CN108595516A - Electric energy meter error method for analyzing stability, device, storage medium and equipment - Google Patents
Electric energy meter error method for analyzing stability, device, storage medium and equipment Download PDFInfo
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Abstract
The invention discloses a kind of electric energy meter error method for analyzing stability, device, storage medium and equipment, this method to include：According to setting Plan of Double Sampling Inspection, sampling observation obtains the error information of a collection of electric energy meter；Histogram and/or just too distribution map are drawn using the error information；Based on the histogram and/or just too error robustness of batch electric energy meter described in profiling analysis.Present invention data and figure are according to the error robustness for illustrating electric energy meter, and the experience that can exclude relies on and analytical error.
Description
Technical field
The present invention relates to technical field of electric power more particularly to a kind of electric energy meter error method for analyzing stability, device, storages
Medium and equipment.
Background technology
The error robustness for correctly understanding the electric energy meter of each producer's production, contributes to the electric energy meter for positioning each producer to miss
Poor performance bottleneck or potential performance bottleneck.In the prior art, the experience for only relying on staff differentiates the electric energy of different manufacturers
The error robustness difference of table, this so that the differentiation result of error robustness is irregular and different because of staff's experience,
And it can not intuitively obtain error robustness difference.
Invention content
The present invention provides a kind of electric energy meter error method for analyzing stability, to reduce electric energy meter error stability analysis to warp
The dependence tested, and improve the accuracy of electric energy meter error stability analysis.The electric energy meter error method for analyzing stability, including：
According to setting Plan of Double Sampling Inspection, sampling observation obtains the error information of a collection of electric energy meter；Using the error information draw histogram and/or
Just too distribution map；Based on the histogram and/or just too error robustness of batch electric energy meter described in profiling analysis.
In one embodiment, according to setting Plan of Double Sampling Inspection, sampling observation obtains the error information of a collection of electric energy meter, including：According to
Electric energy meter manufacturer, setting electric energy meter model, setting electric energy meter quantity and setting error dot are set, sampling observation obtains described batch of electricity
The error information of energy table.
In one embodiment, histogram is drawn using the error information, including：It is ranked sequentially in the error information
All error amounts find out worst error value and minimum error values；It is calculated using the worst error value and the minimum error values
It obtains very poor；Using the very poor and setting group number be calculated group away from；According to described group away to the mistake in the error information
Difference is grouped, and calculates the frequency per set of error values；Utilize the error amount of each frequency and error information sum
The frequency of each set of error values is calculated；Histogram is drawn using the frequency of each set of error values, obtains the histogram
Figure；And/or
Just too distribution map is drawn using the error information, including：Calculate the average value of error amount in the error information；
The variance of error amount in the error information is calculated using error amount in the average value and the error information；Using institute
It states variance and standard deviation is calculated；Using the average value and the standard deviation as the population mean just too in distribution formula
Value and standard deviation substitute into just too distribution formula；Using substitute into after the average value and the standard deviation just too distribution formula is painted
Make the just too distribution map.
In one embodiment, the error of based on the histogram and/or just too batch electric energy meter described in profiling analysis is stablized
Property, including：The histogram obtained by comparing according to the error information of the electric energy meter of multiple and different electric energy meter manufacturers, and/
Or by comparing according to the error information of the electric energy meters of multiple and different electric energy meter manufacturers obtain just too distribution map, identification miss
The best electric energy meter manufacturer of poor stability.
The present invention also provides a kind of electric energy meter error analysis of stability analysis apparatus, to reduce electric energy meter error stability analysis pair
The dependence of experience, and improve the accuracy of electric energy meter error stability analysis.The electric energy meter error analysis of stability analysis apparatus, packet
It includes：Error information acquiring unit, is used for：According to setting Plan of Double Sampling Inspection, sampling observation obtains the error information of a collection of electric energy meter；Datagram
Shape drawing unit, is used for：Histogram and/or just too distribution map are drawn using the error information；Error robustness analytic unit,
For：Based on the histogram and/or just too error robustness of batch electric energy meter described in profiling analysis.
In one embodiment, error information acquiring unit, including：Error information acquisition module, is used for：According to setting electric energy
Table manufacturer, setting electric energy meter model, setting electric energy meter quantity and setting error dot, sampling observation obtain the mistake of described batch of electric energy meter
Difference data.
In one embodiment, datagraphic drawing unit, including：
Histogram drafting module, is used for：Histogram is drawn using the error information, including：Extreme value acquisition module is used
In：All error amounts being ranked sequentially in the error information, find out worst error value and minimum error values；Very poor calculating mould
Block is used for：It is calculated using the worst error value and the minimum error values very poor；Group is used for away from computing module：It utilizes
The very poor and setting group number be calculated group away from；Frequency acquisition module, is used for：According to described group away in the error information
Error amount be grouped, and calculate per set of error values the frequency；Frequency computing module, is used for：Utilize each frequency and institute
The frequency of each set of error values is calculated in the error amount sum for stating error information；Histogram generation module, is used for：Using described each
The frequency of set of error values draws histogram, obtains the histogram；And/or
Just too distribution map drafting module, is used for：Just too distribution map is drawn using the error information, including：Average value meter
Module is calculated, is used for：Calculate the average value of error amount in the error information；Variance computing module, is used for：Utilize the average value
The variance of error amount in the error information is calculated with error amount in the error information；Standard deviation computing module, is used for：
Standard deviation is calculated using the variance；Just too distribution formula generation module, is used for：By the average value and the standard deviation
Respectively as just too in distribution formula population mean and standard deviation substitute into just too distribution formula；Just too distribution map generates mould
Block is used for：Using substitute into after the average value and the standard deviation just too distribution formula draws the just too distribution map.
In one embodiment, error robustness analytic unit, including：Error robustness analysis module, is used for：By comparing
According to the histogram that the error information of the electric energy meter of multiple and different electric energy meter manufacturers obtains, and/or by comparing according to more
The just too distribution map that the error information of the electric energy meter of a difference electric energy meter manufacturer obtains, the best electricity of identification error stability
It can table manufacturer.
The present invention also provides a kind of computer readable storage mediums, to reduce electric energy meter error stability analysis to experience
It relies on, and improves the accuracy of electric energy meter error stability analysis.Computer journey is stored on the computer readable storage medium
The step of sequence, which realizes above-described embodiment the method when being executed by processor.
The present invention also provides a kind of computer equipments, to reduce dependence of the electric energy meter error stability analysis to experience, and
Improve the accuracy of electric energy meter error stability analysis.The computer equipment, including memory, processor and it is stored in memory
Computer program that is upper and can running on a processor, the processor realize side described in above-described embodiment when executing described program
The step of method.
The embodiment of the present invention obtains the error information for being detected electric energy meter in the form of sampling observation, and with histogram and/or just
The form of state distribution map gradually dissects each producer's electric energy meter error stability distribution situation, is according to explanation with data, trend
The error robustness of each producer's electric energy meter, the experience for eliminating electric energy meter error stability analysis relies on and error.
Description of the drawings
In order to more clearly explain the embodiment of the invention or the technical proposal in the existing technology, to embodiment or will show below
There is attached drawing needed in technology description to be briefly described, it should be apparent that, the accompanying drawings in the following description is only this
Some embodiments of invention for those of ordinary skill in the art without creative efforts, can be with
Obtain other attached drawings according to these attached drawings.In the accompanying drawings：
Fig. 1 is the flow diagram of the electric energy meter error method for analyzing stability of the embodiment of the present invention；
Fig. 2 is the method flow diagram for drawing histogram in one embodiment of the invention using error information；
Fig. 3 is to draw the just too method flow diagram of distribution map using error information in one embodiment of the invention；
Fig. 4 is the error robustness analysis process schematic diagram of one embodiment of the invention；
Fig. 5 is the error distribution histogram that method according to an embodiment of the invention obtains；
Fig. 6 is the error distribution just too distribution map that method according to an embodiment of the invention obtains；
Fig. 7 is the obtained more producer's errors of method according to an embodiment of the invention just too distribution map；
Fig. 8 is the structural schematic diagram of the electric energy meter error analysis of stability analysis apparatus of one embodiment of the invention；
Fig. 9 is the structural schematic diagram of histogram drafting module in one embodiment of the invention；
Figure 10 is the just too structural schematic diagram of distribution map drafting module in one embodiment of the invention；
Figure 11 is the structural schematic diagram of the computer equipment of one embodiment of the invention.
Specific implementation mode
Understand in order to make the object, technical scheme and advantages of the embodiment of the invention clearer, below in conjunction with the accompanying drawings to this hair
Bright embodiment is described in further details.Here, the illustrative embodiments of the present invention and their descriptions are used to explain the present invention, but simultaneously
It is not as a limitation of the invention.
Experience in order to exclude electric energy meter error stability relies on and analytical error, and the present invention provides a kind of electric energy meter mistakes
Poor method for analyzing stability.
Fig. 1 is the flow diagram of the electric energy meter error method for analyzing stability of the embodiment of the present invention.As shown in Figure 1, this
The electric energy meter error method for analyzing stability of inventive embodiments, it may include：
Step 110：According to setting Plan of Double Sampling Inspection, sampling observation obtains the error information of a collection of electric energy meter；
Step 120：Histogram and/or just too distribution map are drawn using the error information；
Step 130：Based on the histogram and/or just too error robustness of batch electric energy meter described in profiling analysis.
In step 110, sampling observation rule can be set in setting Plan of Double Sampling Inspection.For example, it may be determined that sampling observation electric energy meter
Producer and electric energy meter model determine sampling observation electric energy meter quantity, and determine sampling observation calibrating scheme (error dot).The error of electric energy meter
Data for example may be used automation inspection table line and examine and determine to obtain.In the step 120, the abscissa of histogram and just too distribution map can
To be error amount, ordinate can reflect the concentration situation of error amount.In step 130, can divide very much from histogram and/or just
The error robustness of the graphic characteristics analysis electric energy meter of Butut.
In the embodiment of the present invention, electric energy meter error data (calibrating data) are obtained by sampling observation, and then be based on the margin of error
According to obtaining histogram and/or just too distribution map, and based on this progress electric energy meter error stability analysis, can not only make to electricity
Can the analysis of Watch Error stability carried out according to data, avoid the dependence of artificial experience, and histogram and/or be just distributed very much
Figure can intuitively reflect that such as error robustness of certain producer or certain batch electric energy meter, analysis are convenient.
When it is implemented, according to setting Plan of Double Sampling Inspection, sampling observation obtains the method (step of the error information of a collection of electric energy meter
110), may include：According to setting electric energy meter manufacturer, setting electric energy meter model, setting electric energy meter quantity and setting error
Point, sampling observation obtain the error information of described batch of electric energy meter.In embodiment, each electric energy meter can obtain two or more errors
Value.
Fig. 2 is the method flow diagram for drawing histogram in one embodiment of the invention using error information.As shown in Fig. 2, step
In rapid 120, the method for drawing histogram using the error information may include：
Step 1211：All error amounts being ranked sequentially in the error information, find out worst error value and minimal error
Value；
Step 1212：It is calculated using the worst error value and the minimum error values very poor；
Step 1213：Using the very poor and setting group number be calculated group away from；
Step 1214：According to described group away from being grouped to the error amount in the error information, and calculate per grouping error
The frequency of value；
Step 1215：Each set of error values is calculated using the error amount sum of each frequency and the error information
Frequency；
Step 1216：Histogram is drawn using the frequency of each set of error values, obtains the histogram.
In step 1211, such as can be by all error amounts in error information according to being ranked sequentially from small to large.
Error information after being ranked sequentially easily can therefrom find worst error value and minimum error values.In step 1212, pole
Difference is to be used for indicating the measures of variation in statistics, the gap between maxima and minima, i.e. maximum value in statistics
Subtract the data of minimum value gained.In above-mentioned steps 1213, group number can be suitably determined according to the data volume of error information.Group away from
It refer to very poor divided by group number.In step 1214, the frequency can be obtained by traversal.Such as it falls in -0.08~-0.01 range
Error amount has 9, then the frequency of the grouping error data can be 9.In step 1214, if error information sum is 600,
The frequency (relative frequency) of the grouping error data can be 9/600, i.e., 0.015.It, can be by each set of error values in step 1216
Error range and frequency draw out histogram respectively as abscissa and ordinate.
Fig. 3 is to draw the just too method flow diagram of distribution map using error information in one embodiment of the invention.Such as Fig. 3 institutes
Show, in step 120, draws the just too method of distribution map using the error information, may include：
Step 1221：Calculate the average value of error amount in the error information；
Step 1222：It is calculated in the error information accidentally using error amount in the average value and the error information
The variance of difference；
Step 1223：Standard deviation is calculated using the variance；
Step 1224：Using the average value and the standard deviation as just too in distribution formula population mean and
Standard deviation substitutes into just too distribution formula；
Step 1225：It draws and described is just dividing very much using the just too distribution formula after the average value and the standard deviation is substituted into
Butut.
In step 1221~step 1223, mean value refers to the arithmetic mean of instantaneous value of one group of data, can indicate the concentration of data
Position, calculation formula can be x=(x1+x2+...+xn)/n, wherein x indicate mean value, x1, x2 ..., xn indicate error amount, n
Indicate the total number of error amount.Variance refers to the average of the quadratic sum of each data and the difference of average, calculation formula s^2=
[(x1-x) ^2+ (x2-x) ^2+...... (xn-x) ^2]/(n), x is average.Standard deviation refers to the arithmetic square root of variance.
In above-mentioned steps 1224, inventor according to error amount and the corresponding frequency of error (relative frequency) it is considered that can obtain just
State distribution map (error amount and frequency are respectively as abscissa and ordinate), while histogram can be obtained according to frequency, and work as
Error data value number infinitely increases, and group is away from micro component is decreased to, i.e., when error amount tends to consecutive variations, the shape of histogram will
Gradually tend to the full curve of a crest, this meets normal distribution curve, in conjunction with the meaning of average value and variance, so hair
Now using the average value and the standard deviation as just too in distribution formula population mean and standard deviation substitute into just
Too distribution formula, obtain just too distribution map can be used in analytical error stability.
In embodiment, step 120 specific implementation mode may include that the utilization shown in Fig. 2 error information draws histogram
The specific implementation step of figure and/or shown in Fig. 3 draw the just too specific implementation mode of distribution map using the error information
Specific implementation step.
In embodiment, step 130, based on the histogram and/or just too error of batch electric energy meter described in profiling analysis
The method of stability may include：It is obtained by comparing the error information of the electric energy meter according to multiple and different electric energy meter manufacturers
The histogram arrived, and/or obtained just by comparing the error information of the electric energy meter according to multiple and different electric energy meter manufacturers
Too distribution map, the best electric energy meter manufacturer of identification error stability.It, can be by comparing for example just too in other embodiment
The error robustness of the electric energy meter of each manufacturer of standard error analysis of distribution map.
In embodiment, electric energy meter error method for analyzing stability may include：The electric energy meter of each producer is inspected by random samples,
Stability analysis is carried out to the gauging error data of generation；And reflect the steady of ammeter by key index data and its distribution map
Qualitative differences.The electric energy meter error performance bottleneck of each producer or potential performance bottleneck can be positioned with this.With data, trend
For according to the error robustness for illustrating each producer's electric energy meter, the experience that excludes relies on and error.
In embodiment, the error information for being detected electric energy meter is obtained in the form of sampling observation, and with histogram, normal distribution
Form gradually dissect each producer's electric energy meter error stability distribution situation.With normal distribution formula and calculus theoretical calculation
Error density and draw each producer's normal distribution of error figure.Sampling observation rule is as follows：
(1) sampling observation electric energy meter producer and electric energy meter model are determined；
(2) sampling observation electric energy meter quantity is determined；
(3) sampling observation calibrating scheme (error dot) is determined.
In embodiment, error robustness overall flow figure is as shown in figure 4, concrete analysis step may include：
(1) all error informations are taken into a minimum value and a maximum value by being ranked sequentially from small to large, and
Calculate extreme value.
(2) according to the error original value data of all propositions, average value is calculated；
(3) according to the error original value data and average value of all propositions, variance yields is calculated.
(4) further according to variance yields, standard deviation is obtained by standard deviation formula.
(5) traversed to obtain the number that the same error amount occurs in entire error information to each error information.
(6) relative frequency for accounting for entire error information is calculated according to the corresponding frequency of error of each error.
(7) normal distribution is obtained according to error amount and the corresponding relative frequency of error.
The implementation of the present invention illustrated below and feasibility：
1, go out error initial data by sampling observation rule search and show, such as 600 records, as shown in table 1.
1 initial error tables of data 2 of table carries out statistical disposition to initial error data, draws：
(1) descending, it is arranged in sequence, finds out maximum value and minimum value.
(2) it calculates very poor：Very poor=maximum value-minimum value
(3) calculating group away from：Very poor divided by group figure out group away from；
(4) with group away from grouping calculate the frequency, frequency (relative frequency), as shown in table 2；
(5) histogram is painted, as shown in Figure 5.
| Serial number | Grouping | Frequency | Frequency (relative frequency) |
| 1 | - 0.08~-0.01 | 9 | 0.0150 |
| 2 | - 0.01~-0.06 | 164 | 0.2729 |
| 3 | - 0.06~+0.13 | 350 | 0.5824 |
| 4 | + 0.13~+0.20 | 68 | 0.1148 |
| 5 | + 0.20~+0.27 | 5 | 0.0083 |
| 6 | + 0.27~+0.34 | 4 | 0.0067 |
2 frequency distribution data table of table
3, rule：
The presence of random error in detection process keeps analysis result height uneven, i.e., measurement data has the characteristic of dispersion.
But the distribution of measurement data is not disorderly and unsystematic, and certain statistical law is presented.Data between average value are more,
Data are few within the scope of other.The smaller data of bigger are less, i.e., measured value has apparent central tendency.It is contemplated that working as
Error data value number infinitely increases, and when group is away from micro component, i.e. error amount consecutive variations is reduced to, the shape of histogram will gradually become
In a crest.Full curve, this meets normal distribution curve.Normal distribution curve, also known as Gaussian Profile.Its curve is：It is right
Claim bell, small at both ends and big in the middle, distribution curve has peak, as shown in Figure 6.
4, error character calculates：
Normal distribution formula is：
Wherein：Y indicates probability density, it is the function of variable x, that is, indicates the frequency that measured value x occurs；μ is overall flat
Mean value, i.e., the average value of unlimited error information are the corresponding x values of curve maximum, and in the presence of no systematic error, it is just
It is actual value.σ is standard deviation in population, is that one of inflection point of normal distribution curve both sides arrives straight line x=μ distances.σ reflects mistake
The degree of scatter of difference.σ is bigger, and curve is more flat, and error amount more disperses, and σ is smaller, and curve is more sharp, and measured value is more concentrated.σ
It is two basic parameters of normal distribution with μ.Generally indicated with N (μ, σ ^2)：Population mean is μ, and standard deviation is σ's
Normal distribution.μ reflects that the central tendency of error Distribution value, μ reflect the degree of scatter of error Distribution value.Peak-shaped curve peak pair
The abscissa x- μ values answered are equal to zero, show the maximum probability that the value that error is zero occurs.Curve is under peak value is quick to both sides
Drop illustrates that the probability that small error occurs is big, and the probability that big error occurs is small, and king-sized error probability of occurrence is minimum.Error
Distribution has limited range, and value size is bounded.
By taking the comparison of more producer's error robustness as an example：
It grades after being analyzed successively the error robustness of more producer's electric energy meters according to the analysis method of above example.Mark
Quasi- difference is smaller, and error robustness is better.More producer's error robustness control cases are as shown in table 3, and more producer's errors are just distributed very much
Figure comparative situation is as shown in Figure 7.
Table producer more than 3 error robustness table of comparisons
The analysis method of the embodiment of the present invention carries out science by the electric energy meter calibration error information to each producer and cuts open
Analysis, and directly reflected with represented as histograms by data distribution, rule is found, the theory and normal state of infinitesimal calculus are utilized
Distribution formula obtains the otherness of the error robustness normal distribution of each producer's electric energy meter, passes through graphic characteristics and standard deviation
Value identifies the best producer of stability.
Based on inventive concept identical with electric energy meter error method for analyzing stability shown in FIG. 1, the embodiment of the present application is also
A kind of electric energy meter error analysis of stability analysis apparatus is provided, as described in following example.Due to the electric energy meter error analysis of stability
The principle that analysis apparatus solves the problems, such as is similar to electric energy meter error method for analyzing stability, therefore the electric energy meter error stability analysis
The implementation of device may refer to the implementation of electric energy meter error method for analyzing stability, and overlaps will not be repeated.
Fig. 8 is the structural schematic diagram of the electric energy meter error analysis of stability analysis apparatus of one embodiment of the invention.As shown in figure 8,
The electric energy meter error analysis of stability analysis apparatus of the embodiment of the present invention, it may include：Error information acquiring unit 210, datagraphic are painted
Unit 220 and error robustness analytic unit 230 processed, above-mentioned each unit are linked in sequence.
Error information acquiring unit 210, is used for：According to setting Plan of Double Sampling Inspection, sampling observation obtains the margin of error of a collection of electric energy meter
According to；
Datagraphic drawing unit 220, is used for：Histogram and/or just too distribution map are drawn using the error information；
Error robustness analytic unit 230, is used for：Based on the histogram and/or just too batch electricity described in profiling analysis
The error robustness of energy table.
In embodiment, error information acquiring unit 210, it may include：Error information acquisition module.Error information obtains mould
Block is used for：According to setting electric energy meter manufacturer, setting electric energy meter model, setting electric energy meter quantity and setting error dot, sampling observation
Obtain the error information of described batch of electric energy meter.
In embodiment, datagraphic drawing unit 220 may include：Histogram drafting module and/or just too distribution map drafting
Module.Histogram drafting module, is used for：Histogram, and/or just too distribution map drafting module are drawn using the error information,
For：Just too distribution map is drawn using the error information.
Fig. 9 is the structural schematic diagram of histogram drafting module in one embodiment of the invention.As shown in figure 9, histogram is drawn
Module, it may include：Extreme value acquisition module 2211, very poor computing module 2212, group are away from computing module 2213, frequency acquisition module
2214, frequency computing module 2215 and histogram generation module 2216, above-mentioned each sequence of modules connection.
Extreme value acquisition module 2211, is used for：All error amounts being ranked sequentially in the error information, find out worst error
Value and minimum error values；
Very poor computing module 2212, is used for：It is calculated using the worst error value and the minimum error values very poor；
Group is used for away from computing module 2213：Using the very poor and setting group number be calculated group away from；
Frequency acquisition module 2214, is used for：According to described group away from being grouped to the error amount in the error information, and
Calculate the frequency per set of error values；
Frequency computing module 2215, is used for：It is calculated using the error amount sum of each frequency and the error information
To the frequency of each set of error values；
Histogram generation module 2216, is used for：Histogram is drawn using the frequency of each set of error values, obtains institute
State histogram.
Figure 10 is the just too structural schematic diagram of distribution map drafting module in one embodiment of the invention.As shown in Figure 10, just too
Distribution map drafting module, it may include：Mean value calculation module 2221, variance computing module 2222, standard deviation computing module 2223,
Just too distribution formula generation module 2224 and just too distribution map generation module 2225, above-mentioned each sequence of modules connection.
Mean value calculation module 2221, is used for：Calculate the average value of error amount in the error information；
Variance computing module 2222, is used for：Institute is calculated using error amount in the average value and the error information
State the variance of error amount in error information；
Standard deviation computing module 2223, is used for：Standard deviation is calculated using the variance；
Just too distribution formula generation module 2224, is used for：Using the average value and the standard deviation as just dividing very much
Population mean in cloth formula and standard deviation substitute into just too distribution formula；
Just too distribution map generation module 2225, is used for：Utilize just dividing very much after the substitution average value and the standard deviation
Cloth formula draws the just too distribution map.
In embodiment, datagraphic drawing unit 220 may include：Histogram drafting module and/or such as figure as shown in Figure 9
Just too distribution map drafting module shown in 10.
In embodiment, error robustness analytic unit 230, it may include：Error robustness analysis module.Error robustness point
Module is analysed, is used for：The histogram obtained by comparing according to the error information of the electric energy meter of multiple and different electric energy meter manufacturers,
And/or by comparing the just too distribution map obtained according to the error information of the electric energy meters of multiple and different electric energy meter manufacturers, know
The best electric energy meter manufacturer of other error robustness.
The embodiment of the present invention also provides a kind of computer readable storage medium, is stored thereon with computer program, the program
The step of method of the various embodiments described above is realized when being executed by processor.
The present invention also provides a kind of computer equipments, and as shown in figure 11, which includes memory 310, place
The computer program managed device 320 and storage on a memory and can run on a processor, the processor 320 execute the journey
The step of method of the various embodiments described above is realized when sequence.
In conclusion electric energy meter error method for analyzing stability, device, storage medium and the equipment of the embodiment of the present invention are adopted
Obtain the error information for being detected electric energy meter with the form of sampling observation, and gradually solved in the form of histogram and/or normal distribution
Pou Ge producers electric energy meter error stability distribution situation is that foundation illustrates that the error of each producer's electric energy meter is steady with data, trend
Qualitative, the experience for eliminating electric energy meter error stability analysis relies on and error.
In the description of this specification, reference term " one embodiment ", " specific embodiment ", " some implementations
Example ", " such as ", the description of " example ", " specific example " or " some examples " etc. mean it is described in conjunction with this embodiment or example
Particular features, structures, materials, or characteristics are included at least one embodiment or example of the invention.In the present specification,
Schematic expression of the above terms may not refer to the same embodiment or example.Moreover, the specific features of description, knot
Structure, material or feature can be combined in any suitable manner in any one or more of the embodiments or examples.Each embodiment
Involved in the step of implementation of the sequence for schematically illustrating the present invention, sequence of steps therein is not construed as limiting, can be as needed
It appropriately adjusts.
It should be understood by those skilled in the art that, the embodiment of the present invention can be provided as method, system or computer program
Product.Therefore, complete hardware embodiment, complete software embodiment or reality combining software and hardware aspects can be used in the present invention
Apply the form of example.Moreover, the present invention can be used in one or more wherein include computer usable program code computer
The computer program production implemented in usable storage medium (including but not limited to magnetic disk storage, CD-ROM, optical memory etc.)
The form of product.
The present invention be with reference to according to the method for the embodiment of the present invention, the flow of equipment (system) and computer program product
Figure and/or block diagram describe.It should be understood that can be realized by computer program instructions every first-class in flowchart and/or the block diagram
The combination of flow and/or box in journey and/or box and flowchart and/or the block diagram.These computer programs can be provided
Instruct the processor of all-purpose computer, special purpose computer, Embedded Processor or other programmable data processing devices to produce
A raw machine so that the instruction executed by computer or the processor of other programmable data processing devices is generated for real
The device for the function of being specified in present one flow of flow chart or one box of multiple flows and/or block diagram or multiple boxes.
These computer program instructions, which may also be stored in, can guide computer or other programmable data processing devices with spy
Determine in the computer-readable memory that mode works so that instruction generation stored in the computer readable memory includes referring to
Enable the manufacture of device, the command device realize in one flow of flow chart or multiple flows and/or one box of block diagram or
The function of being specified in multiple boxes.
These computer program instructions also can be loaded onto a computer or other programmable data processing device so that count
Series of operation steps are executed on calculation machine or other programmable devices to generate computer implemented processing, in computer or
The instruction executed on other programmable devices is provided for realizing in one flow of flow chart or multiple flows and/or block diagram one
The step of function of being specified in a box or multiple boxes.
Particular embodiments described above has carried out further in detail the purpose of the present invention, technical solution and advantageous effect
Describe in detail it is bright, it should be understood that the above is only a specific embodiment of the present invention, the guarantor being not intended to limit the present invention
Range is protected, all within the spirits and principles of the present invention, any modification, equivalent substitution, improvement and etc. done should be included in this
Within the protection domain of invention.
Claims (10)
1. a kind of electric energy meter error method for analyzing stability, which is characterized in that including：
According to setting Plan of Double Sampling Inspection, sampling observation obtains the error information of a collection of electric energy meter；
Histogram and/or just too distribution map are drawn using the error information；
Based on the histogram and/or just too error robustness of batch electric energy meter described in profiling analysis.
2. electric energy meter error method for analyzing stability as described in claim 1, which is characterized in that according to setting Plan of Double Sampling Inspection,
Sampling observation obtains the error information of a collection of electric energy meter, including：
It is obtained according to setting electric energy meter manufacturer, setting electric energy meter model, setting electric energy meter quantity and setting error dot, sampling observation
The error information of described batch of electric energy meter.
3. electric energy meter error method for analyzing stability as described in claim 1, which is characterized in that
Histogram is drawn using the error information, including：
All error amounts being ranked sequentially in the error information, find out worst error value and minimum error values；
It is calculated using the worst error value and the minimum error values very poor；
Using the very poor and setting group number be calculated group away from；
According to described group away from being grouped to the error amount in the error information, and calculate the frequency per set of error values；
The frequency of each set of error values is calculated using the error amount sum of each frequency and the error information；
Histogram is drawn using the frequency of each set of error values, obtains the histogram；And/or
Just too distribution map is drawn using the error information, including：
Calculate the average value of error amount in the error information；
The variance of error amount in the error information is calculated using error amount in the average value and the error information；
Standard deviation is calculated using the variance；
Using the average value and the standard deviation as just too in distribution formula population mean and standard deviation substitute into
Just too distribution formula；
Using substitute into after the average value and the standard deviation just too distribution formula draws the just too distribution map.
4. electric energy meter error method for analyzing stability as described in claim 1, which is characterized in that based on the histogram and/
Or the just too error robustness of batch electric energy meter described in profiling analysis, including：
The histogram obtained by comparing according to the error information of the electric energy meter of multiple and different electric energy meter manufacturers, and/or it is logical
Cross compare according to the error information of the electric energy meter of multiple and different electric energy meter manufacturers obtain just too distribution map, identification error are steady
Qualitative best electric energy meter manufacturer.
5. a kind of electric energy meter error analysis of stability analysis apparatus, which is characterized in that including：
Error information acquiring unit, is used for：According to setting Plan of Double Sampling Inspection, sampling observation obtains the error information of a collection of electric energy meter；
Datagraphic drawing unit, is used for：Histogram and/or just too distribution map are drawn using the error information；
Error robustness analytic unit, is used for：Based on the histogram and/or just too mistake of batch electric energy meter described in profiling analysis
Poor stability.
6. electric energy meter error analysis of stability analysis apparatus as claimed in claim 5, which is characterized in that error information acquiring unit,
Including：
Error information acquisition module, is used for：According to setting electric energy meter manufacturer, setting electric energy meter model, setting electric energy meter number
Amount and setting error dot, sampling observation obtain the error information of described batch of electric energy meter.
7. electric energy meter error analysis of stability analysis apparatus as claimed in claim 5, which is characterized in that datagraphic drawing unit,
Including：
Histogram drafting module, is used for：Histogram is drawn using the error information, including：
Extreme value acquisition module, is used for：All error amounts being ranked sequentially in the error information, find out worst error value and minimum
Error amount；
Very poor computing module, is used for：It is calculated using the worst error value and the minimum error values very poor；
Group is used for away from computing module：Using the very poor and setting group number be calculated group away from；
Frequency acquisition module, is used for：According to described group away from being grouped to the error amount in the error information, and calculate every group
The frequency of error amount；
Frequency computing module, is used for：Each group is calculated using the error amount sum of each frequency and the error information to miss
The frequency of difference；
Histogram generation module, is used for：Histogram is drawn using the frequency of each set of error values, obtains the histogram
Figure；And/or
Just too distribution map drafting module, is used for：Just too distribution map is drawn using the error information, including：
Mean value calculation module, is used for：Calculate the average value of error amount in the error information；
Variance computing module, is used for：The margin of error is calculated using error amount in the average value and the error information
According to the variance of middle error amount；
Standard deviation computing module, is used for：Standard deviation is calculated using the variance；
Just too distribution formula generation module, is used for：Using the average value and the standard deviation as just too in distribution formula
Population mean and standard deviation substitute into just too distribution formula；
Just too distribution map generation module, is used for：Using substitute into after the average value and the standard deviation just too distribution formula is painted
Make the just too distribution map.
8. electric energy meter error analysis of stability analysis apparatus as claimed in claim 5, which is characterized in that error robustness analysis is single
Member, including：
Error robustness analysis module, is used for：By comparing according to the error of the electric energy meter of multiple and different electric energy meter manufacturers
The histogram that data obtain, and/or obtained by comparing the error information of the electric energy meter according to multiple and different electric energy meter manufacturers
The just too distribution map arrived, the best electric energy meter manufacturer of identification error stability.
9. a kind of computer readable storage medium, is stored thereon with computer program, which is characterized in that the program is held by processor
The step of Claims 1-4 the method is realized when row.
10. a kind of computer equipment, including memory, processor and storage are on a memory and the meter that can run on a processor
Calculation machine program, which is characterized in that the step of processor realizes Claims 1-4 the method when executing described program.
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| CN112488472A (en) * | 2020-11-17 | 2021-03-12 | 西安飞机工业（集团）有限责任公司 | Method for evaluating health state and processing stability of equipment |
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