CN109102210A - Monitoring defect based on big data analysis technology intelligently assists disposal system - Google Patents
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Abstract
The monitoring defect based on big data analysis technology that the invention discloses a kind of intelligently assists disposal system, including monitoring defect information detecting identification module, monitoring defect intelligent decision module, typical defect signal analysis expert knowledge base, monitoring defect that disposition module, defect is assisted to dispose situation automatic tracing module；Monitoring defect information detecting identification module, typical defect signal analysis expert knowledge base are connected with monitoring defect intelligent decision module, defect detection information is transmitted to monitoring defect intelligent decision module by monitoring defect information detecting identification module, information exchange is carried out between typical defect signal analysis expert knowledge base and monitoring defect intelligent decision module, monitoring defect auxiliary disposition module is connected with monitoring defect intelligent decision module, and defect disposes situation automatic tracing module and is connected with monitoring defect auxiliary disposition module.The present invention has found and eliminates the effects of the act in time the insecurity factor of power system stability operation, and defect is eliminated in budding state, guarantees electric power netting safe running.
Description
Technical field
The present invention relates to substation equipment defect monitoring identifications, judgement, disposition, more particularly to one kind to be based on big data analysis
The monitoring defect of technology intelligently assists disposal system, belongs to electrical equipment technical field.
Background technique
The defect of substation equipment is a big hidden danger of power network safety operation, promptly and accurately finds and disposes unmanned value
The equipment deficiency for keeping substation is the important prerequisite for guaranteeing grid equipment safe and stable operation.The monitoring of equipment deficiency is known at present
Not, judge, dispose, recording by manually completing, it is simple by manually there is following problems: may in identification process
Signal of interest can be omitted, in the judgment process may erroneous judgement, not perfect, defect record may be handled in disposal process
May exceed the time limit non-closed loop etc..
With the continuous development of big data analysis technology, operation of power networks analysis intelligence degree is increasingly improved, massive information
Mining analysis efficiency persistently promoted.Traditional equipment deficiency manually monitor identifying processing mode need to active real-time perception and
Standard intelligently disposes Mode change, thus the insecurity factor for the power system stability operation that finds and eliminate the effects of the act in time, scarce
It falls into and eliminates in budding state, guarantee electric power netting safe running.
Summary of the invention
The purpose of the present invention is to provide a kind of, and the monitoring defect based on big data analysis technology intelligently assists disposal system,
Traditional equipment deficiency is manually monitored into identifying processing mode and intelligently disposes Mode change to active real-time perception and standard, in time
It was found that and power system stability operation of eliminating the effects of the act insecurity factor, defect is eliminated in budding state, guarantees power grid security
Operation.
The purpose of the present invention is achieved by the following technical programs:
A kind of intelligently auxiliary disposal system, including monitoring defect information detecting of the monitoring defect based on big data analysis technology
Identification module 1, monitoring defect intelligent decision module 2, typical defect signal analysis expert knowledge base 3, monitoring defect auxiliary disposition
Module 4, defect dispose situation automatic tracing module 5；The monitoring defect information detecting identification module 1, typical defect signal are special
Family's analysis knowledge library 3 is connected with monitoring defect intelligent decision module 2, and the monitoring defect information detects identification module 1 for defect
Detecting information is transmitted to monitoring defect intelligent decision module 2, the typical defect signal analysis expert knowledge base 3 and monitoring defect
Familial defect analysis information is carried out between intelligent decision module 2, warning information incidence relation analyzes information, typical defect signal
The interaction of predictive information, the monitoring defect auxiliary disposition module 4 are connected with monitoring defect intelligent decision module 2, the defect
Disposition situation automatic tracing module 5 is connected with monitoring defect auxiliary disposition module 4.
The purpose of the present invention can also be further realized by following technical measures:
The aforementioned monitoring defect based on big data analysis technology intelligently assists disposal system, wherein monitoring defect information detecting
Identification module 1 carries out detecting identification to the data source of system, and it further includes real-time that the data source of system, which includes the data of scheduling system,
The remote signalling of scan schedule D5000web database, telemetry, while on-line monitoring system, OMS, failure wave-recording system are read in timing
System, prudential sub-station, video monitoring system data, and PMS, Meteorological Information System, lightning location system data are read, detecting is known
Following Chu not monitor those suspected defects: the monitoring alarm information of non-involution, the signal of frequent movement, telemetering do not refresh for a long time, telemetering
Mutation, DC bus-bar voltage are relatively low.
The aforementioned monitoring defect based on big data analysis technology intelligently assists disposal system, wherein monitoring defect intelligent decision
2 pairs of monitoring defects of module carry out intelligent decision, and a monitoring defect event is usually associated with multiple associated alarm letters
Breath, only comprehensively considers all warning information and its sequential relationship, could correctly judge to monitor defect, establishes monitoring defect intelligence
Judgment module excavates history alarm information realization without the multi-source information depth of characterization using regulation big data mining algorithm, point
Remote signalling, the telemetry intelligence (TELINT) for analysing history monitoring defect event institute association, establish monitoring defect standard library；And certainly by depth big data
Learning algorithm constantly improves monitoring defect standard library, and the self study by monitoring defect event handling every time is analyzed, automatic to discriminate
Ineffective association information, and safeguard association information to monitoring defect standard library；By the related information and drawbacks of the standard of those suspected defects
Related information carry out Auto-matching, successful match i.e. judge automatically for monitor defect, and according to the extent of injury of defect define the level,
Realize the intelligent decision of monitoring defect.
The aforementioned monitoring defect based on big data analysis technology intelligently assists disposal system, wherein typical defect signal expert
Analysis knowledge library 3 carries out following analysis:
(1) familial defect analyze: according to monitoring defect intelligent decision module 2 judgement, the relevant information of analyzing defect,
Positioning to failure exception equipment, extract equipment correlation account realizes that failure exception equipment and equipment are raw using fuzzy matching technology
The auto-associating of producer, batch, date of manufacture information is produced, and analysis and early warning is carried out to unit exception familial trend automatically；
(2) warning information incidence relation analyze: using Text Mining Technology from non-structured instrument for equipment alarm signal from
Unit exception signal sequence model is precipitated, determines between unit exception signal exist using the association analysis algorithm of incremental learning
Potential incidence relation, unit exception signal correlation model is formed, to having strong association to close in same substation's contemporaneity
The warning information of system is analyzed, the correctness of checking signal logical circuit；
(3) typical defect signal estimation: by big data mining analysis technology, to history typical defect event course of emergency
It is analyzed, restores the associated alarm information in typical defect generating process, including Weather information, temperature information, rainfall letter
Breath calculates typical defect and season, meteorology, temperature and humidity, the confidence level between wind speed factor, forms effective confidence interval, sentence
Whether disconnected current factor is in effective confidence interval, to predict the generation feelings of typical defect signal in power grid following a period of time
Condition prompts monitor to carry out reply processing and prepares.
The aforementioned monitoring defect based on big data analysis technology intelligently assists disposal system, wherein monitoring defect auxiliary disposition
Module 4:
(1) paraphrase is carried out to defect correlation alarm signal automatically, and shows the secondary circuit that signal generates；
(2) judge whether the defect is familial defect；
(3) influence of the defect to equipment and power grid is analyzed；
(4) it generates defect disposal method: being examined by big data analysis technology monitoring defect event identical to history
Rope shows the time of origin of identical defect, site inspection feedback, defect processing process, defect elimination temporal information in history, to
Monitor provides the suggestion and points for attention of this defect processing, and auxiliary is when value monitor is quick, correctly handles this defect.
The aforementioned monitoring defect based on big data analysis technology intelligently assists disposal system, and wherein defect disposition situation is automatic
The disposition situation of 5 tracing and monitoring defect of tracing module detects that alarm signal involution associated by defect, abnormal telemetering restore just
Often, system pop-up reminds monitor to verify whether this defect is processed, and notice is supervised not in time after preventing operation maintenance personnel from handling defect
Control；
To the processing time limit is closed on and untreated defect carries out early warning of exceeding the time limit, monitor is reminded to notify operation maintenance personnel processing；
To be more than processing the time limit and untreated defect alerts, be labeled as having exceeded the time limit, by regulation center notice transport inspection department handle.
Compared with prior art, the beneficial effects of the present invention are: the present invention realizes that monitoring defect detecting real-time, intelligence are sentenced
Disconnected, auxiliary is disposed, the function of automatic tracing passes through on the basis of regulating and controlling big data analysis technology and monitors defect standard library, allusion quotation
The sound monitoring defect of type flaw indication analysis expert knowledge base intelligently assists disposal system, avoids omitting important letter when manual identified
Breath, false judgment when artificial judgment, when artificial disposition, handle not perfect, and when manual trace does not find defect of exceeding the time limit.Work as substation
When defect occurs for equipment, energy automatic identification judges associated alarm information, and intelligent decision simultaneously proposes disposition proposed projects.To be promoted
The automation of monitoring business, intelligent level promote monitor to the control ability of operating condition of transformer station equipment, promote regulation
Lean ability of regulation and control of the profession as operation of power networks commander's hinge.
Detailed description of the invention
Fig. 1 is the monitoring defect of the invention based on big data analysis technology intelligently auxiliary disposal system functional module structure
Figure；
Fig. 2 is to monitor defect intelligently disposal process figure of the auxiliary disposal system for substation equipment defect.
Specific embodiment
The present invention will be further explained below with reference to the attached drawings and specific examples.
As shown in Figure 1, a kind of monitoring defect based on big data analysis technology intelligently assists disposal system, including monitoring to lack
Sunken information detecting identification module 1, monitoring defect intelligent decision module 2, typical defect signal analysis expert knowledge base 3, monitoring lack
Fall into auxiliary disposition module 4, defect disposes situation automatic tracing module 5；The monitoring defect information detecting identification module 1, typical case
Flaw indication analysis expert knowledge base 3 is connected with monitoring defect intelligent decision module 2, the monitoring defect information detecting identification mould
Defect detection information is transmitted to monitoring defect intelligent decision module 2, the typical defect signal analysis expert knowledge base 3 by block 1
Familial defect analysis information is carried out between monitoring defect intelligent decision module 2, warning information incidence relation analyzes information, allusion quotation
The interaction of type flaw indication predictive information, the monitoring defect auxiliary disposition module 4 and monitoring 2 phase of defect intelligent decision module
Even, the defect disposition situation automatic tracing module 5 is connected with monitoring defect auxiliary disposition module 4.
It is illustrated in figure 2 monitoring defect intelligently disposal process figure of the auxiliary disposal system for substation equipment defect.Respectively
Module is sequentially completed following steps:
Monitoring defect information detecting identification module 1 carries out detecting identification to the data source of system, and the data source of system includes
The data of scheduling system further include remote signalling, the telemetry of real time scan scheduling D5000web database, while timing is read
Line monitoring system, OMS, fault recording system, prudential sub-station, video monitoring system data, and read PMS, weather information system
System, lightning location system data, detecting identify following monitoring those suspected defects: the monitoring alarm information of non-involution, frequent movement
Signal, telemetering do not refresh for a long time, telemetering mutation, DC bus-bar voltage it is relatively low.
It monitors 2 pairs of monitoring defects of defect intelligent decision module and carries out intelligent decision, the generation of a monitoring defect event is past
Toward along with multiple associated warning information, only comprehensively considers all warning information and its sequential relationship, could correctly judge
Monitor defect, establish monitoring defect intelligent decision module, using regulation big data mining algorithm, to history alarm information realization without
The multi-source information depth of characterization is excavated, and analysis of history monitors the remote signalling of defect event institute association, telemetry intelligence (TELINT), establishes monitoring defect
Java standard library；And monitoring defect standard library is constantly improved by depth big data self-learning algorithm, by monitoring defect thing every time
The self study analysis of part processing, screens effective association information automatically, and safeguards association information to monitoring defect standard library；It will be doubtful
The related information of defect and the related information of drawbacks of the standard carry out Auto-matching, and successful match judges automatically to monitor defect,
And defined the level according to the extent of injury of defect, realize the intelligent decision of monitoring defect.
Typical defect signal analysis expert knowledge base 3 carries out following analysis:
(1) familial defect analyze: according to monitoring defect intelligent decision module 2 judgement, the relevant information of analyzing defect,
Positioning to failure exception equipment, extract equipment correlation account realizes that failure exception equipment and equipment are raw using fuzzy matching technology
The auto-associating of producer, batch, date of manufacture information is produced, and analysis and early warning is carried out to unit exception familial trend automatically；
(2) warning information incidence relation analyze: using Text Mining Technology from non-structured instrument for equipment alarm signal from
Unit exception signal sequence model is precipitated, determines between unit exception signal exist using the association analysis algorithm of incremental learning
Potential incidence relation, unit exception signal correlation model is formed, to having strong association to close in same substation's contemporaneity
The warning information of system is analyzed, the correctness of checking signal logical circuit；
(3) typical defect signal estimation: by big data mining analysis technology, to history typical defect event course of emergency
It is analyzed, restores the associated alarm information in typical defect generating process, including Weather information, temperature information, rainfall letter
Breath calculates typical defect and season, meteorology, temperature and humidity, the confidence level between wind speed factor, forms effective confidence interval, sentence
Whether disconnected current factor is in effective confidence interval, to predict the generation feelings of typical defect signal in power grid following a period of time
Condition prompts monitor to carry out reply processing and prepares.
Monitoring defect auxiliary disposition module 4:(1) paraphrase is carried out automatically to defect correlation alarm signal, and show that signal is raw
At secondary circuit；(2) judge whether the defect is familial defect；(3) influence of the defect to equipment and power grid is analyzed；
(4) it generates defect disposal method: being retrieved by big data analysis technology monitoring defect event identical to history, displaying is gone through
The time of origin of identical defect, site inspection feedback, defect processing process, defect elimination temporal information, mention to monitor in history
For the suggestion and points for attention of this defect processing, auxiliary is when value monitor is quick, correctly handles this defect.
Defect disposes the disposition situation of 5 tracing and monitoring defect of situation automatic tracing module, detects announcement associated by defect
Alert signal return, abnormal telemetering restore normal, and whether system pop-up reminds monitor to verify this defect processed, prevent O&M people
Notice monitoring not in time after member's processing defect；
To the processing time limit is closed on and untreated defect carries out early warning of exceeding the time limit, monitor is reminded to notify operation maintenance personnel processing；
To be more than processing the time limit and untreated defect alerts, be labeled as having exceeded the time limit, by regulation center notice transport inspection department handle.
In addition to the implementation, the present invention can also have other embodiments, all to use equivalent substitution or equivalent transformation shape
At technical solution, be all fallen within the protection domain of application claims.
Claims (6)
1. a kind of monitoring defect based on big data analysis technology intelligently assists disposal system, which is characterized in that lacked including monitoring
It is auxiliary to fall into information detecting identification module, monitoring defect intelligent decision module, typical defect signal analysis expert knowledge base, monitoring defect
Help disposition module, defect disposition situation automatic tracing module；The monitoring defect information detects identification module, typical defect signal
Analysis expert knowledge base is connected with monitoring defect intelligent decision module, and the monitoring defect information detecting identification module detects defect
Measurement information is transmitted to monitoring defect intelligent decision module, the typical defect signal analysis expert knowledge base and monitoring defect intelligence
Familial defect analysis information is carried out between judgment module, warning information incidence relation analyzes information, typical defect signal estimation
The interaction of information, the monitoring defect auxiliary disposition module are connected with monitoring defect intelligent decision module, and the defect disposes feelings
Condition automatic tracing module is connected with monitoring defect auxiliary disposition module.
2. intelligently auxiliary disposal system, feature exist the monitoring defect based on big data analysis technology as described in claim 1
In the monitoring defect information detecting identification module carries out detecting identification to the data source of system, and the data source of system includes adjusting
The data of degree system further include remote signalling, the telemetry of real time scan scheduling D5000web database, while timing is read online
Monitoring system, OMS, fault recording system, prudential sub-station, video monitoring system data, and read PMS, Meteorological Information System,
Lightning location system data, detecting identify following monitoring those suspected defects: the letter of the monitoring alarm information of non-involution, frequent movement
Number, telemetering do not refresh for a long time, telemetering mutation, DC bus-bar voltage it is relatively low.
3. intelligently auxiliary disposal system, feature exist the monitoring defect based on big data analysis technology as described in claim 1
In the monitoring defect intelligent decision module carries out intelligent decision to monitoring defect, and the generation of a monitoring defect event is often
Along with multiple associated warning information, all warning information and its sequential relationship are only comprehensively considered, could correctly judge to supervise
Defect is controlled, monitoring defect intelligent decision module is established, using regulation big data mining algorithm, to history alarm information realization without table
The multi-source information depth of sign is excavated, and analysis of history monitors the remote signalling of defect event institute association, telemetry intelligence (TELINT), establishes monitoring defect mark
Quasi- library；And monitoring defect standard library is constantly improved by depth big data self-learning algorithm, by monitoring defect event every time
The self study of processing is analyzed, and screens effective association information automatically, and safeguards association information to monitoring defect standard library；It is lacked doubtful
The related information of sunken related information and drawbacks of the standard carries out Auto-matching, and successful match judges automatically to monitor defect, and
It is defined the level according to the extent of injury of defect, realizes the intelligent decision of monitoring defect.
4. intelligently auxiliary disposal system, feature exist the monitoring defect based on big data analysis technology as described in claim 1
In the typical defect signal analysis expert knowledge base carries out following analysis:
(1) familial defect is analyzed: according to the judgement of monitoring defect intelligent decision module 2, the relevant information of analyzing defect, positioning
To failure exception equipment, extract equipment correlation account realizes failure exception equipment and equipment factory using fuzzy matching technology
Family, batch, date of manufacture information auto-associating, and automatically to unit exception familial trend carry out analysis and early warning；
(2) warning information incidence relation is analyzed: being isolated from non-structured instrument for equipment alarm signal using Text Mining Technology
Unit exception signal sequence model is determined existing latent between unit exception signal using the association analysis algorithm of incremental learning
In incidence relation, form unit exception signal correlation model, in same substation's contemporaneity with strong incidence relation
Warning information is analyzed, the correctness of checking signal logical circuit；
(3) typical defect signal estimation: by big data mining analysis technology, history typical defect event course of emergency is carried out
Analysis restores the associated alarm information in typical defect generating process, including Weather information, temperature information, rainfall information, meter
Typical defect and season, meteorology, temperature and humidity, the confidence level between wind speed factor are calculated, forms effective confidence interval, judgement is current
Whether factor is in effective confidence interval, to predict that a situation arises for typical defect signal in power grid following a period of time, mentions
Show that monitor carries out reply processing and prepares.
5. intelligently auxiliary disposal system, feature exist the monitoring defect based on big data analysis technology as described in claim 1
In the monitoring defect auxiliary disposition module:
(1) paraphrase is carried out to defect correlation alarm signal automatically, and shows the secondary circuit that signal generates；
(2) judge whether the defect is familial defect；
(3) influence of the defect to equipment and power grid is analyzed；
(4) it generates defect disposal method: being retrieved by big data analysis technology monitoring defect event identical to history, opened up
Show the time of origin of identical defect, site inspection feedback, defect processing process, defect elimination temporal information in history, to monitoring
Member provides the suggestion and points for attention of this defect processing, and auxiliary is when value monitor is quick, correctly handles this defect.
6. intelligently auxiliary disposal system, feature exist the monitoring defect based on big data analysis technology as described in claim 1
In the disposition situation of the defect disposition situation automatic tracing module tracks monitoring defect detects alarm associated by defect
Signal return, abnormal telemetering restore normal, and whether system pop-up reminds monitor to verify this defect processed, prevent operation maintenance personnel
Monitoring is notified not in time after handling defect；
To the processing time limit is closed on and untreated defect carries out early warning of exceeding the time limit, monitor is reminded to notify operation maintenance personnel processing；To
More than the processing time limit, untreated defect is alerted, and is labeled as having exceeded the time limit, and is handled by regulation center notice transport inspection department.
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Cited By (10)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN109993443A (en) * | 2019-04-04 | 2019-07-09 | 北京科东电力控制系统有限责任公司 | A kind of grid equipment operating status space-time Situation Awareness model method for digging |
| CN110380514A (en) * | 2019-08-02 | 2019-10-25 | 云南电网有限责任公司电力科学研究院 | A kind of intelligent substation relay protection secondary circuit method for diagnosing faults |
| CN110610321A (en) * | 2019-09-19 | 2019-12-24 | 四川电力设计咨询有限责任公司 | Intelligent auxiliary control system based on Internet of things and event classification processing mechanism |
| CN110866695A (en) * | 2019-11-15 | 2020-03-06 | 国网天津市电力公司 | Auxiliary maintenance decision method based on association of equipment running state and maintenance work |
| CN110956447A (en) * | 2019-11-27 | 2020-04-03 | 云南电网有限责任公司电力科学研究院 | Method and system for determining suspected familial defect |
| CN111311133A (en) * | 2020-04-24 | 2020-06-19 | 广东卓维网络有限公司 | Monitoring system applied to power grid production equipment |
| CN111709597A (en) * | 2020-04-24 | 2020-09-25 | 广东卓维网络有限公司 | Power grid production domain operation monitoring system |
| CN112116108A (en) * | 2020-09-22 | 2020-12-22 | 云南电网有限责任公司电力科学研究院 | Expert system and method for failure analysis of power equipment |
| CN113065978A (en) * | 2021-03-15 | 2021-07-02 | 国网江苏省电力有限公司南通供电分公司 | Analysis method for monitoring information defect event |
| WO2024098986A1 (en) * | 2022-11-09 | 2024-05-16 | 云南电网有限责任公司普洱供电局 | Relay protection apparatus defect detection method and system based on intelligent oscillograph |
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