CN115932706A - Electric energy meter data analysis method, electric energy meter and storage medium - Google Patents
Electric energy meter data analysis method, electric energy meter and storage medium Download PDFInfo
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Abstract
The application discloses an electric energy meter data analysis method which comprises the steps of obtaining a data analysis instruction, determining a corresponding data analysis time sequence according to the data analysis instruction, executing the data analysis time sequence, and generating a corresponding inspection report according to an execution result of the data analysis time sequence. The technical problem that the data analysis capability of the existing electric energy meter is weak is solved by the scheme.
Description
Technical Field
The present disclosure relates to the field of electric energy meter technologies, and in particular, to a method and an apparatus for analyzing data of an electric energy meter, and a storage medium.
Background
At present, with the development of intellectualization and automation, more requirements are put forward on the functions of the electric energy meter. In the prior art, the following two situations exist to test the parameters or related performances of the electric energy meter:
(1) Manual testing, namely, a tester needs to have quite high specialty and sets interval time and mode characters of a load curve for the electric meter, then starts the electric meter to automatically record data, then closes the electric meter at set time, and collects various parameter data of the electric meter through a collector, so that the manual steps are complicated, the comprehensive testing as far as possible cannot be achieved, only a sampling method is adopted, and the collected parameter data of the electric meter are analyzed one by one through manual calculation or related instruments at the later stage to obtain results, which is time-consuming and labor-consuming;
(2) Manufacturers with related art: when the indexes of the load curve of the electric meter are checked, software is used for checking one by one, and in one detection, for example: if the increment of the current of an electric energy meter needs to be determined, the current needs to be detected and stored for a period of time separately, when the data to be detected changes or the data amount increases, the related data amount to be detected and the calculation complexity change, in the prior art, the detection of the electric energy meter is generally the detection of instantaneous data, and after the data is detected and the increment or the difference is obtained, the detected data is not further analyzed, and the further implication of the data cannot be revealed.
Content of application
The application mainly aims to provide a method and a device for analyzing data of an electric energy meter and a storage medium, and aims to solve the technical problem that the existing electric energy meter is poor in data analysis capability.
In order to achieve the above object, the present application provides a method for analyzing data of an electric energy meter, where the method for analyzing data of an electric energy meter includes:
acquiring a data analysis instruction;
determining a corresponding data analysis time sequence according to the data analysis instruction and executing the data analysis time sequence;
and generating a corresponding inspection report according to the execution result of the data analysis time sequence.
Optionally, the data analysis instruction includes an instruction for determining a growth trend type, an instruction for determining a current value type, and an instruction for determining a growth step size type.
Optionally, the data analysis time sequence includes an electric meter data standing time sequence and a load curve inspection time sequence; the step of determining a corresponding data analysis time sequence according to the data analysis instruction and executing the data analysis time sequence comprises the following steps:
setting parameters of an ammeter;
determining a corresponding target standing time length, an ammeter data standing time sequence and a load curve inspection time sequence according to the data analysis instruction;
executing the ammeter data standing time sequence until the real-time freezing time length meets the target standing time length;
executing the load curve verification schedule to generate an execution result.
Optionally, the data analysis time sequence comprises an electric meter data freezing time sequence and a load curve inspection time sequence; the step of determining a corresponding data analysis time sequence according to the data analysis instruction and executing the data analysis time sequence comprises:
setting parameters of an ammeter;
determining corresponding target freezing times, ammeter data freezing time sequence and load curve inspection time sequence according to the data analysis instruction;
executing the electric meter data freezing time sequence until the real-time freezing times meet the target freezing times;
executing the load curve verification schedule to generate an execution result.
Optionally, the electricity meter data freeze-like timing comprises an instant freeze timing and an hour freeze timing.
Optionally, the load curve verification time sequence comprises an increase value load curve verification time sequence and a current value load curve verification time sequence;
and when the data analysis instruction is an instruction for judging the increasing trend type, the electric meter data freezing time sequence is an instantaneous freezing time sequence, and the load curve inspection time sequence is an increasing value load curve inspection time sequence.
Optionally, before the step of determining a corresponding data analysis timing sequence according to the data analysis instruction and executing the data analysis timing sequence, the method further includes:
executing a meter reading parameter time sequence to obtain a first meter parameter data set;
after the step of determining a corresponding data analysis timing sequence according to the data analysis instruction and executing the data analysis timing sequence, the method further comprises:
executing the reading ammeter parameter time sequence to obtain a second ammeter parameter data set;
comparing the first meter parameter data set to the second meter parameter data set to determine the accuracy of the inspection report.
Optionally, the parameters of the load curve test timing sequence include a reading mode, an object attribute descriptor, a reading starting condition, a reading ending condition, a data interval, a freezing period, a single reading number, a reading item OAD, and a reading item OAD comparison condition.
Optionally, the execution result includes a theoretical starting sequence number, a theoretical sequence number step length, a theoretical starting time, and a theoretical time step length.
In order to achieve the above object, the present application also provides an electric energy meter, including: the electric energy meter data analysis method comprises the following steps of storing electric energy meter data, storing the electric energy meter data into a memory, storing the electric energy meter data into a processor, and executing a computer program stored in the memory and capable of running on the processor.
In order to achieve the above object, the present application further provides a storage medium, where at least one executable instruction is stored, and when the executable instruction is executed on an electronic device, the electronic device executes the operations of the electric energy meter data analysis method as described above.
According to the technical scheme, a data analysis instruction is obtained; determining a corresponding data analysis time sequence according to the data analysis instruction and executing the data analysis time sequence; according to the data analysis time sequence execution result, the corresponding inspection report is generated, through the scheme, the analysis can be performed according to different instructions as required, namely different data analysis instructions, the corresponding data analysis time sequence is selected and executed, so that the diversification and diversity of the detection data are realized, the analysis on real-time data can be realized, the increase judgment on the time change amount can be performed, the stability of the tested electric energy meter can be further predicted, the data analysis capability of the existing electric energy meter is strengthened, and the problem that the data analysis capability of the existing electric energy meter is weak is avoided.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present application, and for those skilled in the art, other drawings can be obtained according to the structures shown in the drawings without creative efforts.
FIG. 1 is a schematic flow chart of a method for analyzing data of an electric energy meter according to the present application;
FIG. 2 is a schematic illustration of a test report of the method for analyzing data of an electric energy meter according to the present application;
FIG. 3 is a schematic diagram of another inspection report of the electric energy meter data analysis method of the present application;
FIG. 4 is a schematic flow chart of a method for analyzing data of an electric energy meter according to the present application;
FIG. 5 is another schematic flow chart of a method for analyzing data of an electric energy meter according to the present application;
FIG. 6 is another schematic flow chart of a method for analyzing data of an electric energy meter according to the present application;
FIG. 7 is a schematic flow chart of a method for analyzing data of an electric energy meter according to the present application;
FIG. 8 is a schematic circuit diagram of a power supply circuit of the electric energy meter detected in the electric energy meter data analysis method of the present application;
FIG. 9 is a schematic circuit diagram of a power supply circuit of an electric energy meter for detection in the electric energy meter data analysis method of the present application;
FIG. 10 is a schematic circuit diagram of a power supply circuit of the electric energy meter detected in the electric energy meter data analysis method of the present application;
FIG. 11 is a block diagram of a storage medium according to the present application;
FIG. 12 is a block diagram of an electric energy meter freeze data storage device according to the present application.
The objectives, features, and advantages of the present application will be further described with reference to the accompanying drawings.
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and if there is a description of "first", "second", etc. in the embodiments of the present application, the description of "first", "second", etc. is only for descriptive purposes and is not to be construed as indicating or implying relative importance or implicitly indicating the number of indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one such feature.
The application provides a data analysis method for an electric energy meter, and aims to solve the technical problem that the data analysis capability of the existing electric energy meter is weak.
In an embodiment, as shown in fig. 1, the electric energy meter data analysis method includes:
s1, acquiring a data analysis instruction;
optionally, the data analysis instruction includes an instruction for determining a growth trend type, an instruction for determining a current value type, and an instruction for determining a growth step size type.
Wherein, judging the growth trend type instruction: and simulating the data condition that the electricity meter time passes through the freezing time point, and focusing on trend type growth parameters, such as parameters with certain growth trend changes along with the time changes, such as electricity consumption, power and the like.
The freezing time point at this time can be set as needed, focusing on the time increase.
Judging the type of the current value: the instruction of judging the growth trend type can be referred to, the constant parameters are focused, and only the parameters which are generally stable in a certain range, such as current, power factor and the like, are compared with the parameters which are changed before and after the parameters.
Judging an increasing step size type instruction: the step growth class parameters are of great interest, for example: the length of electricity meter usage, etc. parameters that increase over time.
It should be noted that there may also be some special instructions at this time, such as: and judging the meter performance instruction, such as simulating the change of the meter operation or standing for a long time through the short-time meter operation or standing.
S2, determining a corresponding data analysis time sequence according to the data analysis instruction and executing the data analysis time sequence;
the data analysis time sequence refers to a process of collecting and analyzing data of the electric energy meter, wherein the process comprises a plurality of different data acquisition schemes and a plurality of analysis schemes, and the corresponding data acquisition schemes and the plurality of analysis schemes are selected according to the data analysis instruction, so that the analysis of the plurality of data can be realized according to the requirement.
And S3, generating a corresponding inspection report according to the execution result of the data analysis time sequence.
Through the scheme, the corresponding data analysis time sequence is selected and executed according to different instructions needing to be analyzed, namely different data analysis instructions, so that diversification and diversity of detection data are realized, and then the corresponding inspection report can be generated according to the execution result, and the method is shown in the figure 2 and the figure 3, so that a user can conveniently check the analysis result. When the electric energy meter needs to be delivered from a factory for inspection after production is completed, the scheme can be used for inspecting a large number of electric meters in a short time, one electric energy meter data analysis method can cover a large number of electric meter parameter indexes, the redundancy and complexity of the inspection scheme can be greatly reduced, the inspection time is shortened, unattended operation is realized, and therefore the method, the equipment or the system can be used for greatly improving the inspection efficiency and reducing the labor cost.
By the scheme, analysis on real-time data can be realized, and judgment such as increase and prediction on time change can be performed, so that the stability of the tested electric energy meter can be further predicted, the data analysis capability of the existing electric energy meter is enhanced, and the problem that the data analysis capability of the existing electric energy meter is weak is solved.
In an alternative embodiment, referring to fig. 4, the data analysis sequence includes a meter data resting sequence and a load curve checking sequence; the step of determining a corresponding data analysis time sequence according to the data analysis instruction and executing the data analysis time sequence comprises the following steps:
s21, setting ammeter parameters;
the electric meter parameters at this time comprise the time and date of the electric meter, the basic data caching period, the number of effective data and the like. The electricity meter time and date generally refers to the time when the electricity meter is calibrated to the current time and date. And according to the basic data cache period and the number of the effective data, generating an OAD (object attribute descriptor) for describing the meaning, the attribute and the characteristic data item of a certain electric meter data type every other data cache period after the current time and storing the OAD into an electric meter storage area, wherein the electric meter storage area stores at most the number of the effective data of the OAD, and the OAD data is covered by the first OAD data if the number of the effective data exceeds the number of the effective data, and so on.
S22, determining a corresponding target standing time, an ammeter data standing time sequence and a load curve inspection time sequence according to the data analysis instruction;
the target standing time is generally set according to a real-time data analysis instruction.
The electric meter data standing time sequence refers to an electric meter standing time sequence executed according to the target standing time length, and comprises starting time, ending time, OAD (operating access device) required to be stored in natural standing time length and storage times. The specific numerical value is also preset according to the data analysis instruction.
Load curve check sequence: some of the execution parameters set therein include: the method comprises the steps of reading, object attribute descriptors, reading starting conditions, reading ending conditions, data intervals, freezing periods, the number of reading strips in one time, reading OAD (entry load) and reading OAD comparison conditions and the like, wherein the comparison condition values are X _ Y, X _ Y and 8230, and the X _ Y is a format for configuring the comparison mode of each column so as to separate the columns. X is a comparison mode, different comparison modes correspond to different judgment rules, Y is a column index, if the column index is a single-column index, a column number is 1 to represent a 1 st column, and if the column index is a multi-column index, an expression is a starting index-ending index number, such as 9-10, to represent a column 9 and a column 10. Example (c): n2_1, T1_2, W1_3-4, U1_5, I1_6, P1_7-8, C1_9-10, column index, and the alignment of column index selections are matched to the actual transcription content.
S23, executing the ammeter data standing time sequence until the real-time freezing time length meets the target standing time length;
and S24, executing the load curve checking time sequence to generate an execution result.
Based on the scheme, the load curve test time sequence is executed by reading the values of OADs of the reading items of the load curve from the electric meter data storage area, forming a data by a plurality of OAD values and forming a queue form by a plurality of data in sequence according to the time sequence. Obtaining reading results, comparing the reading results in real time, and obtaining the judgment rule that parameters KZ00010C and KZ000A02 are calculated according to the reading parameters and are assigned by a system in the reading execution process. The reading condition can be divided into reading according to time and reading according to sequence numbers, beginTime = KZ00010C is reading starting time, and Interval = KZ000A02 is reading time Interval. And (4) judging the reading result line by line and column by the system according to a judgment rule. Current value = the transcription value of the corresponding column of the current row. Growth value = the difference between the current row value and the previous row value. The difference units are different for different data types. The theoretical starting serial number, the theoretical serial number step length, the theoretical starting time and the theoretical time step length are calculated according to the load curve reading parameters and the reading result, and the specific judgment process can be executed by referring to the table 1.
In the above embodiment, the scheme is mainly used for judging the meter performance instruction, for example, by the short-time meter operation or standing to simulate the change of the meter operation or standing for a long time. At the moment, the electric energy meter can be simulated for a longer time by standing or running for a period of time, and the change of the current electric energy meter in a longer period of time can be reasonably predicted by the simulation for a shorter time, so that the trend parameters and the fixed value parameters can be effectively tested, and the defect that the measurement of the parameters cannot be carried out in a shorter measurement time is avoided.
Optionally, the parameters in the load curve test time sequence include a reading mode, an object attribute descriptor, a reading starting condition, a reading ending condition, a data interval, a freezing period, a single reading number, a reading item OAD, and a reading item OAD comparison condition.
In an alternative embodiment, referring to fig. 5, the data analysis sequence includes an electric meter data freezing sequence and a load curve checking sequence; the step of determining a corresponding data analysis time sequence according to the data analysis instruction and executing the data analysis time sequence comprises:
s25, setting ammeter parameters;
the electric meter parameters at this time comprise electric meter time and date, basic data caching period, effective data number and the like. The electricity meter time and date generally refers to the time when the electricity meter is calibrated to the current time and date. And according to the basic data cache period and the number of the effective data, generating an OAD (object attribute descriptor) for describing the meaning, the attribute and the characteristic data item of a certain electric meter data type every other data cache period after the current time and storing the OAD into an electric meter storage area, wherein the electric meter storage area stores at most the number of the effective data of the OAD, and the OAD data is covered by the first OAD data if the number of the effective data exceeds the number of the effective data, and so on.
S26, determining corresponding target freezing times, ammeter data freezing time sequence and load curve inspection time sequence according to the data analysis instruction;
the target freezing times are set according to actual instruction requirements.
The method comprises the steps of setting parameters including freezing OAD, freezing time interval (any positive integer type, the value is the same as the current freezing period of the electric meter), freezing times and the like, preferably, the time sequence is a pen pointing to the eye, repeating the time sequence for many times in a circulating mode, creatively simulating the verification of the electric meter on trend parameters which need to meet the requirements of months or years, such as electric energy verification and time verification, executing the electric meter data freezing time sequence when a tester only concerns whether the electric quantity increase trend and the time increase trend meet the expected conditions, calibrating the electric meter backwards according to the electric meter time to t1 second before the nearest node to be frozen, and recording a piece of frozen data to an electric meter storage area after t1 second. And then repeating the cycle execution, taking the nearest node to be frozen as the initial freezing time, pushing the node to be frozen backwards according to the freezing interval, copying and reading the ammeter parameter data of the freezing time point to an ammeter data storage area, and repeating the steps until the cycle is finished. The time sequence can shorten the elapsed time of the ammeter in the natural days, the natural months and the natural years, and the aim of testing the trend parameters and the fixed value parameters is fulfilled.
S27, executing the electric meter data freezing time sequence until the real-time freezing times meet the target freezing times;
and S28, executing the load curve checking time sequence to generate an execution result.
When the load curve checking sequence is executed, the comparison condition values are X _ Y, X _ Y, \8230, X _ Y is the format to configure the comparison mode of each row, so as to separate the rows. X is a comparison mode, different comparison modes correspond to different judgment rules, Y is a column index, if the column index is a single-column index, a column number is 1 to represent a 1 st column, and if the column index is a multi-column index, an expression is a starting index-ending index number, such as 9-10, to represent a column 9 and a column 10. Example (c): n2_1, T1_2, W1_3-4, U1_5, I1_6, P1_7-8, C1_9-10, column index, and the alignment of column index selections are matched to the actual transcription content. Referring to fig. 6, reading out the values of OAD items of the load curve reading items from the data storage area of the electric meter, combining a plurality of OAD values into one data, and sequentially combining the plurality of data into a queue form according to the time sequence. Obtaining reading results, comparing the reading results in real time, and obtaining the judgment rule that parameters KZ00010C and KZ000A02 are calculated according to the reading parameters and are assigned by a system in the reading execution process. The reading condition can be divided into reading according to time and reading according to sequence numbers, beginTime = KZ00010C is reading starting time, and Interval = KZ000A02 is reading time Interval. And (4) judging rules, namely judging the reading results line by line and line by the system. Current value = the transcription value of the corresponding column of the current row. Growth value = the difference between the current row value and the previous row value. The difference units are different for different data types. The theoretical starting serial number, the theoretical serial number step length, the theoretical starting time and the theoretical time step length are calculated according to the load curve reading parameters and the reading result, and the specific judgment scheme is as shown in the following table 1:
TABLE 1
The following is, for example, a specific judgment process to explain a process performed for different parameters or different judgment targets:
data one:
0,2020-01-1617:15:00,0.0350,2.0790,0.0000,0.0190,0.0000,0.0070,0.0120,0.0000,0.0000,0.0000,220.0,220.0,220.1,5.000,5.000,5.000,0.000,7.500,3301.8,1100.4,1100.3,1100.7,3.0,0.5,3.0,-0.5,0.999,0.999,0.999,0.999；
data II:
1,2020-01-1617:30:00,0.0400,2.0790,0.0010,0.0190,0.0010,0.0070,0.0120,0.0000,0.0033,0.0041,220.3,220.2,220.3,5.000,-5.005,-4.998,0.000,0.023,-3.3,1101.5,-549.6,-555.3,4.3,-0.4,955.6,-951.2,-0.609,0.999,-0.499,-0.505；
data three:
2,2020-01-1617:45:00,0.0410,2.0790,0.0020,0.0190,0.0020,0.0070,0.0120,0.0000,0.0031,0.0040,220.4,220.3,220.3,5.001,-5.006,-5.000,0.000,0.023,-3.2,1102.1,-549.5,-555.6,4.2,-0.5,956.3,-951.5,-0.618,0.999,-0.499,-0.505。
at this time, the first data is the first data, the comparison rule of the first data is followed, if the comparison condition is N1, the first data is judged to be qualified according to the rule of the current value = theoretical starting number, and if the first data is not the first data, the first data is judged to be qualified according to the rule of the growth value = theoretical starting number step length. And sequentially judging the values of the returned data, such as a voltage A phase, a voltage B phase, a voltage C phase, a current A phase and the like, which are read by each row of OADs, and if the values are unqualified, explaining the unqualified reason, wherein the specific implementation process refers to the process shown in FIG. 7.
Optionally, the electricity meter data freeze-like timing comprises an instant freeze timing and an hour freeze timing.
In this case, the specific scheme of the freeze sequence may be actually set by the user according to the purpose to be measured.
In an alternative embodiment, the load curve verification timing comprises a growth value load curve verification timing and a current value load curve verification timing;
and when the data analysis instruction is an instruction for judging the increasing trend type, the electric meter data freezing time sequence is an instantaneous freezing time sequence, and the load curve inspection time sequence is an increasing value load curve inspection time sequence.
In an alternative embodiment, referring to fig. 8, before the step of determining the corresponding data analysis timing according to the data analysis instruction and executing the data analysis timing, the method further includes:
s4, executing meter reading parameter time sequence to obtain a first meter parameter data set;
referring to fig. 9, the first meter parameter includes a plurality of OADs (freeze associated object attributes), and the first meter parameter data set at this time is a specific reading value of each OAD. After the step of determining a corresponding data analysis timing sequence according to the data analysis instruction and executing the data analysis timing sequence, the method further comprises:
s5, executing the reading ammeter parameter time sequence to obtain a second ammeter parameter data set;
referring to fig. 10, the time sequence of reading the meter parameters after checking is as follows: generally, after the load curve verification sequence, the load curve verification sequence is placed and paired with the reading electric meter parameter data sequence before verification, and the correctness of the execution of the load curve time sequence is verified by reading the load curve frozen data associated object attribute again, comparing with the associated object attribute of the first electric meter parameter data group before verification and the like.
S6, comparing the first ammeter parameter data set with the second ammeter parameter data set to determine the accuracy of the inspection report.
Through the scheme, the correctness of the time sequence execution result of the load curve can be verified before, when the data ranges of the first electric meter parameter data group and the second electric meter parameter data group are the same, the accuracy of the issued inspection report is higher, and if the difference between the data ranges of the first electric meter parameter data group and the second electric meter parameter data group is larger, the accuracy of the issued inspection report is lower.
Optionally, the execution result includes a theoretical starting sequence number, a theoretical sequence number step size, a theoretical starting time, and a theoretical time step size.
Optionally, the step of generating a corresponding inspection report according to the execution result of the data analysis time sequence further includes:
generating a load curve reading comparison result report according to the execution result of the data analysis time sequence;
and (4) reading and comparing the load curve and storing the comparison result into a database in an Excel form.
At the moment, the paper can be displayed on the interface and also can be printed as paper, so that unqualified reasons and time are provided for checking by inspectors. The scheme value is that the load curve reads data contents formed by each component of OAD, the return value is a verification detailed result of the data contents, if the data contents are unqualified, unqualified clear information is updated, and the conclusion value records a general conclusion of the data qualification verification.
The present application also proposes an electric energy meter, as shown with reference to fig. 12, the electric energy meter including:
the detection module 10 is used for acquiring a data analysis instruction;
the control module 30: and determining a corresponding data analysis time sequence according to the data analysis instruction, executing the data analysis time sequence, and generating a corresponding inspection report according to an execution result of the data analysis time sequence.
Optionally, the data analysis instruction includes an instruction for determining a growth trend type, an instruction for determining a current value type, and an instruction for determining a growth step size type.
Optionally, the control module 30 is also used for
Setting parameters of an ammeter;
determining a corresponding target standing time length, an ammeter data standing time sequence and a load curve inspection time sequence according to the data analysis instruction;
executing the ammeter data standing time sequence until the real-time freezing time length meets the target standing time length;
executing the load curve verification schedule to generate an execution result.
Optionally, the control module 30 is further configured to set the electric meter parameters;
determining corresponding target freezing times, ammeter data freezing time sequence and load curve inspection time sequence according to the data analysis instruction;
executing the electric meter data freezing time sequence until the real-time freezing times meet the target freezing times;
executing the load curve verification schedule to generate an execution result.
Optionally, the electricity meter data freeze-like timing comprises an instant freeze timing and an hour freeze timing.
Optionally, the load curve verification time sequence comprises an increase value load curve verification time sequence and a current value load curve verification time sequence;
and when the data analysis instruction is an instruction for judging the increasing trend type, the electric meter data freezing time sequence is an instantaneous freezing time sequence, and the load curve inspection time sequence is an increasing value load curve inspection time sequence.
Optionally, the control module 30 is also used for
Executing a meter reading parameter time sequence to obtain a first meter parameter data set;
after the step of determining a corresponding data analysis timing sequence according to the data analysis instruction and executing the data analysis timing sequence, the method further comprises:
executing the reading ammeter parameter time sequence to obtain a second ammeter parameter data set;
comparing the first meter parameter data set to the second meter parameter data set to determine the accuracy of the inspection report.
Optionally, the parameters of the load curve test time sequence include a reading mode, an object attribute descriptor, a reading starting condition, a reading ending condition, a data interval, a freezing period, a single reading number, a reading item OAD, and a reading item OAD comparison condition.
Optionally, the execution result includes a theoretical starting sequence number, a theoretical sequence number step length, a theoretical starting time, and a theoretical time step length.
Through the scheme, the corresponding data analysis time sequence is selected and executed according to different instructions needing to be analyzed, namely different data analysis instructions, so that diversification and diversity of detection data are realized, and then the corresponding inspection report can be generated according to the execution result, and the method is shown in the figure 2 and the figure 3, so that a user can conveniently check the analysis result.
By means of the scheme, analysis on real-time data can be achieved, and judgment such as increase and prediction on time change can be conducted, so that the stability of the tested electric energy meter can be further predicted, the data analysis capability of the existing electric energy meter is enhanced, and the problem that the data analysis capability of the existing electric energy meter is weak is solved.
The present application further provides a storage medium, where at least one executable instruction is stored in the storage medium, and when the executable instruction is run on an electronic device, the electronic device executes the operations of the electric energy meter data analysis method described above.
The embodiments of the present application provide a computer program product, which when running on a mobile terminal, enables the mobile terminal to implement the steps in the above method embodiments when executed.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, all or part of the flow of the method of the embodiments described above can be implemented by instructing relevant hardware by a computer program, and the computer program can be stored in a storage medium, and when being executed by a processor, the computer program can implement the steps of the embodiments of the methods described above. Wherein the computer program comprises computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer-readable medium may include at least: any entity or device capable of carrying computer program code to a photographing apparatus/terminal apparatus, a recording medium, computer Memory, read-Only Memory (ROM), random Access Memory (RAM), an electrical carrier signal, a telecommunications signal, and a software distribution medium. Such as a usb-disk, a removable hard disk, a magnetic or optical disk, etc. In certain jurisdictions, computer-readable media may not be an electrical carrier signal or a telecommunications signal in accordance with legislative and patent practice.
The application also provides an electric energy meter, which comprises a memory, a processor and a computer program stored in the memory and capable of running on the processor, wherein the processor implements the electric energy meter data analysis method when executing the computer program.
Referring to fig. 11, the storage 21 may be an internal storage unit of the terminal device 2 in some embodiments, for example, a hard disk or a memory of the terminal device 2. The memory 21 may also be an external storage device of the terminal device 2 in other embodiments, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like, provided on the terminal device 2. Further, the memory 21 may also include both an internal storage unit of the terminal device 2 and an external storage device. The memory 21 is used for storing an operating system, an application program, a BootLoader (BootLoader), data, and other programs, such as program codes of the computer programs. The memory 21 may also be used to temporarily store data that has been output or is to be output.
Fig. 12 shows a structural block diagram of the electric energy meter provided in the embodiment of the present application, corresponding to the electric energy meter data analysis method described in the above embodiment, and only the parts related to the embodiment of the present application are shown for convenience of description.
It should be noted that, for the information interaction, execution process, and other contents between the above devices/units, the specific functions and technical effects thereof based on the same concept as those of the method embodiment of the present application can be specifically referred to the method embodiment portion, and are not described herein again.
In addition, optionally, in an embodiment, the electric energy meter is provided with a byte-modifiable storage medium EEPROM and a sector-modifiable storage medium FLASH for executing the electric energy meter data analysis method, and is further configured with a metering off-line communication interface and the like to realize signal interaction and execute data calculation required by the microcontroller, i.e., the processor.
It should be clear to those skilled in the art that, for convenience and simplicity of description, the foregoing division of the functional units and modules is only used for illustration, and in practical applications, the above function distribution may be performed by different functional units and modules as needed, that is, the internal structure of the apparatus may be divided into different functional units or modules to perform all or part of the above described functions. Each functional unit and module in the embodiments may be integrated in one processing unit, or each unit may exist alone physically, or two or more units are integrated in one unit, and the integrated unit may be implemented in a form of hardware, or in a form of software functional unit. In addition, specific names of the functional units and modules are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present application. The specific working processes of the units and modules in the system may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the technical solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus/network device and method may be implemented in other ways. For example, the above-described apparatus/network device embodiments are merely illustrative, and for example, the division of the modules or units is only one logical division, and there may be other divisions when actually implementing, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not implemented. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be through some interfaces, indirect coupling or communication connection of devices or units, and may be in an electrical, mechanical or other form.
The above description is only an alternative embodiment of the present application, and not intended to limit the scope of the present application, and all modifications and equivalents of the subject matter of the present application, which are made by the following claims and their equivalents, or which are directly or indirectly applicable to other related arts, are intended to be included within the scope of the present application.
Claims (10)
1. A method for analyzing data of an electric energy meter is characterized by comprising the following steps:
acquiring a data analysis instruction;
determining a corresponding data analysis time sequence according to the data analysis instruction and executing the data analysis time sequence;
and generating a corresponding inspection report according to the execution result of the data analysis time sequence.
2. The method according to claim 1, wherein the data analysis commands comprise a command for determining a growth trend type, a command for determining a current value type, and a command for determining a growth step type.
3. The electric energy meter data analysis method according to claim 2, wherein the data analysis time sequence comprises an electric meter data standing time sequence and a load curve checking time sequence; the step of determining a corresponding data analysis time sequence according to the data analysis instruction and executing the data analysis time sequence comprises:
setting parameters of an ammeter;
determining a corresponding target standing time length, an ammeter data standing time sequence and a load curve inspection time sequence according to the data analysis instruction;
executing the ammeter data standing time sequence until the real-time freezing time length meets the target standing time length;
executing the load curve verification schedule to generate an execution result.
4. The method according to claim 2, wherein the data analysis sequence comprises a meter data freezing sequence and a load curve checking sequence; the step of determining a corresponding data analysis time sequence according to the data analysis instruction and executing the data analysis time sequence comprises the following steps:
setting electric meter parameters;
determining corresponding target freezing times, ammeter data freezing time sequences and load curve inspection time sequences according to the data analysis instructions;
executing the electric meter data freezing time sequence until the real-time freezing times meet the target freezing times;
executing the load curve verification schedule to generate an execution result.
5. The method for analyzing electric energy meter data according to claim 4, wherein the electric meter data freeze-like timing comprises an instant freeze timing and an integral freeze timing.
6. The method for analyzing electric energy meter data according to claim 5, wherein the load curve check timing sequence includes an increase value load curve check timing sequence and a current value load curve check timing sequence;
and when the data analysis instruction is an instruction for judging the increasing trend type, the electric meter data freezing time sequence is an instantaneous freezing time sequence, and the load curve inspection time sequence is an increasing value load curve inspection time sequence.
7. The method for analyzing electric energy meter data according to claim 1, wherein the step of determining the corresponding data analysis timing sequence according to the data analysis command and executing the data analysis timing sequence further comprises:
executing a meter reading parameter time sequence to obtain a first meter parameter data set;
after the step of determining a corresponding data analysis timing sequence according to the data analysis instruction and executing the data analysis timing sequence, the method further comprises:
executing the reading ammeter parameter time sequence to obtain a second ammeter parameter data set;
comparing the first meter parameter data set to the second meter parameter data set to determine the accuracy of the inspection report.
8. The electric energy meter data analysis method according to claim 3 or 4, wherein the parameters of the load curve test time sequence comprise a reading mode, an object attribute descriptor, a reading starting condition, a reading ending condition, a data interval, a freezing period, a single reading number, a reading item OAD and a reading item OAD comparison condition.
9. An electric energy meter, characterized in that the electric energy meter comprises:
memory, processor and computer program stored in the memory and executable on the processor, characterized in that the processor implements the method of analyzing electric energy meter data according to any of claims 1 to 8 when executing the computer program.
10. A storage medium having stored therein at least one executable instruction, which when executed on an electronic device, causes the electronic device to perform the operations of the power meter data analysis method according to any one of claims 1 to 8.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN116824602A (en) * | 2023-07-17 | 2023-09-29 | 国网浙江省电力有限公司 | Electric charge data analysis processing method, device and storage medium |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116824602A (en) * | 2023-07-17 | 2023-09-29 | 国网浙江省电力有限公司 | Electric charge data analysis processing method, device and storage medium |
| CN116824602B (en) * | 2023-07-17 | 2023-12-01 | 国网浙江省电力有限公司 | Electricity bill data analysis and processing method, device and storage medium |
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