CN113723748A - Method and system for evaluating batch quality state of running electric energy meter - Google Patents
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Abstract
The invention discloses a method and a system for evaluating batch quality states of running electric energy meters, wherein the method comprises the following steps: step one, acquiring batch operation condition data of the electric energy meters; step two, classifying and screening the data; step three, establishing an electric energy meter batch operation state evaluation model; step four, determining the evaluation index of the batch running state of the electric energy meter; step five, classifying the batch operation state conditions of the electric energy meters; sixthly, analyzing and checking the reliability of the batch operation condition data of the electric energy meter by utilizing Weibull distribution; step seven, evaluating the batch running state of the electric energy meters; step eight, verifying the evaluation result of the batch operation state of the electric energy meter; step nine, extracting and classifying fault states in batch running states of the electric energy meters, and performing fault mode division; tenthly, prejudging the service life of the electric energy meter; and step eleven, performing final analysis on the state evaluation result. The method and the device are beneficial to timely and quickly evaluating the batch running state of the electric energy meter by operators.
Description
Technical Field
The invention relates to the field of electric energy metering, in particular to a method and a system for evaluating batch quality state of an operating electric energy meter.
Background
In recent years, with the continuous development of smart power grids, power grid companies are gradually developing operation and distribution information through work, the ubiquitous power internet of things is built and operated, the smart electric energy meter is used as an important recombination part of the ubiquitous power internet of things, the operation quality of the smart electric energy meter is directly related to the economic benefit of the power grid companies, and the smart electric energy meter is of great importance for improving the power supply reliability management level and the power supply service capacity. Therefore, how to effectively improve the operation stability, reliability and accuracy of the intelligent electric energy meter and discover the hidden quality danger of the intelligent electric energy meter in time becomes an urgent need for supporting the intelligent acquisition, operation and maintenance work of a power grid company, and the field detection, spot inspection and operation and maintenance workload of the electric energy meter are increased greatly along with the rapid increase of the application quantity of the intelligent electric energy meter.
Therefore, it is necessary to design a method and a system for evaluating the batch quality status of the running electric energy meters to evaluate the batch running status of the electric energy meters.
Disclosure of Invention
The invention aims to provide a method and a system for evaluating batch quality states of running electric energy meters, so as to solve the problems in the background technology.
In order to achieve the purpose, the invention provides the following technical scheme:
a method for evaluating batch quality state of an operating electric energy meter comprises the following steps:
the method comprises the following steps: firstly, acquiring batch operation condition data of the electric energy meter;
step two: classifying and screening the data;
step three: establishing an electric energy meter batch running state evaluation model;
step four: determining an evaluation index of batch running states of the electric energy meters;
step five: classifying and recording the batch running state conditions of the electric energy meters;
step six: the reliability of the batch operation condition data of the electric energy meter is analyzed and checked by utilizing Weibull distribution;
step seven: further evaluating the batch running state of the electric energy meter;
step eight: verifying the evaluation result of the batch running state of the electric energy meter;
step nine: extracting and classifying fault states in batch running states of the electric energy meters, and performing fault mode division;
step ten: the service life of the electric energy meter is further pre-judged by recording fault data;
step eleven: and finally analyzing the state evaluation result to obtain a final batch operation state evaluation result of the electric energy meter.
As a further scheme of the invention: the electric energy meter batch operation condition data in the first step comprise operation data information, overhaul data information, production link basic data information, environment data information and power supply data information, and the data information is further classified, recorded and stored.
And in the second step, the data information is quickly classified, so that data cross overlapping is avoided, meanwhile, invalid data information is removed, the influence of the invalid data information on a final evaluation result is avoided, and the valid data information is rearranged and classified after classification and screening are finished.
And the third step is used for constructing an electric energy meter batch operation state evaluation model to evaluate the electric energy meter batch operation state.
And step four, referring to the operation data information, the overhaul data information, the production link basic data information, the environment data information and the power supply data information, so as to determine the evaluation index of the batch operation state of the electric energy meter, and conveniently evaluating the batch operation state of the electric energy meter according to the evaluation index.
And the fifth step is used for classifying and recording the specific conditions after the batch operation state condition evaluation of the electric energy meters.
And the seventh step is further used for evaluating the batch operation state of the electric energy meter after the reliability analysis is carried out on the sixth step.
And step eight, verifying the evaluation result of the electric energy meter batch running state after the reliability analysis in the step seven.
And step nine, extracting and classifying the fault states in the evaluation result after the batch operation state of the electric energy meter is verified.
And step ten, analyzing the fault state in the evaluation result after the batch operation state of the electric energy meters is verified according to the extracted and classified electric energy meters, thereby further realizing the prejudgment of the service life of the electric energy meters.
As a still further scheme of the invention: the sixth step is used for counting the data information recorded in the fifth step to obtain the monthly abnormal quantity Ni of the electric energy meter in the running state in the batch, the total number m of the months since the meter is changed for the first time, the current number i of the months and the accumulated abnormal quantity ratio Fi of the electric energy meter in the running state in the batch, wherein the total quantity N and the total quantity N of the electric energy meter in the batch represent the quantity of the electric energy meters running at the current moment and all the detached verification results are the sum of the abnormal quantities of the electric energy meter in the running state in the batch; average running time Ti of abnormal running state quantity of batches of the electric energy meters per month;
where i represents the number of months since installation;
estimating the reliability of the electric energy meter by adopting Weibull distribution, wherein the parameter solving process of the Weibull distribution is as follows:
applying least square method to Xi、YiFitting into the form Y ═ AX + B; screening data points, and fitting the first 2, 3 and 4 data points to obtain Y2＝A2X+B2，Y3＝A3X+B3，Y4＝A4X+B4Three straight lines, A2、A3、A4Respectively represent the slopes of three straight lines; calculating the slope change V of three straight lines1、V2；
If V is simultaneously present1<0，V2>0, then X is1、Y1Removing, if not, retaining all data; fitting all the remaining data points, and finally obtaining a Weibull distribution parameter according to a fitting result:
the other technical scheme adopted by the invention is as follows: a batch quality state evaluation system for operating electric energy meters comprises:
an operation condition data acquisition unit: acquiring batch operation condition data of the electric energy meters;
data classification and screening unit: classifying and screening the data;
an operation state evaluation model establishing unit: establishing an electric energy meter batch running state evaluation model;
an operating state evaluation index determination unit: determining an evaluation index of batch running states of the electric energy meters;
an operating state situation classification unit: classifying and recording the batch running state conditions of the electric energy meters;
a reliability analysis unit: the reliability of the batch operation condition data of the electric energy meter is analyzed and checked by utilizing Weibull distribution;
an operating state evaluation unit: evaluating the batch running state of the electric energy meter;
a state evaluation result verification unit: verifying the evaluation result of the batch running state of the electric energy meter;
a fault state extraction and classification unit: extracting and classifying fault states in batch running states of the electric energy meters, and performing fault mode division;
a life pre-judging unit: the service life of the electric energy meter is further pre-judged by recording fault data;
final analysis unit for state evaluation result: and finally analyzing the state evaluation result to obtain a final batch operation state evaluation result of the electric energy meter.
Compared with the prior art, the invention has the beneficial effects that: the electric energy meter batch quality state evaluation method is simple in operation, scientific and reasonable, and is beneficial to operators to timely and quickly obtain the evaluation result of the electric energy meter batch running state.
Drawings
Fig. 1 is a schematic flow chart of the batch quality state evaluation method for operating electric energy meters according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Example 1
Referring to fig. 1, in an embodiment of the present invention, a method for evaluating quality status of batches of running electric energy meters includes the following steps:
the method comprises the following steps: acquiring batch operation condition data of the electric energy meters;
step two: classifying and screening the data;
step three: establishing an electric energy meter batch running state evaluation model;
step four: determining an evaluation index of batch running states of the electric energy meters;
step five: classifying and recording the batch running state conditions of the electric energy meters;
step six: the reliability of the electric energy meter batch running state condition data is analyzed and checked by utilizing Weibull distribution;
step seven: evaluating the batch running state of the electric energy meter;
step eight: verifying the evaluation result of the batch running state of the electric energy meter;
step nine: extracting and classifying fault states in batch running states of the electric energy meters, and performing fault mode division;
step ten: the service life of the electric energy meter is further pre-judged by recording fault data;
step eleven: and finally analyzing the state evaluation result to obtain a final batch operation state evaluation result of the electric energy meter.
The electric energy meter batch operation condition data in the first step comprise operation data information, overhaul data information, production link basic data information, environment data information and power supply data information, and the data information is further classified, recorded and stored.
And in the second step, the data information is quickly classified, so that data cross overlapping is avoided, meanwhile, invalid data information is removed, the influence of the invalid data information on a final evaluation result is avoided, and the valid data information is rearranged and classified after classification and screening are finished.
And the third step is used for constructing an electric energy meter batch operation state evaluation model to evaluate the electric energy meter batch operation state.
And step four, referring to the operation data information, the overhaul data information, the production link basic data information, the environment data information and the power supply data information, so as to determine the evaluation index of the batch operation state of the electric energy meter, and conveniently evaluating the batch operation state of the electric energy meter according to the evaluation index.
And the fifth step is used for classifying and recording the specific conditions after the batch operation state condition evaluation of the electric energy meters.
The sixth step is used for counting the data information recorded in the fifth step to obtain the monthly abnormal quantity Ni of the electric energy meter in the running state in the batch, the total number m of the months since the meter is changed for the first time, the current number i of the months and the accumulated abnormal quantity ratio Fi of the electric energy meter in the running state in the batch, wherein the total quantity N and the total quantity N of the electric energy meter in the batch represent the quantity of the electric energy meters running at the current moment and all the detached verification results are the sum of the abnormal quantities of the electric energy meter in the running state in the batch; average running time Ti of abnormal running state quantity of batches of the electric energy meters per month;
where i represents the number of months since installation;
estimating the reliability of the electric energy meter by adopting Weibull distribution, wherein the parameter solving process of the Weibull distribution is as follows:
fitting Xi and Yi into a form of Y ═ AX + B by using a least square method; screening data points, and fitting the previous 2, 3 and 4 data points to obtain three straight lines, namely, Y2-A2X + B2, Y3-A3X + B3, Y4-A4X + B4, wherein A2, A3 and A4 represent slopes of the three straight lines; obtaining slope changes V1 and V2 of the three straight lines;
if V1<0, V2>0 exists at the same time, X1 and Y1 are removed, and if not, all data are reserved; fitting all the remaining data points, and finally obtaining a Weibull distribution parameter according to a fitting result:
and the seventh step is further used for evaluating the batch operation state of the electric energy meter after the reliability analysis is carried out on the sixth step.
And step eight, verifying the evaluation result of the electric energy meter batch running state after the reliability analysis in the step seven.
And step nine, extracting and classifying the fault states in the evaluation result after the batch operation state of the electric energy meter is verified.
And step ten, analyzing the fault state in the evaluation result after the batch operation state of the electric energy meters is verified according to the extracted and classified electric energy meters, thereby further realizing the prejudgment of the service life of the electric energy meters.
Example 2
The embodiment provides an operating electric energy meter batch quality state evaluation system which comprises an operating condition data acquisition unit, a data classification and screening unit, an operating condition evaluation model establishing unit, an operating condition evaluation index determining unit, an operating condition classification unit, a reliability analysis unit, an operating condition evaluation unit, a state evaluation result verification unit, a fault state extraction classification unit, a service life pre-judgment unit and a state evaluation result final analysis unit.
An operation condition data acquisition unit: acquiring batch operation condition data of the electric energy meters;
data classification and screening unit: classifying and screening the data;
an operation state evaluation model establishing unit: establishing an electric energy meter batch running state evaluation model;
an operating state evaluation index determination unit: determining an evaluation index of batch running states of the electric energy meters;
an operating state situation classification unit: classifying and recording the batch running state conditions of the electric energy meters;
a reliability analysis unit: the reliability of the batch operation condition data of the electric energy meter is analyzed and checked by utilizing Weibull distribution;
an operating state evaluation unit: evaluating the batch running state of the electric energy meter;
a state evaluation result verification unit: verifying the evaluation result of the batch running state of the electric energy meter;
a fault state extraction and classification unit: extracting and classifying fault states in batch running states of the electric energy meters, and performing fault mode division;
a life pre-judging unit: the service life of the electric energy meter is further pre-judged by recording fault data;
final analysis unit for state evaluation result: and finally analyzing the state evaluation result to obtain a final batch operation state evaluation result of the electric energy meter.
In the operation condition data acquisition unit, the electric energy meter batch operation condition data comprise operation data information, overhaul data information, production link basic data information, environment data information and power supply data information, and the data information is further classified, recorded and stored.
In the operation state evaluation index determining unit, the operation data information, the overhaul data information, the production link basic data information, the environmental data information and the power supply data information are referred to, so that the batch operation state evaluation index of the electric energy meter is determined, and the batch operation state condition of the electric energy meter is evaluated conveniently according to the operation state evaluation index.
The reliability analysis unit is used for counting the data information recorded in the operation state condition classification unit to obtain monthly abnormal quantity Ni of the operation state of the electric energy meter batch, total number of months m since the meter is replaced for the first time, current number of months i, and accumulated abnormal quantity proportion Fi of the operation state of the electric energy meter batch, wherein the total quantity N and N of the electric energy meter batch represent the quantity of the electric energy meters which are operated at the current moment and all the detached verification results are the sum of the abnormal quantities of the operation state of the electric energy meter batch; average running time Ti of abnormal running state quantity of batches of the electric energy meters per month;
where i represents the number of months since installation;
estimating the reliability of the electric energy meter by adopting Weibull distribution, wherein the parameter solving process of the Weibull distribution is as follows:
applying least square method to Xi、YiFitting into the form Y ═ AX + B; screening data points, and fitting the first 2, 3 and 4 data points to obtain Y2＝A2X+B2，Y3＝A3X+B3，Y4＝A4X+B4Three straight lines, A2、A3、A4Respectively represent the slopes of three straight lines; calculating the slope change V of three straight lines1、V2；
If V is simultaneously present1<0，V2>0, then X is1、Y1Removing, if not, retaining all data; fitting all the remaining data points, and finally obtaining a Weibull distribution parameter according to a fitting result:
although the present invention has been described in detail with reference to the foregoing embodiments, it will be apparent to those skilled in the art that various changes in the embodiments and/or modifications of the invention can be made, and equivalents and modifications of some features of the invention can be made without departing from the spirit and scope of the invention.
Claims (10)
1. A method for evaluating batch quality state of an operating electric energy meter is characterized by comprising the following steps:
the method comprises the following steps: acquiring batch operation condition data of the electric energy meters;
step two: classifying and screening the data;
step three: establishing an electric energy meter batch running state evaluation model;
step four: determining an evaluation index of batch running states of the electric energy meters;
step five: classifying and recording the batch running state conditions of the electric energy meters;
step six: the reliability of the electric energy meter batch running state condition data is analyzed and checked by utilizing Weibull distribution;
step seven: evaluating the batch running state of the electric energy meter;
step eight: verifying the evaluation result of the batch running state of the electric energy meter;
step nine: extracting and classifying fault states in batch running states of the electric energy meters, and performing fault mode division;
step ten: the service life of the electric energy meter is further pre-judged by recording fault data;
step eleven: and finally analyzing the state evaluation result to obtain a final batch operation state evaluation result of the electric energy meter.
2. The batch quality state evaluation method for the running electric energy meters according to claim 1, characterized by comprising the following steps: the electric energy meter batch operation condition data in the first step comprise operation data information, overhaul data information, production link basic data information, environment data information and power supply data information, and the data information is further classified, recorded and stored.
3. The batch quality state evaluation method for the running electric energy meters according to claim 2, characterized by comprising the following steps: and step four, referring to the operation data information, the overhaul data information, the production link basic data information, the environment data information and the power supply data information, so as to determine the evaluation index of the batch operation state of the electric energy meters, and conveniently evaluating the batch operation state condition of the electric energy meters according to the operation state evaluation index.
4. The batch quality state evaluation method for the running electric energy meters according to claim 1, characterized by comprising the following steps: the sixth step is used for counting the data information recorded in the fifth step to obtain the monthly abnormal quantity Ni of the electric energy meter in the running state in the batch, the total number m of the months since the meter is changed for the first time, the current number i of the months and the accumulated abnormal quantity ratio Fi of the electric energy meter in the running state in the batch, wherein the total quantity N and the total quantity N of the electric energy meter in the batch represent the quantity of the electric energy meters running at the current moment and all the detached verification results are the sum of the abnormal quantities of the electric energy meter in the running state in the batch; average running time Ti of abnormal running state quantity of batches of the electric energy meters per month;
where i represents the number of months since installation;
estimating the reliability of the electric energy meter by adopting Weibull distribution, wherein the parameter solving process of the Weibull distribution is as follows:
applying least square method to Xi、YiFitting into the form Y ═ AX + B; screening data points, and fitting the first 2, 3 and 4 data points to obtain Y2＝A2X+B2，Y3＝A3X+B3，Y4＝A4X+B4Three straight lines, A2、A3、A4Respectively represent the slopes of three straight lines; calculating the slope change V of three straight lines1、V2；
If V is simultaneously present1<0，V2>0, then X is1、Y1Removing, if not, retaining all data; fitting all the rest data points according to the fitting resultSo as to finally obtain the Weibull distribution parameters:
5. the batch quality state evaluation method for the running electric energy meters according to claim 1, characterized by comprising the following steps: and step nine, extracting and classifying the fault states in the evaluation result after the batch operation state of the electric energy meter is verified.
6. The batch quality state evaluation method for the running electric energy meters according to claim 1, characterized by comprising the following steps: and step ten, analyzing the fault state in the evaluation result after the batch operation state of the electric energy meters is verified according to the extracted and classified electric energy meters, thereby further realizing the prejudgment of the service life of the electric energy meters.
7. A batch quality state evaluation system for operating electric energy meters is characterized by comprising:
an operation condition data acquisition unit: acquiring batch operation condition data of the electric energy meters;
data classification and screening unit: classifying and screening the data;
an operation state evaluation model establishing unit: establishing an electric energy meter batch running state evaluation model;
an operating state evaluation index determination unit: determining an evaluation index of batch running states of the electric energy meters;
an operating state situation classification unit: classifying and recording the batch running state conditions of the electric energy meters;
a reliability analysis unit: the reliability of the batch operation condition data of the electric energy meter is analyzed and checked by utilizing Weibull distribution;
an operating state evaluation unit: evaluating the batch running state of the electric energy meter;
a state evaluation result verification unit: verifying the evaluation result of the batch running state of the electric energy meter;
a fault state extraction and classification unit: extracting and classifying fault states in batch running states of the electric energy meters, and performing fault mode division;
a life pre-judging unit: the service life of the electric energy meter is further pre-judged by recording fault data;
final analysis unit for state evaluation result: and finally analyzing the state evaluation result to obtain a final batch operation state evaluation result of the electric energy meter.
8. The batch quality status evaluation system for the running electric energy meters according to claim 7, characterized in that: in the operation condition data acquisition unit, the electric energy meter batch operation condition data comprise operation data information, overhaul data information, production link basic data information, environment data information and power supply data information, and the data information is further classified, recorded and stored.
9. The batch quality status evaluation system for the running electric energy meters according to claim 8, characterized in that: in the operation state evaluation index determining unit, the operation data information, the overhaul data information, the production link basic data information, the environmental data information and the power supply data information are referred to, so that the batch operation state evaluation index of the electric energy meter is determined, and the batch operation state condition of the electric energy meter is evaluated conveniently according to the operation state evaluation index.
10. The batch quality status evaluation system for the running electric energy meters according to claim 7, characterized in that: the reliability analysis unit is used for counting the data information recorded in the operation state condition classification unit to obtain monthly abnormal quantity Ni of the operation state of the electric energy meter batch, total number of months m since the meter is replaced for the first time, current number of months i, and accumulated abnormal quantity proportion Fi of the operation state of the electric energy meter batch, wherein the total quantity N and N of the electric energy meter batch represent the quantity of the electric energy meters which are operated at the current moment and all the detached verification results are the sum of the abnormal quantities of the operation state of the electric energy meter batch; average running time Ti of abnormal running state quantity of batches of the electric energy meters per month;
where i represents the number of months since installation;
estimating the reliability of the electric energy meter by adopting Weibull distribution, wherein the parameter solving process of the Weibull distribution is as follows:
applying least square method to Xi、YiFitting into the form Y ═ AX + B; screening data points, and fitting the first 2, 3 and 4 data points to obtain Y2＝A2X+B2，Y3＝A3X+B3，Y4＝A4X+B4Three straight lines, A2、A3、A4Respectively represent the slopes of three straight lines; calculating the slope change V of three straight lines1、V2；
If V is simultaneously present1<0，V2>0, then X is1、Y1Removing, if not, retaining all data; fitting all the remaining data points, and finally obtaining a Weibull distribution parameter according to a fitting result:
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| CN110927654A (en) * | 2019-08-23 | 2020-03-27 | 国网天津市电力公司电力科学研究院 | Batch running state evaluation method for intelligent electric energy meters |
| CN110991826A (en) * | 2019-11-18 | 2020-04-10 | 国网浙江省电力有限公司电力科学研究院 | Method for evaluating running state of low-voltage electric energy meter |
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Application publication date: 20211130 |