CN109523190A - A kind of management method of electric energy meter, managing device and terminal - Google Patents
A kind of management method of electric energy meter, managing device and terminal Download PDFInfo
- Publication number
- CN109523190A CN109523190A CN201811441537.6A CN201811441537A CN109523190A CN 109523190 A CN109523190 A CN 109523190A CN 201811441537 A CN201811441537 A CN 201811441537A CN 109523190 A CN109523190 A CN 109523190A
- Authority
- CN
- China
- Prior art keywords
- electric energy
- energy meter
- health assessment
- management method
- failure
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/21—Design or setup of recognition systems or techniques; Extraction of features in feature space; Blind source separation
- G06F18/214—Generating training patterns; Bootstrap methods, e.g. bagging or boosting
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/24—Classification techniques
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
- G06Q50/06—Electricity, gas or water supply
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/80—Management or planning
- Y02P90/82—Energy audits or management systems therefor
Abstract
The present invention is suitable for technical field of electric power, provides management method, managing device, terminal and the computer readable storage medium of a kind of electric energy meter, and the management method includes: to carry out failure predication to electric energy meter；It is based on failure predication as a result, to the electric energy meter carry out health assessment；Based on health assessment as a result, determining the management strategy of the electric energy meter.The present invention is conducive to the electric energy meter timely judging to be likely to occur failure and being replaced, and the timeliness of replacement failure electric energy meter can be improved, and ensures the interests of Utilities Electric Co. or power consumer.
Description
Technical field
The invention belongs to technical field of electric power more particularly to a kind of management method of electric energy meter, managing device, terminal and meters
Calculation machine readable storage medium storing program for executing.
Background technique
Electric energy meter is the instrument for measuring electric energy, also known as kilowatt-hour meter.Currently, electric energy meter is usually to be found the presence of event
Corresponding management strategy is taken again after barrier, for example, carrying out sampling observation in electric power personnel finds that certain electric energy meter has metering class failure,
Metering can just not replace the electric energy meter on time.
However, current this electric energy meter way to manage is not prompt enough to the replacement of failure electric energy meter, when discovery electric energy meter
Failure when, failure have existed a period of time, this may result in Utilities Electric Co. or individual benefit damage.
Summary of the invention
In view of this, the embodiment of the invention provides a kind of management method of electric energy meter, managing device, terminal and computers
Readable storage medium storing program for executing is not prompt enough to the replacement of failure electric energy meter in the prior art to solve the problems, such as.
The first aspect of the embodiment of the present invention provides a kind of management method of electric energy meter, and the management method includes:
Failure predication is carried out to electric energy meter；
It is based on failure predication as a result, to the electric energy meter carry out health assessment；
Based on health assessment as a result, determining the management strategy of the electric energy meter.
The second aspect of the embodiment of the present invention provides a kind of managing device of electric energy meter, and the managing device includes:
Failure predication unit, for carrying out failure predication to electric energy meter；
Health assessment unit, for based on failure predication unit carry out failure predication as a result, to the electric energy meter carry out
Health assessment；
Management strategy determination unit, for based on health assessment unit carry out health assessment as a result, determining the electric energy
The management strategy of table.
The third aspect of the embodiment of the present invention provides a kind of terminal, including memory, processor and is stored in described
In memory and the computer program that can run on the processor, the processor are realized when executing the computer program
As described in any one the step of the management method of electric energy meter.
The fourth aspect of the embodiment of the present invention provides a kind of computer readable storage medium, the computer-readable storage
Media storage has computer program, and the management of the electric energy meter as described in any one is realized when the computer program is executed by processor
The step of method.
Existing beneficial effect is the present invention compared with prior art:
The present invention by electric energy meter carry out failure predication, can find the failure that electric energy meter is likely to occur in advance, for
The failure that electric energy meter is likely to occur may further carry out health assessment, and the fortune of electric energy meter is reflected by the result of health assessment
Row health status, and then according to the operation health status of electric energy meter, determine the management strategy of the electric energy meter, namely determine if
It is replaced.Therefore, the present invention is conducive to the electric energy meter timely judging to be likely to occur failure and being replaced,
The timeliness of replacement failure electric energy meter can be improved, ensure the interests of Utilities Electric Co. or power consumer.
Detailed description of the invention
It to describe the technical solutions in the embodiments of the present invention more clearly, below will be to embodiment or description of the prior art
Needed in attached drawing be briefly described, it should be apparent that, the accompanying drawings in the following description is only of the invention some
Embodiment for those of ordinary skill in the art without any creative labor, can also be according to these
Attached drawing obtains other attached drawings.
Fig. 1 is the implementation flow chart of the management method of electric energy meter provided in an embodiment of the present invention；
Fig. 2 is the implementation flow chart of the management method of electric energy meter provided in an embodiment of the present invention；
Fig. 3 is the schematic diagram of terminal provided in an embodiment of the present invention.
Specific embodiment
In being described below, for illustration and not for limitation, the tool of such as particular system structure, technology etc is proposed
Body details, to understand thoroughly the embodiment of the present invention.However, it will be clear to one skilled in the art that there is no these specific
The present invention also may be implemented in the other embodiments of details.In other situations, it omits to well-known system, device, electricity
The detailed description of road and method, in case unnecessary details interferes description of the invention.
To make the object, technical solutions and advantages of the present invention clearer, pass through specific embodiment below in conjunction with attached drawing
To be illustrated.
Referring to Fig. 1, it illustrates the implementation flow charts of the management method of electric energy meter provided in an embodiment of the present invention, are described in detail such as
Under:
In a step 101, failure predication is carried out to electric energy meter.
In embodiments of the present invention, it is necessary first to which electric energy meter progress failure predication is needed to carry out failure predication herein
Electric energy meter refer to the electric energy meter in the operation phase.In power marketing professional system, exists and largely can be used for electric energy meter event
Hinder the data of trend analysis.For example, metering production scheduling platform has the full performance data before the electric energy meter supply of material, electric energy meter arrival
Afterwards sample comparison, sampling observation, full inspection, the acceptance of the bid batch for each link gauging error data and each supplier such as tearing back open, receipt lot,
The data such as the fault message that return of goods batch information and operation link occur；In power information acquisition system, there is electric energy meter metering electricity
Amount, operating condition and logout and sales service application system tear table reason open, bug list note complains the data such as work order.Also
It is to say, in existing electric system, can be relatively easy to and get electric energy meter in the Life Cycles such as factory stage and operation phase
The calibrating data and operational monitoring data of phase.
Statistics and analysis is carried out using these data, the prediction of the failure of electric energy meter may be implemented, for example, can be with CART
Based on algorithm, by analyzing multiple attributes relevant to electrical energy meter fault, simultaneously Optimal Decision-making tree is established, to calculate electric energy meter
Fault rate.
Optionally, above-mentioned steps 101 can be realized based on following steps:
Step A1 obtains the characteristic when electric energy meter is in different life stages；
Step A2 carries out fusion treatment to the characteristic, obtains the feature vector for characterizing the electric energy meter；
Described eigenvector is inputted trained fault prediction model in advance, obtains the event of the electric energy meter by step A3
Hinder probability of happening.
In embodiments of the present invention, characteristic when available electric energy meter is in different life stages, these features
Data are data relevant to electrical energy meter fault；By carrying out fusion treatment to these characteristics, to obtain for characterizing electricity
The feature vector of the operation characteristic of energy table；Obtained feature vector is inputted into trained fault prediction model in advance later, it can
To obtain the fault rate of the electric energy meter.
In embodiments of the present invention, fault prediction model can be based on XGBOOST (extreme Gradient
Boosting) algorithm constructs.
Optionally, before above-mentioned steps A3, can also include:
Step B1 obtains the fault message for tearing back electric energy meter open；
Step B2 tears back characteristic when electric energy meter is in different life stages described in acquisition open；
Step B3, using it is described tear open back electric energy meter in different life stages when characteristic and the fault message
Form training set；
Step B4 is trained the fault prediction model for being in advance based on the building of XGBOOST algorithm using the training set,
Obtain trained fault prediction model.
Fault prediction model based on the building of XGBOOST algorithm has the various atypical characteristics of learning data
Ability needs to carry out the parameter adjustment of model for lift scheme effect.In embodiments of the present invention, it can use and tear telegram in reply open
The relevant information of energy table, is formed training set, is trained to the fault prediction model constructed based on XGBOOST algorithm, and then
To trained fault prediction model.
Electric energy meter can be split back due to failure rotation, business change, application verification etc., tear telegram in reply open by obtaining these
Can table fault message and these tear back electric energy meter open in the operation information of operation phase, formation training set, both to tearing telegram in reply energy open
The relevant information of table has accomplished effective use, and realizes the training and parameter adjustment to fault prediction model.
Optionally, above-mentioned steps B1 can be realized based on following steps:
Step B11 is obtained and is torn back electric energy meter picture library open as training sample set with mark and label, wherein is described
Label is used to indicate the fault message for tearing back electric energy meter open, described to be noted for indicating to tear back the fault bit on the picture of electric energy meter open
It sets；
Step B12 is trained the electric energy meter appearance fault identification model pre-established using the training sample set,
Obtain trained electric energy meter appearance fault identification model, wherein the electric energy meter appearance fault identification model is based on Fast-
The convolutional neural networks of Rcnn algorithm；
Step B13 obtains the image information to be identified for tearing back electric energy meter open, will train described in described image information input
Electric energy meter appearance fault identification model, obtain the fault message to be identified for tearing back electric energy meter open.
Usually longer due to tearing back electric energy meter runing time open, the fault type being related to is more, needs manually to pass through appearance
Detect the fault message, such as fault type etc. for determining electric energy meter.In embodiments of the present invention, it can be based on by establishing
The convolutional neural networks of Fast-Rcnn algorithm identify and judge electric energy meter progress failure to be identified of tearing open back.To may be used also
To improve the recognition efficiency for the failure for tearing back electric energy meter open.
In embodiments of the present invention, may include: by the failure that electric energy meter appearance fault identification model can recognize
The scarce picture of blank screen, liquid crystal, rainbow screen, tripping lamp are bad, programming key is gone bad and the failures such as liquid crystal leakage.
Optionally, in embodiments of the present invention, the different life stages may include factory stage and operation phase, institute
Stating characteristic includes at calibrating information and component information, the electric energy meter when electric energy meter is in the factory stage
Weather information, electrical work information and abnormal events information when the operation phase.
In embodiments of the present invention, meteorologic factor to a certain degree can impact the malfunction of electric energy meter, therefore, need
Fully consider that the regional disparity of electric energy meter, the weather information may include temperature, rainfall (humidity), illumination, interior/room
Outside, the information such as one-storey house/building.
In embodiments of the present invention, abnormal events information may include over-voltage events, overcurrent events, under-voltage event, Tai Qu
The information such as rate of qualified voltage, each batch operation troubles rate.
In embodiments of the present invention, electrical work information may include the statistical information of electricity consumption, thus analyze electricity consumption
Measure big, the small influence to electric energy table function of electricity consumption.Such as: it is better that the big electric energy meter of electricity consumption may be used more, and electricity consumption is small
Electric energy meter does not have to high failure rate instead for a long time.
In embodiments of the present invention, it for component information, can establish for electric energy meter producer, electric energy meter component type
Number assessment of fault model, realizes the accident analysis based on component rank, can be applied to component management and Lectotype Decision Making, prevents
Only there is familial defect.
In embodiments of the present invention, it can also study and establish electrical energy meter fault related degree model, utilize clustering algorithm and skin
Ademilson correlation analysis algorithm research influence factor and failure modes correlation.
In a step 102, based on failure predication as a result, to the electric energy meter carry out health assessment.
In embodiments of the present invention, the result of failure predication includes the probability of happening of various failures, for example, non-metering class
The probability of happening of failure, the probability of happening for measuring class failure.It, can be in the case of certain fault rates are lower than designated value
Think that the operating status of the electric energy meter is good.
In embodiments of the present invention, according to failure predication as a result, can the current health state to electric energy meter comment
Valence obtains the health assessment score of the electric energy meter.
Optionally, above-mentioned steps 102 can be realized based on following manner:
The result of the failure predication of the electric energy meter is inputted into preset Topsis health assessment model, obtains the electric energy
The health assessment score of table.
TOPSIS(Technique for Order Preference by Similarity to an Ideal
Solution) method is the method being ranked up according to the degree of closeness of limited evaluation object and idealization target, is existing
Object in carry out relative superior or inferior evaluation method.
In embodiments of the present invention, according to the failure predication of electric energy meter as a result, and preassigned various results refer to
Target weight can be obtained by the way that the result of the failure predication of the electric energy meter is inputted preset Topsis health assessment model
To the health assessment score of the electric energy meter.
In step 103, based on health assessment as a result, determining the management strategy of the electric energy meter.
In embodiments of the present invention, the result of health assessment includes health assessment score, and health assessment score can be anti-
The operating status of electric energy meter is answered, the higher electric energy meter operating status of health assessment score is good, can reduce to this kind of electric energy meter
Concern, advantageously reduces the workload of base electric power personnel.
Optionally, above-mentioned steps 103 can be realized based on following manner:
Electric energy meter to the health assessment score lower than the first preset value carries out batch replacement；
First preset value is not less than to the health assessment score, and, the electric energy meter lower than the second preset value carries out
Emphasis monitoring.
In embodiments of the present invention, the lower electric energy meter of health assessment score needs to carry out more there may be operation problem
It changes or emphasis monitors.
From the foregoing, it will be observed that the present invention can have found in advance what electric energy meter was likely to occur by carrying out failure predication to electric energy meter
Failure may further carry out health assessment for the failure that electric energy meter is likely to occur, and reflect electricity by the result of health assessment
The operation health status of energy table, and then according to the operation health status of electric energy meter, determine the management strategy of the electric energy meter, namely really
Whether fixed its is replaced.Therefore, the present invention is conducive to timely judge to be likely to occur failure and replace
Electric energy meter, the timeliness of replacement failure electric energy meter can be improved, ensure the interests of Utilities Electric Co. or power consumer.
It should be understood that the size of the serial number of each step is not meant that the order of the execution order in above-described embodiment, each process
Execution sequence should be determined by its function and internal logic, the implementation process without coping with the embodiment of the present invention constitutes any limit
It is fixed.
The following are the device of the invention embodiments can refer to above-mentioned corresponding the details of wherein not detailed description
Embodiment of the method.
Fig. 2 shows the structural schematic diagrams of the managing device of electric energy meter provided in an embodiment of the present invention, for ease of description,
Only parts related to embodiments of the present invention are shown, and details are as follows:
As shown in Fig. 2, the managing device 2 of electric energy meter includes: failure predication unit, health assessment unit and management strategy are true
Order member.
Failure predication unit 21, for carrying out failure predication to electric energy meter；
Health assessment unit 22, for based on failure predication unit 21 carry out failure predication as a result, to the electric energy meter
Carry out health assessment；
Management strategy determination unit 23, for based on health assessment unit 22 carry out health assessment as a result, determine described in
The management strategy of electric energy meter.
Optionally, the managing device 2 of electric energy meter further include:
Characteristic acquiring unit, for obtaining the characteristic when electric energy meter is in different life stages；
Characteristic integrated unit is obtained for carrying out fusion treatment to the characteristic for characterizing the electric energy
The feature vector of table；
Failure predication unit 21 is also used to, and described eigenvector is inputted trained fault prediction model in advance, is obtained
The fault rate of the electric energy meter.
Optionally, the managing device 2 of electric energy meter further include:
Fault message acquiring unit, for obtaining the fault message for tearing back electric energy meter open；
Training set acquiring unit, for obtaining the characteristic torn open back when electric energy meter is in different life stages；And
Using it is described tear open back electric energy meter in different life stages when characteristic and fault message composition training set；
Training unit instructs the fault prediction model for being in advance based on the building of XGBOOST algorithm using the training set
Practice, obtains trained fault prediction model.
Optionally, the managing device 2 of electric energy meter further include:
Sample acquisition unit, for obtain have mark and a label tear back electric energy meter picture library open as training sample set,
Wherein, the label is used to indicate the fault message for tearing back electric energy meter open, described to be noted for indicating to tear open back on the picture of electric energy meter
Abort situation；
Appearance fault identification model training unit, for using the training sample set to the electric energy meter appearance pre-established
Fault identification model is trained, and obtains trained electric energy meter appearance fault identification model, wherein the electric energy meter appearance event
Barrier identification model is the convolutional neural networks based on Fast-Rcnn algorithm；
Fault message acquiring unit is specifically used for, and the image information to be identified for tearing back electric energy meter open is obtained, by described image
Trained electric energy meter appearance fault identification model described in information input obtains the failure letter to be identified for tearing back electric energy meter open
Breath.
Optionally, the different life stages include factory stage and operation phase, and the characteristic includes the electricity
It can calibrating information and component information of the table when being in the factory stage, the gas when electric energy meter is in the operation phase
Image information, electrical work information and abnormal events information.
Optionally, health assessment unit 22 is specifically used for, and the result input of the failure predication of the electric energy meter is preset
Topsis health assessment model obtains the health assessment score of the electric energy meter.
Optionally, management strategy determination unit 23 is specifically used for, to the health assessment score lower than the first preset value
Electric energy meter carries out batch replacement；
First preset value is not less than to the health assessment score, and, the electric energy meter lower than the second preset value carries out
Emphasis monitoring.
From the foregoing, it will be observed that the present invention can have found in advance what electric energy meter was likely to occur by carrying out failure predication to electric energy meter
Failure may further carry out health assessment for the failure that electric energy meter is likely to occur, and reflect electricity by the result of health assessment
The operation health status of energy table, and then according to the operation health status of electric energy meter, determine the management strategy of the electric energy meter, namely really
Whether fixed its is replaced.Therefore, the present invention is conducive to timely judge to be likely to occur failure and replace
Electric energy meter, the timeliness of replacement failure electric energy meter can be improved, ensure the interests of Utilities Electric Co. or power consumer.
Fig. 3 is the schematic diagram for the terminal that one embodiment of the invention provides.As shown in figure 3, the terminal 3 of the embodiment includes:
Processor 30, memory 31 and it is stored in the computer program that can be run in the memory 31 and on the processor 30
32.The processor 30 realizes the step in the management method embodiment of above-mentioned each electric energy meter when executing the computer program 32
Suddenly, such as step 101 shown in FIG. 1 is to step 103.Alternatively, realization when the processor 30 executes the computer program 32
The function of each module/unit in above-mentioned each Installation practice, such as the function of unit 21 to 23 shown in Fig. 2.
Illustratively, the computer program 32 can be divided into one or more module/units, it is one or
Multiple module/units are stored in the memory 31, and are executed by the processor 30, to complete the present invention.Described one
A or multiple module/units can be the series of computation machine program instruction section that can complete specific function, which is used for
Implementation procedure of the computer program 32 in the terminal 3 is described.For example, the computer program 32 can be divided into
Failure predication unit, health assessment unit and management strategy determination unit, each unit concrete function are as follows:
Failure predication unit, for carrying out failure predication to electric energy meter；
Health assessment unit, for based on failure predication unit carry out failure predication as a result, to the electric energy meter carry out
Health assessment；
Management strategy determination unit, for based on health assessment unit carry out health assessment as a result, determining the electric energy
The management strategy of table.
The terminal 3 can be desktop PC, notebook, palm PC and cloud server etc. and calculate equipment.Institute
Stating terminal may include, but be not limited only to, processor 30, memory 31.It will be understood by those skilled in the art that Fig. 3 is only eventually
The example at end 3, the not restriction of structure paired terminal 3 may include than illustrating more or fewer components, or the certain portions of combination
Part or different components, such as the terminal can also include input-output equipment, network access equipment, bus etc..
Alleged processor 30 can be central processing unit (Central Processing Unit, CPU), can also be
Other general processors, digital signal processor (Digital Signal Processor, DSP), specific integrated circuit
(Application Specific Integrated Circuit, ASIC), field programmable gate array (Field-
Programmable Gate Array, FPGA) either other programmable logic device, discrete gate or transistor logic,
Discrete hardware components etc..General processor can be microprocessor or the processor is also possible to any conventional processor
Deng.
The memory 31 can be the internal storage unit of the terminal 3, such as the hard disk or memory of terminal 3.It is described
Memory 31 is also possible to the External memory equipment of the terminal 3, such as the plug-in type hard disk being equipped in the terminal 3, intelligence
Storage card (Smart Media Card, SMC), secure digital (Secure Digital, SD) card, flash card (Flash Card)
Deng.Further, the memory 31 can also both include the internal storage unit of the terminal 3 or set including external storage
It is standby.The memory 31 is for other programs and data needed for storing the computer program and the terminal.It is described to deposit
Reservoir 31 can be also used for temporarily storing the data that has exported or will export.
It is apparent to those skilled in the art that for convenience of description and succinctly, only with above-mentioned each function
Can unit, module division progress for example, in practical application, can according to need and by above-mentioned function distribution by different
Functional unit, module are completed, i.e., the internal structure of described device is divided into different functional unit or module, more than completing
The all or part of function of description.Each functional unit in embodiment, module can integrate in one processing unit, can also
To be that each unit physically exists alone, can also be integrated in one unit with two or more units, it is above-mentioned integrated
Unit both can take the form of hardware realization, can also realize in the form of software functional units.In addition, each function list
Member, the specific name of module are also only for convenience of distinguishing each other, the protection scope being not intended to limit this application.Above system
The specific work process of middle unit, module, can refer to corresponding processes in the foregoing method embodiment, and details are not described herein.
In the above-described embodiments, it all emphasizes particularly on different fields to the description of each embodiment, is not described in detail or remembers in some embodiment
The part of load may refer to the associated description of other embodiments.
Those of ordinary skill in the art may be aware that list described in conjunction with the examples disclosed in the embodiments of the present disclosure
Member and algorithm steps can be realized with the combination of electronic hardware or computer software and electronic hardware.These functions are actually
It is implemented in hardware or software, the specific application and design constraint depending on technical solution.Professional technician
Each specific application can be used different methods to achieve the described function, but this realization is it is not considered that exceed
The scope of the present invention.
In embodiment provided by the present invention, it should be understood that disclosed device/terminal and method can pass through
Other modes are realized.For example, device/terminal embodiment described above is only schematical, for example, the module or
The division of unit, only a kind of logical function partition, there may be another division manner in actual implementation, such as multiple units
Or component can be combined or can be integrated into another system, or some features can be ignored or not executed.Another point, institute
Display or the mutual coupling or direct-coupling or communication connection discussed can be through some interfaces, device or unit
INDIRECT COUPLING or communication connection can be electrical property, mechanical or other forms.
The unit as illustrated by the separation member may or may not be physically separated, aobvious as unit
The component shown may or may not be physical unit, it can and it is in one place, or may be distributed over multiple
In network unit.It can select some or all of unit therein according to the actual needs to realize the mesh of this embodiment scheme
's.
It, can also be in addition, the functional units in various embodiments of the present invention may be integrated into one processing unit
It is that each unit physically exists alone, can also be integrated in one unit with two or more units.Above-mentioned integrated list
Member both can take the form of hardware realization, can also realize in the form of software functional units.
If the integrated module/unit be realized in the form of SFU software functional unit and as independent product sale or
In use, can store in a computer readable storage medium.Based on this understanding, the present invention realizes above-mentioned implementation
All or part of the process in example method, can also instruct relevant hardware to complete, the meter by computer program
Calculation machine program can be stored in a computer readable storage medium, the computer program when being executed by processor, it can be achieved that on
The step of stating each embodiment of the method.Wherein, the computer program includes computer program code, the computer program generation
Code can be source code form, object identification code form, executable file or certain intermediate forms etc..The computer-readable medium
It may include: any entity or device, recording medium, USB flash disk, mobile hard disk, magnetic that can carry the computer program code
Dish, CD, computer storage, read-only memory (ROM, Read-Only Memory), random access memory (RAM,
Random Access Memory), electric carrier signal, telecommunication signal and software distribution medium etc..It should be noted that described
The content that computer-readable medium includes can carry out increasing appropriate according to the requirement made laws in jurisdiction with patent practice
Subtract, such as in certain jurisdictions, according to legislation and patent practice, computer-readable medium do not include be electric carrier signal and
Telecommunication signal.
Embodiment described above is merely illustrative of the technical solution of the present invention, rather than its limitations；Although referring to aforementioned reality
Applying example, invention is explained in detail, those skilled in the art should understand that: it still can be to aforementioned each
Technical solution documented by embodiment is modified or equivalent replacement of some of the technical features；And these are modified
Or replacement, the spirit and scope for technical solution of various embodiments of the present invention that it does not separate the essence of the corresponding technical solution should all
It is included within protection scope of the present invention.
Claims (10)
1. a kind of management method of electric energy meter, which is characterized in that the management method includes:
Failure predication is carried out to electric energy meter；
It is based on failure predication as a result, to the electric energy meter carry out health assessment；
Based on health assessment as a result, determining the management strategy of the electric energy meter.
2. the management method of electric energy meter according to claim 1, which is characterized in that described to carry out failure predication to electric energy meter
Include:
Obtain the characteristic when electric energy meter is in different life stages；
Fusion treatment is carried out to the characteristic, obtains the feature vector for characterizing the electric energy meter；
Described eigenvector is inputted into trained fault prediction model in advance, obtains the fault rate of the electric energy meter.
3. the management method of electric energy meter according to claim 2, which is characterized in that input described eigenvector described
Before preparatory trained fault prediction model further include:
Obtain the fault message for tearing back electric energy meter open；
Tear back characteristic when electric energy meter is in different life stages described in acquisition open；
Using it is described tear open back electric energy meter in different life stages when characteristic and fault message composition training set；
The fault prediction model for being in advance based on the building of XGBOOST algorithm is trained using the training set, is trained
Fault prediction model.
4. the management method of electric energy meter according to claim 3, which is characterized in that described to obtain the failure for tearing back electric energy meter open
Information includes:
It obtains and tears back electric energy meter picture library open as training sample set with mark and label, wherein the label is used to indicate
Tear back the fault message of electric energy meter open, it is described to be noted for indicating to tear back the abort situation on the picture of electric energy meter open；
The electric energy meter appearance fault identification model pre-established is trained using the training sample set, is obtained trained
Electric energy meter appearance fault identification model, wherein the electric energy meter appearance fault identification model is the volume based on Fast-Rcnn algorithm
Product neural network；
The image information to be identified for tearing back electric energy meter open is obtained, by trained electric energy meter appearance described in described image information input
Fault identification model obtains the fault message to be identified for tearing back electric energy meter open.
5. the management method of electric energy meter according to claim 3, which is characterized in that the difference life stage includes factory
Stage and operation phase, the characteristic include the calibrating information and component when the electric energy meter is in the factory stage
Information, the electric energy meter are in weather information, electrical work information and abnormal events information when the operation phase.
6. the management method of electric energy meter according to any one of claims 1 to 5, which is characterized in that described pre- based on failure
Survey as a result, to the electric energy meter carry out health assessment include:
The result of the failure predication of the electric energy meter is inputted into preset Topsis health assessment model, obtains the electric energy meter
Health assessment score.
7. the management method of electric energy meter according to claim 6, which is characterized in that it is described based on health assessment as a result,
The management strategy for determining the electric energy meter includes:
Electric energy meter to the health assessment score lower than the first preset value carries out batch replacement；
First preset value is not less than to the health assessment score, and, the electric energy meter lower than the second preset value carries out emphasis
Monitoring.
8. a kind of managing device of electric energy meter, which is characterized in that the managing device includes:
Failure predication unit, for carrying out failure predication to electric energy meter；
Health assessment unit, for based on failure predication unit progress failure predication as a result, to electric energy meter progress health
Evaluation；
Management strategy determination unit, for based on health assessment unit carry out health assessment as a result, determining the electric energy meter
Management strategy.
9. a kind of terminal, including memory, processor and storage can be run in the memory and on the processor
Computer program, which is characterized in that the processor is realized when executing the computer program as claim 1 to 7 is any
The step of management method of the item electric energy meter.
10. a kind of computer readable storage medium, the computer-readable recording medium storage has computer program, and feature exists
In realizing the management method of electric energy meter as described in any one of claim 1 to 7 when the computer program is executed by processor
Step.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811441537.6A CN109523190A (en) | 2018-11-29 | 2018-11-29 | A kind of management method of electric energy meter, managing device and terminal |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811441537.6A CN109523190A (en) | 2018-11-29 | 2018-11-29 | A kind of management method of electric energy meter, managing device and terminal |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN109523190A true CN109523190A (en) | 2019-03-26 |
Family
ID=65794621
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201811441537.6A Pending CN109523190A (en) | 2018-11-29 | 2018-11-29 | A kind of management method of electric energy meter, managing device and terminal |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109523190A (en) |
Cited By (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110210632A (en) * | 2019-05-31 | 2019-09-06 | 国网河北省电力有限公司沧州供电分公司 | Failure emergency processing method, device and terminal based on ubiquitous electric power Internet of Things |
| CN110765797A (en) * | 2019-10-14 | 2020-02-07 | 国网河北省电力有限公司 | Portable intelligent terminal with electric energy meter overall process management and control function |
| CN110888101A (en) * | 2019-12-05 | 2020-03-17 | 新奥数能科技有限公司 | Electric energy meter abnormity diagnosis method and device |
| CN110956091A (en) * | 2019-11-05 | 2020-04-03 | 广州供电局有限公司 | Electric energy meter identification method and device, computer equipment and storage medium |
| CN111102123A (en) * | 2019-12-13 | 2020-05-05 | 国家电网有限公司 | Automatic control method for auxiliary engine system of pumped storage power station |
| CN111612322A (en) * | 2020-05-14 | 2020-09-01 | 国网河北省电力有限公司电力科学研究院 | Intelligent electric energy meter quality early warning method |
| CN111738573A (en) * | 2020-06-09 | 2020-10-02 | 国网河北省电力有限公司营销服务中心 | Health evaluation method based on electric energy meter full life cycle data |
| CN112036725A (en) * | 2020-08-24 | 2020-12-04 | 国网河北省电力有限公司营销服务中心 | Electric energy meter fault identification method |
| CN113449258A (en) * | 2021-05-28 | 2021-09-28 | 国网河北省电力有限公司营销服务中心 | Quality evaluation method and device for intelligent electric meter, terminal equipment and storage medium |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106203875A (en) * | 2016-07-19 | 2016-12-07 | 广西电网有限责任公司电力科学研究院 | A kind of model for power equipment health state evaluation |
| CN107832867A (en) * | 2017-10-10 | 2018-03-23 | 北京交通大学 | A kind of railway equipment based on failure predication technology is health management system arranged |
| CN107967485A (en) * | 2017-11-16 | 2018-04-27 | 国网冀北电力有限公司电力科学研究院 | Electro-metering equipment fault analysis method and device |
| CN108072858A (en) * | 2017-12-25 | 2018-05-25 | 深圳市航天泰瑞捷电子有限公司 | Electric energy meter method for quality control, system and terminal device |
| CN108320043A (en) * | 2017-12-19 | 2018-07-24 | 江苏瑞中数据股份有限公司 | A kind of distribution network equipment state diagnosis prediction method based on electric power big data |
-
2018
- 2018-11-29 CN CN201811441537.6A patent/CN109523190A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106203875A (en) * | 2016-07-19 | 2016-12-07 | 广西电网有限责任公司电力科学研究院 | A kind of model for power equipment health state evaluation |
| CN107832867A (en) * | 2017-10-10 | 2018-03-23 | 北京交通大学 | A kind of railway equipment based on failure predication technology is health management system arranged |
| CN107967485A (en) * | 2017-11-16 | 2018-04-27 | 国网冀北电力有限公司电力科学研究院 | Electro-metering equipment fault analysis method and device |
| CN108320043A (en) * | 2017-12-19 | 2018-07-24 | 江苏瑞中数据股份有限公司 | A kind of distribution network equipment state diagnosis prediction method based on electric power big data |
| CN108072858A (en) * | 2017-12-25 | 2018-05-25 | 深圳市航天泰瑞捷电子有限公司 | Electric energy meter method for quality control, system and terminal device |
Cited By (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110210632A (en) * | 2019-05-31 | 2019-09-06 | 国网河北省电力有限公司沧州供电分公司 | Failure emergency processing method, device and terminal based on ubiquitous electric power Internet of Things |
| CN110765797A (en) * | 2019-10-14 | 2020-02-07 | 国网河北省电力有限公司 | Portable intelligent terminal with electric energy meter overall process management and control function |
| CN110956091A (en) * | 2019-11-05 | 2020-04-03 | 广州供电局有限公司 | Electric energy meter identification method and device, computer equipment and storage medium |
| CN110956091B (en) * | 2019-11-05 | 2022-07-01 | 广东电网有限责任公司广州供电局 | Electric energy meter identification method and device, computer equipment and storage medium |
| CN110888101A (en) * | 2019-12-05 | 2020-03-17 | 新奥数能科技有限公司 | Electric energy meter abnormity diagnosis method and device |
| CN110888101B (en) * | 2019-12-05 | 2022-11-22 | 新奥数能科技有限公司 | Method and device for diagnosing abnormity of electric energy meter |
| CN111102123B (en) * | 2019-12-13 | 2022-01-25 | 国家电网有限公司 | Automatic control method for auxiliary engine system of pumped storage power station |
| CN111102123A (en) * | 2019-12-13 | 2020-05-05 | 国家电网有限公司 | Automatic control method for auxiliary engine system of pumped storage power station |
| CN111612322A (en) * | 2020-05-14 | 2020-09-01 | 国网河北省电力有限公司电力科学研究院 | Intelligent electric energy meter quality early warning method |
| CN111738573A (en) * | 2020-06-09 | 2020-10-02 | 国网河北省电力有限公司营销服务中心 | Health evaluation method based on electric energy meter full life cycle data |
| CN112036725A (en) * | 2020-08-24 | 2020-12-04 | 国网河北省电力有限公司营销服务中心 | Electric energy meter fault identification method |
| CN112036725B (en) * | 2020-08-24 | 2024-04-30 | 国网河北省电力有限公司营销服务中心 | Fault identification method for electric energy meter |
| CN113449258A (en) * | 2021-05-28 | 2021-09-28 | 国网河北省电力有限公司营销服务中心 | Quality evaluation method and device for intelligent electric meter, terminal equipment and storage medium |
| CN113449258B (en) * | 2021-05-28 | 2022-12-27 | 国网河北省电力有限公司营销服务中心 | Quality evaluation method and device for intelligent electric meter, terminal equipment and storage medium |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109523190A (en) | A kind of management method of electric energy meter, managing device and terminal | |
| Tu et al. | Big data issues in smart grid–A review | |
| Esenogho et al. | Integrating artificial intelligence Internet of Things and 5G for next-generation smartgrid: A survey of trends challenges and prospect | |
| Zidi et al. | Theft detection dataset for benchmarking and machine learning based classification in a smart grid environment | |
| Hong et al. | Probabilistic electric load forecasting: A tutorial review | |
| Slama | Prosumer in smart grids based on intelligent edge computing: A review on Artificial Intelligence Scheduling Techniques | |
| US20220115867A1 (en) | Advanced power distribution platform | |
| US9134353B2 (en) | Comfort-driven optimization of electric grid utilization | |
| CN108353034A (en) | Framework for data center's infrastructure monitoring | |
| US10379146B2 (en) | Detecting non-technical losses in electrical networks based on multi-layered statistical techniques from smart meter data | |
| CN113918139A (en) | Identifying non-technical losses using machine learning | |
| US20190228353A1 (en) | Competition-based tool for anomaly detection of business process time series in it environments | |
| Satapathy | An analysis for service quality enhancement in electricity utility sector of India by SEM | |
| Pham et al. | Deep learning for intelligent demand response and smart grids: A comprehensive survey | |
| Bessa | Future trends for big data application in power systems | |
| CN114596693A (en) | Method, system, medium, and program product for energy monitoring and management | |
| Hampton et al. | A review of current analytical methods, modelling tools and development frameworks applicable for future retail electricity market design | |
| CN109685344A (en) | A kind of power equipment O&M strategy determines method, apparatus and storage medium | |
| Khosrojerdi et al. | Integrating artificial intelligence and analytics in smart grids: a systematic literature review | |
| Oprea et al. | An Edge-Fog-Cloud computing architecture for IoT and smart metering data | |
| Vinjamuri et al. | Efficient energy management system using Internet of things with FORDF technique for distribution system | |
| Khan et al. | Power grid stability analysis using pipeline machine | |
| Eto et al. | Demand response as a system reliability resource | |
| Olar et al. | The Design and Applications of Dashboards Used in Electrical and Power Systems | |
| Mbuya | Short-term forecast techniques for energy management systems in microgrid applications |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| TA01 | Transfer of patent application right | ||
| TA01 | Transfer of patent application right |
Effective date of registration: 20210929 Address after: 050021 No. 238 South Sports street, Hebei, Shijiazhuang Applicant after: STATE GRID HEBEI ELECTRIC POWER Research Institute Applicant after: Marketing service center of State Grid Hebei Electric Power Co.,Ltd. Applicant after: STATE GRID CORPORATION OF CHINA Applicant after: STATE GRID HEBEI ENERGY TECHNOLOGY SERVICE Co.,Ltd. Address before: 050011 no.238, TIYU South Street, Yuhua District, Shijiazhuang City, Hebei Province Applicant before: STATE GRID HEBEI ELECTRIC POWER Research Institute Applicant before: STATE GRID CORPORATION OF CHINA Applicant before: STATE GRID HEBEI ENERGY TECHNOLOGY SERVICE Co.,Ltd. |
|
| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20190326 |