CN105652232A - Stream processing-based electric energy metering device online abnormality diagnosis method and system - Google Patents
Stream processing-based electric energy metering device online abnormality diagnosis method and system Download PDFInfo
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Abstract
The invention discloses a stream processing-based electric energy metering device online abnormality diagnosis method and system. The method includes the following steps of: metering abnormality analysis data acquisition: data required by abnormality analysis are acquired from a database of an electricity utilization information collection system; logical chain generation: a plurality of kinds of single-abnormality diagnosis logic chains are generated; stream processing control: the single-abnormality diagnosis logic chains are processed, and results are stored in a stream processing state storage module; processing tasks are assigned to stream processing work nodes in a balanced manner according to the load sate information of the updated stream processing work nodes in the stream processing state storage module; stream processing work: single-abnormality diagnosis on an electric energy metering device is completed, and parallel processing of the plurality of stream processing work nodes is realized; and abnormality relevant diagnosis: relevant diagnosis is carried out, so that metering abnormality diagnosis results and operation and maintenance recommendations are generated, and are sent to the electricity utilization information collection system. With the method and system adopted, rapid online abnormality diagnosis on the electric energy metering device can be realized.
Description
Technical field
The present invention relates to electric energy metrical technical field, particularly relate to a kind of online abnormality diagnostic method of electric power meter based on stream process and system.
Background technology
In power system, electric power meter is one of indispensable important component part, primarily of various types of electric energy table, metering voltage, current transformer and the composition such as secondary circuits, electric energy metering cabinet (case) thereof, being the important evidence that power supply enterprise realizes power trade, its operation conditions and the whether accurate of image data are directly connected to the interests of user and the economic benefit of power supply enterprise. Simultaneously, along with the propelling of China's new round power system reform, social capital is encouraged to enter power sales, electric company improves customer satisfaction and himself the market competitiveness, promote the fortune dimension efficiency of electric power meter, in the detection of electric power meter and the fast quick-recovery of fault etc., carry out research.
Traditional user's electric power meter detection work mainly relies on testing staff regularly to arrive electricity consumption scene to carry out inspection, and the plenty of time has all spent in the road rushing for electricity consumption scene, reduces working efficiency. Along with the development of microelectronics, the communication technology etc. and perfect, accelerate electric energy table and develop to intelligent direction; Simultaneously, the built useful power utilization information collection system of electric company, current acquisition system has stored a large amount of information that can be used for measuring apparatus on-line monitoring, comprise the data such as voltage, electric current, wattful power, wattless power, power factor and clock of power meter, but not yet obtaining abundant analysis mining, these make the remote monitoring of electric energy table and are more and more paid attention at radiodiagnosis x.
In addition, along with the progressively realization of " all standing, full collection " target, the electric power meter quantity of access increases, the lifting of data mining level, the data scale all making on-line monitoring to process increases sharply, requiring more and more higher to the promptness of the abnormal feedback of electric power meter in business, current on-line monitoring method and system are difficult to meet these present situations simultaneously. Reply mass data processing at present generally adopts distributed data processing pattern.
Summary of the invention
The object of the present invention is exactly to solve the problem, a kind of online abnormality diagnostic method of electric power meter based on stream process and system are provided, required business datum is extracted from power information acquisition system, process at stream and the basis of framework carries out the single abnormity diagnosis of electric power meter, abnormal relevant diagnosis, it is achieved that to the online fast abnormity diagnosis of electric power meter.
In order to realize above-mentioned purpose, the present invention adopts following technical scheme:
Based on the online abnormality diagnostic method of electric power meter of stream process, comprise the steps:
Step (1): metering anomaly analysis data acquisition step: data to be extracted in power information acquisition system are configured by the single abnormity diagnosis rule according to obtaining from metering abnormity diagnosis rule base, the data needed for anomaly analysis are obtained, stored in metering anomaly analysis database from the database of power information acquisition system;
Step (2): logic chain generation step: according to the multiple single abnormity diagnosis logic chain of single abnormity diagnosis generate rule;
Step (3): stream processing controls step: the single abnormity diagnosis logic chain that receive logic chain generation step is submitted to, single abnormity diagnosis logic chain is done serializing process, according to the logic block that serializing process produces, for single abnormity diagnosis logic chain allocation process task, and result is stored in stream treated state memory module; Also according to the load state information of each stream work for the treatment of node upgraded in stream treated state memory module, balanced to stream work for the treatment of peer distribution Processing tasks;
Step (4): stream work for the treatment of step: run the every Processing tasks in single abnormity diagnosis logic chain, the load state information of each stream work for the treatment of node being stored in real time flows in treated state memory module, complete the single abnormity diagnosis to electric power meter, it is achieved the parallel processing of multiple stream work for the treatment of node;
Step (5): abnormal relevant diagnosis step: on the basis of single abnormity diagnosis result, carry out further relevant diagnosis, generates metering abnormity diagnosis result and fortune dimension suggestion, and send is to power information acquisition system.
Described metering anomaly analysis data acquisition step, comprising:
Information extraction sub-step: extract anomaly analysis basic data from power information acquisition system;
Data conversion sub-step: obtain anomaly analysis basic data, process the data redundancy owing to communicative reasons causes and disappearance, remove redundant data, benefit calls missing data together, and undertaken merging, transforming and partition operation by the metering anomaly analysis data of extraction according to the single abnormity diagnosis business demand of metering, form the analytical data needed for anomaly analysis;
Data import sub-step: the analytical data needed for anomaly analysis is loaded in metering anomaly analysis database.
Anomaly analysis basic data comprises the relevant event information of the measuring apparatus such as electric energy table game clock lid event, SOT state of termination quantitative change position record, the data that the electric power meters such as active energy indicating value, powertrace collect, the steering order message that the acquisition systems such as expense control message issue to electric power meter, the measuring apparatus archives etc. such as user's contract capacity, maximum requirement.
Described stream work for the treatment of step, comprising:
Guard sub-step: from stream treated state memory module, obtain the logic block that all logic blocks and Processing tasks map relation, task matching table and stream work for the treatment of node and need to process, and be distributed to work sub-step; Monitor the heartbeat message of Processing tasks and the state of loading situation of stream work for the treatment of node simultaneously, it is stored in stream treated state memory module; Guarding sub-step adopts the mode of wheel inquiry to inquire about the information whether having renewal in stream treated state memory module, and upgrade in time local information.
Work sub-step: obtain the logic block flowing work for the treatment of node and need to processing from guarding sub-step, process code in operation logic block, and the ordinal relation run according to logic block sets up logic block and the connection of other work module, complete the real-time single anomaly analysis of electric power meter, generate single abnormity diagnosis result.
Described abnormal relevant diagnosis step, comprising:
Association coupling sub-step: obtain single abnormity diagnosis result from stream work for the treatment of step, and carry out rule match according to obtaining abnormal relevant diagnosis model from metering abnormity diagnosis rule base, coupling adds up the relational degree between theme and theme obtaining existing association relation, and then draws the relevant diagnosis result of electric power meter;
Association analysis sub-step: obtain the relational degree between theme and theme that there is association relation from association coupling sub-step, abnormal relevant diagnosis model is obtained from metering abnormity diagnosis rule base, multi-threaded abnormal association analysis is realized by association analysis algorithm, according to abnormal association analysis result, judge the state residing for electric power meter, and then take corresponding counter-measure.
Described metering abnormity diagnosis rule base, for the electric power meter abnormity diagnosis rule that concentrated storage extracts from the actual maintenance work of electric power meter, comprise the single abnormity diagnosis rule carrying out the single anomaly analysis of electric energy measuring equipment, and on single abnormity diagnosis rule-based approach, carry out abnormal relevant diagnosis model two portions of the abnormal relevant diagnosis of electric energy measuring equipment.
Described single abnormity diagnosis rule comprises diagnostic method, threshold levels, towards user, required data source with analyze the information such as frequency; Described abnormal relevant diagnosis model comprises the information such as relating subject, relational degree and on-the-spot fortune dimension suggestion.
Single abnormity diagnosis rule and abnormal relevant diagnosis model are all expressed as production rule by rule description language, and the production rule of generation represents the structure for If (condition) Then (behavior). Adopt the form of production rule to store, it is stored in metering abnormity diagnosis rule base.
Described metering anomaly analysis database, stores each item data and analytical results information that metering anomaly analysis data acquisition step extracts from power information acquisition system, provides analytical data basis to stream work for the treatment of step.
Described stream treated state memory module, at least comprise 3 memory nodes, for the information of storage flow processing controls step and stream work for the treatment of step, stream processing controls step and stream work for the treatment of step are all from stream treated state memory module interactive information, realize distributed coordination, ensure the consistence of stream Processing Cluster.
Described step (1) configures the extraction scope of data to be extracted and extracts strategy.
The file data of the data comprise electric power meter needed for described step (1) anomaly analysis and real time traffic data.
Each single abnormity diagnosis logic chain of described step (2) comprises a data-in logic block and some data process method blocks;
Described step (2): each single abnormity diagnosis theme generates a logic chain; Logic block includes process code and the ordinal relation of logic block operation. The event that comprises described multiple single abnormity diagnosis logic chain repeats to report diagnostic logic chain, electric energy table to stop walking diagnostic logic chain, electricity sampling open-phase diagnostic logic chain, requirement super appearance diagnostic logic chain etc.
Described step (3) is data-in logic block and data process method block configuration process task respectively.
Described step (3): measure the distribution of single abnormity diagnosis task and monitor stream work for the treatment of step, the single abnormality diagnostic distributed stream treating processes of metering is unified management and control;
Described step (3) sets up the heartbeat catalogue of single abnormity diagnosis logic chain, preserve the heartbeat message of all Processing tasks in this single abnormity diagnosis logic chain, the mapping relation of single abnormity diagnosis logic chain, data-in logic block and some data process method blocks and Processing tasks, heartbeat catalogue are stored in stream treated state memory module.
Each stream work for the treatment of node of described step (4) comprises one and guards module and some work modules.
Described step (1) metering anomaly analysis data acquisition step, according to configuration, periodically from power information acquisition system, extract single abnormity diagnosis business datum, comprise the data such as event, image data, instruction message and measuring apparatus archives, then the single abnormity diagnosis business datum extracted is carried out conversion process, ensure accuracy and the consistence of data, finally the analytical data after process is loaded in metering anomaly analysis database.
According to single abnormity diagnosis rule, analyze process logic wherein and data stream to relation, it is the process node that multiple logic is complete by rational for analysis process cutting, a data-in logic block and multiple data process method block is defined for every class rule, each logic block all comprises process code and the ordinal relation of logic block operation, thus generates complete single abnormity diagnosis logic chain. Wherein, data-in logic block comprises digital independent and encapsulation logic, for reading desired data and data are packaged into the form of a data block by date and measuring apparatus from metering anomaly analysis database; Data process method block comprises process logic, for according to the program processing data input logic block of configuration and the data block of preamble data process logic block input, order sequenced data process logic block exports intermediate result or exports net result backward.
Single abnormity diagnosis logic chain is submitted to stream processing controls step, after flowing the reception of processing controls step and single abnormity diagnosis logic chain being carried out necessary verification, the data-in logic block and the data process method block that it are comprised are analyzed, for each logic block configures one or more Processing tasks respectively, the mapping relation of formation logic block and Processing tasks, and set up the heartbeat catalogue of single abnormity diagnosis logic chain, for preserving the heartbeat message of all Processing tasks in this logic chain, by single abnormity diagnosis logic chain, the mapping relation of logic block and Processing tasks, heartbeat catalogue etc. is stored in stream treated state memory module.
Based on the online abnormity diagnostic system of electric power meter of stream process, comprising:
Metering anomaly analysis data acquisition module: data to be extracted in power information acquisition system are configured by the single abnormity diagnosis rule according to obtaining from metering abnormity diagnosis rule base, the data needed for anomaly analysis are obtained, stored in metering anomaly analysis database from the database of power information acquisition system;
Logic chain generation module: according to the multiple single abnormity diagnosis logic chain of single abnormity diagnosis generate rule;
Stream processing and control module: the single abnormity diagnosis logic chain that receive logic chain generation module is submitted to, single abnormity diagnosis logic chain is done serializing process, according to the logic block that serializing process produces, for single abnormity diagnosis logic chain allocation process task, and result is stored in stream treated state memory module; Also according to the load state information of each stream work for the treatment of node upgraded in stream treated state memory module, balanced to stream work for the treatment of peer distribution Processing tasks;
Stream work for the treatment of module: run the every Processing tasks in single abnormity diagnosis logic chain, the load state information of each stream work for the treatment of node being stored in real time flows in treated state memory module, complete the single abnormity diagnosis to electric power meter, it is achieved the parallel processing of multiple stream work for the treatment of node;
Abnormal relevant diagnosis module: on the basis of single abnormity diagnosis result, carry out further relevant diagnosis, generates metering abnormity diagnosis result and fortune dimension suggestion, and send is to power information acquisition system.
Described metering anomaly analysis data acquisition module, comprising:
Information extraction submodule block: extract anomaly analysis basic data from power information acquisition system;
Data transform subblock: obtain anomaly analysis basic data, process the data redundancy owing to communicative reasons causes and disappearance, remove redundant data, benefit calls missing data together, and undertaken merging, transforming and partition operation by the metering anomaly analysis data of extraction according to the single abnormity diagnosis business demand of metering, form the analytical data needed for anomaly analysis;
Data import submodule block: the analytical data needed for anomaly analysis is loaded in metering anomaly analysis database.
Anomaly analysis basic data comprises: the event information that the measuring apparatus such as electric energy table game clock lid event, SOT state of termination quantitative change position record are relevant, the data that the electric power meters such as active energy indicating value, powertrace collect, the steering order message that the acquisition systems such as expense control message issue to electric power meter, the measuring apparatus archives etc. such as user's contract capacity, maximum requirement.
Described stream work for the treatment of module, comprising:
Guard submodule block: from stream treated state memory module, obtain the logic block that all logic blocks and Processing tasks map relation, task matching table and stream work for the treatment of node and need to process, and be distributed to work submodule block; Monitor the heartbeat message of Processing tasks and the state of loading situation of stream work for the treatment of node simultaneously, it is stored in stream treated state memory module; Guarding submodule block adopts the mode of wheel inquiry to inquire about the information whether having renewal in stream treated state memory module, and upgrade in time local information.
Work submodule block: obtain the logic block flowing work for the treatment of node and need to processing from guarding submodule block, process code in operation logic block, and the ordinal relation run according to the logic block comprised in logic block sets up logic block and the connection of other work module, complete the real-time single anomaly analysis of electric power meter, generate single abnormity diagnosis result.
Described abnormal relevant diagnosis module, comprising:
Association matched sub-block: obtain single abnormity diagnosis result from stream work for the treatment of module, and carry out rule match according to obtaining abnormal relevant diagnosis model from metering abnormity diagnosis rule base, coupling adds up the relational degree between theme and theme obtaining existing association relation, and then draws the relevant diagnosis result of electric power meter;
Association analysis submodule block: obtain the relational degree between theme and theme that there is association relation from association matched sub-block, abnormal relevant diagnosis model is obtained from metering abnormity diagnosis rule base, multi-threaded abnormal association analysis is realized by association analysis algorithm, according to abnormal association analysis result, judge the state residing for electric power meter, and then take corresponding counter-measure.
Described metering abnormity diagnosis rule base, for the electric power meter abnormity diagnosis rule that concentrated storage extracts from the actual maintenance work of electric power meter, comprise the single abnormity diagnosis rule carrying out the single anomaly analysis of electric energy measuring equipment, and on single abnormity diagnosis rule-based approach, carry out abnormal relevant diagnosis model two portions of the abnormal relevant diagnosis of electric energy measuring equipment.
Described single abnormity diagnosis rule comprises diagnostic method, threshold levels, towards user, required data source with analyze the information such as frequency; Described abnormal relevant diagnosis model comprises the information such as relating subject, relational degree and on-the-spot fortune dimension suggestion.
Single abnormity diagnosis rule and abnormal relevant diagnosis model are all expressed as production rule by rule description language, and the production rule of generation represents the structure for If (condition) Then (behavior). Adopt the form of production rule to store, it is stored in metering abnormity diagnosis rule base.
Described metering anomaly analysis database, stores each item data and analytical results information that metering anomaly analysis data acquisition module extracts from power information acquisition system, provides analytical data basis to stream work for the treatment of module.
Described stream treated state memory module, at least comprise 3 memory nodes, for the information of storage flow processing and control module and stream work for the treatment of module, stream processing and control module and stream work for the treatment of module are all from stream treated state memory module interactive information, realize distributed coordination, ensure the consistence of stream Processing Cluster.
Described metering anomaly analysis data acquisition module configures the extraction scope of data to be extracted and extracts strategy.
The file data of the data comprise electric power meter needed for described metering anomaly analysis data acquisition module anomaly analysis and real time traffic data.
Each single abnormity diagnosis logic chain of described logic chain generation module comprises a data-in logic block and some data process method blocks;
Each single abnormity diagnosis theme of described logic chain generation module generates a logic chain; Logic block includes process code and the ordinal relation of logic block operation. The event that comprises described multiple single abnormity diagnosis logic chain repeats to report diagnostic logic chain, electric energy table to stop walking diagnostic logic chain, electricity sampling open-phase diagnostic logic chain, requirement super appearance diagnostic logic chain etc.
Described stream processing and control module is data-in logic block and data process method block configuration process task respectively.
Described stream processing and control module is measured the distribution of single abnormity diagnosis task and is monitored stream work for the treatment of module, and the single abnormality diagnostic distributed stream treating processes of metering is unified management and control;
Described stream processing and control module sets up the heartbeat catalogue of single abnormity diagnosis logic chain, preserve the heartbeat message of all Processing tasks in this single abnormity diagnosis logic chain, the mapping relation of single abnormity diagnosis logic chain, data-in logic block and some data process method blocks and Processing tasks, heartbeat catalogue are stored in stream treated state memory module.
Each stream work for the treatment of node of described stream work for the treatment of module comprises one and guards module and some work modules.
The heartbeat message guarding in its work module of module monitor in real time the Processing tasks run in each stream work for the treatment of node, comprise heart time, Runtime and Statistical information etc., for monitoring Processing tasks running condition, obtain the load state information of each stream work for the treatment of node simultaneously, all it is stored in the heartbeat catalogue of stream treated state memory module.
Stream processing and control module obtains the heartbeat message of each Processing tasks and the load state information of stream work for the treatment of node from stream treated state memory module, balanced to stream work for the treatment of peer distribution Processing tasks accordingly, form the task matching table of reflection Processing tasks and working node corresponding relation, and the task matching table write stream treated state memory module that will generate, if having new Processing tasks or Processing tasks time-out, upgrade task matching table.
Module of guarding in each stream work for the treatment of node obtains all logic blocks and Processing tasks mapping relation, task matching table from stream treated state memory module, statistics task matching table in be assigned in this node each work module Processing tasks, relation is mapped according to logic block and Processing tasks, from stream treated state memory module, obtain corresponding logic block again, and it is distributed to work module. Guarding module adopts the mode of wheel inquiry to inquire about the information whether having renewal in stream treated state memory module, and upgrade in time local information.
After work module receives the order startup guarding module, the logic block that need to process is obtained from guarding module, process code in operation logic block, and the ordinal relation run according to logic block sets up the connection with other work module, wherein data-in logic block constantly obtains analytical data, the data that data process method block flows into according to code process, output processing result backward from metering anomaly analysis database, finally complete real-time single abnormity diagnosis, generate single abnormity diagnosis result.
The invention has the beneficial effects as follows:
(1) the present invention is applied to electric power meter monitoring, and stream processes the real-time online abnormity diagnosis that thought is incorporated into electric power meter, it is to increase the real-time of metering on-line monitoring, reduces human cost;
(2) electric power meter abnormity diagnosis rule is separated by the present invention with diagnostic device system code, it may be achieved the flexible formulation of metering anomaly analysis, diagnosis rule and change, lifting system handiness, extensibility and maintainability.
(3) flowing tupe and have great advantage towards the process field of dynamic data, distributed stream process has the feature such as retractility, real-time, is reply this kind of real-time height, a kind of good tool of business processing demand that logicality is strong. Therefore, its business datum, on the basis of power information acquisition system, is analyzed by the present invention, adopts distributed stream process thought, designs a kind of online abnormity diagnostic system of electric power meter based on stream process and method, to support measuring apparatus monitoring business.
Accompanying drawing explanation
Fig. 1 is a kind of online abnormity diagnostic system of electric power meter based on stream process that the present invention proposes.
Embodiment
Below in conjunction with accompanying drawing and embodiment, the invention will be further described.
Fig. 1, being a kind of online abnormity diagnostic system of electric power meter based on stream process realized based on the present invention, this system comprises metering abnormity diagnosis rule base 1, metering anomaly analysis data acquisition module 2, metering anomaly analysis database 3, logic chain generation module 4, stream processing and control module 5, stream treated state memory module 6, stream work for the treatment of module 7, abnormal relevant diagnosis module 8; Described metering anomaly analysis data acquisition module 2 comprises information extraction module 201, data conversion module 202, Data import module 203; Described stream treated state memory module 6 at least to be comprised more than 3 memory nodes; Described stream work for the treatment of module 7 comprises n stream work for the treatment of node, and each node comprises guards module 701 and multiple work module 702; Described abnormal relevant diagnosis module 8 comprises association matching module 801 and association analysis module 802.
Metering abnormity diagnosis rule base 1, for the electric power meter abnormity diagnosis knowledge that concentrated storage is extracted from electric power meter actual fortune dimension experience by domain expert, comprise the single abnormity diagnosis knowledge carrying out the single anomaly analysis of electric energy measuring equipment, with the abnormal relevant diagnosis knowledge two portions carrying out the abnormal relevant diagnosis of electric energy measuring equipment on the former basis, single abnormity diagnosis knowledge comprises diagnostic method, threshold levels, towards user, the information such as required data source and analysis frequency, abnormal relevant diagnosis knowledge comprises relating subject, the information such as relational degree and on-the-spot fortune dimension suggestion. and it being expressed as a series of production rule by rule description language, the production rule of generation represents the structure for If (condition) Then (behavior).
Metering anomaly analysis data acquisition module 2, for mutual by interface and power information acquisition system, scope and strategy is extracted according to single abnormity diagnosis rule configuration data, file data and the real time traffic data of required electric power meter is obtained from power information acquisition system database, and these business datums are converted to the analytical data needed for anomaly analysis, stored in metering anomaly analysis database 3.
Described metering anomaly analysis data acquisition module 2 also comprises with lower module: information extraction module 201, for the extraction information based on configuration, pass through web Service interface, the multiple mode such as middleware extracts analytical data basis from power information acquisition system, comprise electric energy table game clock lid event, the event information that the measuring apparatus such as SOT state of termination quantitative change position record are relevant, active energy indicating value, the data that the electric power meters such as powertrace collect, the steering order message that the acquisition systems such as expense control message issue to electric power meter, user's contract capacity, the measuring apparatus archives etc. such as maximum requirement.
Data conversion module 202, for obtaining metering anomaly analysis raw data from information extraction module 201, process the data redundancy owing to communicative reasons causes and disappearance, remove redundant data, benefit calls missing data together, and undertaken the metering anomaly analysis data of extraction according to the single abnormity diagnosis business demand of metering merging, transform and the conversion operation such as partition, the analytical data of formation needed for anomaly analysis.
Data import module 203, for the Data import that processed by data conversion module 202 in metering anomaly analysis database 3.
Metering anomaly analysis database 3, for storing each item data and the analytical results information that metering anomaly analysis data acquisition module 2 extracts from power information acquisition system, there is provided analytical data basis to stream work for the treatment of module 7, adopt relevant database to store.
Logic chain generation module 4, for according to the multiple single abnormity diagnosis logic chain of single abnormity diagnosis generate rule, each single abnormity diagnosis theme generates a logic chain, repeats such as event to report the uneven diagnostic logic chain of diagnostic logic chain, electric energy representative value, electricity sampling open-phase diagnostic logic chain, requirement super appearance diagnostic logic chain etc. Each logic chain can comprise a data-in logic block and multiple data process method block, includes process code and the ordinal relation of logic block operation in logic block.
Stream processing and control module 5, for measuring the distribution of single abnormity diagnosis task and flow the monitoring of work for the treatment of module 7, unifies management and control to the single abnormality diagnostic distributed stream treating processes of metering. The single abnormity diagnosis logic chain that stream processing and control module receive logic chain generation module is submitted to, logic chain is done serializing, the data-in logic block and the data process method block that comprise for it configure one or more Processing tasks respectively, and set up the heartbeat catalogue of single abnormity diagnosis logic chain, preserve the heartbeat message of all Processing tasks in this logic chain, the mapping relation of single abnormity diagnosis logic chain, logic block and Processing tasks, heartbeat catalogue etc. are stored in stream treated state memory module 6. The heartbeat message of each Processing tasks is obtained from stream treated state memory module 6, and each load state information flowing work for the treatment of node in stream work for the treatment of module 7, balanced to stream work for the treatment of peer distribution Processing tasks on this basis, and the task matching table write stream treated state memory module 6 that will generate.
Stream treated state memory module 6, at least comprise the high availability that 3 memory nodes ensure this module, for storage flow processing and control module 5 and the status information and the configuration information that flow work for the treatment of module 7, such as the state etc. of the mapping relation of logic block, logic block and Processing tasks, task matching table, heartbeat message, stream work for the treatment of node, stream processing and control module 5 and stream module 7 of dealing with the work all communicates with this module 6 obtaining information, realize distributed coordination, ensure the consistence of stream Processing Cluster.
Stream work for the treatment of module 7, for every Processing tasks of running in single abnormity diagnosis logic chain to complete the single abnormity diagnosis to electric power meter, can realizing the parallel processing of multiple stream work for the treatment of node, each stream work for the treatment of node comprises one and guards module 701 and multiple work module 702.
Described stream work for the treatment of module 7 also comprises with lower module:
Guard module 701, for the work module managed on this stream work for the treatment of node, from stream treated state memory module 6, obtain the logic block that all logic blocks and Processing tasks map relation, task matching table and this node and need to process, and it is distributed to work module 702. Monitor the heartbeat message of Processing tasks and the state of loading situation of this node simultaneously, it is stored in stream treated state memory module 6. Guarding module 701 adopts the mode of wheel inquiry to inquire about the information whether having renewal in stream treated state memory module 6, and upgrade in time local information.
Work module 702, for obtaining, from guarding module 701, the logic block that need to process, process code in operation logic block, and according to logic block run ordinal relation (logic block can be understood as a code module, when numerous logic block runs, there is sequencing, what to be described here is exactly that all logic blocks are connected by the ordinal relation according to logic block, form a complete treatment scheme) set up the connection with other work module, complete the real-time single anomaly analysis of electric power meter, generate single abnormity diagnosis result.
Abnormal relevant diagnosis module 8, for the basis in single abnormity diagnosis result, carries out further relevant diagnosis, generates metering abnormity diagnosis result and transports dimension suggestion send to power information acquisition system.
Described abnormal relevant diagnosis module 8 also comprises with lower module:
Association matching module 801, for obtaining single abnormity diagnosis result from stream work for the treatment of module 7, add up the single abnormity diagnosis result of a certain electric power meter one day, and carry out rule match according to the abnormal relevant diagnosis model obtained from metering abnormity diagnosis rule base 1, coupling statistics can by relational degree between which theme association and theme, draw the relevant diagnosis result of this electric power meter of this day, as doubtful stealing, equipment failure etc. occur, and corresponding fortune dimension suggestion.
Association analysis module 802, for obtaining the relating subject after gathering and relational degree from association matching module 801, abnormal relevant diagnosis model is obtained from metering abnormity diagnosis rule base 1, multi-threaded abnormal association analysis is realized by association analysis algorithm, judge that this electric power meter is in and exception do not occur according to result, need to continue to pay close attention to, need auxiliary judgement and extremely make a definite diagnosis which kind of state in four kinds of states, and take corresponding counter-measure, wherein for needing auxiliary judgement and the abnormal electric power meter making a definite diagnosis two states, the relevant diagnosis result of this electric power meter obtained in association analysis module 801 and fortune dimension suggestion are encapsulated, form metering abnormity diagnosis result and the fortune dimension suggestion of this day all electric power meter, diagnostic result and fortune dimension suggestion are sent to power information acquisition system.
Stopping for electric energy table to walk this abnormity diagnosis theme, working process of the present invention is described below:
Steps A: domain expert stops to walk this single abnormal formulation and diagnoses rule for electric energy table, it is all users towards user, data source be freeze day positive/negative to active energy indicating value and tri-phase current day curve, analyzing frequency is one day, diagnostic method is: in electric energy table 2 day, the positive/negative difference to meritorious total electric energy indicating value equals 0 day, and monitors tri-phase current I in this periodA, IB, IC3 points are had to be greater than 0.1A mutually arbitrarily. Then electric energy table stops walking diagnosis Rule Expression and is:
By the above-mentioned single abnormity diagnosis rule taken out stored in metering abnormity diagnosis rule base 1.
And when carrying out multi-threaded abnormal association analysis, the abnormal relevant diagnosis model of employing comprises relating subject model, theme weights model, association analysis algorithm, result judge the parts such as interval.
The relating subject model stopping such as electric energy table to walk this theme relevant is as follows:
Can represent and be:
Definable all exception topic weights model is as follows:
The basis of relating subject model and exception topic weights model defines association analysis algorithm and carries out multi-threaded abnormal association analysis, following algorithm can be adopted:
Wherein n is simultaneous exception topic quantity, PiIt is the weights of i-th theme, PjkFor the relational degree of jth theme and kth theme.
Arranging result according to experience judges interval, can be defined as follows:
The relating subject model that takes out above-mentioned, theme weights model, association analysis algorithm, result judge interval etc. as abnormal relevant diagnosis model stored in measuring in abnormity diagnosis rule base 1.
Step B: according to the data source of all single abnormity diagnosis rule of steps A generation and frequency requirement, information extraction module 201 in configuration metering anomaly analysis data acquisition module 2, periodically extracts required single abnormity diagnosis business datum from power information acquisition system. For whether analysis exists electric energy table stop walking, configuration and obtained from power information acquisition system by middleware freeze all days that need to monitor electric power meter positive/negative to active energy indicating value and tri-phase current day curve data, cycle is once a day, is stored in metering anomaly analysis database 3.
Step C: stop walking diagnosis rule according to the electric energy table that steps A generates, formulates electric energy table and stops walking diagnostic logic chain, be 1 data-in logic block and 2 data process method blocks by its cutting:
Logic that what data-in logic block comprised realize for constantly read from metering anomaly analysis database 3 freeze day positive/negative to active energy indicating value and tri-phase current day curve, and according to by electric power meter, the positive/negative tri-phase current day curve number to active energy indicating value, the same day and first a day of freezing day before its same day and 2 days is encapsulated as data block, it is sent to data process method block 1;
What data process method block 1 comprised realizes logic is the data block receiving the transmission of data-in logic block, judge whether tri-phase current wherein has at least 3 points to be greater than 0.1A in totally 576 collection points, it is encapsulated as new data block by positive/negative for freezing day before the same day of the electric power meter satisfied condition and 2 days to active energy indicating value, it is sent to data process method block 2;
Logic that what data process method block 2 comprised realize is receive the data block that data process method block 1 sends, and calculates this day electric energy indicating value and the difference of electric energy indicating value before 2 days of this measuring apparatus, if 0 judges that this measuring apparatus occurs that electric energy table stops walking exception.
On this basis, write corresponding code wrap and enter data-in logic block and data process method block, form electric energy table and stop walking diagnostic logic chain.
Step D: electric energy table stops walk diagnostic logic chain and submits to stream processing and control module 5, stream processing and control module 5 receives and electric energy table stops walk diagnostic logic chain and carries out necessary verification, as whether whether this logic chain exist, can use.
Verify errorless after, the data-in logic block and the data process method block that it are comprised are analyzed, and are these 3 logic blocks configuration process tasks respectively, as shown in the table, the mapping relation of formation logic block and Processing tasks. The complexity of the Processing tasks of all metering anomaly analysis logic chains is not only considered in the configuration of Processing tasks, it is also contemplated that the number of the module 702 that works in stream work for the treatment of node.
| Electric energy table stops walking diagnostic logic block | Electric energy table stops walking diagnostic process task |
| Data-in logic block | Task1, Task2, Task3 |
| Data process method block 1 | Task4, Task5, Task6, Task7 |
| Data process method block 2 | Task8, Task9 |
Simultaneously, stop to walk diagnostic logic chain for electric energy table and set up heartbeat catalogue, for preserving the heartbeat message of all Processing tasks in this logic chain, the mapping relation of 3 logic block contents, logic block and Processing tasks, heartbeat catalogue etc. are stored in stream treated state memory module 6.
Step e: the heartbeat message guarding in its work module 702 of module 701 monitor in real time the Processing tasks run in each stream work for the treatment of node, comprise heart time, Runtime and Statistical information etc., obtain the load state information of each stream work for the treatment of node simultaneously, it is stored in the heartbeat catalogue of stream treated state memory module 6.
Step F: stream processing and control module 5 obtains the heartbeat message of each Processing tasks and the load state information of the stream work for the treatment of each node of module 7 from stream treated state memory module 6, balanced accordingly stop walking diagnostic process task to stream work for the treatment of peer distribution electric energy table, form the task matching table of reflection Processing tasks with work module 702 corresponding relation, as shown in the table, and the task matching table write stream treated state memory module 6 that will generate, if having new Processing tasks or Processing tasks time-out, upgrade task matching table.
| Electric energy table stops walking diagnostic process task | Work module |
| Task1 | Stream work for the treatment of node 1 works module 3 |
| Task2 | Stream work for the treatment of node 3 works module 1 |
| Task3 | Stream work for the treatment of node 2 works module 4 |
| ���� | ���� |
Step G: the module 701 of guarding in each stream work for the treatment of node obtains logic block and Processing tasks mapping relation, the task matching table that electric energy table stops walking diagnosis from stream treated state memory module 6, statistics task matching table in be assigned in this node each work module 702 Processing tasks, relation is mapped according to logic block and Processing tasks, from stream treated state memory module 6, obtain corresponding logic block again, and it is distributed to work module 702. Guarding module 701 adopts the mode of wheel inquiry to inquire about the information whether having renewal in stream treated state memory module 6, and upgrade in time local information.
Step H: after work module 702 receives the order startup guarding module 701, obtains the logic block that need to process, the process code in operation logic block from guarding module 701, and the ordinal relation run according to logic block sets up the connection with other work module.
Wherein, process data-in logic block work module from metering anomaly analysis database constantly read freeze day positive/negative to active energy indicating value and tri-phase current day curve, and according to by electric power meter, the positive/negative tri-phase current day curve number to active energy indicating value, the same day and first a day of freezing day before its same day and 2 days is encapsulated as the electric energy table on electric power meter same day is stopped walking diagnostic data block, find, according to the ordinal relation that logic block runs, the work module processing data process method block 1, set up data cube computation;
After the work module of process data process method block 1 and the work module processing data-in logic block connect, obtain packaged data block, judge whether tri-phase current 576 collection points wherein have at least 3 points to be greater than 0.1A, it is encapsulated as new data block to active energy indicating value by positive/negative for freezing day before the same day of the electric power meter satisfied condition and 2 days, find the work module of process data process method block 2, set up data cube computation;
The data block comprising electric energy indicating value that the work module of the work module reception process data process method block 1 of process data process method block 2 sends, calculate this day electric energy indicating value and the difference of electric energy indicating value before 2 days of this measuring apparatus, if 0 judges that this measuring apparatus occurs that electric energy table stops walking exception.
Step I: association matching module 801 obtains, from stream work for the treatment of module 7, the single abnormity diagnosis result produced, add up all single exception of this electric power meter appearance on the same day, assume that occurred that electric energy meter cover opening is abnormal stops walking exception with electric energy table simultaneously, then according to abnormal relevant diagnosis model, judging that this electric energy table occurs the probability of doubtful stealing to be 1.0, on-the-spot fortune dimension suggestion is for checking table cover and end button cover, reading electric energy representative value.
Step J: from association matching module 801, association analysis module 802 knows that the same day, this electric power meter occurred that electric energy meter cover opening and electric energy table stop walking 2 kinds of exceptions, may there is doubtful stealing in diagnosis, calculate this electric power meter by association analysis algorithm and occurred the same day E of doubtful stealing to be
Judge that this electric power meter is according to result and need auxiliary judgement state, need to auxiliary judgements such as curve datas, abnormal to power information acquisition system alarm to what confirm, and the relevant diagnosis result of this electric power meter obtained in association analysis module and fortune dimension suggestion are encapsulated, form metering abnormity diagnosis result and the fortune dimension suggestion of this day all electric power meter, it is sent to power information acquisition system.
By reference to the accompanying drawings the specific embodiment of the present invention is described although above-mentioned; but not limiting the scope of the invention; one of ordinary skill in the art should be understood that; on the basis of the technical scheme of the present invention, those skilled in the art do not need to pay various amendment or distortion that creative work can make still within protection scope of the present invention.
Claims (10)
1., based on the online abnormality diagnostic method of electric power meter of stream process, it is characterized in that, comprise the steps:
Step (1): metering anomaly analysis data acquisition step: data to be extracted in power information acquisition system are configured by the single abnormity diagnosis rule according to obtaining from metering abnormity diagnosis rule base, the data needed for anomaly analysis are obtained, stored in metering anomaly analysis database from the database of power information acquisition system;
Step (2): logic chain generation step: according to the multiple single abnormity diagnosis logic chain of single abnormity diagnosis generate rule;
Step (3): stream processing controls step: the single abnormity diagnosis logic chain that receive logic chain generation step is submitted to, single abnormity diagnosis logic chain is done serializing process, according to the logic block that serializing process produces, for single abnormity diagnosis logic chain allocation process task, and result is stored in stream treated state memory module; Also according to the load state information of each stream work for the treatment of node upgraded in stream treated state memory module, balanced to stream work for the treatment of peer distribution Processing tasks;
Step (4): stream work for the treatment of step: run the every Processing tasks in single abnormity diagnosis logic chain, the load state information of each stream work for the treatment of node being stored in real time flows in treated state memory module, complete the single abnormity diagnosis to electric power meter, it is achieved the parallel processing of multiple stream work for the treatment of node;
Step (5): abnormal relevant diagnosis step: on the basis of single abnormity diagnosis result, carry out further relevant diagnosis, generates metering abnormity diagnosis result and fortune dimension suggestion, and send is to power information acquisition system.
2. as claimed in claim 1 a kind of based on stream process the online abnormality diagnostic method of electric power meter, it is characterized in that,
Described metering anomaly analysis data acquisition step, comprising:
Information extraction sub-step: extract anomaly analysis basic data from power information acquisition system;
Data conversion sub-step: obtain anomaly analysis basic data, process the data redundancy owing to communicative reasons causes and disappearance, remove redundant data, benefit calls missing data together, and undertaken merging, transforming and partition operation by the metering anomaly analysis data of extraction according to the single abnormity diagnosis business demand of metering, form the analytical data needed for anomaly analysis;
Data import sub-step: the analytical data needed for anomaly analysis is loaded in metering anomaly analysis database.
3. as claimed in claim 1 a kind of based on stream process the online abnormality diagnostic method of electric power meter, it is characterized in that,
Described stream work for the treatment of step, comprising:
Guard sub-step: from stream treated state memory module, obtain the logic block that all logic blocks and Processing tasks map relation, task matching table and stream work for the treatment of node and need to process, and be distributed to work sub-step; Monitor the heartbeat message of Processing tasks and the state of loading situation of stream work for the treatment of node simultaneously, it is stored in stream treated state memory module; Guarding sub-step adopts the mode of wheel inquiry to inquire about the information whether having renewal in stream treated state memory module, and upgrade in time local information;
Work sub-step: obtain the logic block flowing work for the treatment of node and need to processing from guarding sub-step, process code in operation logic block, and the ordinal relation run according to logic block sets up logic block and the connection of other work module, complete the real-time single anomaly analysis of electric power meter, generate single abnormity diagnosis result.
4. as claimed in claim 1 a kind of based on stream process the online abnormality diagnostic method of electric power meter, it is characterized in that,
Described abnormal relevant diagnosis step, comprising:
Association coupling sub-step: obtain single abnormity diagnosis result from stream work for the treatment of step, and carry out rule match according to obtaining abnormal relevant diagnosis model from metering abnormity diagnosis rule base, coupling adds up the relational degree between theme and theme obtaining existing association relation, and then draws the relevant diagnosis result of electric power meter;
Association analysis sub-step: obtain the relational degree between theme and theme that there is association relation from association coupling sub-step, abnormal relevant diagnosis model is obtained from metering abnormity diagnosis rule base, multi-threaded abnormal association analysis is realized by association analysis algorithm, according to abnormal association analysis result, judge the state residing for electric power meter, and then take corresponding counter-measure.
5. as claimed in claim 1 a kind of based on stream process the online abnormality diagnostic method of electric power meter, it is characterized in that,
Described metering abnormity diagnosis rule base, for the electric power meter abnormity diagnosis rule that concentrated storage extracts from the actual maintenance work of electric power meter, comprise the single abnormity diagnosis rule carrying out the single anomaly analysis of electric energy measuring equipment, and on single abnormity diagnosis rule-based approach, carry out abnormal relevant diagnosis model two portions of the abnormal relevant diagnosis of electric energy measuring equipment;
Described metering anomaly analysis database, stores each item data and analytical results information that metering anomaly analysis data acquisition step extracts from power information acquisition system, provides analytical data basis to stream work for the treatment of step;
Described stream treated state memory module, at least comprise 3 memory nodes, for the information of storage flow processing controls step and stream work for the treatment of step, stream processing controls step and stream work for the treatment of step are all from stream treated state memory module interactive information, realize distributed coordination, ensure the consistence of stream Processing Cluster.
6., based on the online abnormity diagnostic system of electric power meter of stream process, it is characterized in that, comprising:
Metering anomaly analysis data acquisition module: data to be extracted in power information acquisition system are configured by the single abnormity diagnosis rule according to obtaining from metering abnormity diagnosis rule base, the data needed for anomaly analysis are obtained, stored in metering anomaly analysis database from the database of power information acquisition system;
Logic chain generation module: according to the multiple single abnormity diagnosis logic chain of single abnormity diagnosis generate rule;
Stream processing and control module: the single abnormity diagnosis logic chain that receive logic chain generation module is submitted to, single abnormity diagnosis logic chain is done serializing process, according to the logic block that serializing process produces, for single abnormity diagnosis logic chain allocation process task, and result is stored in stream treated state memory module; Also according to the load state information of each stream work for the treatment of node upgraded in stream treated state memory module, balanced to stream work for the treatment of peer distribution Processing tasks;
Stream work for the treatment of module: run the every Processing tasks in single abnormity diagnosis logic chain, the load state information of each stream work for the treatment of node being stored in real time flows in treated state memory module, complete the single abnormity diagnosis to electric power meter, it is achieved the parallel processing of multiple stream work for the treatment of node;
Abnormal relevant diagnosis module: on the basis of single abnormity diagnosis result, carry out further relevant diagnosis, generates metering abnormity diagnosis result and fortune dimension suggestion, and send is to power information acquisition system.
7. as claimed in claim 6 a kind of based on stream process the online abnormity diagnostic system of electric power meter, it is characterized in that,
Described metering anomaly analysis data acquisition module, comprising:
Information extraction submodule block: extract anomaly analysis basic data from power information acquisition system;
Data transform subblock: obtain anomaly analysis basic data, process the data redundancy owing to communicative reasons causes and disappearance, remove redundant data, benefit calls missing data together, and undertaken merging, transforming and partition operation by the metering anomaly analysis data of extraction according to the single abnormity diagnosis business demand of metering, form the analytical data needed for anomaly analysis;
Data import submodule block: the analytical data needed for anomaly analysis is loaded in metering anomaly analysis database.
8. as claimed in claim 6 a kind of based on stream process the online abnormity diagnostic system of electric power meter, it is characterized in that,
Described stream work for the treatment of module, comprising:
Guard submodule block: from stream treated state memory module, obtain the logic block that all logic blocks and Processing tasks map relation, task matching table and stream work for the treatment of node and need to process, and be distributed to work submodule block; Monitor the heartbeat message of Processing tasks and the state of loading situation of stream work for the treatment of node simultaneously, it is stored in stream treated state memory module; Guarding submodule block adopts the mode of wheel inquiry to inquire about the information whether having renewal in stream treated state memory module, and upgrade in time local information;
Work submodule block: obtain the logic block flowing work for the treatment of node and need to processing from guarding submodule block, process code in operation logic block, and the ordinal relation run according to the logic block comprised in logic block sets up logic block and the connection of other work module, complete the real-time single anomaly analysis of electric power meter, generate single abnormity diagnosis result.
9. as claimed in claim 6 a kind of based on stream process the online abnormity diagnostic system of electric power meter, it is characterized in that,
Described abnormal relevant diagnosis module, comprising:
Association matched sub-block: obtain single abnormity diagnosis result from stream work for the treatment of module, and carry out rule match according to obtaining abnormal relevant diagnosis model from metering abnormity diagnosis rule base, coupling adds up the relational degree between theme and theme obtaining existing association relation, and then draws the relevant diagnosis result of electric power meter;
Association analysis submodule block: obtain the relational degree between theme and theme that there is association relation from association matched sub-block, abnormal relevant diagnosis model is obtained from metering abnormity diagnosis rule base, multi-threaded abnormal association analysis is realized by association analysis algorithm, according to abnormal association analysis result, judge the state residing for electric power meter, and then take corresponding counter-measure.
10. as claimed in claim 6 a kind of based on stream process the online abnormity diagnostic system of electric power meter, it is characterized in that,
Described metering abnormity diagnosis rule base, for the electric power meter abnormity diagnosis rule that concentrated storage extracts from the actual maintenance work of electric power meter, comprise the single abnormity diagnosis rule carrying out the single anomaly analysis of electric energy measuring equipment, and on single abnormity diagnosis rule-based approach, carry out abnormal relevant diagnosis model two portions of the abnormal relevant diagnosis of electric energy measuring equipment;
Described metering anomaly analysis database, stores each item data and analytical results information that metering anomaly analysis data acquisition module extracts from power information acquisition system, provides analytical data basis to stream work for the treatment of module;
Described stream treated state memory module, at least comprise 3 memory nodes, for the information of storage flow processing and control module and stream work for the treatment of module, stream processing and control module and stream work for the treatment of module are all from stream treated state memory module interactive information, realize distributed coordination, ensure the consistence of stream Processing Cluster.
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