CN110544031B - Method and device for predicting reliability of electric energy meter, computer equipment and storage medium - Google Patents
Method and device for predicting reliability of electric energy meter, computer equipment and storage medium Download PDFInfo
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Abstract
The application relates to a method and a device for predicting reliability of an electric energy meter, computer equipment and a storage medium, and belongs to the technical field of electric power. Acquiring the failure rate of each component of a target electric energy meter, then acquiring the estimated failure rate of each component of the target electric energy meter, and then acquiring the total failure rate of the target electric energy meter according to the failure rate of each component of the target electric energy meter and the estimated failure rate of each component of the target electric energy meter; and obtaining a reliability function of the target electric energy meter according to the total failure rate of the target electric energy meter, and outputting a reliability prediction curve of the target electric energy meter according to the reliability function. By adopting the method, the accuracy of the reliability prediction of the electric energy meter can be improved.
Description
Technical Field
The present application relates to the field of power technologies, and in particular, to a method and an apparatus for predicting reliability of an electric energy meter, a computer device, and a storage medium.
Background
With the continuous development of the power industry, a large number of electric energy meters in China are put into operation, and the electric energy meters are measuring instruments with the functions of electric energy metering, data processing, real-time monitoring, automatic control, information interaction and the like. The requirement of the power grid on the reliability of the electric energy meter is gradually improved, and the reliability refers to the capability of the electric energy meter to complete specified functions in specified time and under specified conditions. The reliability of the electric energy meter is expected to be an important technical means for improving the reliability of the electric energy meter, and the importance of the reliability is also obviously improved.
At present, various researches are made on the reliability prediction of the electric energy meter at home and abroad, and various reliability prediction manuals of the electric energy meter are provided, such as SN29500 standard of Siemens company, IEC62059 series standard issued by International electrotechnical Commission, Telcordia SR-332 standard developed by original Bell communication research center, and the reliability prediction of the electric energy meter can be carried out according to the reliability prediction manuals of the electric energy meter.
However, in practical applications, due to the complexity of environmental factors, the reliability of the electric energy meter cannot be predicted accurately by only relying on the reliability prediction manual of the electric energy meter.
Disclosure of Invention
In view of the above, it is necessary to provide a method, an apparatus, a computer device, and a storage medium for estimating reliability of an electric energy meter, which can improve accuracy of a result of estimating reliability of an electric energy meter, in view of the above technical problems.
In a first aspect, the present application provides a method for predicting reliability of an electric energy meter, the method comprising:
acquiring the failure rate of each component of a target electric energy meter, wherein the failure rate of the manual is calculated according to stress factors recorded in a reliability prediction manual of the target electric energy meter, and the stress factors are used for representing the influence degree of environmental factors on the performance of each component of the target electric energy meter;
obtaining estimated failure rates of all components of the target electric energy meter, wherein the estimated failure rates are obtained by predicting the failure rates of all components in the electric energy meter which is recycled historically;
acquiring the total failure rate of the target electric energy meter according to the manual failure rate of each component of the target electric energy meter and the estimated failure rate of each component of the target electric energy meter;
obtaining a reliability function of the target electric energy meter according to the total failure rate of the target electric energy meter, wherein the reliability function is used for representing the capability of the target electric energy meter to realize specified functions under different operation time lengths;
and outputting a reliability prediction curve of the target electric energy meter according to the reliability function.
In one embodiment, the obtaining of the failure rate of the handbook for each component of the target electric energy meter includes:
obtaining a component failure rate formula recorded in the reliability prediction manual;
acquiring the stress factor recorded in the reliability prediction manual;
and calculating the failure rate of each component of the target electric energy meter according to the component failure rate formula and the stress factor.
In one embodiment, the obtaining of the estimated failure rate of each component of the target electric energy meter includes:
and analyzing the failure rate of each component in the historically recycled electric energy meter by adopting a point estimation method to obtain the estimated failure rate of each component of the target electric energy meter.
In one embodiment, the obtaining the total failure rate of the target electric energy meter according to the manual failure rate of each component of the target electric energy meter and the estimated failure rate of each component of the target electric energy meter includes:
acquiring failure rates of all functional modules of the target electric energy meter according to the manual failure rate of all components of the target electric energy meter and the estimated failure rate of all components of the target electric energy meter, wherein all functional modules of the target electric energy meter comprise at least one component of the target electric energy meter;
and summing the failure rates of all the functional modules of the target electric energy meter to obtain the total failure rate of the target electric energy meter.
In one embodiment, the obtaining the failure rate of each functional module of the target electric energy meter according to the manual failure rate of each component of the target electric energy meter and the estimated failure rate of each component of the target electric energy meter includes:
for each functional module, summing the failure rates of the manuals of the components contained in the functional module to obtain the failure rate of the manuals of the functional module;
for each functional module, summing the estimated failure rates of the components contained in the functional module to obtain the estimated failure rate of the functional module;
for each of the functional modules, determining an average of the manual failure rate of the functional module and the estimated failure rate of the functional module as the failure rate of the functional module.
In one embodiment, the obtaining the reliability function of the target electric energy meter according to the total failure rate of the target electric energy meter includes:
determining a first function as a reliability function of the target electric energy meter;
the first function is:
wherein λ issAnd t represents the running time of the target electric energy meter.
And obtaining the average service life of the target electric energy meter according to the total failure rate of the target electric energy meter, wherein the average service life of the target electric energy meter is used for representing the average working time of the target electric energy meter before failure.
In one embodiment, after obtaining the failure rates of the functional modules of the target electric energy meter according to the manual failure rate of each component of the target electric energy meter and the estimated failure rate of each component of the target electric energy meter, the method further includes:
obtaining the difference value between the estimated failure rates of the same functional module in different batches of target electric energy meters to obtain a plurality of first difference values;
and when a target first difference value in the plurality of first difference values is larger than a first preset difference value threshold, outputting a fault prompt of the functional module corresponding to the target first difference value.
Obtaining difference values between failure rates of manuals of the same functional module in different batches of target electric energy meters to obtain a plurality of second difference values;
and outputting a fault prompt of the functional module corresponding to the target second difference value when the target second difference value in the plurality of second difference values is larger than a second preset difference value threshold.
In a second aspect, the present application provides an apparatus for predicting reliability of an electric energy meter, the apparatus comprising:
the first acquisition module is used for acquiring the failure rate of a manual of each component of the target electric energy meter, the failure rate of the manual is obtained by calculation according to stress factors recorded in a reliability prediction manual of the target electric energy meter, and the stress factors are used for representing the influence degree of environmental factors on the performance of each component of the target electric energy meter;
the second acquisition module is used for acquiring the estimated failure rate of each component of the target electric energy meter, and the estimated failure rate is obtained by predicting the failure rate of each component in the electric energy meter which is recycled historically;
the third acquisition module is used for acquiring the total failure rate of the target electric energy meter according to the manual failure rate of each component of the target electric energy meter and the estimated failure rate of each component of the target electric energy meter;
the reliability function acquisition module is used for acquiring a reliability function of the target electric energy meter according to the total failure rate of the target electric energy meter, and the reliability function is used for representing the capability of the target electric energy meter for realizing specified functions under different running time lengths;
and the output module is used for outputting the reliability prediction curve of the target electric energy meter according to the reliability function.
In one embodiment, the first obtaining module is specifically configured to:
obtaining a component failure rate formula recorded in the reliability prediction manual;
acquiring the stress factor recorded in the reliability prediction manual;
and calculating the failure rate of each component of the target electric energy meter according to the component failure rate formula and the stress factor.
In one embodiment, the second obtaining module is specifically configured to:
and analyzing the failure rate of each component in the historically recycled electric energy meter by adopting a point estimation method to obtain the estimated failure rate of each component of the target electric energy meter.
In one embodiment, the third obtaining module is specifically configured to:
acquiring failure rates of all functional modules of the target electric energy meter according to the manual failure rate of all components of the target electric energy meter and the estimated failure rate of all components of the target electric energy meter, wherein all functional modules of the target electric energy meter comprise at least one component of the target electric energy meter;
and summing the failure rates of all the functional modules of the target electric energy meter to obtain the total failure rate of the target electric energy meter.
In one embodiment, the third obtaining module is specifically configured to:
for each functional module, summing the failure rates of the manuals of the components contained in the functional module to obtain the failure rate of the manuals of the functional module;
for each functional module, summing the estimated failure rates of the components contained in the functional module to obtain the estimated failure rate of the functional module;
for each of the functional modules, determining an average of the manual failure rate of the functional module and the estimated failure rate of the functional module as the failure rate of the functional module.
In one embodiment, the reliability function obtaining module is specifically configured to:
determining a first function as a reliability function of the target electric energy meter;
the first function is:
wherein λ issAnd t represents the running time of the target electric energy meter.
In one embodiment, the apparatus further comprises an average lifetime obtaining module, configured to:
and obtaining the average service life of the target electric energy meter according to the total failure rate of the target electric energy meter, wherein the average service life of the target electric energy meter is used for representing the average working time of the target electric energy meter before failure.
In one embodiment, the apparatus further comprises a prompt module configured to:
obtaining the difference value between the estimated failure rates of the same functional module in different batches of target electric energy meters to obtain a plurality of first difference values;
and when a target first difference value in the plurality of first difference values is larger than a first preset difference value threshold, outputting a fault prompt of the functional module corresponding to the target first difference value.
In one embodiment, the prompt module is further configured to:
obtaining difference values between failure rates of manuals of the same functional module in different batches of target electric energy meters to obtain a plurality of second difference values;
and outputting a fault prompt of the functional module corresponding to the target second difference value when the target second difference value in the plurality of second difference values is larger than a second preset difference value threshold.
In a third aspect, the present application provides a computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the steps of any of the first aspects when executing the computer program.
In a fourth aspect, the present application provides a computer readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of any of the first aspects described above.
According to the method, the device, the computer equipment and the storage medium for predicting the reliability of the electric energy meter, the failure rate of each component of the target electric energy meter is obtained by obtaining the failure rate of each component of the target electric energy meter, the failure rate of each component is obtained by calculation according to the stress factor recorded in the reliability prediction manual of the target electric energy meter, and the stress factor is used for representing the influence degree of environmental factors on the performance of each component of the target electric energy meter; then, obtaining the estimated failure rate of each component of the target electric energy meter, wherein the estimated failure rate is obtained by predicting the failure rate of each component in the electric energy meter which is recycled according to history; then, acquiring the total failure rate of the target electric energy meter according to the manual failure rate of each component of the target electric energy meter and the estimated failure rate of each component of the target electric energy meter; obtaining a reliability function of the target electric energy meter according to the total failure rate of the target electric energy meter, wherein the reliability function is used for representing the capability of the target electric energy meter to realize specified functions under different operation time lengths; and finally, outputting a reliability prediction curve of the target electric energy meter according to the reliability function.
The failure rate of the manual in the scheme is obtained according to the reliability prediction manual; the estimated failure rate in the scheme is obtained by analyzing the failure rate of the electric energy meter recovered historically, and the estimated failure rate fully considers the influence of environmental factors on the reliability of the electric energy meter when the electric energy meter is applied on site. Therefore, the method and the device solve the problem that in the related technology, the reliability of the electric energy meter is predicted only by means of the reliability prediction manual, and the accuracy of the predicted reliability is low due to the fact that the influence of field environment factors on the reliability of the electric energy meter is not considered by combining the failure rate of the manual with the estimation failure rate.
Drawings
FIG. 1 is a diagram illustrating an exemplary implementation of a method for estimating reliability of an electric energy meter;
FIG. 2 is a schematic flow chart illustrating a method for estimating reliability of an electric energy meter according to an embodiment;
FIG. 3 is a flowchart illustrating the step of obtaining the total failure rate of the target electric energy meter in one embodiment;
FIG. 4 is a flowchart illustrating a step of obtaining failure rates of functional modules of the target electric energy meter in one embodiment;
FIG. 5 is a flowchart of the output fault indication step in one embodiment;
FIG. 6 is a flow diagram of another step of outputting a fault indication in one embodiment;
FIG. 7 is a schematic diagram of an exemplary embodiment of an apparatus for predicting reliability of an electric energy meter;
FIG. 8 is a block diagram of another apparatus for predicting reliability of an electric energy meter, according to an embodiment;
FIG. 9 is a diagram illustrating an internal structure of a computer device according to an embodiment.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.
The method for predicting the reliability of the electric energy meter can be applied to the application environment shown in fig. 1. In which a terminal 101 communicates with a server 102 via a network. Firstly, the server 102 acquires the failure rate of each component of the target electric energy meter, wherein the failure rate of each component is calculated according to the stress factor recorded in the reliability prediction manual of the target electric energy meter, and the stress factor is used for representing the influence degree of the environmental factor on the performance of each component of the target electric energy meter; then, the server 102 obtains estimated failure rates of all components of the target electric energy meter, wherein the estimated failure rates are obtained by predicting the failure rates of all components in the electric energy meter which is recycled historically; then, the server 102 obtains the total failure rate of the target electric energy meter according to the manual failure rate of each component of the target electric energy meter and the estimated failure rate of each component of the target electric energy meter; then the server 102 obtains a reliability function of the target electric energy meter according to the total failure rate of the target electric energy meter, wherein the reliability function is used for representing the capability of the target electric energy meter to realize specified functions under different operation time lengths; finally, the server 102 outputs the reliability prediction curve of the target electric energy meter to the terminal 101 according to the reliability function.
The terminal 101 may be, but not limited to, various personal computers, notebook computers, smart phones, tablet computers, and portable wearable devices, and the server 102 may be implemented by an independent server or a server cluster formed by a plurality of servers.
In one embodiment, as shown in fig. 2, a method for predicting reliability of an electric energy meter is provided, which is described by taking the method as an example applied to the server 102 in fig. 1, and includes the following steps:
The failure rate of the handbook is calculated according to stress factors recorded in a reliability prediction handbook of the target electric energy meter, and the stress factors are used for representing the influence degree of environmental factors on the performance of each element of the target electric energy meter.
Failure rate refers to the probability that a product will lose its intended function after it has been used for a given length of time under given conditions of use. For example, diodes produced in the same batch are used for a specified period of time of 50 hours at 0 ℃ to 60 ℃ and for a specified function of reverse conductivity. If the batch of diodes has a failure rate of 0.2 when the batch of diodes is used for 50 hours under the use condition of 0-60 ℃, the diodes losing reverse conduction capability account for 20% of the batch of diodes.
The stress factor is a numerical value, and in the embodiment of the present application, is used to indicate the degree to which the performance of the object is affected by environmental factors (e.g., force, temperature, humidity, current, voltage, etc.). The stress factor in calculating the component failure rate represents factors (e.g., quality factor, temperature factor, humidity factor, electrical stress factor, etc.) that affect the component failure rate. Different stress factors are used when calculating the failure rates of different components, and the same stress factor has different values for different types of components.
In this step, a formula for calculating the failure rate of each component and a stress factor corresponding to each type of component are recorded in the reliability prediction manual. Different reliability prediction manuals may give different calculation formulas for each component failure rate. In the examples of the present application,. pi.iExpressing the stress factor by λpAnd indicating the failure rate of each component in the target electric energy meter.
The estimated failure rate is obtained by predicting the failure rate of each component in the electric energy meter which is recycled according to the history.
The historical recovered electric energy meter refers to an electric energy meter which is recovered from an actual application environment and is operated for a specified time.
In this step, the prediction method may include a point estimation method and a statistical method.
In the examples of this application, λ is usedcAnd representing the estimated failure rate of each component in the target electric energy meter.
And step 203, the server acquires the total failure rate of the target electric energy meter according to the manual failure rate of each component of the target electric energy meter and the estimated failure rate of each component of the target electric energy meter.
The total failure rate of the target electric energy meter is that the electric energy meter is taken as a whole, the integral failure rate of the electric energy meter is judged, and the total failure rate of the electric energy meter is obtained. An electric energy meter typically includes a plurality of components.
In this step, the total failure rate of the target electric energy meter can be obtained through a mathematical calculation mode. In the present application with lambdasRepresenting the total failure rate of the target electric energy meter.
And 204, the server obtains a reliability function of the target electric energy meter according to the total failure rate of the target electric energy meter.
The reliability function is used for representing the capability of the target electric energy meter to realize the specified function under different operation time lengths.
In this step, the total failure rate λ of the target electric energy meter can be determinedsAnd substituting the reliability function into a reliability calculation formula to obtain the reliability function of the target electric energy meter. The reliability function of the target power meter is represented by R (t), which is a time-dependent function.
In step 205, the server outputs a reliability prediction curve of the target electric energy meter according to the reliability function.
The reliability prediction curve is in a coordinate axis with time t as an abscissa and reliability R (t) as an ordinate, and the reliability of the target electric energy meter at each time can be known through the reliability prediction curve.
In the method for predicting the reliability of the electric energy meter, the failure rate of each component of the target electric energy meter is obtained by obtaining the failure rate of each component of the target electric energy meter, wherein the failure rate of each component is obtained by calculation according to the stress factor recorded in the reliability prediction manual of the target electric energy meter, and the stress factor is used for representing the influence degree of environmental factors on the performance of each component of the target electric energy meter; then, obtaining the estimated failure rate of each component of the target electric energy meter, wherein the estimated failure rate is obtained by predicting the failure rate of each component in the electric energy meter which is recycled according to history; then, acquiring the total failure rate of the target electric energy meter according to the manual failure rate of each component of the target electric energy meter and the estimated failure rate of each component of the target electric energy meter; obtaining a reliability function of the target electric energy meter according to the total failure rate of the target electric energy meter, wherein the reliability function is used for representing the capability of the target electric energy meter to realize specified functions under different operation time lengths; and finally, outputting a reliability prediction curve of the target electric energy meter according to the reliability function.
Because the failure rate of the manual in the scheme is obtained according to the reliability prediction manual; the estimated failure rate in the scheme is obtained by analyzing the failure rate of the electric energy meter used on site, and the estimated failure rate fully considers the influence of environmental factors on the reliability of the electric energy meter when the electric energy meter is applied on site. Therefore, the method and the device solve the problem that in the related technology, the reliability of the electric energy meter is predicted only by means of the reliability prediction manual, and the accuracy of the predicted reliability is low due to the fact that the influence of field environment factors on the reliability of the electric energy meter is not considered by combining the failure rate of the manual with the estimation failure rate.
In one embodiment, a method for acquiring manual failure rate of each component of the target electric energy meter is provided, and the method comprises the following steps:
and finally, the server calculates the failure rate of each component of the target electric energy meter according to the failure rate formula of the component and the stress factor.
Component manual failure rate formula that this embodiment providedIs that
Wherein λbIs a fundamental failure rate, which is usually a certain value. The stress factor and component manual failure rate formula is stored in the server, and a calculation result can be obtained by directly calling during calculation without spending a large amount of time for searching data and calculating, so that certain calculation time is saved.
In one embodiment, a method for obtaining an estimated failure rate of each component of the target electric energy meter is provided, and the method includes:
and analyzing the failure rate of each component in the historically recovered electric energy meter by the server by adopting a point estimation method to obtain the estimated failure rate of each component of the target electric energy meter.
In the embodiment of the application, the historically recycled electric energy meter is influenced by the actual application environment, so that the influence factors of the actual application environment are fully considered in the obtained estimated failure rate. The estimated failure rate is used for subsequently calculating the total failure rate of the target electric energy meter, so that the total failure rate of the target electric energy meter is more accurate than that calculated by only depending on a reliability prediction manual.
In one embodiment, referring to fig. 3, the step of obtaining the total failure rate of the target electric energy meter includes:
Each functional module of the target electric energy meter comprises at least one component of the target electric energy meter.
In this step, the target electric energy meter may be regarded as being formed by connecting at least one functional module in series, wherein each functional module may be regarded as being formed by connecting at least one component in series. Therefore, the failure rate of the functional module can be obtained first through the failure of the components, and then the total failure rate of the target electric energy meter can be obtained according to the failure rate of the functional module.
In this step, since the functional modules included in the target electric energy meter are regarded as being connected in series, the failure rates of the functional modules can be summed to obtain the total failure rate of the target electric energy meter,
in the embodiment of the application, when the total failure rate of the target electric energy meter is calculated, the target electric energy meter is regarded as being formed by connecting a plurality of functional modules in series, so that the calculation complexity is simplified during calculation, and the time for calculating the total failure rate of the target electric energy meter is reduced. In the examples of this application, λ is usediAnd indicating the failure rate of each functional module of the target electric energy meter.
In one embodiment, please refer to fig. 4, a step of obtaining failure rates of functional modules of a target electric energy meter is provided, which includes:
In this step, each functional module is regarded as being composed of at least one component connected in series, and therefore, the failure rates of the manuals of the functional modules can be obtained by summing the failure rates of the manuals of the components included in the functional modules.
This step is the same as step 401 and will not be described again.
In step 403, for each of the function modules, the server determines the average of the manual failure rate of the function module and the estimated failure rate of the function module as the failure rate of the function module.
In this step, the failure rate of each functional module is determined by the mean of the manual failure rate and the estimated failure rate of the functional module. The purpose is to ensure that the failure rate of each finally obtained functional module has manual failureRate and estimated failure rate. Alternatively, the manual failure rate and the estimated failure rate may be fused together in other ways, such as multiplication or addition. In the present application with lambdaAiA manual for indicating failure rate of each functional module by λBiIndicating the estimated failure rate of each functional module. The failure rate of each functional module can be defined byi＝1/2(λAi+λBi) And (6) calculating.
In the embodiment of the application, when the failure rate of each functional module is calculated, the failure rate of the manual of the functional module and the failure rate estimation are reasonably fused, so that the failure rate of each functional module obtained by the embodiment not only considers the result of the electric energy meter prediction manual, but also considers the factors of the field environment, and the failure rate of each functional module obtained by the embodiment of the application has higher accuracy compared with the failure rate calculated only by relying on the electric energy meter prediction manual in practical application.
In one embodiment, a method for obtaining a reliability function of a target electric energy meter according to a total failure rate of the target electric energy meter is provided, and the method includes:
the server determines a first function as a reliability function of the target electric energy meter, wherein the first function is as follows:
wherein λ issAnd t represents the running time of the target electric energy meter.
In the embodiment of the application, the total failure rate and the running time of the target electric energy meter can be substituted into the first function to obtain the reliability value of the target electric energy meter at each moment, a specific value can be accurately obtained by using the first function, and a user can conveniently inquire the reliability of the target electric energy meter.
In one embodiment, a method for obtaining an average life of a target electric energy meter is provided, and the method comprises the following steps:
and the server obtains the average service life of the target electric energy meter according to the total failure rate of the target electric energy meter, wherein the average service life of the target electric energy meter is used for representing the average working time of the target electric energy meter before failure.
In the embodiment of the present application, the average life of the target electric energy meter is expressed by MTTF, and in the embodiment, a calculation method of MTTF is given, where MTTF is 1/λsAnd the current use condition of the target electric energy meter can be judged more specifically by calculating the MTTF.
In one embodiment, referring to fig. 5, a process of outputting a fault indication step is provided, where the process includes:
In this step, generally, the reliability of the electric energy meters produced in the same batch is substantially the same, so that the electric energy meters in the same batch are described by using the same reliability value. The same functional modules contained in the same batch of electric energy meters can also be described by the same reliability value. The difference value between the estimated failure rates of the same functional module in different batches of electric energy meters is obtained. The difference value represents the difference of the estimated reliability of the same functional module in different batches, and the larger the difference value is, the larger the reliability difference of each batch of the functional module is, so that it can be estimated that the stability of the functional module is poor, that is, in practical use, the functional module has a high probability of failure.
In this step, a first difference threshold value may be preset to help determine whether each functional module has a fault, so as to give a corresponding fault prompt.
In the embodiment of the application, through reasonable use of the data of the predicted failure rates of the functional modules, after the reliability of the electric energy meter is obtained, corresponding fault prompts can be further provided, and maintenance work of the electric energy meter in actual use is facilitated.
In one embodiment, referring to fig. 6, another flow of outputting the failure indication step is provided, where the flow includes:
The embodiment of the present application is similar to the steps 501 and 502, and is not described herein again.
It should be understood that although the various steps in the flow charts of fig. 2-6 are shown in order as indicated by the arrows, the steps are not necessarily performed in order as indicated by the arrows. The steps are not performed in the exact order shown and described, and may be performed in other orders, unless explicitly stated otherwise. Moreover, at least some of the steps in fig. 2-6 may include multiple sub-steps or multiple stages that are not necessarily performed at the same time, but may be performed at different times, and the order of performance of the sub-steps or stages is not necessarily sequential, but may be performed in turn or alternating with other steps or at least some of the sub-steps or stages of other steps.
In one embodiment, as shown in fig. 7, there is provided an electric energy meter reliability prediction apparatus 700 including: a first obtaining module 701, a second obtaining module 702, a third obtaining module 703, a reliability function obtaining module 704, and an output module 705, wherein:
the first obtaining module 701 is used for obtaining the failure rate of a manual of each component of the target electric energy meter, wherein the failure rate of the manual is obtained by calculation according to a stress factor recorded in a reliability prediction manual of the target electric energy meter, and the stress factor is used for representing the influence degree of an environmental factor on the performance of each component of the target electric energy meter;
a second obtaining module 702, configured to obtain an estimated failure rate of each component of the target electric energy meter, where the estimated failure rate is obtained by predicting the failure rate of each component in the electric energy meter recycled historically;
a third obtaining module 703, configured to obtain a total failure rate of the target electric energy meter according to the manual failure rate of each component of the target electric energy meter and the estimated failure rate of each component of the target electric energy meter;
a reliability function obtaining module 704, configured to obtain a reliability function of the target electric energy meter according to the total failure rate of the target electric energy meter, where the reliability function is used to represent the capability of the target electric energy meter to implement a specified function under different operation durations;
the output module 705 is configured to output a reliability prediction curve of the target electric energy meter according to the reliability function.
In one embodiment, the first obtaining module 701 is specifically configured to:
obtaining a component failure rate formula recorded in the reliability prediction manual;
acquiring the stress factor recorded in the reliability prediction manual;
and calculating the failure rate of each component of the target electric energy meter according to the component failure rate formula and the stress factor.
In one embodiment, the second obtaining module 702 is specifically configured to:
and analyzing the failure rate of each component in the historically recycled electric energy meter by adopting a point estimation method to obtain the estimated failure rate of each component of the target electric energy meter.
In one embodiment, the third obtaining module 703 is specifically configured to:
acquiring failure rates of all functional modules of the target electric energy meter according to the manual failure rate of all components of the target electric energy meter and the estimated failure rate of all components of the target electric energy meter, wherein all functional modules of the target electric energy meter comprise at least one component of the target electric energy meter;
and summing the failure rates of all the functional modules of the target electric energy meter to obtain the total failure rate of the target electric energy meter.
In one embodiment, the third obtaining module 703 is specifically configured to:
for each functional module, summing the failure rates of the manuals of the components contained in the functional module to obtain the failure rate of the manuals of the functional module;
for each functional module, summing the estimated failure rates of the components contained in the functional module to obtain the estimated failure rate of the functional module;
for each of the functional modules, determining an average of the manual failure rate of the functional module and the estimated failure rate of the functional module as the failure rate of the functional module.
In one embodiment, the reliability function obtaining module 704 is further configured to:
determining a first function as a reliability function of the target electric energy meter;
the first function is:
wherein λ issAnd t represents the running time of the target electric energy meter.
Referring to fig. 8, another electric energy meter reliability prediction apparatus 800 is provided in the embodiments of the present application, where the electric energy meter reliability prediction apparatus 800 includes, in addition to the modules of the electric energy meter reliability prediction apparatus 700, optionally, the electric energy meter reliability prediction apparatus 800 further includes an average lifetime obtaining module 706 and a prompting module 707.
In one embodiment, the average lifetime obtaining module 706 is configured to: and obtaining the average service life of the target electric energy meter according to the total failure rate of the target electric energy meter, wherein the average service life of the target electric energy meter is used for representing the average working time of the target electric energy meter before failure.
In one embodiment, the prompt module 707 is configured to:
obtaining the difference value between the estimated failure rates of the same functional module in different batches of target electric energy meters to obtain a plurality of first difference values;
and when a target first difference value in the plurality of first difference values is larger than a first preset difference value threshold, outputting a fault prompt of the functional module corresponding to the target first difference value.
In one embodiment, the prompt module 706 is further configured to:
obtaining difference values between failure rates of manuals of the same functional module in different batches of target electric energy meters to obtain a plurality of second difference values;
and outputting a fault prompt of the functional module corresponding to the target second difference value when the target second difference value in the plurality of second difference values is larger than a second preset difference value threshold.
For specific limitations of the device for predicting the reliability of the electric energy meter, reference may be made to the above limitations of the method for predicting the reliability of the electric energy meter, and details thereof are not repeated here. The modules in the device for predicting the reliability of the electric energy meter can be completely or partially realized by software, hardware and a combination thereof. The modules can be embedded in a hardware form or independent from a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.
In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as shown in fig. 9. The computer device includes a processor, a memory, a network interface, and a database connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The database of the computer device is used for storing reliability prediction data of the electric energy meter. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement a method of reliability prediction for an electric energy meter.
Those skilled in the art will appreciate that the architecture shown in fig. 9 is merely a block diagram of some of the structures associated with the disclosed aspects and is not intended to limit the computing devices to which the disclosed aspects apply, as particular computing devices may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.
In one embodiment, a computer device is provided, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, the processor implementing the following steps when executing the computer program:
acquiring the failure rate of each component of a target electric energy meter, wherein the failure rate of the manual is calculated according to stress factors recorded in a reliability prediction manual of the target electric energy meter, and the stress factors are used for representing the influence degree of environmental factors on the performance of each component of the target electric energy meter;
obtaining estimated failure rates of all components of the target electric energy meter, wherein the estimated failure rates are obtained by predicting the failure rates of all components in the electric energy meter which is recycled historically;
acquiring the total failure rate of the target electric energy meter according to the manual failure rate of each component of the target electric energy meter and the estimated failure rate of each component of the target electric energy meter;
obtaining a reliability function of the target electric energy meter according to the total failure rate of the target electric energy meter, wherein the reliability function is used for representing the capability of the target electric energy meter to realize specified functions under different operation time lengths;
and outputting a reliability prediction curve of the target electric energy meter according to the reliability function.
In one embodiment, the obtaining of the failure rate of the handbook for each component of the target electric energy meter includes:
obtaining a component failure rate formula recorded in the reliability prediction manual;
acquiring the stress factor recorded in the reliability prediction manual;
and calculating the failure rate of each component of the target electric energy meter according to the component failure rate formula and the stress factor.
In one embodiment, the obtaining of the estimated failure rate of each component of the target electric energy meter includes:
and analyzing the failure rate of each component in the historically recycled electric energy meter by adopting a point estimation method to obtain the estimated failure rate of each component of the target electric energy meter.
In one embodiment, the obtaining the total failure rate of the target electric energy meter according to the manual failure rate of each component of the target electric energy meter and the estimated failure rate of each component of the target electric energy meter includes:
acquiring failure rates of all functional modules of the target electric energy meter according to the manual failure rate of all components of the target electric energy meter and the estimated failure rate of all components of the target electric energy meter, wherein all functional modules of the target electric energy meter comprise at least one component of the target electric energy meter;
and summing the failure rates of all the functional modules of the target electric energy meter to obtain the total failure rate of the target electric energy meter.
In one embodiment, the obtaining the failure rate of each functional module of the target electric energy meter according to the manual failure rate of each component of the target electric energy meter and the estimated failure rate of each component of the target electric energy meter includes:
for each functional module, summing the failure rates of the manuals of the components contained in the functional module to obtain the failure rate of the manuals of the functional module;
for each functional module, summing the estimated failure rates of the components contained in the functional module to obtain the estimated failure rate of the functional module;
for each of the functional modules, determining an average of the manual failure rate of the functional module and the estimated failure rate of the functional module as the failure rate of the functional module.
In one embodiment, the obtaining the reliability function of the target electric energy meter according to the total failure rate of the target electric energy meter includes:
determining a first function as a reliability function of the target electric energy meter;
the first function is:
wherein λ issAnd t represents the running time of the target electric energy meter.
And obtaining the average service life of the target electric energy meter according to the total failure rate of the target electric energy meter, wherein the average service life of the target electric energy meter is used for representing the average working time of the target electric energy meter before failure.
In one embodiment, after obtaining the failure rates of the functional modules of the target electric energy meter according to the manual failure rate of each component of the target electric energy meter and the estimated failure rate of each component of the target electric energy meter, the method further includes:
obtaining the difference value between the estimated failure rates of the same functional module in different batches of target electric energy meters to obtain a plurality of first difference values;
and when a target first difference value in the plurality of first difference values is larger than a first preset difference value threshold, outputting a fault prompt of the functional module corresponding to the target first difference value.
Obtaining difference values between failure rates of manuals of the same functional module in different batches of target electric energy meters to obtain a plurality of second difference values;
and outputting a fault prompt of the functional module corresponding to the target second difference value when the target second difference value in the plurality of second difference values is larger than a second preset difference value threshold.
In one embodiment, a computer-readable storage medium is provided, having a computer program stored thereon, which when executed by a processor, performs the steps of:
acquiring the failure rate of each component of a target electric energy meter, wherein the failure rate of the manual is calculated according to stress factors recorded in a reliability prediction manual of the target electric energy meter, and the stress factors are used for representing the influence degree of environmental factors on the performance of each component of the target electric energy meter;
obtaining estimated failure rates of all components of the target electric energy meter, wherein the estimated failure rates are obtained by predicting the failure rates of all components in the electric energy meter which is recycled historically;
acquiring the total failure rate of the target electric energy meter according to the manual failure rate of each component of the target electric energy meter and the estimated failure rate of each component of the target electric energy meter;
obtaining a reliability function of the target electric energy meter according to the total failure rate of the target electric energy meter, wherein the reliability function is used for representing the capability of the target electric energy meter to realize specified functions under different operation time lengths;
and outputting a reliability prediction curve of the target electric energy meter according to the reliability function.
In one embodiment, the obtaining of the failure rate of the handbook for each component of the target electric energy meter includes:
obtaining a component failure rate formula recorded in the reliability prediction manual;
acquiring the stress factor recorded in the reliability prediction manual;
and calculating the failure rate of each component of the target electric energy meter according to the component failure rate formula and the stress factor.
In one embodiment, the obtaining of the estimated failure rate of each component of the target electric energy meter includes:
and analyzing the failure rate of each component in the historically recycled electric energy meter by adopting a point estimation method to obtain the estimated failure rate of each component of the target electric energy meter.
In one embodiment, the obtaining the total failure rate of the target electric energy meter according to the manual failure rate of each component of the target electric energy meter and the estimated failure rate of each component of the target electric energy meter includes:
acquiring failure rates of all functional modules of the target electric energy meter according to the manual failure rate of all components of the target electric energy meter and the estimated failure rate of all components of the target electric energy meter, wherein all functional modules of the target electric energy meter comprise at least one component of the target electric energy meter;
and summing the failure rates of all the functional modules of the target electric energy meter to obtain the total failure rate of the target electric energy meter.
In one embodiment, the obtaining the failure rate of each functional module of the target electric energy meter according to the manual failure rate of each component of the target electric energy meter and the estimated failure rate of each component of the target electric energy meter includes:
for each functional module, summing the failure rates of the manuals of the components contained in the functional module to obtain the failure rate of the manuals of the functional module;
for each functional module, summing the estimated failure rates of the components contained in the functional module to obtain the estimated failure rate of the functional module;
for each of the functional modules, determining an average of the manual failure rate of the functional module and the estimated failure rate of the functional module as the failure rate of the functional module.
In one embodiment, the obtaining the reliability function of the target electric energy meter according to the total failure rate of the target electric energy meter includes:
determining a first function as a reliability function of the target electric energy meter;
the first function is:
wherein λ issAnd t represents the running time of the target electric energy meter.
And obtaining the average service life of the target electric energy meter according to the total failure rate of the target electric energy meter, wherein the average service life of the target electric energy meter is used for representing the average working time of the target electric energy meter before failure.
In one embodiment, after obtaining the failure rates of the functional modules of the target electric energy meter according to the manual failure rate of each component of the target electric energy meter and the estimated failure rate of each component of the target electric energy meter, the method further includes:
obtaining the difference value between the estimated failure rates of the same functional module in different batches of target electric energy meters to obtain a plurality of first difference values;
and when a target first difference value in the plurality of first difference values is larger than a first preset difference value threshold, outputting a fault prompt of the functional module corresponding to the target first difference value.
Obtaining difference values between failure rates of manuals of the same functional module in different batches of target electric energy meters to obtain a plurality of second difference values;
and outputting a fault prompt of the functional module corresponding to the target second difference value when the target second difference value in the plurality of second difference values is larger than a second preset difference value threshold.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in the embodiments provided herein may include non-volatile and/or volatile memory, among others. Non-volatile memory can include read-only memory (ROM), Programmable ROM (PROM), Electrically Programmable ROM (EPROM), Electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDRSDRAM), Enhanced SDRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), Rambus Direct RAM (RDRAM), direct bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).
The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (10)
1. A method for predicting reliability of an electric energy meter, the method comprising:
acquiring the failure rate of each component of a target electric energy meter, wherein the failure rate of the manual is calculated according to stress factors recorded in a reliability prediction manual of the target electric energy meter, and the stress factors are used for representing the influence degree of environmental factors on the performance of each component of the target electric energy meter;
obtaining estimated failure rates of all components of the target electric energy meter, wherein the estimated failure rates are obtained by predicting the failure rates of all components in the electric energy meter which is recycled historically;
acquiring failure rates of all functional modules of the target electric energy meter according to the manual failure rate of all components of the target electric energy meter and the estimated failure rate of all components of the target electric energy meter, wherein all functional modules of the target electric energy meter comprise at least one component of the target electric energy meter;
summing failure rates of all functional modules of the target electric energy meter to obtain a total failure rate of the target electric energy meter;
obtaining a reliability function of the target electric energy meter according to the total failure rate of the target electric energy meter, wherein the reliability function is used for representing the capability of the target electric energy meter to realize specified functions under different operation time lengths;
and outputting a reliability prediction curve of the target electric energy meter according to the reliability function.
2. The method of claim 1, wherein the obtaining of the manual failure rate of each component of the target electric energy meter comprises:
obtaining a component failure rate formula recorded in the reliability prediction manual;
acquiring the stress factor recorded in the reliability prediction manual;
and calculating the failure rate of each component of the target electric energy meter according to the component failure rate formula and the stress factor.
3. The method of claim 1, wherein the obtaining the estimated failure rate of each component of the target electric energy meter comprises:
and analyzing the failure rate of each component in the historically recycled electric energy meter by adopting a point estimation method to obtain the estimated failure rate of each component of the target electric energy meter.
4. The method of claim 1, wherein the obtaining the failure rate of each functional module of the target electric energy meter according to the handbook failure rate of each component of the target electric energy meter and the estimated failure rate of each component of the target electric energy meter comprises:
for each functional module, summing the failure rates of the manuals of the components contained in the functional module to obtain the failure rate of the manuals of the functional module;
for each functional module, summing the estimated failure rates of the components contained in the functional module to obtain the estimated failure rate of the functional module;
for each of the functional modules, determining an average of the manual failure rate of the functional module and the estimated failure rate of the functional module as the failure rate of the functional module.
5. The method of claim 1, wherein the deriving the reliability function of the target electric energy meter according to the total failure rate of the target electric energy meter comprises:
determining a first function as a reliability function of the target electric energy meter;
the first function is: r (t) ═ e-λs tWherein λ issThe total failure rate of the target electric energy meter is represented, and t represents the running time of the target electric energy meter;
and obtaining the average service life of the target electric energy meter according to the total failure rate of the target electric energy meter, wherein the average service life of the target electric energy meter is used for representing the average working time of the target electric energy meter before failure.
6. The method of claim 1, wherein after obtaining the failure rate of each functional module of the target electric energy meter according to the manual failure rate of each component of the target electric energy meter and the estimated failure rate of each component of the target electric energy meter, the method further comprises:
obtaining the difference value between the estimated failure rates of the same functional module in different batches of target electric energy meters to obtain a plurality of first difference values;
when a target first difference value in the plurality of first difference values is larger than a first preset difference value threshold value, outputting a fault prompt of a functional module corresponding to the target first difference value;
obtaining difference values between failure rates of manuals of the same functional module in different batches of target electric energy meters to obtain a plurality of second difference values;
and when a target second difference value in the plurality of second difference values is larger than a second preset difference value threshold, outputting a fault prompt of the functional module corresponding to the target second difference value.
7. An electric energy meter reliability prediction apparatus, characterized in that the apparatus comprises:
the system comprises a first acquisition module, a second acquisition module and a third acquisition module, wherein the first acquisition module is used for acquiring the failure rate of a manual of each component of a target electric energy meter, the failure rate of the manual is obtained by calculation according to stress factors recorded in a reliability prediction manual of the target electric energy meter, and the stress factors are used for representing the influence degree of environmental factors on the performance of each component of the target electric energy meter;
the second obtaining module is used for obtaining estimated failure rates of all components of the target electric energy meter, and the estimated failure rates are obtained after prediction is carried out according to the failure rates of all components in the electric energy meter which is recycled historically;
the third obtaining module is used for obtaining the failure rate of each functional module of the target electric energy meter according to the manual failure rate of each component of the target electric energy meter and the estimated failure rate of each component of the target electric energy meter, wherein each functional module of the target electric energy meter comprises at least one component of the target electric energy meter; summing failure rates of all functional modules of the target electric energy meter to obtain a total failure rate of the target electric energy meter;
the reliability function obtaining module is used for obtaining a reliability function of the target electric energy meter according to the total failure rate of the target electric energy meter, and the reliability function is used for representing the capability of the target electric energy meter for realizing specified functions under different operation time lengths;
and the output module is used for outputting the reliability prediction curve of the target electric energy meter according to the reliability function.
8. The apparatus according to claim 7, wherein the first obtaining module is specifically configured to obtain a component failure rate formula recorded in the reliability prediction manual; acquiring the stress factor recorded in the reliability prediction manual; and calculating the failure rate of each component of the target electric energy meter according to the component failure rate formula and the stress factor.
9. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the steps of the method of any of claims 1 to 6 are implemented when the computer program is executed by the processor.
10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 6.
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| CN112667957A (en) * | 2020-12-03 | 2021-04-16 | 国网天津市电力公司营销服务中心 | Intelligent electric energy meter failure rate prediction method based on deep neural network |
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