method for a normal distribution of errors in a smart energy meter and a terminal. When the program for an automatic compensation calibration method for a normal distribution of errors in a smart energy meter and a terminal is executed by a processor, the steps of an automatic compensation calibration method for a normal distribution of errors in a smart energy meter and a terminal as described in any one of claims 1 to 6 are implemented.

Images