CN106324549A - Mutual inductor access-type three-phase intelligent ammeter automatic error detection device monitoring method - Google Patents

Abstract

The invention discloses a mutual inductor access-type three-phase intelligent ammeter automatic error detection device monitoring method belonging to an automatic error detection device monitoring method technology field. The monitoring method comprises a quality control test, uncertainty evaluation, and verification of uncertainty evaluation results. By adopting the monitoring method, the monitoring test of the mutual inductor access-type three-phase intelligent ammeter automatic error detection device is realized, and unmanned management of a testing process is realized, and then subjective errors are prevented; data acquired by the test adopting the monitoring method is stored in a database way, and transmission and archiving management are facilitated, and then paperless management is realized; an ammeter position in the automatic error detection device is used as the comparison set of the uncertainty evaluation results, and after random abnormities are eliminated, the hardware fault problem of the ammeter position is determined. The monitoring method is advantageous in that design is scientific, operation is convenient, accurate, and reliable, and the performance of the mutual inductor access-type three-phase intelligent ammeter automatic error detection device is guaranteed, and detection quality of a mutual inductor access-type three-phase intelligent ammeter is guaranteed.

Description

Transformer access type three-phase intelligent ammeter automatization error verification device monitoring method

Technical field

The invention belongs to the monitoring method technical field of automatization's error verification device, especially relate to a kind of transformer Access type three-phase intelligent ammeter automatization error verification device monitoring method.

Background technology

In order to safeguard the fair and just of electric energy trade settlement, intelligent electric energy meter has to pass through authorized department after dispatching from the factory Legal calibrating, only qualified products just can be installed and used.Along with developing rapidly of China's intelligent grid, intelligent electric energy meter Production scale and installation quantity rise year by year, and traditional artificial calibrating mode inefficiency, human cost are high, are easily introduced subjectivity Error, is difficult to meet the demand for development of calibration operation.

Based on above-mentioned present situation, technical staff develops transformer access type three-phase intelligent ammeter automatic Verification streamline, mutually Sensor access type three-phase intelligent ammeter can complete elementary error test, outward appearance detection test, industrial frequency withstand voltage on this streamline The legal measurement verification projects such as test, coordinate production scheduling platform and the collaborative work of intelligent three-dimensional warehousing system, Ke Yishi Existing transformer access type three-phase intelligent ammeter goes out warehouse-in, calibrating, the automated execution of data process, meets the quantity of calibration operation Greatly, efficiency demand high, unmanned.

Transformer access type three-phase intelligent ammeter automatic Verification streamline comprises the corresponding different calibrating of multiple special plane unit Function, wherein, complete calibra tion is the automatization's error verification device in streamline, and this device has multiple table Position, transformer access type three-phase intelligent ammeter wiring in corresponding epi-position, carry out elementary error test, judge according to test data Whether it meets installation requirement.As a kind of important measurement instrument, the error in dipping of transformer access type three-phase intelligent ammeter Having direct relation with electricity trading clearing justice, the annual test of automatization's error verification device, quantitatively up to millions of, works Load is high, and device performance once changes, and will cause error test data misalignment.If this problem can not be found in time And correction, will result in a large amount of electric energy meter calibration result and break one's promise, and then affect the fair and just of power energy market clearing.So, carry out Performance monitoring work for transformer access type three-phase intelligent ammeter automatization error verification device has highly important meaning Justice.

Current device performance monitoring method uses high-grade standard scale that volume is bigger as test product, continues to use artificial calibrating Platform quality verification method is carried out the work, and this method is applied in automatization's error verification device and had the disadvantage that

1, standard electric energy meter belongs to autonomous device, it is impossible to carry out binding circulation, work effect with automatic Verification flow line tray Rate is low；

2, automatization's error verification device is furnished with multiple epi-position, separate, it is necessary to each epi-position is carried out prison Survey work；

3, for the abnormal data in monitoring test, still can not directly judge to belong to random abnormal or device instrument event Barrier.

Therefore need badly in the middle of prior art and want a kind of novel technical scheme to solve this problem.

Summary of the invention

The technical problem to be solved is: provide transformer access type three-phase intelligent ammeter automatization error testing Device monitoring method, is used for solving current device performance monitoring method and continues to use artificial verification table quality verification method, work effect Rate is low, can not directly judge to belong to random exception or the technology of device instrument failure for the abnormal data in monitoring test Problem.

Transformer access type three-phase intelligent ammeter automatization error verification device monitoring method, is characterized in that: include following Step,

Step one, being assigned epi-position Monitoring instruction by production scheduling platform, transformer access type three-phase intelligent ammeter is automatic The transformer access type three-phase intelligent ammeter test product of calibrating streamline automatic reception smart three-dimensional warehousing system transmission, and will examination Product circulate to corresponding premonitoring epi-position, and the quantity of test product is consistent with the epitope number of premonitoring, and one_to_one corresponding；

Step 2, quality control testing

1. under the conditions of rated voltage, at transformer access type three-phase intelligent ammeter test product, rated current, rated frequency, Repeat the measurement of n electric energy, it is thus achieved that n measured value be referred to as a subgroup, wherein n is the natural number more than or equal to 10,

Keep the rated voltage of test product, rated current, rated frequency constant, repeat test, it is thus achieved that d subgroup, wherein d is Natural number more than or equal to 20；

2., by measured value being uploaded to production scheduling platform, it is as follows that production scheduling platform calculates process:

The measured value of each subgroup is taken arithmetic mean of instantaneous value, obtains the meansigma methods of each subgroup respectively

According to formulaObtain the standard deviation s of each subgroup,

By each subgroup meansigma methods of d subgroupTake arithmetic mean of instantaneous value, it is thus achieved that the meansigma methods of each subgroup meansigma methods

The standard deviation s of each subgroup of d subgroup is taken arithmetic mean of instantaneous value, it is thus achieved that the meansigma methods of each subgroup standard deviation

3., meansigma methods is obtained according to formula (1) to (3)Control the centrage of figureUpper control limitAnd lower control limit

${\mathrm{CL}}_{\stackrel{\‾}{x}}=\stackrel{\‾}{\stackrel{\‾}{x}}---\left(1\right)$

${\mathrm{UCL}}_{\stackrel{\‾}{x}}=\stackrel{\‾}{\stackrel{\‾}{x}}+A_3\stackrel{\‾}{s}---\left(2\right)$

${\mathrm{LCL}}_{\stackrel{\‾}{x}}=\stackrel{\‾}{\stackrel{\‾}{x}}-A_3\stackrel{\‾}{s}---\left(3\right)$

In formula, A₃For the constant relevant to pendulous frequency n；

4., obtain standard deviation s according to formula (4) to (6) and control the centrage CL of figure_s, upper control limit UCL_sAnd lower control limit LCL_s:

${\mathrm{CL}}_s=\stackrel{\‾}{s}---\left(4\right)$

${\mathrm{UCL}}_s=B_4\stackrel{\‾}{s}---\left(5\right)$

${\mathrm{LCL}}_s=B_3\stackrel{\‾}{s}---\left(6\right)$

In formula, B₃, B₄For the constant relevant to pendulous frequency n；

5., production scheduling platform is according to meansigma methodsCentrageUpper control limitAnd lower control limitPaint Meansigma methods processedControl figure,

Production scheduling platform is according to the centrage CL of standard deviation s_s, upper control limit UCL_sWith lower control limit LCL_sDraw mark Quasi-deviation s controls figure,

Meansigma methodsControl in figure, meansigma methodsIt is respectively positioned on upper control limitAnd lower control limitBetween, or flat AverageThe quantity being incremented by continuously or successively decrease continuously is all less than six, or meansigma methodsIt is positioned at centrage continuouslyThe same side Quantity is less than nine, then meansigma methodsControl figure normal,

Standard deviation s controls in figure, and standard deviation s is respectively positioned on upper control limit UCL_sWith lower control limit LCL_sBetween, or mark Quasi-deviation s is incremented by continuously or the quantity successively decreased continuously is all less than six, or standard deviation s is positioned at centrage CL continuously_sSame The quantity of side is less than nine, then standard deviation s controls figure normally,

Meansigma methodsControl figure normal, and standard deviation s control figure is normal, then the epi-position monitored is normal；

The epi-position abnormal to monitoring carries out the evaluation of uncertainty and the checking of evaluation result；

Step 3, the evaluation of uncertainty

1. under the conditions of rated voltage, at transformer access type three-phase intelligent ammeter test product, rated current, rated frequency, The test product treated in checking epi-position carries out electric energy measurement；

2., standard uncertainty evaluation

Standard uncertainty component u (γ_x) evaluation:

To test product repeated measure, pendulous frequency is m, and wherein m is the natural number more than or equal to 10, by measured value and device Standard electric energy meter indicating value compare, obtain m measurement error γ_xi, take the arithmetic mean of instantaneous value of the absolute value of this grouping errorThen should The test standard difference that group is measured is

$s\left({\mathrm{\γ}}_x\right)=\sqrt{\frac{\underset{i=1}{\overset{m}{\Σ}}{({\mathrm{\γ}}_{xi}-\stackrel{\‾}{\mathrm{\γ}})}^2}{m-1}}---\left(7\right)$

Being measured, by m time, the partial uncertainty introduced is

$u\left(y_x\right)=\frac{s\left({\mathrm{\γ}}_x\right)}{\sqrt{m}}---\left(8\right)$

Standard uncertainty component u (γ_b) evaluation:

According to formula

$u\left({\mathrm{\γ}}_b\right)=\frac{a}{k}---\left(9\right)$

In formula, a represents the half width of tested probable value distributed area, and k represents Coverage factor,

Standard uncertainty component u (γ_j) evaluation:

According to formula

$u\left({\mathrm{\γ}}_j\right)=\frac{a}{k}---\left(10\right)$

In formula, a represents the half width of tested probable value distributed area, and k represents Coverage factor,

3., combined standard uncertainty

Standard uncertainty each component relation is

γ_x0=γ_x+γ_b+γ_j (11)

Local derviation is asked to obtain to the above formula right side is every

$c_x=\frac{\∂{\mathrm{\γ}}_{x0}}{\∂{\mathrm{\γ}}_x}=1,c_b=\frac{\∂{\mathrm{\γ}}_{x0}}{\∂{\mathrm{\γ}}_b}=1,c_j=\frac{\∂{\mathrm{\γ}}_{x0}}{\∂{\mathrm{\γ}}_j}=1$

Then combined standard uncertainty is

$u_c^2\left({\mathrm{\γ}}_{x0}\right)=u^2\left({\mathrm{\γ}}_x\right)+u^2\left({\mathrm{\γ}}_b\right)+u^2\left({\mathrm{\γ}}_j\right)$

4., expanded uncertainty U

According to formula

U=k u_c(γ_x0) (12)

Obtaining expanded uncertainty U, in formula, k represents Coverage factor, k=2；

Step 4, the checking of uncertainty evaluation result

By same test product in M epi-position including epi-position to be verified successively wiring repeat step 3, wherein M is big In the natural number equal to 3, M sets the numbered i of epi-position to be verified [1, M], by formula (7), formula (8), formula (9), formula (10) and formula (12), it is thus achieved that the uncertainty evaluation result of epi-position to be verified is U_i,

Test product is after M epi-position is all measured, it is thus achieved that the electric energy measurement data of epi-position to be verified and whole M epi-position The measurement data of electric energy, take the arithmetic mean of instantaneous value of epi-position measurement data to be verified, it is thus achieved that this epi-position measurement data average y_i, take All arithmetic mean of instantaneous values of the measurement data of whole electric energy of M epi-position, it is thus achieved that all the measurement data of the electric energy of M epi-position is equal Value

According to formula

$\left|y_i-\stackrel{\‾}{y}\right|\≤\sqrt{\frac{M-1}{M}}\·U_i---\left(13\right)$

Meet formula (13), uncertainty U of epi-position to be verified_iBeing correct, above-mentioned control figure is abnormal is random abnormal；

Being unsatisfactory for formula (13), there is instrument and equipment fault in epi-position the most to be verified.

Described A₃、B₃, B₄It is that JJF 1,033 2008 " measurement criteria examination specification " is attached with the corresponding relation of pendulous frequency n Corresponding relation in table C-1.

By above-mentioned design, the present invention can bring following beneficial effect:

1. this method can realize the monitoring examination to transformer access type three-phase intelligent ammeter automatization error verification device Test, by and production scheduling platform and the cooperative scheduling of Intelligent storage system, substantially reduce required for monitoring test time Between, reduce delaying work the time of transformer access type three-phase intelligent ammeter automatic calibration streamline, meanwhile, experiment process realizes Unmanned management, it is to avoid subjective error；

2. this method test gathers data with database mode preservation, it is simple to transmit and stay shelves to manage, it is achieved to manage with no paper at all Reason；

3. this method using the epi-position in automatization's error verification device as the comparison collection of uncertainty evaluation result Close, can distinguish whether the control figure of a certain epi-position is random exception extremely, after getting rid of the most extremely, show that this epi-position is implicitly present in Hardware fault problem；

4. this method design science, simple operation, accurately and reliably, it is ensured that transformer access type three-phase intelligent ammeter is automatic The performance changing error verification device is controlled, it is ensured that the calibrating quality of tested transformer access type three-phase intelligent ammeter.

Accompanying drawing explanation

Below in conjunction with the drawings and specific embodiments, the present invention is further illustrated:

Fig. 1 is the flow chart element of transformer of the present invention access type three-phase intelligent ammeter automatization error verification device monitoring method Figure.

Fig. 2 is the monitoring test in the present invention for transformer access type three-phase intelligent ammeter automatization error verification device The structured flowchart of basic embodiment.

Fig. 3 is the calculating in transformer of the present invention access type three-phase intelligent ammeter automatization error verification device monitoring method Control the coefficient table of limit.

Fig. 4 is the meansigma methods of transformer of the present invention access type three-phase intelligent ammeter automatization error verification device monitoring methodControl figure.

Fig. 5 is the standard deviation of transformer of the present invention access type three-phase intelligent ammeter automatization error verification device monitoring method Difference s controls figure.

Detailed description of the invention

As it can be seen, one, Major Systems involved in the present invention constitute

1, the present invention designs Major Systems and includes production scheduling platform, transformer access type three-phase intelligent ammeter automatic Verification Streamline, smart three-dimensional warehousing system.Wherein, production scheduling platform is described calibrating streamline and the pipe of described warehousing system Platform, is responsible for the task such as verification task and project management, warehousing management, data management, is mainly responsible for The work such as the calculating of the assigning of test mission, the management of test product storage and test data；

2, transformer access type three-phase intelligent ammeter automatic Verification streamline is plugged into communication network with described by physics Platform and described warehousing system seamless link, it is possible to achieve transmit on the line to transformer access type three-phase intelligent ammeter, test The operations such as wiring, test execution, automatic sorting, automatic labeling, automatic boxing warehouse-in, complete the base for described electric energy meter simultaneously The detection test of the projects such as this error, pressure, outward appearance, main execution tests test product transmission, test connection, test in the present invention The collection of data and the function such as upload.

3, Intelligent storage system, described warehousing system is responsible for testing the in-out-storehouse management of test product used, in the present invention Main execution verifies the storage of test product, reach the standard grade detection and the functions such as Hui Ku that roll off the production line.

Present invention detection used test test product is through overstability according to JJF1033-2008 " measurement criteria examination specification " The transformer access type three-phase intelligent ammeter of examination.

Two, monitoring method implementing procedure of the present invention

The monitoring test that the present invention comprises includes the test of quality control testing, uncertainty evaluation and evaluation result checking examination Test.The basic mode that above-mentioned test performs is: set up task by production scheduling platform, and it is vertical that described calibrating streamline receives intellectuality The test product of body warehousing system transmission, test product circulation is tested to related device epi-position according to testing program, is tested by streamline After completing, test product returns Intelligent storage system.

(1) quality control testing

1.. first carrying out quality control testing, quality control testing scheme requires test product quantity and assay device epi-position number Equal, under the conditions of rated voltage, rated current, rated frequency, carry out the secondary independent repetition electric energy measurement of n (n >=10), n time is surveyed Amount result is referred to as a subgroup, keeps above-mentioned condition constant, repeats test, measures d (d >=20) individual subgroup altogether；

2.. data measured is uploaded to production scheduling platform, and production scheduling platform according to JJF1033-2008, " examine by measurement criteria Core specification " it is calculated as follows:

The measured value of each subgroup is taken arithmetic mean of instantaneous value, obtains the meansigma methods of each subgroup respectively

According to formulaObtain the standard deviation s of each subgroup,

By each subgroup meansigma methods of d subgroupTake arithmetic mean of instantaneous value, it is thus achieved that the meansigma methods of each subgroup meansigma methods

The standard deviation s of each subgroup of d subgroup is taken arithmetic mean of instantaneous value, it is thus achieved that the meansigma methods of each subgroup standard deviation

3.. calculate meansigma methods according to formula (1) to (3)Control the centrage of figureUpper control limitAnd lower control limit

${\mathrm{CL}}_{\stackrel{\‾}{x}}=\stackrel{\‾}{\stackrel{\‾}{x}}---\left(1\right)$

${\mathrm{UCL}}_{\stackrel{\‾}{x}}=\stackrel{\‾}{\stackrel{\‾}{x}}+A_3\stackrel{\‾}{s}---\left(2\right)$

${\mathrm{LCL}}_{\stackrel{\‾}{x}}=\stackrel{\‾}{\stackrel{\‾}{x}}-A_3\stackrel{\‾}{s}---\left(3\right)$

4.. calculate standard deviation s according to formula (4) to (6) and control the centrage CL of figure_s, upper control limit UCL_sAnd lower control limit LCL_s；

${\mathrm{CL}}_s=\stackrel{\‾}{s}---\left(4\right)$

${\mathrm{UCL}}_s=B_4\stackrel{\‾}{s}---\left(5\right)$

${\mathrm{LCL}}_s=B_3\stackrel{\‾}{s}---\left(6\right)$

In formula, A₃, B₃, B₄Value relevant to pendulous frequency n, A₃, B₃, B₄Value by JJF 1,033 2008 " metering mark Quasi-examination specification " form that calculates the coefficient table controlling limit in subordinate list C-1 i.e. accompanying drawing 3 can look into；

5.. production scheduling platform draws meansigma methods the most automatically according to above-mentioned key parameterControl figure and standard deviation s is controlled Drawing, meansigma methods in analysis and Control figureWith standard deviation s situation, work as meansigma methodsOr standard deviation s occurs that a value falls in control Beyond system limit, or continuous more than 6 be incremented by or continuous more than 6 successively decrease, or continuous more than 9 are positioned at centrage together During side, assert that above-mentioned control figure exists abnormal, occur controlling the epi-position that figure is abnormal, uncertainty evaluation test need to be carried out and comment Determine result verification test.

(2) qualification test of uncertainty

1.. test procedure follows JJF 1059.1-2012 " evaluation of uncertainty in measurement and expression " and JJF1033-2008 The guidance of related specifications such as " measurement criteria examination specifications ", carries out certificate test, at volume by test product and above-mentioned abnormal epi-position wiring Under the conditions of determining voltage, rated current, rated frequency, electric flux is measured；

2.. standard uncertainty is evaluated

Uncertainty of measurement is made up of some components, and each component correspondence represents the standard deviation of its probability distribution and estimates Value, is repeated to examine and determine test product by fixing epi-position in the present invention, and partial uncertainty has: (1) is by test test product error of indication γ_xPoint Partial uncertainty u (the γ that scattered property causes_x)；(2) transformer access type three-phase intelligent ammeter automatization error verification device phase Answer the measurement loop errer γ of epi-position_bPartial uncertainty u (the γ caused_b)；(3) error information γ is recorded_jThe revision of the conventionization is whole to be caused Partial uncertainty u (γ_j).Wherein u (γ_x) can be calculated by the standard deviation of a series of measurement data, i.e. use type A evaluation Method, u (γ_b) and u (γ_j) can be calculated by the probability distribution estimated according to prior information, i.e. use type B evaluation method.

Standard uncertainty component u (γ_x) evaluation: by device to test product repeated measure, if pendulous frequency be m (m >= 10), measured value is subtracted each other with the standard electric energy meter indicating value in device, obtains m measurement error γ_xi, take the absolute of this grouping error The arithmetic mean of instantaneous value of valueThe test standard difference that then this group is measured is

$s\left({\mathrm{\γ}}_x\right)=\sqrt{\frac{\underset{i=1}{\overset{m}{\Σ}}{({\mathrm{\γ}}_{xi}-\stackrel{\‾}{\mathrm{\γ}})}^2}{m-1}}---\left(7\right)$

Being measured, by m time, the partial uncertainty introduced is

$u\left({\mathrm{\γ}}_x\right)=\frac{s\left({\mathrm{\γ}}_x\right)}{\sqrt{m}}---\left(8\right)$

Standard uncertainty component u (γ_b) evaluation use type B evaluation:

$u\left({\mathrm{\γ}}_b\right)=\frac{a}{k}---\left(9\right)$

In formula, a represents the half width of tested probable value distributed area, the maximum error here allowed equal to test epi-position Value absolute value, k represents Coverage factor, shows through lot of experiments statistical analysis, and the error of test epi-position belongs to and is uniformly distributed, because of This looks into table 2 in JJF 1059.1-2012 " evaluation of uncertainty in measurement and expression " and can obtain

Standard uncertainty component u (γ_j) evaluation use type B evaluation:

$u\left({\mathrm{\γ}}_j\right)=\frac{a}{k}---\left(10\right)$

In formula, a represents the half width of tested probable value distributed area, here equal to the half of test product rounding interval, k table Show Coverage factor, lot of experiments statistical analysis to show by the standard uncertainty component of the test product whole introducing of the error revision of the conventionization and belong to equal Even distribution, therefore tables look-up and can obtain

3.. combined standard uncertainty

The above analysis, standard uncertainty each component relation can be write as

γ_x0=γ_x+γ_b+γ_j (11)

Local derviation is asked to obtain to the above formula right side is every

$c_x=\frac{\∂{\mathrm{\γ}}_{x0}}{\∂{\mathrm{\γ}}_x}=1,c_b=\frac{\∂{\mathrm{\γ}}_{x0}}{\∂{\mathrm{\γ}}_b}=1,c_j=\frac{\∂{\mathrm{\γ}}_{x0}}{\∂{\mathrm{\γ}}_j}=1$

Then combined standard uncertainty is represented by

$u_c^2\left({\mathrm{\γ}}_{x0}\right)=u^2\left({\mathrm{\γ}}_x\right)+u^2\left({\mathrm{\γ}}_b\right)+u^2\left({\mathrm{\γ}}_j\right)$

4.. expanded uncertainty

U=k u_c(γ_x0) (12)

Expanded uncertainty U be can be calculated by formula (12), in transformer access type three-phase intelligent ammeter metrological standard unit During evaluation, the value of Coverage factor k is generally k=2；

(3) the checking test of uncertainty evaluation result

Then the checking test of above-mentioned evaluation result is carried out, multiple by automatization's error verification device during test Epi-position is as comparison set, and testing program requires that same test product depends in M (M >=3) the individual epi-position including epi-position to be verified Secondary wiring is tested, and under the conditions of rated voltage, rated current, rated frequency, repeated measure is repeatedly, if the numbered i of epi-position to be verified [1, M], by formula (7), formula (8), formula (9), formula (10) and formula (12), it is thus achieved that the uncertainty evaluation result of this epi-position is U_i, When described test product is after whole M epi-positions are measured, the arithmetic mean of instantaneous value y of epi-position measurement data to be verified can be obtained_iWith whole M The arithmetic mean of instantaneous value of individual epi-position measurement dataIts correctness is verified by formula (13).

$\left|y_i-\stackrel{\‾}{y}\right|\≤\sqrt{\frac{M-1}{M}}\·U_i---\left(13\right)$

When formula that and if only if (13) inequality is set up, it is believed that uncertainty U of epi-position to be verified_iIt is correct, and above-mentioned It is random abnormal for controlling figure abnormal.If inequality is false, then show really to be existed by checking device instrument and equipment fault, need Take to disassemble the corrective actions such as maintenance to relevant device.

Claims (2)

1. transformer access type three-phase intelligent ammeter automatization error verification device monitoring method, is characterized in that: include following step Suddenly,

Step one, assigned epi-position Monitoring instruction by production scheduling platform, transformer access type three-phase intelligent ammeter automatic Verification The transformer access type three-phase intelligent ammeter test product of streamline automatic reception smart three-dimensional warehousing system transmission, and by test product stream Going to corresponding premonitoring epi-position, the quantity of test product is consistent with the epitope number of premonitoring, and one_to_one corresponding；

Step 2, quality control testing

1., under the conditions of rated voltage, at transformer access type three-phase intelligent ammeter test product, rated current, rated frequency, repeat Carry out the measurement of n electric energy, it is thus achieved that n measured value be referred to as a subgroup, wherein n is the natural number more than or equal to 10,

Keep the rated voltage of test product, rated current, rated frequency constant, repeat test, it is thus achieved that d subgroup, wherein d is for being more than Natural number equal to 20；

2., by measured value being uploaded to production scheduling platform, it is as follows that production scheduling platform calculates process:

The measured value of each subgroup is taken arithmetic mean of instantaneous value, obtains the meansigma methods of each subgroup respectively

According to formulaObtain the standard deviation s of each subgroup,

By each subgroup meansigma methods of d subgroupTake arithmetic mean of instantaneous value, it is thus achieved that the meansigma methods of each subgroup meansigma methods

The standard deviation s of each subgroup of d subgroup is taken arithmetic mean of instantaneous value, it is thus achieved that the meansigma methods of each subgroup standard deviation

3., meansigma methods is obtained according to formula (1) to (3)Control the centrage of figureUpper control limitAnd lower control limit

${\mathrm{CL}}_{\stackrel{\‾}{x}}=\stackrel{\‾}{\stackrel{\‾}{x}}---\left(1\right)$

${\mathrm{UCL}}_{\stackrel{\‾}{x}}=\stackrel{\‾}{\stackrel{\‾}{x}}+A_3\stackrel{\‾}{s}---\left(2\right)$

${\mathrm{LCL}}_{\stackrel{\‾}{x}}=\stackrel{\‾}{\stackrel{\‾}{x}}-A_3\stackrel{\‾}{s}---\left(3\right)$

In formula, A₃For the constant relevant to pendulous frequency n；

4., obtain standard deviation s according to formula (4) to (6) and control the centrage CL of figure_s, upper control limit UCL_sAnd lower control limit LCL_s:

${\mathrm{CL}}_s=\stackrel{\‾}{s}---\left(4\right)$

${\mathrm{UCL}}_s=B_4\stackrel{\‾}{s}---\left(5\right)$

${\mathrm{LCL}}_s=B_3\stackrel{\‾}{s}---\left(6\right)$

In formula, B₃, B₄For the constant relevant to pendulous frequency n；

5., production scheduling platform is according to meansigma methodsCentrageUpper control limitAnd lower control limitDraw average ValueControl figure,

Production scheduling platform is according to the centrage CL of standard deviation s_s, upper control limit UCL_sWith lower control limit LCL_sDraw standard deviation Difference s controls figure,

Meansigma methodsControl in figure, meansigma methodsIt is respectively positioned on upper control limitAnd lower control limitBetween, or meansigma methods The quantity being incremented by continuously or successively decrease continuously is all less than six, or meansigma methodsIt is positioned at centrage continuouslyThe quantity of the same side Less than nine, then meansigma methodsControl figure normal,

Standard deviation s controls in figure, and standard deviation s is respectively positioned on upper control limit UCL_sWith lower control limit LCL_sBetween, or standard deviation Difference s is incremented by continuously or the quantity successively decreased continuously is all less than six, or standard deviation s is positioned at centrage CL continuously_sThe same side Quantity is less than nine, then standard deviation s controls figure normally,

Meansigma methodsControl figure normal, and standard deviation s control figure is normal, then the epi-position monitored is normal；

The epi-position abnormal to monitoring carries out the evaluation of uncertainty and the checking of evaluation result；

Step 3, the evaluation of uncertainty

1., under the conditions of rated voltage, at transformer access type three-phase intelligent ammeter test product, rated current, rated frequency, treat Test product in checking epi-position carries out electric energy measurement；

2., standard uncertainty evaluation

Standard uncertainty component u (γ_x) evaluation:

To test product repeated measure, pendulous frequency is m, and wherein m is the natural number more than or equal to 10, by measured value and the mark in device Quasi-electric energy meter indicating value compares, and obtains m measurement error γ_xi, take the arithmetic mean of instantaneous value of the absolute value of this grouping errorThen this group is surveyed The test standard difference of amount is

$s\left({\mathrm{\γ}}_x\right)=\sqrt{\frac{\underset{i=1}{\overset{m}{\mathrm{\Σ}}}{({\mathrm{\γ}}_{xi}-\stackrel{\‾}{\mathrm{\γ}})}^2}{m-1}}---\left(7\right)$

Being measured, by m time, the partial uncertainty introduced is

$u\left({\mathrm{\γ}}_x\right)=\frac{s\left({\mathrm{\γ}}_x\right)}{\sqrt{m}}---\left(8\right)$

Standard uncertainty component u (γ_b) evaluation:

According to formula

$u\left({\mathrm{\γ}}_b\right)=\frac{a}{k}---\left(9\right)$

In formula, a represents the half width of tested probable value distributed area, and k represents Coverage factor,

Standard uncertainty component u (γ_j) evaluation:

According to formula

$u\left({\mathrm{\γ}}_j\right)=\frac{a}{k}---\left(10\right)$

In formula, a represents the half width of tested probable value distributed area, and k represents Coverage factor,

3., combined standard uncertainty

Standard uncertainty each component relation is

γ_x0=γ_x+γ_b+γ_j (11)

Local derviation is asked to obtain to the above formula right side is every

$c_x=\frac{\∂{\mathrm{\γ}}_{x0}}{\∂{\mathrm{\γ}}_x}=1,c_b=\frac{\∂{\mathrm{\γ}}_{x0}}{\∂{\mathrm{\γ}}_b}=1,c_j=\frac{\∂{\mathrm{\γ}}_{x0}}{\∂{\mathrm{\γ}}_j}=1$

Then combined standard uncertainty is

$u_c^2\left({\mathrm{\γ}}_{x0}\right)=u^2\left({\mathrm{\γ}}_x\right)+u^2\left({\mathrm{\γ}}_b\right)+u^2\left({\mathrm{\γ}}_j\right)$

4., expanded uncertainty U

According to formula

U=k u_c(γ_x0) (12)

Obtaining expanded uncertainty U, in formula, k represents Coverage factor, k=2；

Step 4, the checking of uncertainty evaluation result

By same test product in M epi-position including epi-position to be verified successively wiring repeat step 3, wherein M is for being more than In the natural number of 3, M sets the numbered i of epi-position to be verified [1, M], by formula (7), formula (8), formula (9), formula (10) and formula (12), The uncertainty evaluation result obtaining epi-position to be verified is U_i,

Test product is after M epi-position is all measured, it is thus achieved that the electric energy measurement data of epi-position to be verified and the electricity of whole M epi-position The measurement data of energy, takes the arithmetic mean of instantaneous value of epi-position measurement data to be verified, it is thus achieved that this epi-position measurement data average y_i, take all The arithmetic mean of instantaneous value of the measurement data of whole electric energy of M epi-position, it is thus achieved that all measurement data averages of the electric energy of M epi-position

According to formula

$\left|y_i-\stackrel{\‾}{y}\right|\≤\sqrt{\frac{M-1}{M}}\·U_i---\left(13\right)$

Meet formula (13), uncertainty U of epi-position to be verified_iBeing correct, above-mentioned control figure is abnormal is random abnormal；

Being unsatisfactory for formula (13), there is instrument and equipment fault in epi-position the most to be verified.

Transformer the most according to claim 1 access type three-phase intelligent ammeter automatization error verification device monitoring method, It is characterized in that: described A₃、B₃, B₄It is that JJF 1,033 2008 " measurement criteria examination specification " is attached with the corresponding relation of pendulous frequency n Corresponding relation in table C-1.