CN104283318A - Power equipment integrated monitoring and early warning system based on big data and analysis method thereof - Google Patents
Power equipment integrated monitoring and early warning system based on big data and analysis method thereof Download PDFInfo
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- CN104283318A CN104283318A CN201410579501.XA CN201410579501A CN104283318A CN 104283318 A CN104283318 A CN 104283318A CN 201410579501 A CN201410579501 A CN 201410579501A CN 104283318 A CN104283318 A CN 104283318A
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02B—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO BUILDINGS, e.g. HOUSING, HOUSE APPLIANCES OR RELATED END-USER APPLICATIONS
- Y02B70/00—Technologies for an efficient end-user side electric power management and consumption
- Y02B70/30—Systems integrating technologies related to power network operation and communication or information technologies for improving the carbon footprint of the management of residential or tertiary loads, i.e. smart grids as climate change mitigation technology in the buildings sector, including also the last stages of power distribution and the control, monitoring or operating management systems at local level
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
- Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
- Y04S20/00—Management or operation of end-user stationary applications or the last stages of power distribution; Controlling, monitoring or operating thereof
- Y04S20/20—End-user application control systems
- Y04S20/242—Home appliances
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Abstract
The invention discloses a power equipment integrated monitoring and early warning system based on big data and an analysis method of the power equipment integrated monitoring and early warning system. The system comprises a sensor group, a monitoring unit group and a power equipment integrated diagnosis platform, wherein the sensor group comprises multiple sensors used for obtaining monitoring parameters of a coupling transformer, a power cable and a GIS; the monitoring unit group comprises monitoring units used for monitoring the monitoring parameters of the coupling transformer, the power cable and the GIS, and each monitoring unit is connected with the corresponding sensor; the power equipment integrated diagnosis platform is connected with the monitoring unit group and used for achieving storage and management of multi-target power equipment monitoring data based on an HDFS, diagnosis based on the MapReduce technology and a fault sample bank, and real-time storage of monitoring index quantity and diagnosis results based on the NoSQL database technology; through a high-speed two-way data transmission mechanism, uploading of mass data monitored by multi-target power equipment in real time to a monitoring center is achieved on one hand, and feedback and early warning of the diagnosis results are achieved on the other hand.
Description
Technical field
The present invention relates to electrical equipment online supervision technical field, particularly relate to a kind of electric power apparatus integrated monitoring index system system based on large data and analytical method thereof.
Background technology
In recent years, along with global energy problem is increasingly serious, the research work of intelligent grid has all been carried out in countries in the world.The final goal of intelligent grid turns into cover the whole production process of electric power system, comprises the panorama real-time system of multiple links such as generating, transmission of electricity, power transformation, distribution, electricity consumption and scheduling.Power equipment state monitoring and diagnosis are the important component parts of intelligent grid, the power supply reliability of the enforcement energy extension device useful life of its key technology, the generation reducing catastrophic discontinuityfailure, raising power equipment, is therefore widely used in electric power system.
But the impact of the factor such as diversity, the diversity of power equipment monitor signal, the diversity of electrical equipment fault generation development law due to power equipment, the status monitoring of power equipment also exists the shortcoming of diagnosis and warning function deficiency, and this constrains all-round popularization and the application of power equipment state monitoring technology greatly.
Electrical equipment online supervision data increase in real time, add monitoring system and generally comprise multiple power equipment, different power equipment monitoring index is various, therefore for the on-line monitoring of power equipment, its Monitoring Data amount is very big, Monitoring Data is of a great variety, Monitoring Data produces speed and is exceedingly fast, typical large data, therefore the large data critical technology of forefront is applied on the monitoring and diagnosis of power equipment by the present invention, the development of power equipment state monitoring and diagnostic techniques will be promoted greatly, to the accuracy and the reliability that improve power equipment monitoring and diagnosis, there is revolutionary meaning.
Based on the power transmission and transformation equipment state monitoring system of large data, can well solve in the condition monitoring and diagnosis of power equipment the intrinsic difficult problem existed, be the important means realizing power transmission and transformation equipment state overhauling management, promote electrical production operational management lean level.Its general principle realizes the real-time perception of power equipment running status, analyzing and diagnosing and evaluation prediction by various sensor technology, wide-area communication and the information processing technology, and it is built and popularization has positive and profound significance to lifting electrical network intelligent level.
Summary of the invention
The present invention, in order to solve the problem, proposes a kind of electric power apparatus integrated monitoring index system system based on large data and analytical method thereof, and this system may be used for transformer, power cable, the comprehensive monitoring of GIS and failure diagnosis.
To achieve these goals, the present invention adopts following technical scheme:
Based on an electric power apparatus integrated monitoring index system system for large data, comprise transducer group, monitoring means group and electric power apparatus integrated diagnostic platform, wherein:
Described transducer group, comprises multiple transducers of the monitoring parameter for coupling transformer, power cable, GIS;
Described monitoring means group, comprise the monitoring means of monitoring parameter of monitoring coupling transformer, power cable, GIS, each monitoring means connects with corresponding transducer respectively;
Described electric power apparatus integrated diagnostic platform, connect monitoring means group, for realizing the storage and management of the multiple target power equipment Monitoring Data based on HDFS, realize based on MapReduce technology and fault sample storehouse diagnosis and realize based on the monitoring index amount of NoSQL database technology and the real-time storage of diagnostic result.
Diagnostic result is fed back to each now monitoring means, alert status of updating the equipment by bidirectional data transfers mechanism by described electric power apparatus integrated diagnostic platform.
Described electric power apparatus integrated diagnostic platform, comprise algorithmic dispatching module, task management module and dispatching and monitoring module, wherein algorithmic dispatching module is used for the scheduling of different monitoring equipment diagnostic analysis method and apolegamy, task management module is used for the dispatching management to data communication, data analysis, data store tasks, and the effect of dispatching and monitoring module is to carry out monitoring and management to the execution flow process of task management module.
The data of described electric power apparatus integrated diagnostic platform comprise equipment on-line monitoring data and equipment off-line status data; Described equipment off-line status data comprises equipment operation condition historical record, device history failure logging, unit type, device fabrication producer, the failure logging of same model equipment and device history experimental data.
Described monitoring means group at least comprises GIS monitoring means, cable monitoring unit and transformer monitoring unit.
The relevant monitoring parameter of described monitoring means group to GIS, power cable and transformer carries out continuous acquisition and analysis, and provides diagnosis and early warning result, at the traffic light system advanced warning grade now by different colours.
Based on an analytical method for above-mentioned electric power apparatus integrated monitoring index system system, concrete steps are as follows:
(1) GIS monitoring means, cable monitoring unit carry out continuous acquisition and analysis to the relevant monitoring parameter of GIS, power cable and transformer respectively to transformer monitoring unit, and provide diagnosis and early warning result in real time, at the traffic light system advanced warning grade now by different colours;
(2) initial data of monitoring means imported into the electric power apparatus integrated diagnostic platform based on large data by bidirectional data transfers mechanism at a high speed;
(3) equipment Real-time Monitoring Data and equipment off-line status data are managed concentratedly;
(4) equipment on-line monitoring data and equipment off-line status data are by the device status data parallel processing system (PPS) based on MapReduce, real-time Precise Diagnosis is carried out to equipment state, obtain corresponding diagnostic result, and early warning information is fed back to existing stratum in time by bidirectional data transfers mechanism at a high speed;
(5) if diagnostic result is for there being fault, then give a warning information; Now monitoring means is after receiving the feedback based on the comprehensive diagnos platform of large data, upgrades early warning signal now.
The concrete grammar of described step (1) is: utilize multiple method monitoring parameter, if the equal fault-free of the result of multiple method occurs, then system attonity, continues monitoring; Measured result has been fault and has occurred, and now can determine that fault enters the failure diagnosis stage; Measured result is inconsistent enters the data fusion stage, using its Output rusults as criterion.
In described step (1), when monitoring the partial discharge of transformer, use hyperfrequency method, ultrasonic method and oil colours spectrometry.
In described step (2), the storage adopt magnanimity original sampling data and management method, comprise following two:
(2-1) the real time mass initial data of monitoring multiple power equipment adopts the memory technology based on the data of HDFS to store, and supports that quick, magnanimity, high scalability data store and inquiry;
(2-2) data processing method based on MapReduce technology is adopted to magnanimity monitoring initial data and equipment off-line status data, realize the real-time process to the large data of monitoring, thus realize the real-time Accurate Diagnosis to equipment health status.
In described step (4), the method for diagnosis comprises:
(4-1) to the same monitoring index amount that multiple power equipment is monitored, by the dependency relation analysis of large data, the parameter attribute of contrast distinct device Monitoring Data under synchronization, same event, judge the position that fault occurs, provide diagnostic result, and to the diagnostic result of other power equipments revise '
(4-2) to the data of same monitoring index under different sensing mode of same monitoring equipment, on this comprehensive monitoring and diagnostic platform, by the fusion of the multi-source heterogeneous data of large data, carry out comprehensive Analysis and judgments, provide diagnostic result;
(4-3) to the real time data of same monitoring equipment, in conjunction with the fault sample storehouse of monitoring historical data, same model equipment, carry out the multidimensional of whole sample, real time contrast, provide diagnosis.
Beneficial effect of the present invention is: the electric power apparatus integrated monitoring index system system based on large data that the present invention proposes, by the large data critical technology in forward position and electrical equipment online supervision technology are organically combined, solve the storage of magnanimity Monitoring Data, the real-time analysis of magnanimity Monitoring Data, the real-time diagnosis of magnanimity Monitoring Data etc. power equipment monitoring field a difficult problem.By bidirectional data transfers mechanism at a high speed, achieve multiple target power equipment Real-Time Monitoring mass data uploading to monitoring center on the one hand, achieve the feedback early warning of diagnostic result on the other hand.By the analytical method of the multisource data fusion of large data technique, comprehensive analysis and judgement, full Sample Storehouse contrast, greatly improve the accuracy of power equipment real-time diagnosis and evaluation.
Accompanying drawing explanation
Fig. 1 is that the present invention forms schematic diagram;
Fig. 2 is the composition schematic diagram based on the electric power apparatus integrated diagnostic platform of large data in the present invention;
Fig. 3 is overall flowchart of the present invention;
Fig. 4 is multi-source heterogeneous data fusion based on large data analysis and diagnostic flow chart;
Fig. 5 is transformer, GIS, power cable partial discharge comprehensive monitoring flow chart based on large data analysis.
Wherein in Fig. 1: 1-UHF partial discharge monitoring point, 2-SF6 gas density monitoring point, the micro-water monitoring point of 3-, 4-oxygen concentration monitoring point, 5-servomotor stroke monitoring point, 6-A phase optical fiber temperature-measurement monitoring point, 7-B phase optical fiber temperature-measurement monitoring point, 8-C phase optical fiber temperature-measurement monitoring point, 9-A phase partial discharge monitoring point, 10-B phase partial discharge monitoring point, 11-C phase partial discharge monitoring point, 12-A phase earth current monitoring point, 13-B phase earth current monitoring point, 14-C phase earth current monitoring point, 15-oil chromatography monitoring point, 16-UHF partial discharge monitoring point, 17-ultrasonic wave partial discharge monitoring point.
Embodiment:
Below in conjunction with accompanying drawing and embodiment, the invention will be further described.
A kind of electric power apparatus integrated monitoring index system system based on large data, comprise the transducer of the every monitoring parameter for coupling transformer, power cable, GIS, transducer corresponding to each equipment is connected with the monitoring means of each equipment respectively, the monitoring means of GIS, transformer, power cable is connected with the electric power apparatus integrated diagnostic platform based on large data by bidirectional data transfers mechanism at a high speed, realizes the storage and management based on the multiple target power equipment magnanimity Monitoring Data of HDFS by this platform; Realize the diagnosis based on MapReduce technology and magnanimity fault sample storehouse; Realize based on the monitoring index amount of NoSQL database technology and the real-time storage of diagnostic result; The Data Multimedia Visualization realizing monitoring result is issued, and diagnostic result is fed back to each now monitoring means, alert status function of updating the equipment by bidirectional data transfers mechanism at a high speed.
As a preferred embodiment of the present invention, based on electric power apparatus integrated monitoring index system system and the analytical method of large data, comprise the following steps:
(1) GIS monitoring means, cable monitoring unit carry out continuous acquisition and analysis to the relevant monitoring parameter of GIS, power cable and transformer respectively to transformer monitoring unit, and provide diagnosis and early warning result, at the traffic light system advanced warning grade now by different colours.
(2) initial data of monitoring means uploaded to the electric power apparatus integrated diagnostic platform based on large data by bidirectional data transfers mechanism at a high speed.
(3) by based on the electric equipment diagnosis platform of large data, realize that the large data of monitoring store, monitor that large data calculate, monitor large data analysis, result issues and the function such as feedback.
As a preferred embodiment of the present invention, based on the electric power apparatus integrated monitoring index system system of large data, it is characterized in that:
(1) packet based on the electric equipment diagnosis platform of large data contains equipment on-line monitoring data and equipment off-line status data.Equipment off-line status data comprises the failure logging, device history experimental data etc. of equipment operation condition historical record, device history failure logging, unit type, device fabrication producer, same model equipment.
(2) equipment on-line monitoring data and equipment off-line status data are by functional modules such as task scheduling, task management, Mission Monitors and manage concentratedly based on the Mass Data Management system module of the HDFS increased income.
(3) equipment on-line monitoring data and equipment off-line status data are by the parallel data processing module based on MapReduce, obtain equipment health status diagnostic result, and early warning information is fed back to existing ground monitoring means by bidirectional data transfers mechanism at a high speed.
(4) monitoring means, after receiving the feedback based on the comprehensive diagnos platform of large data, upgrades early warning signal now now.
As a preferred embodiment of the present invention, based on the running of the electric equipment diagnosis platform of large data, the storage adopt magnanimity original sampling data and management method, comprise following two:
(1) the real time mass initial data of monitoring multiple power equipment adopts the memory technology based on the data of HDFS to store, and supports that quick, magnanimity, high scalability data store and inquiry;
(2) data processing method based on MapReduce technology is adopted to magnanimity monitoring initial data and equipment off-line status data, realize the real-time process to the large data of monitoring, thus realize the real-time Accurate Diagnosis to equipment health status.
As a preferred embodiment of the present invention, based on the running of the electric equipment diagnosis platform of large data, its diagnostic analysis method, comprises following three:
(1) to the same monitoring index amount that multiple power equipment is monitored, by the dependency relation analysis of large data, the parameter attribute of contrast distinct device Monitoring Data under synchronization, same event, judge the position that fault occurs, provide diagnostic result, and the diagnostic result of other power equipments is revised.
(2) to the data of same monitoring index under different sensing mode of same monitoring equipment, on this comprehensive monitoring and diagnostic platform, by the fusion of the multi-source heterogeneous data of large data, carry out comprehensive Analysis and judgments, provide diagnostic result.
(3) to the real time data of same monitoring equipment, in conjunction with the magnanimity fault sample storehouse of monitoring historical data, same model equipment, by large data analysis technique, carry out the multidimensional of whole sample, real time contrast, provide diagnosis.
As shown in Figure 1, the present invention includes multiple power equipment now monitoring means, speed two-way transmission unit and the electric power apparatus integrated diagnostic platform based on large data, wherein 1 ~ 17 representative is for the transducer of the running status of sensor transformer, power cable, GIS, transducer corresponding to each equipment is connected with the monitoring means of each equipment respectively, and the monitoring means of GIS, transformer, power cable is connected with the electric power apparatus integrated diagnostic platform based on large data by bidirectional data transfers mechanism at a high speed.Electric power apparatus integrated diagnostic platform based on large data comprises the large data memory module of status monitoring, the large data processing module of status monitoring, the large data analysis module of status monitoring, the large data exhibiting module of status monitoring four major parts.
As shown in Figure 2, composition based on the electric power apparatus integrated diagnostic platform of large data comprises following components: based on the parallel data processing module (the large data processing module of status monitoring) of Map Reduce, task management, task scheduling and Mission Monitor module (the large data processing module of status monitoring), status of equipment real-time Precise Diagnosis module (the large data analysis module of status monitoring), based on the magnanimity initial data administration module (the large data memory module of status monitoring) of HDFS, based on the non-relational database module of increasing income (the large data memory module of status monitoring) of HBASE, result is issued and early warning feedback module (the large data exhibiting module of status monitoring).
Equipment on-line monitoring data (containing equipment on-line monitoring initial data, data acquisition time, data acquisition place, unit type, device numbering) are transferred to the electric power apparatus integrated diagnostic platform based on large data by bidirectional data transfers mechanism at a high speed.This platform is by task scheduling and Mission Monitor module analysis management equipment online monitoring data and equipment off-line data (failure logging containing equipment operation condition historical record, device history failure logging, unit type, same model equipment), on the one hand these two kinds of data are stored in the magnanimity initial data administration module based on HDFS, on the other hand by realizing the real-time analysis of Monitoring Data based on the parallel data processing module of Map Reduce, analysis result sends into the real-time Precise Diagnosis module of status of equipment.Status of equipment real-time Precise Diagnosis module is by large data analysis technique, provide the diagnostic result with high accuracy, and the non-relational database module of increasing income diagnostic result and corresponding index amount are stored in based on HBASE, diagnostic result is sent into result simultaneously and issue and early warning feedback module.Result is issued with early warning feedback module on the one hand by large data display technology, realize issuing the multimedia of monitoring result, on the other hand by by bidirectional data transfers mechanism at a high speed, diagnostic result is fed back to existing ground monitoring means, realize the renewal to existing ground early warning information.
Overall flowchart shown in Fig. 3 comprises following step:
(1) GIS monitoring means, cable monitoring unit carry out continuous acquisition and analysis to the relevant monitoring parameter of GIS, power cable and transformer respectively to transformer monitoring unit, and provide diagnosis and early warning result in real time, at the traffic light system advanced warning grade now by different colours.
(2) initial data of monitoring means imported into the electric power apparatus integrated diagnostic platform based on large data by bidirectional data transfers mechanism at a high speed.
(3) equipment Real-time Monitoring Data and equipment off-line status data are by functional modules such as algorithmic dispatching, task management, dispatching and monitorings and manage concentratedly based on the Mass Data Management system module of the HBASE increased income.
(4) equipment on-line monitoring data and equipment off-line status data are by the device status data parallel processing system (PPS) based on MapReduce, real-time Precise Diagnosis is carried out to equipment state, obtain corresponding diagnostic result, and early warning information is fed back to existing stratum in time by bidirectional data transfers mechanism at a high speed.
(5) if diagnostic result is for there being fault, then give a warning information.
Figure 4 shows that in the comprehensive diagnos platform based on large data a kind of multi-source data analysis method used, for the monitoring parameter of power equipment, its detection method has a variety of, such as the partial discharge of transformer, its detection means has hyperfrequency method, ultrasonic method, oil colours spectrometry etc., utilize the multi-source heterogeneous Data fusion technique in large aggregation of data diagnostic platform, diagnostic result can be made more accurate.Specifically, the output of multi-source monitoring data may have following several situation:
1. three kinds of equal fault-free of method measured result occur, then system attonity, continues monitoring.
2. three kinds of method measured results have been fault generation, now can determine that fault enters the failure diagnosis stage.
3. three kinds of method measured results are inconsistent enters the data fusion stage, using its Output rusults as criterion.
As shown in Figure 5, with transformer, GIS, the partial discharge of power cable is example, introduce based on the data analysing method used in the comprehensive diagnos platform of large data, for the monitoring of partial discharge, these three kinds of power equipments are at electric power and physically have stronger annexation, by the monitoring and diagnosis to three kinds of apparatus local discharges, when monitoring result show three different power equipments there is partial discharge simultaneously time, start large data fusion and judgement, accurately judge partial discharge is from which power equipment, and judged result is fed back to the diagnostic system of single monitoring equipment, diagnostic result is revised.
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 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 an electric power apparatus integrated monitoring index system system for large data, it is characterized in that: comprise transducer group, monitoring means group and electric power apparatus integrated diagnostic platform, wherein:
Described transducer group, comprises multiple transducers of the monitoring parameter for coupling transformer, power cable, GIS;
Described monitoring means group, comprise the monitoring means of monitoring parameter of monitoring coupling transformer, power cable, GIS, each monitoring means connects with corresponding transducer respectively;
Described electric power apparatus integrated diagnostic platform, connect monitoring means group, for realizing the storage and management of the multiple target power equipment Monitoring Data based on HDFS, realize based on MapReduce technology and fault sample storehouse diagnosis and realize based on the monitoring index amount of NoSQL database technology and the real-time storage of diagnostic result.
2. electric power apparatus integrated monitoring index system system as claimed in claim 1, is characterized in that: diagnostic result is fed back to each now monitoring means, alert status of updating the equipment by bidirectional data transfers mechanism by described electric power apparatus integrated diagnostic platform.
3. electric power apparatus integrated monitoring index system system as claimed in claim 1, it is characterized in that: described electric power apparatus integrated diagnostic platform, comprise algorithmic dispatching module, task management module and dispatching and monitoring module, wherein algorithmic dispatching module is used for the scheduling of different monitoring equipment diagnostic analysis method and apolegamy, the effect of task management module is data communication, data analysis, the dispatching management of the tasks such as data storage, the effect of dispatching and monitoring module is to carry out monitoring and management to the execution flow process of task management module, the data of described electric power apparatus integrated diagnostic platform comprise equipment on-line monitoring data and equipment off-line status data, described equipment off-line status data comprises equipment operation condition historical record, device history failure logging, unit type, device fabrication producer, the failure logging of same model equipment and device history experimental data.
4. electric power apparatus integrated monitoring index system system as claimed in claim 1, is characterized in that: described monitoring means group at least comprises GIS monitoring means, cable monitoring unit and transformer monitoring unit.
5. electric power apparatus integrated monitoring index system system as claimed in claim 4, it is characterized in that: the relevant monitoring parameter of described monitoring means group to GIS, power cable and transformer carries out continuous acquisition and analysis, and provide diagnosis and early warning result, at the traffic light system advanced warning grade now by different colours.
6. the analytical method of the electric power apparatus integrated monitoring index system system according to any one of claim 1-5, is characterized in that: concrete steps are as follows:
(1) GIS monitoring means, cable monitoring unit carry out continuous acquisition and analysis to the relevant monitoring parameter of GIS, power cable and transformer respectively to transformer monitoring unit, and provide diagnosis and early warning result in real time, at the traffic light system advanced warning grade now by different colours;
(2) initial data of monitoring means imported into the electric power apparatus integrated diagnostic platform based on large data by bidirectional data transfers mechanism at a high speed;
(3) equipment Real-time Monitoring Data and equipment off-line status data are managed concentratedly;
(4) equipment on-line monitoring data and equipment off-line status data are by the device status data parallel processing system (PPS) based on MapReduce, real-time Precise Diagnosis is carried out to equipment state, obtain corresponding diagnostic result, and early warning information is fed back to existing stratum in time by bidirectional data transfers mechanism at a high speed;
(5) if diagnostic result is for there being fault, then give a warning information; Now monitoring means is after receiving the feedback based on the comprehensive diagnos platform of large data, upgrades early warning signal now.
7. analytical method as claimed in claim 6, is characterized in that: the concrete grammar of described step (1) is: utilize multiple method monitoring parameter, if the equal fault-free of the result of multiple method occurs, then system attonity, continues monitoring; Measured result has been fault and has occurred, and now can determine that fault enters the failure diagnosis stage; Measured result is inconsistent enters the data fusion stage, using its Output rusults as criterion.
8. analytical method as claimed in claim 6, is characterized in that: in described step (1), when monitoring the partial discharge of transformer, uses hyperfrequency method, ultrasonic method and oil colours spectrometry.
9. analytical method as claimed in claim 6, is characterized in that: in described step (2), and the storage adopt magnanimity original sampling data and management method, comprise following two:
(2-1) the real time mass initial data of monitoring multiple power equipment adopts the memory technology based on the data of HDFS to store, and supports that quick, magnanimity, high scalability data store and inquiry;
(2-2) data processing method based on MapReduce technology is adopted to magnanimity monitoring initial data and equipment off-line status data, realize the real-time process to the large data of monitoring, thus realize the real-time Accurate Diagnosis to equipment health status.
10. analytical method as claimed in claim 6, is characterized in that: in described step (4), the method for diagnosis comprises:
(4-1) to the same monitoring index amount that multiple power equipment is monitored, by the dependency relation analysis of large data, the parameter attribute of contrast distinct device Monitoring Data under synchronization, same event, judge the position that fault occurs, provide diagnostic result, and the diagnostic result of other power equipments is revised;
(4-2) to the data of same monitoring index under different sensing mode of same monitoring equipment, on this comprehensive monitoring and diagnostic platform, by the fusion of the multi-source heterogeneous data of large data, carry out comprehensive Analysis and judgments, provide diagnostic result;
(4-3) to the real time data of same monitoring equipment, in conjunction with the fault sample storehouse of monitoring historical data, same model equipment, carry out the multidimensional of whole sample, real time contrast, provide diagnosis.
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