CN117113833A - Verification method and system of verification device - Google Patents
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Abstract
The invention discloses a verification method and a verification system for a verification device, wherein verification data of the verification device to be verified is obtained, verification data is verified by utilizing a preset electric energy meter error distribution function model, a verification error result is obtained, the error result is compared with a preset value, if the error result is larger than a first preset value and smaller than a second preset value, an alarm process is started, an alarm verification task is generated, if the error result is larger than the second preset value, an early warning process is started, an early warning verification task is generated, and the verification device to be verified is verified according to the alarm verification task or the early warning verification task.
Description
Technical Field
The invention relates to the technical field of electric energy meter verification, in particular to a verification method and a verification system of a verification device.
Background
With the rapid increase of the verification traffic of the electric energy meter, the verification work of the electric energy meter is changed from manual verification to automatic assembly line verification. The verification device has the characteristics of high concentration of distribution, small number of verification personnel, great improvement of verification efficiency and the like, and is particularly important to ensure that the standard performance of the electric energy meter verification device continuously meets the method requirements and to efficiently and high-quality finish period verification work of the verification device.
Under the current automatic verification mode, verification devices are huge in number, verification system operation efficiency is high, daily detection amounts are tens of thousands, and in order to ensure that standard performance of each verification device continuously meets method requirements in two adjacent quantity value tracing periods, periodic and unscheduled period verification needs to be carried out according to actual conditions. The verification work is performed during the manual development period, the operation efficiency is low, the influence on daily verification production is large, the verification frequency and timeliness are difficult to ensure, and meanwhile, the risk of the test process and the data processing under the influence of human factors is large. If the standard performance of the verification system is abnormal, the abnormal standard performance of the verification system is difficult to find, accurately judge and process in time, the recall of the affected detected equipment is difficult, the influence is severe, and the requirements of the precision management and the risk on-line management of the metering verification production cannot be met.
Although the digital checking method of the electric energy meter error distribution function model based on the historical verification data of the intelligent electric energy meter in the same batch can solve the problems of verification work interruption, low verification efficiency, artificial influence and the like caused by manual wiring verification in the traditional period, the digital checking method needs a large amount of quantity accumulation on one hand, is easily influenced by data quality, and causes inaccurate verification results.
Disclosure of Invention
In order to solve the technical problems, the embodiment of the invention provides a verification method and a verification system for a verification device, wherein the verification device is verified by linking an abnormal result of an error distribution function model of an electric energy meter with a verification task trigger mechanism, so that the abnormality of the verification system can be found in time, and the accuracy and the efficiency of the verification result are improved.
A first aspect of an embodiment of the present invention provides a verification method for an assay device, the method including:
acquiring verification data of a verification device to be checked;
checking verification data by using a preset electric energy meter error distribution function model to obtain a checking error result, wherein the preset electric energy meter error distribution function model is constructed according to historical verification data;
comparing the error result with a preset value, if the error result is larger than a first preset value and smaller than a second preset value, starting an alarm process and generating an alarm checking task, and if the error result is larger than the second preset value, starting an early warning process and generating an early warning checking task;
and checking the to-be-checked calibrating device according to the alarm checking task or the early warning checking task to obtain a first checking result, ending the checking if the first checking result reaches a preset condition, checking the to-be-checked calibrating device according to the preset checking task to obtain a second checking result if the error result is smaller than the first preset value, and ending the checking if the second checking result reaches the preset condition.
According to the method, verification data of the verification device to be verified is obtained, verification data are verified by means of a preset electric energy meter error distribution function model to obtain a verification error result, the error result is compared with a preset value, if the error result is larger than a first preset value and smaller than a second preset value, an alarm process is started, an alarm verification task is generated, if the error result is larger than the second preset value, an early warning process is started, an early warning verification task is generated, the verification device to be verified is verified according to the alarm verification task or the early warning verification task to obtain a first verification result, if the first verification result reaches a preset condition, verification is finished, if the error result is smaller than the first preset value, verification is conducted on the device to be verified according to the preset verification task to obtain a second verification result, if the error result reaches a preset condition, verification is finished, verification is conducted through the abnormal result of the electric energy meter error distribution function model and a verification task triggering mechanism, system abnormality can be found timely, and verification accuracy and efficiency are improved.
In one possible implementation manner of the first aspect, whether a plurality of same alarm checking tasks or a plurality of same early warning checking tasks exist or not is judged, if the same alarm checking tasks or the same early warning checking tasks exist and belong to the same line body and device, whether the same alarm checking tasks or the same early warning checking tasks are finished or not is judged, and if the same alarm checking tasks or the same early warning checking tasks are finished, the checking tasks are finished;
if the same alarm checking task or the same early warning checking task exists and belongs to the same line body and different devices, the same alarm checking task or the same early warning checking task is combined into one alarm checking task or one early warning checking task for checking.
In a possible implementation manner of the first aspect, the preset electric energy meter error distribution function model is constructed according to historical verification data, and specifically includes:
calculating the relative error of the electric energy meter to be detected according to the electric power data of the electric energy meter to be detected, and calculating the relative error of the device to be detected according to the verification data of the verification device to be detected;
according to the relative error of the electric energy meter to be detected and the relative error of the device to be detected, a basic error model is obtained through calculation, wherein the basic error model is as follows:
Y(％)＝X(％)―θ(％)
wherein X (%) represents the basic error of the electric energy meter to be detected,θ (%) represents the relative error of the assay device to be tested, +.>W e Indicating electric energy, W, of the device to be inspected 0 Representing the measured electrical energy of the reference standard;
and constructing an error distribution function model of the electric energy meter by combining the basic error model according to the central limit theorem and the Bayesian hierarchical model.
In one possible implementation manner of the first aspect, verification data is checked by using a preset electric energy meter error distribution function model to obtain a verification error result, which specifically includes:
performing error calculation according to the kth verification data of the verification device to be checked to obtain an error distribution model;
obtaining posterior probability distribution according to the Bayes theorem and each parameter in the error distribution model;
and after the posterior probability distribution is sampled by using a Gibbs sampling method, obtaining an edge distribution sample of standard device error by using the samples of the joint distribution, and calculating to obtain an error checking result.
In a possible implementation manner of the first aspect, the verification device to be verified is verified according to an alarm verification task or an early warning verification task, specifically:
and checking the verification device to be checked by adopting preset physical checking equipment according to the alarm checking task or the early warning checking task.
In a possible implementation manner of the first aspect, the preset physical verification device is preferably a 0.02-level physical verification device with a size consistent with an existing electric energy meter and high stability.
A second aspect of an embodiment of the present invention provides a verification system for an assay device, the system comprising:
the acquisition module is used for acquiring verification data of the verification device to be checked;
the first checking module is used for checking verification data by using a preset electric energy meter error distribution function model to obtain a checking error result, wherein the preset electric energy meter error distribution function model is constructed according to historical verification data;
the second checking module is used for comparing the error result with a preset value, if the error result is larger than the first preset value and smaller than the second preset value, starting an alarm process and generating an alarm checking task, and if the error result is larger than the second preset value, starting an early warning process and generating an early warning checking task;
and the third checking module is used for checking the to-be-checked calibrating device according to the alarm checking task or the early warning checking task to obtain a first checking result, ending the checking if the first checking result reaches a preset condition, checking the to-be-checked calibrating device according to the preset checking task to obtain a second checking result if the error result is smaller than the first preset value, and ending the checking if the second checking result reaches the preset condition.
In one possible implementation manner of the second aspect, the judging module is configured to judge whether a plurality of identical alarm checking tasks or a plurality of identical early warning checking tasks exist, if the same alarm checking tasks or the same early warning checking tasks exist and belong to the same line body and device, judge whether the same alarm checking tasks or the same early warning checking tasks are completed, and if the same alarm checking tasks or the same early warning checking tasks are completed, end the checking tasks;
if the same alarm checking task or the same early warning checking task exists and belongs to the same line body and different devices, the same alarm checking task or the same early warning checking task is combined into one alarm checking task or one early warning checking task for checking.
In a possible implementation manner of the second aspect, the preset electric energy meter error distribution function model is constructed according to historical verification data, and specifically includes:
calculating the relative error of the electric energy meter to be detected according to the electric power data of the electric energy meter to be detected, and calculating the relative error of the device to be detected according to the verification data of the verification device to be detected;
according to the relative error of the electric energy meter to be detected and the relative error of the device to be detected, a basic error model is obtained through calculation, wherein the basic error model is as follows:
Y(％)＝X(％)―θ(％)
wherein X (%) represents the basic error of the electric energy meter to be detected,θ (%) represents the relative error of the assay device to be tested, +.>W e Indicating electric energy, W, of the device to be inspected 0 Representing the measured electrical energy with reference to the standard.
In one possible implementation manner of the second aspect, verification data is checked by using a preset electric energy meter error distribution function model to obtain a verification error result, which specifically is:
performing error calculation according to the kth verification data of the verification device to be checked to obtain an error distribution model;
obtaining posterior probability distribution according to the Bayes theorem and each parameter in the error distribution model;
and after the posterior probability distribution is sampled by using a Gibbs sampling method, obtaining an edge distribution sample of standard device error by using the samples of the joint distribution, and calculating to obtain an error checking result.
Drawings
Fig. 1: a flow diagram of an embodiment of a verification method for a verification device provided by the invention;
fig. 2: the invention provides a verification system workflow schematic diagram of one embodiment of a verification method of a verification device;
fig. 3: the invention provides a double-layer model structure schematic diagram of verification data of one embodiment of a verification method of a verification device;
fig. 4: the system structure schematic diagram of another embodiment of the checking method of the verification device is provided by the invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Example 1
Referring to fig. 1, a flow chart of an embodiment of a verification method of an inspection apparatus provided by an embodiment of the present invention includes steps S11 to S14, where each step is specifically as follows:
s11, acquiring verification data of the verification device to be checked.
In this embodiment, verification data of a verification device to be verified is obtained, the verification data including a plurality of verification data.
It should be noted that, verification data of a plurality of verification devices to be checked are obtained in real time.
S12, checking the verification data by using a preset electric energy meter error distribution function model to obtain a checking error result, wherein the preset electric energy meter error distribution function model is constructed according to historical verification data.
In a preferred embodiment, the preset electric energy meter error distribution function model is constructed according to historical verification data, and specifically comprises the following steps:
calculating the relative error of the electric energy meter to be detected according to the electric power data of the electric energy meter to be detected, and calculating the relative error of the device to be detected according to the verification data of the verification device to be detected;
according to the relative error of the electric energy meter to be detected and the relative error of the device to be detected, a basic error model is obtained through calculation, wherein the basic error model is as follows:
Y(％)＝X(％)―θ(％)
wherein X (%) represents the basic error of the electric energy meter to be detected,θ (%) represents the relative error of the assay device to be tested, +.>W e Indicating electric energy, W, of the device to be inspected 0 Representing the measured electrical energy of the reference standard;
and constructing an error distribution function model of the electric energy meter by combining the basic error model according to the central limit theorem and the Bayesian hierarchical model.
In a preferred embodiment, verification data is checked by using a preset electric energy meter error distribution function model to obtain a verification error result, which specifically includes:
performing error calculation according to the kth verification data of the verification device to be checked to obtain an error distribution model;
obtaining posterior probability distribution according to the Bayes theorem and each parameter in the error distribution model;
and after the posterior probability distribution is sampled by using a Gibbs sampling method, obtaining an edge distribution sample of standard device error by using the samples of the joint distribution, and calculating to obtain an error checking result.
In this embodiment, as shown in fig. 2, the same batch of historical verification data of the intelligent electric energy meter is utilized, and an electric energy meter error distribution function model with a higher accuracy level than the verification device is constructed based on a central limit theorem and a bayesian hierarchical model, so that the verification device is checked in real time. The process of processing the historical verification data by the error distribution function model of the electric energy meter is as follows:
modeling a basic error source of the calibrating device, and according to the requirement on basic error calibration in JJG 596-2012 electronic AC electric energy meter, when a standard meter method is used for calibrating the electric energy meter, calculating a relative error calculation formula of the detected electric energy meter:
wherein m represents the number of pulses actually measured, m 0 The number of pulses is calculated and indicated,n represents the low-frequency or high-frequency pulse number of the electric energy meter to be detected, C 0 Representing the (pulse) meter constant of a standard meter, imp/kWh, C L Meter constant (pulse) representing electric energy meter to be tested, imp/kWh, K I ，K U Respectively represents the transformation ratio of the current and voltage transformers externally connected with the standard meter,
when the standard meter has no external current or voltage transformer, K I And K U All equal to 1, the counted number of pulses is Then the relative error of the detected electric energy meter is +.> Wherein W is m For indicating the electric energy of the electric energy meter to be detected, W e Indicating the power for the assay device.
According to the requirement on basic error verification in JJG 597-2005 AC electric energy meter verification device verification rules, the relative error calculation formula of the detected device is as follows:
wherein W is e Indicating electric energy, W, of the device to be inspected 0 Representing the measured electrical energy with reference to the standard.
As can be seen from the above formula, the relative error Y (%) of the detected electric energy meter is the error of the electric energy meter relative to the calibrating device; examined dressThe relative error θ (%) is the error measured by the assay device relative to the reference standard. The true relative error of the electric energy meter is the error measured by the electric energy meter relative to the reference standard, namelyThen there are:
the relation among the basic error Y (%), the basic error X (%), and the basic error theta (%) of the calibrating device is as follows:
X(％)＝θ(％)+Y(％)+0.01*θ(％)*Y(％)
since the value obtained by 0.01 x θ (%) x Y (%) exceeds the accuracy, the effect on the result is very small, and thus the basic error model of the assay device is:
Y(％)＝X(％)―θ(％)
wherein X (%) represents the basic error of the electric energy meter to be detected,θ (%) represents the relative error of the assay device to be tested, +.>W e Indicating electric energy, W, of the device to be inspected 0 Representing the measured electrical energy with reference to the standard.
And then, based on a central limit theorem, accumulating verification data of an error distribution function model of the electric energy meter, wherein the central limit theorem indicates that the mean distribution of independent random variables with the same distribution is asymptotically to normal distribution, and the theorem is a theoretical basis of mathematical statistics and error analysis and is specifically expressed as follows:
for n random variables independently and identically distributed, X 1 ，X 2 ，···，X n The expected and standard values are μ and σ, respectively, the averageDistribution approximation tends to normal distribution +.>
According to the central limit theorem, the average value of verification data of n common production batches of common intelligent electric energy meters can be regarded as verification data of an error distribution function model of the electric energy meters, and the accuracy level of the error distribution function model of the electric energy meters is improved compared with that of a single common intelligent electric energy meterMultiple times. If n is large enough, the accuracy level of the error distribution function model of the electric energy meter can reach the accuracy level of the standard electric energy meter in the physical method, and the electric energy meter can be used for checking the calibrating device.
As an example of this embodiment, taking a single-phase intelligent electric energy meter as an example, the accuracy level is usually 2, and is about 100 times different from the standard electric energy meter in the physical method. If the calibration data of a single calibrating device is utilized to construct an error distribution function model of the electric energy meter, the calibration data of the electric energy meter in the same production batch of 1 ten thousand orders of magnitude are required to be accumulated, and the requirement of the checking accuracy of the calibrating device can be met. However, the assay speed of a single assay device is limited and the data on the above scale requires a longer time to accumulate during the assay operation. In order to solve the problems, the method combines a plurality of verification devices for verifying the same batch of intelligent electric energy meters, introduces a Bayesian hierarchical model, distributes required verification data volume, and uniformly builds an electric energy meter error distribution function model, thereby greatly shortening the data accumulation time and realizing real-time verification of the plurality of verification devices.
Verification data of the intelligent electric energy meters in the same production batch can be grouped based on the verification device where the intelligent electric energy meters are located to form a double-layer model: the first layer is composed of different calibrating devices and is an inter-group model for describing errors of the calibrating devices; the second layer is composed of a plurality of tables to be inspected, which are inspected by the same inspection device, and is used for describing an intra-group model of the inspection data generated by the same inspection device, as shown in fig. 3.
In the first inter-layer model, mu i Representing the error of the ith assay device, assuming it obeys a normal distribution, its model likelihood is:
wherein,and τ 2 The expected and variance of the assay device error distribution, respectively.
In the second group of internal models, Y is used i,k And (3) representing the kth verification data of the ith verification device, and b representing the expectation of errors of the intelligent ammeter inspected in the production batch. Verification data Y i,k The verification error of the to-be-detected table is the difference between the true error of the to-be-detected table and the error of the verification device, and is assumed to obey normal distribution, and the model likelihood is as follows:
wherein sigma 2 Variance of the assay data within the group.
Setting parameters according to Bayesian theoremb,τ 2 ,σ 2 Is the conjugate prior distribution of:
wherein IG represents the inverse Gamma distribution.
The posterior probability distribution is obtained by using the Bayes theorem as follows:
in the posterior distribution of the above parameters, μ 1 ,μ 2 ,…,μ m ,b is a normal distribution, τ 2 Sum sigma 2 The posterior distribution of (2) is the inverse Gamma distribution.
Based on the posterior distribution, the combined posterior distribution p (mu) is obtained by using a Gibbs sampling method 1 ,μ 2 ,...,μ m ,τ 2 ,σ 2 b|Y) sampling, and obtaining standard device error mu directly from the jointly distributed samples 1 ,μ 2 ,…,μ m And further obtaining statistical information such as mean value, median value and the like of the distribution as an obtained checking result.
S13, comparing the error result with a preset value, if the error result is larger than the first preset value and smaller than the second preset value, starting an alarm process and generating an alarm checking task, and if the error result is larger than the second preset value, starting an early warning process and generating an early warning checking task.
In a preferred embodiment, further comprising:
judging whether a plurality of same alarm checking tasks or a plurality of same early warning checking tasks exist, if so, judging whether the same alarm checking tasks or the same early warning checking tasks are finished or not, and if so, ending the checking tasks;
if the same alarm checking task or the same early warning checking task exists and belongs to the same line body and different devices, the same alarm checking task or the same early warning checking task is combined into one alarm checking task or one early warning checking task for checking.
In this embodiment, by calculating the electric energy meter error distribution function model, the error value checked during the calibration device period can be calculated, and then compared with the specified error value, if the error value exceeds the maximum allowable error system, the alarm flow can be automatically started, if the error value is close to the maximum allowable error system, the early warning flow can be automatically started, both the alarm flow and the early warning flow can automatically generate a proxy task, further a physical checking task is generated, and whether the electric energy meter calibration device is abnormal is judged according to the execution result of the task.
When the error result of the electric energy meter error distribution function model operation is close to the maximum allowable error, the system can automatically start an early warning process, a judgment condition system for early warning start can be flexibly set, and the process after the early warning process is started is consistent with an alarm process.
When the system starts the alarm flow, in order to prevent the repeated alarm, the system can judge whether the line body has the flow which is not processed and finished with the same alarm type, for example, the same line body and the same device continuously alarm for three days, the system can automatically judge whether the first alarm is checked to be finished, and if the first alarm is not finished, the second alarm can be automatically closed. Meanwhile, in order to reduce the task amount of verification and improve the verification efficiency, the same type of alarm information of different devices of the same wire body can be automatically combined into one piece of alarm information, for example, the alarm checked during the period of the occurrence of the 1 st verification unit and the 2 nd verification unit of the 1 st wire body is automatically combined into one task, and the 1 st verification unit and the 2 nd verification unit of the 1 st wire body are checked at one time.
It should be noted that, the early warning process aims at discovering the problem of the device in advance, so as to prevent the problem; the alarm process aims to verify the problem of the device and reduce the influence caused by the device problem to the greatest extent after confirming the device problem.
S14, checking the to-be-checked calibrating device according to the alarm checking task or the early warning checking task to obtain a first checking result, ending the checking if the first checking result reaches a preset condition, checking the to-be-checked calibrating device according to the preset checking task to obtain a second checking result if the error result is smaller than the first preset value, and ending the checking if the second checking result reaches the preset condition.
In a preferred embodiment, the verification device to be verified is verified according to an alarm verification task or an early warning verification task, specifically:
and checking the verification device to be checked by adopting preset physical checking equipment according to the alarm checking task or the early warning checking task.
In a preferred embodiment, the preset physical verification device is preferably a 0.02 level physical verification device that is consistent in size with existing power meters and has high stability.
In this embodiment, when an alarm or an early warning is generated, according to an alarm checking task or an early warning checking task, a preset physical checking device is adopted to check the verification device to be checked, and whether the electric energy meter verification device is abnormal is judged according to the execution result of the task. The preset physical checking device is 0.02-level physical checking device which is consistent with the existing electric energy meter in size and has high stability.
Each state during the execution of the physical checking task can be synchronized into the error distribution function model of the electric energy meter in real time, the distributed function model can find problems in advance, the physical checking task is used as a verification mode to realize the final closed loop of warning, the physical checking task and the physical checking task complement each other, the normal daily verification task of the line body can be finally achieved, the accuracy of verification results is ensured, and recall events of the electric energy meter due to the problems of the verification results are avoided.
According to the invention, the abnormal result of the error distribution function model of the electric energy meter is linked with the checking task triggering mechanism, and when the error distribution function model of the electric energy meter finds out abnormality, the checking task is automatically triggered, and the checking work of the calibrating device is completed through the physical checking equipment, so that the abnormality of the calibrating device can be found out in time.
Example two
Accordingly, referring to fig. 4, fig. 4 is a verification system of an assay device according to the present invention, as shown in the drawings, the verification system of the assay device includes:
an acquisition module 401, configured to acquire verification data of a verification device to be verified;
the first checking module 402 is configured to check the verification data by using a preset electric energy meter error distribution function model to obtain a checking error result, where the preset electric energy meter error distribution function model is constructed according to the historical verification data;
the second checking module 403 is configured to compare the error result with a preset value, if the error result is greater than the first preset value and less than the second preset value, start an alarm process and generate an alarm checking task, and if the error result is greater than the second preset value, start an early warning process and generate an early warning checking task;
and the third checking module 404 is configured to check the to-be-checked calibration device according to the alarm checking task or the early warning checking task to obtain a first checking result, if the first checking result reaches a preset condition, end the checking, if the error result is smaller than a first preset value, check the to-be-checked calibration device according to the preset checking task to obtain a second checking result, and if the second checking result reaches the preset condition, end the checking.
In a preferred embodiment, the determining module 405 is configured to determine whether a plurality of identical alarm checking tasks or a plurality of identical early warning checking tasks exist, if so, and each identical alarm checking task or each identical early warning checking task belongs to the same line and device, determine whether each identical alarm checking task or early warning checking task has been completed, and if so, end the checking task;
if the same alarm checking task or the same early warning checking task exists and belongs to the same line body and different devices, the same alarm checking task or the same early warning checking task is combined into one alarm checking task or one early warning checking task for checking.
In a preferred embodiment, the preset electric energy meter error distribution function model is constructed according to historical verification data, and specifically comprises the following steps:
calculating the relative error of the electric energy meter to be detected according to the electric power data of the electric energy meter to be detected, and calculating the relative error of the device to be detected according to the verification data of the verification device to be detected;
according to the relative error of the electric energy meter to be detected and the relative error of the device to be detected, a basic error model is obtained through calculation, wherein the basic error model is as follows:
Y(％)＝X(％)―θ(％)
wherein X (%) represents the basic error of the electric energy meter to be detected,θ (%) represents the relative error of the assay device to be tested, +.>W e Indicating electric energy, W, of the device to be inspected 0 Representing the measured electrical energy with reference to the standard.
In a preferred embodiment, verification data is checked by using a preset electric energy meter error distribution function model to obtain a verification error result, which specifically includes:
performing error calculation according to the kth verification data of the verification device to be checked to obtain an error distribution model;
obtaining posterior probability distribution according to the Bayes theorem and each parameter in the error distribution model;
and after the posterior probability distribution is sampled by using a Gibbs sampling method, obtaining an edge distribution sample of standard device error by using the samples of the joint distribution, and calculating to obtain an error checking result.
In a preferred embodiment, the verification device to be verified is verified according to an alarm verification task or an early warning verification task, specifically:
and checking the verification device to be checked by adopting preset physical checking equipment according to the alarm checking task or the early warning checking task.
In a preferred embodiment, the preset physical verification device is preferably a 0.02 level physical verification device that is consistent in size with existing power meters and has high stability.
In summary, the embodiment of the invention has the following beneficial effects:
the method comprises the steps of obtaining verification data of a to-be-verified device, verifying the verification data by utilizing a preset electric energy meter error distribution function model to obtain a verification error result, comparing the error result with a preset value, starting an alarm process and generating an alarm verification task if the error result is larger than a first preset value and smaller than a second preset value, starting an early warning process and generating an early warning verification task if the error result is larger than the second preset value, verifying the to-be-verified device according to the alarm verification task or the early warning verification task to obtain a first verification result, ending the verification if the first verification result reaches a preset condition, verifying the to-be-verified device according to the preset verification task to obtain a second verification result if the error result is smaller than the first preset value, ending the verification if the second verification result reaches a preset condition, and ending the verification by linking the verification result of the electric energy meter error distribution function model with a verification task triggering mechanism, so that the verification device can be timely found that the verification system is abnormal, and the accuracy and the efficiency of the verification result are improved.
In the description of the present specification, a description referring to terms "one embodiment," "some embodiments," "examples," "specific examples," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present disclosure. In this specification, schematic representations of the above terms are not necessarily directed to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, the different embodiments or examples described in this specification and the features of the different embodiments or examples may be combined and combined by those skilled in the art without contradiction.
Furthermore, the terms "first," "second," and the like, are used for descriptive purposes only and are not to be construed as indicating or implying a relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defining "a first" or "a second" may explicitly or implicitly include at least one such feature. In the description of the present disclosure, the meaning of "a plurality" is at least two, such as two, three, etc., unless explicitly specified otherwise.
The foregoing embodiments have been provided for the purpose of illustrating the general principles of the present invention, and are not to be construed as limiting the scope of the invention. It should be noted that any modifications, equivalent substitutions, improvements, etc. made by those skilled in the art without departing from the spirit and principles of the present invention are intended to be included in the scope of the present invention.
Claims (10)
1. A method of verifying an assay device, comprising:
acquiring verification data of a verification device to be checked;
checking the verification data by using a preset electric energy meter error distribution function model to obtain a checking error result, wherein the preset electric energy meter error distribution function model is constructed according to historical verification data;
comparing the error result with a preset value, if the error result is larger than a first preset value and smaller than a second preset value, starting an alarm process and generating an alarm checking task, and if the error result is larger than the second preset value, starting an early warning process and generating an early warning checking task;
and checking the to-be-checked calibrating device according to the alarm checking task or the early warning checking task to obtain a first checking result, ending the checking if the first checking result reaches a preset condition, checking the to-be-checked calibrating device according to the preset checking task to obtain a second checking result if the error result is smaller than the first preset value, and ending the checking if the second checking result reaches the preset condition.
2. The method of verifying an assay device of claim 1, further comprising:
judging whether a plurality of same alarm checking tasks or a plurality of same early warning checking tasks exist, if yes, judging whether the same alarm checking tasks or the same early warning checking tasks are finished or not, and if yes, finishing the checking tasks;
if the same alarm checking task or the same early warning checking task exists and belongs to the same line body and different devices, combining the same alarm checking task or the same early warning checking task into one alarm checking task or the same early warning checking task for checking.
3. The method for checking an calibrating apparatus according to claim 1, wherein the error distribution function model of the preset electric energy meter is constructed according to historical calibration data, specifically:
calculating the relative error of the electric energy meter to be detected according to the electric power data of the electric energy meter to be detected, and calculating the relative error of the device to be detected according to the verification data of the verification device to be detected;
calculating a basic error model according to the relative error of the detected electric energy meter and the relative error of the detected device, wherein the basic error model is as follows:
Y(％)＝X(％)―θ(％)
wherein X (%) represents the basic error of the electric energy meter to be detected,θ (%) represents the relative error of the assay device to be tested, +.>W e Indicating electric energy, W, of the device to be inspected 0 Representing the measured electrical energy of the reference standard;
and constructing an error distribution function model of the electric energy meter by combining the basic error model according to the central limit theorem and the Bayesian hierarchical model.
4. The method for checking a verification device according to claim 1, wherein the checking the verification data by using a preset electric energy meter error distribution function model to obtain a checking error result comprises:
performing error calculation according to the kth verification data of the verification device to be checked to obtain an error distribution model;
obtaining posterior probability distribution according to the Bayesian theorem and each parameter in the error distribution model;
and after the posterior probability distribution is sampled by using a Gibbs sampling method, obtaining an edge distribution sample of standard device error by using the samples of the joint distribution, and calculating to obtain an error checking result.
5. The method for checking the verification device according to claim 1, wherein the checking the verification device to be checked according to the alarm checking task or the early warning checking task comprises:
and checking the verification device to be checked by adopting preset physical checking equipment according to the alarm checking task or the early warning checking task.
6. A verification method for an assay device as defined in claim 5, wherein said predetermined physical verification means is preferably a 0.02 level physical verification means of a size compatible with existing electrical energy meters and having a high stability.
7. A verification system for an assay device, comprising:
the acquisition module is used for acquiring verification data of the verification device to be checked;
the first checking module is used for checking the verification data by using a preset electric energy meter error distribution function model to obtain a checking error result, wherein the preset electric energy meter error distribution function model is constructed according to historical verification data;
the second checking module is used for comparing the error result with a preset value, if the error result is larger than the first preset value and smaller than the second preset value, starting an alarm process and generating an alarm checking task, and if the error result is larger than the second preset value, starting an early warning process and generating an early warning checking task;
and the third checking module is used for checking the to-be-checked calibrating device according to the alarm checking task or the early warning checking task to obtain a first checking result, ending the checking if the first checking result reaches a preset condition, checking the to-be-checked calibrating device according to the preset checking task to obtain a second checking result if the error result is smaller than a first preset value, and ending the checking if the second checking result reaches the preset condition.
8. The verification system of claim 7, further comprising:
the judging module is used for judging whether a plurality of same alarm checking tasks or a plurality of same early warning checking tasks exist, if yes, judging whether the same alarm checking tasks or the same early warning checking tasks are finished or not, and if yes, finishing the checking tasks;
if the same alarm checking task or the same early warning checking task exists and belongs to the same line body and different devices, combining the same alarm checking task or the same early warning checking task into one alarm checking task or the same early warning checking task for checking.
9. The verification system of claim 7, wherein the error distribution function model of the preset electric energy meter is constructed according to historical verification data, and specifically comprises:
calculating the relative error of the electric energy meter to be detected according to the electric power data of the electric energy meter to be detected, and calculating the relative error of the device to be detected according to the verification data of the verification device to be detected;
calculating a basic error model according to the relative error of the detected electric energy meter and the relative error of the detected device, wherein the basic error model is as follows:
Y(％)＝X(％)―θ(％)
wherein X (%) represents the basic error of the electric energy meter to be detected,θ (%) represents the relative error of the assay device to be tested, +.>W e Indicating electric energy, W, of the device to be inspected 0 Representing the measured electrical energy of the reference standard;
and constructing an error distribution function model of the electric energy meter by combining the basic error model according to the central limit theorem and the Bayesian hierarchical model.
10. The verification system of claim 7, wherein the verification data is verified by using a preset electric energy meter error distribution function model to obtain a verification error result, and the verification error result is specifically:
performing error calculation according to the kth verification data of the verification device to be checked to obtain an error distribution model;
obtaining posterior probability distribution according to the Bayesian theorem and each parameter in the error distribution model;
and after the posterior probability distribution is sampled by using a Gibbs sampling method, obtaining an edge distribution sample of standard device error by using the samples of the joint distribution, and calculating to obtain an error checking result.
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| CN117406161B (en) * | 2023-12-11 | 2024-04-02 | 普华讯光（北京）科技有限公司 | Metering device magnitude deviation early warning method, system, equipment and medium |
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