CN106228246A - Based on semantic unattended duty transformer substation monitoring system and method - Google Patents
Based on semantic unattended duty transformer substation monitoring system and method Download PDFInfo
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- CN106228246A CN106228246A CN201610561767.0A CN201610561767A CN106228246A CN 106228246 A CN106228246 A CN 106228246A CN 201610561767 A CN201610561767 A CN 201610561767A CN 106228246 A CN106228246 A CN 106228246A
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- G06N5/04—Inference or reasoning models
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- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B23/00—Testing or monitoring of control systems or parts thereof
- G05B23/02—Electric testing or monitoring
- G05B23/0205—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults
- G05B23/0218—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterised by the fault detection method dealing with either existing or incipient faults
- G05B23/0224—Process history based detection method, e.g. whereby history implies the availability of large amounts of data
- G05B23/0227—Qualitative history assessment, whereby the type of data acted upon, e.g. waveforms, images or patterns, is not relevant, e.g. rule based assessment; if-then decisions
- G05B23/0229—Qualitative history assessment, whereby the type of data acted upon, e.g. waveforms, images or patterns, is not relevant, e.g. rule based assessment; if-then decisions knowledge based, e.g. expert systems; genetic algorithms
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Abstract
The invention discloses based on semantic unattended duty transformer substation monitoring system and method, based on semantic reasoning technology, the data of multi-Substation carry out convergence analysis, rule of thumb the semantic rule of model extraction sets up Ontology, trains semantic rule storehouse.Carried out the semantic reasoning of data by expert knowledge library and semantic rule storehouse simultaneously, can accurately analyze and predict power equipment situation, immediately give power equipment aging early warning, and continuous complete semantic rule storehouse during data collection so that early warning precision improves constantly.
Description
Technical field
The invention belongs to a kind of transformer substation monitoring system field, especially relate to based on semantic unattended duty transformer station prison
Examining system and method.
Background technology
In May, 2009, national grid proposed to build the developing goal of strong intelligent grid, ended 2015, and newly-built intelligence becomes
Power station has reached 5182, the most progressively starts to move towards present digital intelligent from analog protection circuit in transformer station's development.
Comparing tradition transformer station to gather resource and repeat and design complexity, information is nonstandard lack of standardization, intelligent substation be then use advanced,
Reliably, integrated, low-carbon (LC), the smart machine of environmental protection, with information digitalization of entirely standing, communications platform networking, information sharing standardization
For basic demand, it is automatically performed information gathering, measures, control, protect, measure and the basic function such as monitoring, and can be as required
The senior kinetic energy such as support electrical network automatically controls in real time, Intelligent adjustment, on-line analysis decision-making, collaborative interaction, it is achieved with adjacent power transformation
Stand, transformer station that dispatching of power netwoks etc. is interactive.The monitoring means of transformer station are the most diversified, and unattended duty becomes one of them especially
Popular research topic, it greatly reduces the danger in artificial monitoring on the spot.But the intelligent power transformation at unattended duty
Stand the information island how broken through between each transformer station, it is achieved comprehensive analyses based on big data are never solved
Certainly.
Summary of the invention
Goal of the invention: the present invention is directed to existing unattended duty detecting system, proposes a kind of based on semantic unattended duty
Electrical substation monitoring specialist system, uses semantic technology to realize reasoning and obtains Condition Prediction of Equipment more accurately.
Summary of the invention: a kind of based on semantic unattended duty electrical substation monitoring method, comprises the following steps that
Step 1: collect status of electric power data by electric apparatus monitoring device, according to the attribute number of distinct device
According to preservation；
Step 2: determined scope and the object of domain body by status of electric power early warning knowledge base, and select body
Formal description language describes and represents；
Step 3: set up field of electrical equipment status predication ontological relationship Empirical Mode according to the data that domain expert storehouse provides
Type；
Step 4: set up field of electrical equipment body based on OWL mould according to the ontological relationship empirical model of step 3 prediction
Type；
Step 5: the rule of inference provided according to predicted condition and ontological relationship empirical model, utilizes Jena inference engine institute
The inference machine engine constituted carries out semantic reasoning, is predicted the outcome；
Step 6: connect database-driven, creates data base and connects example, connect data base by servlet；
Step 7: mobile client accesses servlet, and the data obtained are converted in servlet Json data lattice
Formula returns to mobile client.
A kind of based on semantic unattended duty transformer substation monitoring system, set including mobile client, query parser, electric power
Standby status early warning knowledge base, ontology library, inference machine engine, status of electric power early warning knowledge base is used for storing power equipment electric power
Data and resolving and the predicting the outcome of reasoning；Query parser is for analyzing the structure of power equipment electric power data, and therefrom
Extracted valid data；Ontology library is for storing status of electric power ontology model and relevant instance data；Inference machine engine is used
In body is carried out information inference, draw prediction conclusion.
Beneficial effect: the data of multi-Substation, based on semantic reasoning technology, are carried out convergence analysis, rule of thumb by the present invention
The semantic rule of model extraction sets up Ontology, trains semantic rule storehouse.Simultaneously by expert knowledge library and semantic rule
Storehouse carries out the semantic reasoning of data, it is possible to accurately analyzes and prediction power equipment situation, immediately gives power equipment old
Change early warning, and continuous complete semantic rule storehouse during data collection so that early warning precision improves constantly.With existing
Technology is compared and be present invention have the advantage that
(1) present invention can compatible existing SCADA data, use multi-Substation bottom data gather framework, abolish
Original each substation data information island, it is achieved information interconnection and sharing；
(2) semanteme is combined by the present invention with inference technology, it is possible to achieve the fusion of multi-source heterogeneous data, sets for electric power
Standby data semantic Inference Forecast, can solve the accuracy problem to monitoring of tools in unattended duty, it is provided that accurate data
Prediction, it is achieved the ageing equipment early warning in the transformer station of unattended duty；
(3) present invention is monitoring specialist system based on multi-Substation, compares the unit monitorings such as more existing SCADA and is
System, it is possible to the utilization rate of data be greatly promoted, it is achieved a system, multiple platforms use, are derived from more significant figure
According to；
(4) Condition Prediction of Equipment of the present invention uses semantic technology, sets up expertise model, is semantic by model conversion
Rule, semantic rule storehouse based on multi-Substation training, along with being continuously increased of data volume, rule base more complete can be made
Standby, the prediction of data more accurate；
(5) Android interface of the present invention visualization display makes user inquire about the most easily and extract data, for becoming
Power management personnel provide the most hand-held management platform.
Accompanying drawing explanation
Fig. 1 is present system schematic diagram；
Fig. 2 be Ontology of the present invention set up frame diagram；
Fig. 3 is the frame diagram of the present invention.
Detailed description of the invention
Below in conjunction with accompanying drawing, the case study on implementation of the present invention is described in detail；
As it is shown in figure 1, whole frame diagram based on semantic unattended duty electrical substation monitoring specialist system, by Android
Mobile client, query parser, status of electric power early warning knowledge base, ontology library, inference machine engine are constituted.
Status of electric power early warning knowledge base stores common electric power data and resolves and the predicting the outcome of reasoning；Inquiry
Resolver mainly be responsible for analyze power equipment electric power data structure, and therefrom extract in valid data；Ontology library is mainly used in
Store status of electric power ontology model and relevant instance data.Inference machine engine includes Jena inference engine and other reasonings
Engine, is responsible for body is carried out information inference, draws prediction conclusion.
As in figure 2 it is shown, the Ontology of the present invention sets up frame diagram.Setting up of this body uses the method for seven footworks to build
Vertical, (1) determines that the professional field of Ontology and category (2) consider that the probability (3) of the existing Ontology of multiplexing lists semanteme
Important terms (4) definition class (Class) and the attribute (6) of hierarchical system (Hierarchy) (5) the definition class of class in body are fixed
The restriction (7) of justice attribute creates example.Finally use prolog to write rule of inference, then use SPARQL query language to test
Card ontology construct whether reasonability.
As it is shown on figure 3, the frame diagram of the present invention.The data base that Jena currently supports have PostgreSQL, Mysql and
Oracle.First have to connect database-driven, and create DBConnection example.When ontology file persistent storage is to data
Behind storehouse, it can be made inferences inquiry.Major prognostic rule and the rule of inference of expertise knowledge base definition, use Jena work
Tool bag carries out semantic reasoning, is predicted the outcome, then output client display interface.
Step is as follows:
Step 1.: collect relevant status of electric power data by electric apparatus monitoring device, according to the genus of distinct device
Property carries out data preservation；
Step 2.: determine scope and the object of domain body, selects bulk form to describe language and describes and represent；
Step 3: the data and the experience that provide according to domain expert storehouse set up field of electrical equipment status predication ontological relationship
Empirical model；
Step 4: set up field of electrical equipment OWL (Web Ontology Language, net according to the empirical model of step 3
Network Ontology Language) ontology model；
Step 5: the rule of inference provided according to predicted condition and empirical model, (Jena is one to utilize Jena instrument
The API of java, is used for supporting the relevant application of semantic net) bag carries out semantic reasoning, predicted the outcome；
Step 6: connect database-driven, creates data base and connects example, use servlet (servlet full name Java
Servlet, is with the server of written in Java) technology data base；
Step 7: design Android client, accesses servlet, and the data obtained is converted in servlet
Json data form returns to Android client display interface.
Big for semanteme data reasoning technology is introduced in transformer substation system by the present invention.Use based on meta-model semanteme skill
Art, and realize a kind of specialist system centered by expert knowledge library, based on multi-Substation data sharing, by different substation
The huge data that power equipment is returned carry out rule analysis, carry out equipment state analysis accurately by specialist system, improve
The utilization ratio of data, improves accuracy rate and the precision of Condition Prediction of Equipment, it is possible to preferably navigates to some problem or is
Will appear from the equipment of problem, reduce the difficulty of Traditional Man investigation, also reduce the cost of part replacement, for realizing with nothing
Supervisory control of substation centered by people's post provides preferably support.
Claims (2)
1. a unattended duty electrical substation monitoring method based on semanteme, it is characterised in that comprise the following steps that
Step 1: collect status of electric power data by electric apparatus monitoring device, carry out data guarantor according to the attribute of distinct device
Deposit；
Step 2: determined scope and the object of domain body by status of electric power early warning knowledge base, and select bulk form
Change description language describe and represent；
Step 3: set up field of electrical equipment status predication ontological relationship empirical model according to the data that domain expert storehouse provides；
Step 4: set up field of electrical equipment based on OWL ontology model according to the ontological relationship empirical model of step 3 prediction；
Step 5: the rule of inference provided according to predicted condition and ontological relationship empirical model, utilizes Jena inference engine to be constituted
Inference machine engine carry out semantic reasoning, predicted the outcome；
Step 6: connect database-driven, creates data base and connects example, connect data base by servlet；
Step 7: mobile client accesses servlet, and the data obtained are converted in servlet Json data form return
Back to mobile client.
2. a unattended duty transformer substation monitoring system based on semanteme, it is characterised in that include that mobile client, inquiry resolve
Device, status of electric power early warning knowledge base, ontology library, inference machine engine, status of electric power early warning knowledge base is used for storing electricity
Power electric power of equipment data and resolving and the predicting the outcome of reasoning；Query parser is for analyzing the knot of power equipment electric power data
Structure, and therefrom extracted valid data；Ontology library is for storing status of electric power ontology model and relevant instance data；Reasoning
Power traction is held up for body is carried out information inference, draws prediction conclusion.
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Cited By (5)
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| CN107480208A (en) * | 2017-07-26 | 2017-12-15 | 广州供电局有限公司 | Multi-source electric power data method for amalgamation processing and device |
| CN107680195A (en) * | 2017-11-13 | 2018-02-09 | 国网内蒙古东部电力有限公司 | A kind of transformer station intelligent robot inspection Computer Aided Analysis System and method |
| CN110531742A (en) * | 2019-09-16 | 2019-12-03 | 重庆华能水电设备制造有限公司 | A kind of generator current collecting equipment real time monitoring and method for diagnosing faults |
| CN111178603A (en) * | 2019-12-19 | 2020-05-19 | 重庆邮电大学 | Semantic-based industrial production equipment predictive maintenance system |
| CN111752980A (en) * | 2020-07-01 | 2020-10-09 | 浪潮云信息技术股份公司 | Law enforcement supervision intelligent early warning system and method |
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| CN111178603A (en) * | 2019-12-19 | 2020-05-19 | 重庆邮电大学 | Semantic-based industrial production equipment predictive maintenance system |
| CN111752980A (en) * | 2020-07-01 | 2020-10-09 | 浪潮云信息技术股份公司 | Law enforcement supervision intelligent early warning system and method |
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