CN106161138A - A kind of intelligence automatic gauge method and device - Google Patents
A kind of intelligence automatic gauge method and device Download PDFInfo
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- CN106161138A CN106161138A CN201610437205.5A CN201610437205A CN106161138A CN 106161138 A CN106161138 A CN 106161138A CN 201610437205 A CN201610437205 A CN 201610437205A CN 106161138 A CN106161138 A CN 106161138A
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L43/00—Arrangements for monitoring or testing data switching networks
- H04L43/04—Processing captured monitoring data, e.g. for logfile generation
- H04L43/045—Processing captured monitoring data, e.g. for logfile generation for graphical visualisation of monitoring data
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L43/00—Arrangements for monitoring or testing data switching networks
- H04L43/02—Capturing of monitoring data
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L43/00—Arrangements for monitoring or testing data switching networks
- H04L43/06—Generation of reports
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Abstract
The embodiment of the invention discloses a kind of intelligent automatic gauge method and device, solve the decision-making of mistake that current metering system causes, the technical problem that multi-data fusion is low, data visualization information transmits data low, big storage and process.Embodiment of the present invention intelligence automatic gauge method includes: build electric energy data verification and the business rule base of assessment business；Carry out the abnormal data monitoring of electric energy data according to business rule base and clean；The abnormal data determining monitoring carries out preset mode process, and builds abnormal data type tree；Continuous data polymerization process is carried out according to preset electric energy data business.
Description
Technical field
The present invention relates to technical field of electric power, particularly relate to a kind of intelligence automatic gauge method and device.
Background technology
Deepening continuously and advancing along with intelligent grid construction, the informatization development of power industry is swift and violent, south electricity
Net company carries out informatization in " 12 " period comprehensively.In power marketing field, net, province and district three have been built up the most comprehensively
Level metering automation system, it is achieved that the Metrological archives information of prefectures and cities and the administration by different levels of electric energy data, hierarchical application.With
Inspection and the work quality degree that becomes more meticulous is more and more higher, the granularity of data is more and more less, and data type becomes increasingly complex, electric power
Marketing data the most day by day highlights three big basic features of the big data such as quantity is big, real-time is high, data type is diversified, electric power
Marketing has just stepped into big data age with unprecedented speed.
Defining relative to the technology of big data, the big data of electric power are then broader concepts.The big data of electric power are
Refer to produce in power generation with during using, Data Source relate to generating that power generation and electric energy use, transmission of electricity, power transformation,
Distribution, electricity consumption and scheduling links.
Although the big market demand of electric power has a extensive future, but also faces huge challenge.1) challenge of the quality of data.High-quality
Data are the bases of the big market demand of electric power.Data accuracy, integrity are the highest, will affect the quality of decision analysis, and even produce
The decision recommendation of raw mistake.2) challenge of multi-data fusion.Multi-data fusion is the key of the big market demand of electric power.Long-term with specially
Industry information system is main informatization, causes each expert data of power generation independent of one another, forms information island.For abolishing
The data barrier of information island, needs to merge the multi-specialized data such as generating, transmission of electricity, power transformation, distribution, electricity consumption, scheduling, excavates electric power
Big data, services is in the value of electricity power enterprise, power consumer and socio-economic development.3) challenge of data visualization information transmission.
The big data visualization of electric power is the effective means of data value transmission, hides power generation and service economy society in the big data of electric power
The rule that can develop and feature are the most abstract, it is difficult to find.Big data visualization analysis is readily able to the discovery of big data rule,
Show the feature in mass data and rule, it is simple to the transmission of data value is shared with knowledge.4) big data storage and process
Challenge.The big data of electric power are huge with capability requirement to data storage.The structuring to multiple data sources of the electric power big data
It is analyzed processing with unstructured data, needs to store the data of magnanimity, and quick computing capability is provided.
Therefore, in order to solve the decision-making of above-mentioned mistake, multi-data fusion is low, the transmission of data visualization information is low, several
According to storage and the technical problem processed, those skilled in the art day and night research and develop.
Summary of the invention
A kind of intelligence automatic gauge method and device that the embodiment of the present invention provides, solves current metering system and causes
Mistake decision-making, multi-data fusion is low, data visualization information transmits data low, big storage and the technical problem processed.
A kind of intelligence automatic gauge method and device that the embodiment of the present invention provides, including:
Build electric energy data verification and the business rule base of assessment business；
Carry out the abnormal data monitoring of electric energy data according to described business rule base and clean；
The described abnormal data determining monitoring carries out preset mode process, and builds abnormal data type tree；
Continuous data polymerization process is carried out according to preset electric energy data business.
Preferably, the business rule base of the verification of intelligence structure electric energy data and assessment business specifically includes: purifying and pressure stabilizing electricity
Source, is connected by the transmitting terminal of electric power network with intelligent metering automated system.
Carry out the application layer communication association of the plurality of devices such as metering system and concentrator, harvester, measuring terminal, interactive terminal
The structure of the dynamic analysis rule of view；
The data carrying out metering system collection carry out continuous data resolution rules structure；
Carry out the foundation of data rule corresponding to metering system monitoring and warning.
Preferably, the described abnormal data determining monitoring carries out preset mode process, and builds abnormal data type tree
Specifically include:
The described abnormal data determining monitoring is by abnormal continuous data and the typical continuous data curve of its correspondence
Compare process, and build abnormal data type tree；
And/or
The described abnormal data determining monitoring is entered by abnormal continuous data and the event of its correspondence or alarm data
Row comparison processes, and builds abnormal data type tree；
And/or
To the described abnormal data that determines of monitoring by occurring abnormal continuous data and other data to compare process,
And build abnormal data type tree.
Preferably, carry out continuous data polymerization process according to preset electric energy data business to specifically include:
Carry out continuous data according to preset electric energy data business carry out data aggregate process successively and pass through preset number
Process according to processing model.
Preferably, carry out continuous data according to preset electric energy data business and carry out data aggregate process and logical successively
Also include after crossing the processing of preset data processing model:
The electricity consumption that described continuous data after processing polymerization and being processed by preset data processing model carries out correspondence is special
Levy analysis and energy-saving structure diagnosis research.
A kind of intelligent metering automation equipment that the embodiment of the present invention provides, including:
Construction unit, for building electric energy data verification and the business rule base of assessment business；
Monitoring cleaning unit, for carrying out the abnormal data monitoring of electric energy data with clear according to described business rule base
Wash；
Exception processing unit, carries out preset mode process for the described abnormal data determining monitoring, and builds exception
Data type tree；
Polymerization processing unit, for carrying out continuous data polymerization process according to preset electric energy data business.
Preferably, construction unit specifically includes:
First rule builds subelement, is used for carrying out metering system and concentrator, harvester, measuring terminal, interactive terminal
The structure regular etc. the dynamic analysis of the application layer communication protocol of plurality of devices；
Second Rule builds subelement, carries out continuous data resolution rules structure for carrying out the data of metering system collection
Build；
Three sigma rule builds subelement, for carrying out the foundation of data rule corresponding to metering system monitoring and warning.
Preferably, exception processing unit specifically includes:
First comparer unit, the described abnormal data for determining monitoring passes through abnormal continuous data and it is corresponding
Typical continuous data curve compare process, and build abnormal data type tree；
And/or
Second comparer unit, the described abnormal data for determining monitoring passes through abnormal continuous data and it is corresponding
Event or alarm data compare process, and build abnormal data type tree；
And/or
3rd comparer unit, for the described abnormal data that determines of monitoring by occur abnormal continuous data and its
His data are compared process, and build abnormal data type tree.
Preferably, it is polymerized processing unit, specifically for carrying out continuous data successively according to preset electric energy data business
Carry out data aggregate process and processed by preset data processing model.
Preferably, intelligent metering automation equipment also includes:
Analyzing and diagnosing unit, the described continuous data after polymerization being processed and is processed by preset data processing model
Carry out electricity consumption feature analysis and the energy-saving structure diagnosis research of correspondence.
As can be seen from the above technical solutions, the embodiment of the present invention has the advantage that
A kind of intelligence automatic gauge method and device that the embodiment of the present invention provides, intelligence automatic gauge method includes: structure
Build electric energy data verification and the business rule base of assessment business；The abnormal data of electric energy data is carried out according to business rule base
Monitoring and cleaning；The abnormal data determining monitoring carries out preset mode process, and builds abnormal data type tree；According to preset
Electric energy data business carry out continuous data polymerization process.In the present embodiment, verify and assessment by building electric energy data
The business rule base of business；Carry out the abnormal data monitoring of electric energy data according to business rule base and clean；Monitoring is determined
Abnormal data carry out preset mode process, and build abnormal data type tree；Carry out according to preset electric energy data business
Continuous data polymerization processes, and solves that the decision-making of mistake that current metering system causes, multi-data fusion be low, data visualization
Information transmits data low, big storage and the technical problem processed.
Accompanying drawing explanation
In order to be illustrated more clearly that the embodiment of the present invention or technical scheme of the prior art, below will be to embodiment or existing
In having technology to describe, the required accompanying drawing used is briefly described, it should be apparent that, the accompanying drawing in describing below is only this
Some embodiments of invention, for those of ordinary skill in the art, on the premise of not paying creative work, also may be used
To obtain other accompanying drawing according to these accompanying drawings.
The schematic flow sheet of one embodiment of a kind of intelligence automatic gauge method that Fig. 1 provides for the embodiment of the present invention；
The flow process signal of another embodiment of a kind of intelligence automatic gauge method that Fig. 2 provides for the embodiment of the present invention
Figure；
The structural representation of one embodiment of a kind of intelligence self-measuring device that Fig. 3 provides for the embodiment of the present invention；
The structural representation of another embodiment of a kind of intelligence self-measuring device that Fig. 4 provides for the embodiment of the present invention
Figure；
Fig. 5 is lifecycle management and the maintenance process schematic diagram of rule base；
Fig. 6 is abnormal data monitoring and cleans schematic diagram；
Fig. 7 is checking procedure schematic diagram；
Fig. 8 is data aggregate and work flow schematic diagram；
Fig. 9 is technology path schematic diagram；
Figure 10 is general frame schematic diagram；
Figure 11 is high-level schematic functional block diagram.
Detailed description of the invention
A kind of intelligence automatic gauge method and device that the embodiment of the present invention provides, solves current metering system and causes
Mistake decision-making, multi-data fusion is low, data visualization information transmits data low, big storage and the technical problem processed.
For making the goal of the invention of the present invention, feature, the advantage can be the most obvious and understandable, below in conjunction with the present invention
Accompanying drawing in embodiment, is clearly and completely described the technical scheme in the embodiment of the present invention, it is clear that disclosed below
Embodiment be only a part of embodiment of the present invention, and not all embodiment.Based on the embodiment in the present invention, this area
All other embodiments that those of ordinary skill is obtained under not making creative work premise, broadly fall into present invention protection
Scope.
Referring to Fig. 1, an embodiment of a kind of intelligence automatic gauge method that the embodiment of the present invention provides includes:
101, electric energy data verification and the business rule base of assessment business are built；
In the present embodiment, when needs carry out automatic gauge when, it is necessary first to build electric energy data verification and assessment
The business rule base of business.
102, carry out the abnormal data monitoring of electric energy data according to business rule base and clean；
After building the business rule base of electric energy data verification and assessment business, need to carry out according to business rule base
The abnormal data monitoring of electric energy data and cleaning.
103, the abnormal data determining monitoring carries out preset mode process, and builds abnormal data type tree；
After the abnormal data carrying out electric energy data according to business rule base monitors and cleans, need monitoring is determined
Abnormal data carry out preset mode process, and build abnormal data type tree.
104, continuous data polymerization process is carried out according to preset electric energy data business.
After the abnormal data that determines of monitoring being carried out preset mode process, and builds abnormal data type tree, needs
Continuous data polymerization process is carried out according to preset electric energy data business.
In the present embodiment, verify and the business rule base of assessment business by building electric energy data；According to business rule
Storehouse carries out the abnormal data monitoring of electric energy data and cleans；The abnormal data determining monitoring carries out preset mode process, and
Build abnormal data type tree；Carry out continuous data polymerization process according to preset electric energy data business, solve current
The decision-making of mistake, multi-data fusion that metering system causes are low, data visualization information transmits data low, big storage and process
Technical problem.
The above is that the process to intelligence automatic gauge method is described in detail, and will carry out detailed process in detail below
Description, refer to Fig. 2, another embodiment of a kind of intelligence automatic gauge method that the embodiment of the present invention provides includes:
201, the application layer carrying out the plurality of devices such as metering system and concentrator, harvester, measuring terminal, interactive terminal is led to
The structure of the dynamic analysis rule of letter agreement；
In the present embodiment, when needs carry out automatic gauge when, it is necessary first to carry out metering system and concentrator, collection
The structure of the dynamic analysis rule of the application layer communication protocol of the plurality of devices such as device, measuring terminal, interactive terminal.
202, the data carrying out metering system collection carry out continuous data resolution rules structure；
When the application layer communication carrying out the plurality of devices such as metering system and concentrator, harvester, measuring terminal, interactive terminal
After the structure of the dynamic analysis rule of agreement, the data carrying out metering system collection are needed to carry out continuous data resolution rules structure
Build.
203, the foundation of data rule corresponding to metering system monitoring and warning is carried out；
After the data carrying out metering system collection carry out continuous data resolution rules structure, need to carry out metering system
The foundation of the data rule that monitoring and warning is corresponding.
204, carry out the abnormal data monitoring of electric energy data according to business rule base and clean；
After carrying out the foundation of data rule corresponding to metering system monitoring and warning, need to carry out according to business rule base
The abnormal data monitoring of electric energy data and cleaning.
205, the abnormal data determining monitoring is by abnormal continuous data and the typical continuous data curve of its correspondence
Compare process, and build abnormal data type tree and/or abnormal data that monitoring is determined by abnormal continuous data
Compare process with the event of its correspondence or alarm data, and build abnormal data type tree and/or monitoring is determined different
Regular data is by occurring abnormal continuous data and other data to compare process, and builds abnormal data type tree；
After the abnormal data carrying out electric energy data according to business rule base monitors and cleans, need true to monitoring
Fixed abnormal data is compared process by the typical continuous data curve of abnormal continuous data and its correspondence, and builds different
Regular data type tree and/or the abnormal data determining monitoring pass through abnormal continuous data and the event of its correspondence or alarm
Data are compared process, and it is abnormal by occurring to build abnormal data type tree and/or the abnormal data that determines monitoring
Continuous data and other data are compared process, and build abnormal data type tree.
206, carry out continuous data according to preset electric energy data business and carry out data aggregate process successively and by pre-
Put data mart modeling mould processing；
When the abnormal data determining monitoring is entered by the typical continuous data curve of abnormal continuous data and its correspondence
Row comparison processes, and build abnormal data type tree and/or to the abnormal data that determines of monitoring by abnormal continuous data with
The event of its correspondence or alarm data are compared process, and build abnormal data type tree and/or the exception determining monitoring
Data are by occurring abnormal continuous data and other data to compare processs, and after building abnormal data type tree, and need
To carry out continuous data according to preset electric energy data business and to carry out data aggregate process successively and by preset data mart modeling
Mould processing.
207, the electricity consumption that the continuous data after processing polymerization and processed by preset data processing model carries out correspondence is special
Levy analysis and energy-saving structure diagnosis research.
Data aggregate process is carried out successively and by preset when carrying out continuous data according to preset electric energy data business
After data mart modeling mould processing, need the continuous data after processing polymerization and being processed by preset data processing model is entered
The electricity consumption feature analysis of row correspondence and energy-saving structure diagnosis research.
Being described in detail with a concrete application scenarios below, such as Fig. 5 to 11, application examples includes:
1. build electric energy data verification and assessment business rule base-technology path
According to power supply administration's electric energy data type and operational control demand, study data check based on business rule and estimate
Calculate algorithm, all kinds of electric flux abnormal datas are classified, and configures corresponding check formula and corresponding threshold value, it is achieved abnormal number
According to fine-grained management, the method for business rule combing includes analytical table meter in metering automation, the marketing operation system such as MIS
Information counts from table the correspondence (table name, field name) of front end interface data to system background data, operation system and deposits
The difference of storage structure, data rule and constraint etc..For the electric energy data of disappearance, can advise according to its historical data and business
Then, it is achieved the checking of electric energy data, edit and estimate.Building electric energy data verification and assessment rule base, data process can
With online/in real time or batch calls.If it is required, electric energy data can be tested as the independent flow process loaded beyond flow process
Card.
Building anomaly data detection rule base, it is achieved the checking of electric energy data, edit and estimate, data process can be
Line/call in real time or in batches.
1) business rule base builds and life cycle
Rule base realizes the computing formula that all data of system process and the integrated management analyzing decision logic rule, tool
There are all kinds of rule query, amendment and newly-built, and there is the old version management function of each rule-like.Rule base mainly includes as follows
Rule: communication protocol rule base, data parsing rule base, certification rule base, data check rule base, dealing of abnormal data rule
Storehouse, monitoring and warning rule base, business customizing rule base etc..System mainly includes following rule:
1, communication protocol processes: the application of the plurality of devices such as system and concentrator, harvester, measuring terminal, interactive terminal
The dynamic analysis rule of layer communication protocol；
2, continuous data resolves: all kinds of pretreatment rule of the data that system is returned from all kinds of metering automation equipment collections
Then, including verification, the abnormal and relevant statistics of data；
3, monitoring and warning rule: the mathematics that statistics involved by system monitoring early warning, prediction, judgement etc. are used
Computation rule.
Rule base management include computing formula that all data process and analyze the regular integrated management of decision logic and
All kinds of rule queries, amendment and newly-built, the old version management function of each rule-like, the lifecycle management of rule base and dimension
Protect flow process such as Fig. 5.
The abnormal data monitoring of electric energy data based on business rule base and cleaning technique
Abnormal data monitoring is to utilize modern computer communication technology, to electric flux sending out, defeated, join, send out by each link
Raw situation, carries out centralized and unified collection, monitors, adds up, analyzes and the operating mechanism of the standardized management such as issue.Different to data
Often process be mainly based upon the data characteristics of continuous data all kinds of table meter collection and business demand to carry out rule-based data different
Often monitoring and inspection.The primary and foremost purpose of checking, editor and assessment function is to check when continuous data enters application system
And cleaning.As shown in Figure 6, this process relates to following aspect to concrete processing procedure:
Authentication original measurement data, in desired range of tolerable variance, are just datas
If editor's original measurement data are the most wrong, can be modified
If estimation original measurement data imperfect (such as missing value), can automatically estimate the value of disappearance
(1) first pass through interface or adapter (SGG) and obtain the metric data of all kinds of table meters, data acquisition from front-end system
Frequency can be configured according to actual frequency acquisition and business demand, as daily, hour, minute etc.
(2) corresponding initial data is loaded onto data base, i.e. initial measurement
(3) initial measurement carrying out crucial checking, the crucial proof rule calling business rule base carries out crucial checking
(4) after being verified by key, starting to start VEE engine, VEE engine is according to the type of this metric data and parameter
Information is called corresponding VEE rule and is carried out data cleansing and verification
(5) measuring value after over cleaning and verification becomes final measured value, and the final measured value of establishment is totally may be used
The continuous data leaned on
(6) final measured value can also generate according to different computation rules based on final measured value according to service needed
Derive from measured value value
The final measured value analyzed by data exception and process and derivation measured value can be supplied to him by data-interface
Other operation systems carry out data sharing and analysis.
Based on abnormal data management business rule base and data check estimating algorithm, gather metering automation main website is each
Class table meter and terminal data are monitored in real time and analyze, and the data for dissimilar region and user can be advised according to business
Then condition, calls different verification rules, carries out data cleansing.When note abnormalities data time create corresponding backlog, and
Trigger different workflows, carry out the abnormal location of electric energy data and revise.When finding gaps and omissions and deficiency of data and nothing
When method is by filling mining, utilizes historical data and generic population data, in conjunction with corresponding data algorithm, estimate, fill and lack
Leakage data.Monitoring and processing procedure to abnormal data, it is provided that decision-assisting analysis, finds the exception rule of electric energy data in time
Rule and short slab, search abnormal source, repairs the factor causing data exception in time, accurately according to the efficiency of anomaly analysis and simultaneously
Rate, the optimization of rule base business rule of promoting business and renewal, promote abnormal data monitoring capability.
The data evaluating method of standard can be provided, be similar to date value, based on matched curve including linear interpolation method, history
Estimation, and real time data based on meter reading estimate.In addition to the standard method of estimation provided, user it be also possible to use and joins
Instrument of putting adds extra estimation rule by configuring.Allow to run multinomial estimation rule in order to support complicated estimation.
Such as, first call estimation based on matched curve rule, then call real time data based on meter reading and estimate rule.
First rule will utilize matched curve to obtain a use discharge curve meeting reality, and second rule will be adjusted to consumption just
True level.The electric energy data estimated also can be exclusively used in be estimated the rule of reading and verifies, and the record of all estimations is all
There is corresponding labelling.Checking procedure is as shown in Figure 7.
Closed loop dealing of abnormal data-technology path
Based on the various Exception Types during data acquisition for electric energy, according to practical business management strategy, set difference
Exception handling logic, it is achieved the dealing of abnormal data of procedure.Support to find, preserve and process exception, and follow the tracks of abnormal with
Speed up processing.Analyze each Terminal Type and table meter abnormal information, the related data of all kinds of anomalous event of combing and index of correlation,
Build abnormal data type tree, during the data that note abnormalities, according to electric energy data feature and reality operational control mode, for
Different electric energy data types, based on its abnormal class, sets different processing modes, and trigger corresponding process action and
Flow process, the closed-loop data being standardized processes, and is cured as abnormal data flow process, it is provided that configurable differentiation is multiple
Processing mode, as sent abnormality warnings, automatic error-correcting processes, initiates artificial handling process etc., and can pass through backlog and use
Family is interactive, it is ensured that processing in time and feedback of abnormal data.
Abnormality processing core strategy includes:
Support to find, preserve and process data exception
Follow the tracks of abnormal with speed up processing
Configurable differentiation abnormality processing, it is provided that operation flow support
Data exception processes task distribution and Schedule monitoring
Data exception processes detail and checks
Dealing of abnormal data processes detail and checks
After carrying out the checking about initial content data in the correction verification module of backstage, find not validated (to be in ' wrong
By mistake ' or ' extremely ' state) data.Automatically revising by the data check flow process of system if they do not have, operator can
To utilize system standard page interrogation to search.These in-problem initial content data, after operator's problem analysis, Ke Yiyou
The process of 3 aspects: manual tracking problem root, resubmits and verifies it again.Directly the reading after amendment data check is (if really
If Ding), and have been manually done this initial measurement.This can help to use after data check reading value to create usage data
Final value.Can abandon just in the initial measurement of abnormality at the page.No matter operator carries out that class action, system will
It is automatically performed the backlog entry about abnormality initial measurement institute output.Different for find in VEE checking procedure
Often, being divided into is 3 class severity definition.Different seriousness need tracking mode of different nature.
The relevant seriousness that 3 classes are abnormal:
" message " seriousness, this seriousness mainly indicates some things merited attention, but not there is a need to working as simultaneously
Front measured value state is pushed into " exception ".Imply that being not required to operator follows the tracks of relevant thing at once.This type of seriousness different
Often record is served only for the frequency reported about paying close attention to thing, is not to be directed at metric data quality problems.
" problem " seriousness, this seriousness mainly reports some data problems.These data problems have to follow the tracks of place
Reason, thus need temporarily by currently initiate metric data wait decide, wouldn't do and finally determine.Correspondence is surveyed with a collection of initial amount
Data, allow the exception record closing chain multiple " problem " seriousness.When all different verification rules were carried out, if minimum
If one " problem " exception record output, current initial metric data will go to " exception " state.
" stopping " seriousness, this seriousness is mainly some data problems, but these data problems will cause data school
Testing flow process to stop, current initial metric data goes to " exception " state at once.Whole checking process comprises multiple verification rule
Then.As long as first verification rule has been found that exception, need to stop current process.It is serious that system will only generate one " stopping "
The exception record of property.
This data exception closed-loop process needs to pay attention to following characteristic:
Run into abnormal initial metric data, submit to again after correction, it is also necessary to through the most a set of verification rule.
After bringing up again friendship, if running into exception again, also will generate other exception record.
Only by all verification rules, relevant initial metric data just can be determined, and the most formally generates final quantity
Survey data value.
For some initial metric data, it comprises the reading of multiple period interval.If one of them period
The reading at interval runs into exception, and under that the most same intelligent meter, the reading of a whole set of period interval is also to wait to decide.
Such as, the 2nd of the reading of 3 period interval interval missing data below, by not relevant verification.A whole set of 3
The reading of individual period interval is also to wait to decide.Operator only need to handle that missing data well, then submits to, by verification.
The reading of overall 3 period interval can generate final quantity measured value.
Can use multiple ratio method that data exception is processed, it is judged that the reason of abnormality processing and be the most really different
Normal:
(1) occur the typical continuous data curve of abnormal continuous data and its correspondence to compare, calculate it abnormal
Ratio (including abnormal counting and each abnormal percentage ratio etc.), thus assess the degree of its exception
(2) event or the alarm data of abnormal continuous data with its correspondence are compared, the most whether analyze
There is inevitable cause effect relation, thus eliminate the data that part is the most abnormal
(3) continuous data that exception will occur and other data (such as: temperature etc.) are compared, and calculate abnormal data
And between associated data, whether there is relation, thus eliminate the data that part is the most abnormal.
(4) table meter model that the continuous data that exception will occur is corresponding, manufacturer etc. carry out the discriminatory analysis of profound level,
Calculating the continuous data abnormal rate that certain model, producer etc. are corresponding, for choosing suitable producer future, model provides foundation.
Abnormal when occurring, system can be passed through note, alarm, Pending tasks etc. and notify corresponding management personnel.
The continuous data polymerization technique investigative technique route of service-oriented
Based on electric energy data business it is actually needed, builds electric energy data computing engines, carry out according to business rule
Collecting and calculating of electric energy data, it is possible to according to actual service needed, carry out data conversion and calculating, for electric flux number
According to related service provide data, services.
All kinds of continuous datas can be carried out automatically by data computing engines based on downstream application and the business demand of flow process
Collect and pack, it is provided that the data of service-oriented prepare.System generally uses regular batch processing, and user also can return the most again
Collection, and creates at any time and performs to collect especially, and the processing mode collected and business rule can flexible customization as required.Utilize first
Enter data base method to improve and collect the performance of process, and provide view and service access to collect curve, process collect curve and with
Other curve comparison, to support operational analysis and assessment etc..
A) consumption calculates and charging support
Continuous data after verification, can be according to the pricing mode of all types of user and metering period, the use to user
Amount carries out collecting calculating, sends to client accounting system, supports that Fare Collection System generates all kinds of bills
B) data summarization based on business and calculating
And calculating can be collected, as according to industry, user class according to what business rule carried out continuous data according to service needed
Not, geographic area, power network topology carry out statistical summaries, it is possible to according to actual service needed, carry out more complicated data
Converting and calculate, the related service for continuous data provides data, services.Data aggregate and work flow are as shown in Figure 8.
Outside related service system (such as: line loss, ordered electric etc.) is when due to service needed, it is desirable to wait until by counting in real time
According to the data message of processing, these operation systems can send subscription request by UAPI, definition: need by which to be counted in real time
Which kind of according to participating in data mart modeling, computation rule, when carry out calculating (namely real time data being processed computing), by road
Footpath or mode are sent to external service system, and data service platform according to subscription, is friendship undetermined by batch automatically generating state
Easily (or affairs, transaction represents according to user's definition, is processed calculating to the real time data of specific time period), external service system
The request of transaction can be triggered online, or call transaction engine, according to rule to reality according to subscribing to the requests transaction triggering transaction
Time data calculate accordingly, process.Data mart modeling after completing is as a result, it is possible to enter according to the approval process that predefined is good
Row examination & approval, are sent to operation system.
Data mart modeling model, by service point (measuring point) and final live data values (i.e. clean after data process
, available live data values) be associated.Data subscription and service point are the relations of multi-to-multi, and data subscription defines ginseng
The service point calculated with data.By service point and the relation of final live data values, i.e. determine participation data and calculate
Whole live data values, meanwhile, data subscription can also add the data such as network topology by the data resource platform of south electric network,
Because these data will determine service point position in the entire network, thus determines the relativeness between service point, such as:
The relativeness changed changing adjacent service point of network operation position, thus affect the calculating of line loss.Data subscription sum
According to the relation between affairs being one-to-many.Each data subscription correspond to multiple data transactions, namely data (real time data
Processing result), the reaction of each data transactions is the processing to the real time data in a period of time.Data subscription and data set it
Between be the relation of multi-to-multi.Data set is the logical groups of data rule, and each data rule is equivalent to the definition of data calculating puts down
Platform, defines the operational formula of final live data values.
Consumption engine
Consumption engine is the core of data mart modeling, be client configure real time data processing rule platform.
By the configuration strategy such as time, priority, perform corresponding computational algorithm, generate result of calculation, and as measuring point
End value and state dump in data base.Support multiple calculating type: trigger calculating when computation of Period, component variation, determine
Time calculate, manually start calculating；Computing engines includes: types of variables definition, scope of a variable, operator associative law and preferential
Level, grammer, Row control, system function, self-defining function, the content such as interface of host program；The processing procedure of computing engines
Including: editor, syntax error inspection, pseudo-compiling, execution etc.；Scripting Edition: provide scripting tools, uses the mode of IDE,
Support grammer Color-sensitive.Formula calculates abnormality processing.The process of mistake in computation occurs during formula is calculated, uses silent
The mode recognizing value is set, when, after formula mistake in computation, if setting default value, then obtaining default value, without acquiescence
Value, then write exception.
A. consumption group is the logical combination of consumption rule.It is the relation client of multi-to-multi between consumption combination consumption rule
B. consumption rule is to define concrete data mart modeling algorithm.
C. consumption rule has valid period and applicable elements.Client can carry out configuration definition.
D. client can configure use quantity algorithm, the namely processing method of real time data of each consumption rule.Support:
1. convenient, friendly interface for users off-line or online definition amount of calculation and computing formula are provided；
Support that conventional function calculates storehouse, support to add, subtract, the computing such as multiplication and division, triangle, logarithm, it is possible to carry out logic and bar
Part judges computing.
2. data type, operator, canonical function and the statement supported are as follows:
Support the dtd--data type definition that magnanimity near-realtime data service platform is unified, as shown in table 1:
Table 1
Metering automation system realization technology path based on big data framework
Study metering automation system realization scheme based on big data technique, including Technical Architecture, physical structure, logic
Framework and metering automation system acquisition, store, calculate, the technology of each link such as analysis is selected scheme, and is completed based on big number
Develop according to the metering automation system-based application function of technology.
At Technical Architecture when choosing, project intend at tradition metering automation based on relevant database system architecture base
On plinth, research uses based on Spark, Hadoop distributed file system, the cloud storage data base of distributed data processing, cloud
Calculate etc. big data technique and Map Reduce as process the storage of mass data in the big data of electric power, parallel programming model and
Cloud computing framework, it is achieved storage service, calculating service, application and Component service.
Based on big data user's electricity consumption feature analysis and energy-saving structure diagnosis research technology path
In the research of this part, quasi-step matrix daily practical business demand, by choosing three application scenarios: energy-conserving and environment-protective
The energy consumption analysis of building, the diagnosis of energy saving of industrial user and power distribution network industry expand service optimization, analyze model, utilization by setting up
Existing continuous data is carried out sorting out extraction by data mining and machine learning techniques, finds out divide corresponding with different application scene
Analysis data, and solidify in systems, form a set of model about applied business depth analysis, step and technology frame
Frame, realizes intelligent metering automated system based on big data framework offer practical basis for final.This part is studied owing to relating to
And application scenarios there is diversity, therefore, the technology path under each application scenarios is different, specific as follows:
(1), energy-conserving and environment-protective Building Energy Analysis
In view of complexity and the multiformity of building energy system, single Performance Evaluating Indexes is difficult to be fully described by monomer
The energy consumption of building energy system, efficiency and indoor and outdoor surroundings effect situation thereof, also inconvenience is for multiple building energy systematic functions
Relative analysis.For different pieces of information analysis purpose and different pieces of information application demand, used building energy system evaluation refers to
Mark is also not quite similar.For system, in depth evaluating building energy system energy situation, this research will be first according to building energy system
The mode of system Data Source and different demand, set up a set of single building energy resource system Performance Measuring Indicators；Secondly basis
Different administrative grades are different to construction energy conservation monitoring demand, set up building energy system energy consumption evaluation index tree.
(2), the diagnosis of energy saving application of industrial user
In general factory, the distinct of power load, the power consumption difference between various loads is huge, the most existing
In factory a lot of measuring equipment instruments disappearance, therefore, project startup stage, need first to gather facility carry out comprehensively
Know the real situation investigation: if desired for monitoring voltage, electric current, active power, reactive power, power factor, activereactive energy, harmonic wave, ring
Border and the power consumption parameter such as on off state, logout.Monitoring object is included simultaneously: electric power demand side mesolow feeder assembly,
Mainly consume energy electromechanical equipment, other power consumption facilities of Factory Building (living area).Simultaneously can also to water consumption, gas consumption, heat, feed intake
Amount, yield etc., by the site intelligent data acquisitions such as electronic flow table, electronic type calorimeter, belted electronic balance, on-ground weigher, root
The requirement applied according to field condition and system, the data of collection can also take from the data-interface etc. of other intelligence systems of user
Carry out being correlated with supplements and perfect, in the case of above-mentioned infrastructure is complete, can carry out according to the technology path shown in Fig. 9
Carrying out of follow-up work.
After completing a series of activities shown in Fig. 9, also the big data of production load collected are analyzed and grind
Study carefully.Effective energy spectrometer not only needs sufficiently to produce and energy consumption data, in addition it is also necessary to have deep understanding to production process, needs
Various energy spectrometer technology and feature thereof are had deep grasp and can be to its flexible utilization.The Usefulness Pair of energy spectrometer result
Enforcement and the energy-saving effect obtained of energy management system are most important, it practice, the energy spectrometer result of mistake can cause
The information of mistake, the serious operational effect damaging energy management system, even result in the failure of energy management system.Therefore, originally
Project is planned big data technique and is introduced, and emphasis solves load Analysis and the prediction of each workshop section emphasis energy consumption equipment.
The measuring equipment state estimation scale-model investigation technology path learnt based on big data and the degree of depth
Under the big data environment of electric power, correlation rule is used to carry out data mining, by different pieces of information in analytical database
The potential relation existed between attribute, finds out and meets given support and the relation rule of confidence level, and equipment carries out online event
Barrier diagnosis also preserves vibration alarming record.This rule can provide initial failure early warning and failure reason analysis to operations staff,
Thus got rid of, to guarantee the stable operation of power equipment before fault occurs.
During expert diagnosis and state estimation, diagnostic knowledge based on equipment failure mode analysis result will be built
Storehouse, uses Artificial Diagnosis and based on the method such as deep neural network, fuzzy reasoning, to realize examining equipment deficiency and fault
Disconnected.
Target be mainly refined as following some:
1) equipment state assessment rule base management, it is achieved definition and quantity of state to equipment state amount are existing with power supply administration
Marketing system business module, the association of metering automation incident management information；
2) the early warning risk assessment of equipment, the various basis of package and operational monitoring data, show that outfit of equipment is healthy
State, is identified the Key state in measuring equipment based on data mining algorithms such as cluster analyses, Key state one
As can to equipment safe and stable operation produce significant impact, therefore patrol and examine on-site terminal equipment and metering device when system at regular intervals
Time, when catastrophe failure feature occurs in the equipment of perceiving, carry out short message alarm by SMS platform interface in advance；
3) Strategies of Maintenance management.According to equipment evaluation result, overhaul situation based on device history, set up self-study mechanism,
Automatic Optimal Strategies of Maintenance on this basis, and manual intervention flow process is provided on this basis, formulate repair schedule for marketing and carry
For data supporting；
4) the associate device situation according to Tactial problem and actual motion state and according to this equipment is (e.g., same
Interval, same to bar) automatically generate repair schedule, and manual intervention flow process is provided on this basis.
Data visualization technology for revealing investigative technique routes based on big data
Power system visualization is to be shown with lively graphics mode intuitively by electric power system data, and its target is to allow
Operator it will be appreciated that and the behavior of final optimization pass power system and performance, and be predicted before having an accident, prevent and treat or
Make quickly response.Owing to the data in metrical information system are various, data structure is complicated, contain and contain much information, in order to help
Related data management personnel see the information contained in data intuitively, available data are carried out visualization processing significant.
The function that visualization system is to be possessed is the real-time visual function that must meet operation states of electric power system.From with
The demand at family is set out, and this system user that wants help holds Real-Time Power System Operation States intuitively, improve scheduling quality and
Efficiency, it is possible to help the generation of user in predicting fault and can find when fault occurs in time and analyze；From power system
The feature of wide area measurement is set out, and visualization system not only needs with multiple graphic display mode to show substantial amounts of measurement data,
And disclosure satisfy that the quick Dynamic Announce to the data such as frequency, voltage phase angle；From software, software needs to have one
Fixed motility, it is possible to realize carrying out editor and the function of amendment of visual content according to concrete demand.Wide area measurement number
According to visualization system by user management module, data management module, visual edit module and visualization display module four
Part composition, its overall structure block diagram is as shown in Figure 10.Visualization system is from metering system main website receiving real-time data, data pipe
Data are managed by reason module, provide visualization data for visualization model.Visual edit module is in visualization model
Content edit, determine the display content in visualization model, improve system use motility.User manages mould
Block management user right, prevents from, to the illegal of system or maloperation, improving the safety in utilization of visualization system.Concrete function mould
Block designs as shown in figure 11.
Based on quality evaluation, Intelligent Recognition and school by the electrical network of the Bayesian network model big data of multi-source heterogeneous magnanimity
Core, extraction and cleaning technique, it is achieved intelligence " make an uproar denoising, and line loss problem based on CART traditional decision-tree becomes on this basis by knowledge
Because analyzing, it is achieved the auxiliary decision technology route of reducing loss measure suggestion
The traditional analysis of industry passes through state estimation identification " noise " data, but method for estimating state needs in topology
In the case of Zheng Que, it is identified for properly functioning data, it is impossible to be applicable to the big data scene of above-mentioned complexity, and cannot know
Not topology, equipment account mistake；In the case of weak dependence, weak rigidity, state estimation is not normally functioning, and project is intended based on data
" noise " data identified, by Bayesian network model, are carried out clearly by quality evaluation and control, comprehensive control achievement in research
Wash " denoising ", it is ensured that the effectiveness of subsequent analysis, correctness.
By machine learning, use CART decision Tree algorithms, learn expert tactics, analyze line loss problem more accurately and become
Cause, carries out the suggestion of reducing loss measure pointedly；It is simultaneously based on classical algorithm and carries out checking and the assessment of suggested measures.?
Mesh uses and builds criteria for prediction, with the Form generation decision tree of binary tree with the diverse mode of traditional statistics, it is easy to reason
Solve, use and explain；More more accurate than the algebra criteria for prediction that conventional statistical method builds, and data are the most complicated, variable
The most, the superiority of algorithm is the most notable, is highly suitable for mass data scene.
In the present embodiment, verify and the business rule base of assessment business by building electric energy data；According to business rule
Storehouse carries out the abnormal data monitoring of electric energy data and cleans；The abnormal data determining monitoring carries out preset mode process, and
Build abnormal data type tree；Carry out continuous data polymerization process according to preset electric energy data business, solve current
The decision-making of mistake, multi-data fusion that metering system causes are low, data visualization information transmits data low, big storage and process
Technical problem.
Referring to Fig. 3, an embodiment of a kind of intelligent metering automation equipment provided in the embodiment of the present invention includes:
Construction unit 301, for building electric energy data verification and the business rule base of assessment business；
Monitoring cleaning unit 302, for carrying out the abnormal data monitoring of electric energy data and cleaning according to business rule base；
Exception processing unit 303, carries out preset mode process for the abnormal data determining monitoring, and builds abnormal number
According to type tree；
Polymerization processing unit 304, for carrying out continuous data polymerization process according to preset electric energy data business.
In the present embodiment, build electric energy data by construction unit 301 and verify and the business rule base of assessment business；Prison
Control cleaning unit 302 carries out the abnormal data monitoring of electric energy data according to business rule base and cleans；Exception processing unit
The abnormal data that the 303 pairs of monitoring determine carries out preset mode process, and builds abnormal data type tree；Polymerization processing unit 304
Carry out continuous data polymerization process according to preset electric energy data business, solve the mistake that current metering system causes
Decision-making, the technical problem that multi-data fusion is low, data visualization information transmits data low, big storage and process.
The above is that each unit to intelligent metering automation equipment is described in detail, and sub-unit is presented herein below and carries out in detail
Thin description, refers to Fig. 4, another embodiment bag of a kind of intelligent metering automation equipment provided in the embodiment of the present invention
Include:
Construction unit 401, for building electric energy data verification and the business rule base of assessment business；
Construction unit 401 specifically includes:
First rule builds subelement 4011, is used for carrying out metering system and concentrator, harvester, measuring terminal, interaction
The structure of the dynamic analysis rule of the application layer communication protocol of the plurality of devices such as terminal；
Second Rule builds subelement 4012, carries out continuous data resolution rules for carrying out the data of metering system collection
Build；
Three sigma rule builds subelement 4013, for carrying out the foundation of data rule corresponding to metering system monitoring and warning.
Monitoring cleaning unit 402, for carrying out the abnormal data monitoring of electric energy data and cleaning according to business rule base；
Exception processing unit 403, carries out preset mode process for the abnormal data determining monitoring, and builds abnormal number
According to type tree；
Exception processing unit 403 specifically includes:
First comparer unit 4031, the abnormal data for determining monitoring passes through abnormal continuous data and it is corresponding
Typical continuous data curve compare process, and build abnormal data type tree；
And/or
Second comparer unit 4032, the abnormal data for determining monitoring passes through abnormal continuous data and it is corresponding
Event or alarm data compare process, and build abnormal data type tree；
And/or
3rd comparer unit 4033, for the abnormal data that determines of monitoring by occur abnormal continuous data and its
His data are compared process, and build abnormal data type tree.
Polymerization processing unit 404, for carrying out continuous data polymerization process according to preset electric energy data business, poly-
Close processing unit 404, carry out successively at data aggregate specifically for carrying out continuous data according to preset electric energy data business
Manage and processed by preset data processing model.
Analyzing and diagnosing unit 405, the continuous data after polymerization being processed and is processed by preset data processing model
Carry out electricity consumption feature analysis and the energy-saving structure diagnosis research of correspondence.
In the present embodiment, build electric energy data by construction unit 401 and verify and the business rule base of assessment business；Prison
Control cleaning unit 402 carries out the abnormal data monitoring of electric energy data according to business rule base and cleans；Exception processing unit 403
The abnormal data determining monitoring carries out preset mode process, and builds abnormal data type tree；Polymerization processing unit 404 basis
Preset electric energy data business carries out continuous data polymerization process, solves wrong the determining that current metering system causes
Plan, multi-data fusion are low, data visualization information transmits data low, big storage and the technical problem processed.
Those skilled in the art is it can be understood that arrive, for convenience and simplicity of description, and the system of foregoing description,
The specific works process of device and unit, is referred to the corresponding process in preceding method embodiment, does not repeats them here.
In several embodiments provided herein, it should be understood that disclosed system, apparatus and method are permissible
Realize by another way.Such as, device embodiment described above is only schematically, such as, and described unit
Dividing, be only a kind of logic function and divide, actual can have other dividing mode, the most multiple unit or assembly when realizing
Can in conjunction with or be desirably integrated into another system, or some features can be ignored, or does not performs.Another point, shown or
The coupling each other discussed or direct-coupling or communication connection can be the indirect couplings by some interfaces, device or unit
Close or communication connection, can be electrical, machinery or other form.
The described unit illustrated as separating component can be or may not be physically separate, shows as unit
The parts shown can be or may not be physical location, i.e. may be located at a place, or can also be distributed to multiple
On NE.Some or all of unit therein can be selected according to the actual needs to realize the mesh of the present embodiment scheme
's.
It addition, each functional unit in each embodiment of the present invention can be integrated in a processing unit, it is also possible to
It is that unit is individually physically present, it is also possible to two or more unit are integrated in a unit.Above-mentioned integrated list
Unit both can realize to use the form of hardware, it would however also be possible to employ the form of SFU software functional unit realizes.
If described integrated unit realizes and as independent production marketing or use using the form of SFU software functional unit
Time, can be stored in a computer read/write memory medium.Based on such understanding, technical scheme is substantially
The part that in other words prior art contributed or this technical scheme completely or partially can be with the form of software product
Embodying, this computer software product is stored in a storage medium, including some instructions with so that a computer
Equipment (can be personal computer, server, or the network equipment etc.) performs the complete of method described in each embodiment of the present invention
Portion or part steps.And aforesaid storage medium includes: USB flash disk, portable hard drive, read only memory (ROM, Read-Only
Memory), random access memory (RAM, Random Access Memory), magnetic disc or CD etc. are various can store journey
The medium of sequence code.
The above, above example only in order to technical scheme to be described, is not intended to limit；Although with reference to front
State embodiment the present invention has been described in detail, it will be understood by those within the art that: it still can be to front
State the technical scheme described in each embodiment to modify, or wherein portion of techniques feature is carried out equivalent；And these
Amendment or replacement, do not make the essence of appropriate technical solution depart from the spirit and scope of various embodiments of the present invention technical scheme.
Claims (10)
1. an intelligent automatic gauge method, it is characterised in that including:
Build electric energy data verification and the business rule base of assessment business；
Carry out the abnormal data monitoring of electric energy data according to described business rule base and clean；
The described abnormal data determining monitoring carries out preset mode process, and builds abnormal data type tree；
Continuous data polymerization process is carried out according to preset electric energy data business.
Intelligent metering automated system the most according to claim 1, it is characterised in that intelligence build electric energy data verification and
The business rule base of assessment business specifically includes: purified voltage stabilized power source, by electric power network and intelligent metering automated system
Transmitting terminal connects.
Carry out the application layer communication protocol of the plurality of devices such as metering system and concentrator, harvester, measuring terminal, interactive terminal
The structure of dynamic analysis rule；
The data carrying out metering system collection carry out continuous data resolution rules structure；
Carry out the foundation of data rule corresponding to metering system monitoring and warning.
Intelligent metering automated system the most according to claim 2, it is characterised in that the described abnormal number that monitoring is determined
According to carrying out preset mode process, and build abnormal data type tree and specifically include:
The described abnormal data determining monitoring is carried out by the typical continuous data curve of abnormal continuous data and its correspondence
Comparison processes, and builds abnormal data type tree；
And/or
The described abnormal data determining monitoring is compared by abnormal continuous data and the event of its correspondence or alarm data
To process, and build abnormal data type tree；
And/or
To the described abnormal data that determines of monitoring by occurring abnormal continuous data and other data to compare process, and structure
Build abnormal data type tree.
Intelligent metering automated system the most as claimed in any of claims 1 to 3, it is characterised in that according to preset
Electric energy data business carry out continuous data polymerization process specifically include:
Carry out continuous data according to preset electric energy data business carry out data aggregate process successively and added by preset data
Work mould processing.
Intelligent metering automated system the most according to claim 4, it is characterised in that according to preset electric energy data
Business carries out also including after continuous data is carried out data aggregate process successively and processed by preset data processing model:
Described continuous data after processing polymerization and being processed by preset data processing model carries out dividing with electrical feature of correspondence
Analysis and energy-saving structure diagnosis research.
6. an intelligent metering automation equipment, it is characterised in that including:
Construction unit, for building electric energy data verification and the business rule base of assessment business；
Monitoring cleaning unit, for carrying out the abnormal data monitoring of electric energy data and cleaning according to described business rule base；
Exception processing unit, carries out preset mode process for the described abnormal data determining monitoring, and builds abnormal data
Type tree；
Polymerization processing unit, for carrying out continuous data polymerization process according to preset electric energy data business.
Intelligent metering automation equipment the most according to claim 6, it is characterised in that construction unit specifically includes:
First rule builds subelement, is used for carrying out metering system many with concentrator, harvester, measuring terminal, interactive terminal etc.
The structure of the dynamic analysis rule of the application layer communication protocol of the equipment of kind；
Second Rule builds subelement, carries out continuous data resolution rules structure for carrying out the data of metering system collection；
Three sigma rule builds subelement, for carrying out the foundation of data rule corresponding to metering system monitoring and warning.
Intelligent metering automation equipment the most according to claim 7, it is characterised in that exception processing unit specifically includes:
First comparer unit, passes through abnormal continuous data and the allusion quotation of its correspondence for the described abnormal data determining monitoring
Type continuous data curve is compared process, and builds abnormal data type tree；
And/or
Second comparer unit, passes through abnormal continuous data and the thing of its correspondence for the described abnormal data determining monitoring
Part or alarm data are compared process, and build abnormal data type tree；
And/or
3rd comparer unit, for monitoring the described abnormal data determined by there is abnormal continuous data and other numbers
According to process of comparing, and build abnormal data type tree.
9. according to the intelligent metering automation equipment described in any one in claim 6 to 8, it is characterised in that polymerization processes
Unit, carries out data aggregate process and by pre-successively specifically for carrying out continuous data according to preset electric energy data business
Put data mart modeling mould processing.
Intelligent metering automation equipment the most according to claim 9, it is characterised in that intelligent metering automation equipment is also
Including:
Analyzing and diagnosing unit, the described continuous data after processing polymerization and being processed by preset data processing model is carried out
Corresponding electricity consumption feature analysis and energy-saving structure diagnosis research.
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