CN108073586A - Crash analysis method and apparatus based on oil-gas pipeline SCADA system - Google Patents

Crash analysis method and apparatus based on oil-gas pipeline SCADA system Download PDF

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Publication number
CN108073586A
CN108073586A CN201610986160.7A CN201610986160A CN108073586A CN 108073586 A CN108073586 A CN 108073586A CN 201610986160 A CN201610986160 A CN 201610986160A CN 108073586 A CN108073586 A CN 108073586A
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China
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data
time
oil
gas pipeline
daily record
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Inventor
孙铁良
黄河
段然
闫峰
陈鹏
尤冬青
刘芸
咸玉龙
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China Petroleum and Natural Gas Co Ltd
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China Petroleum and Natural Gas Co Ltd
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Priority to CN201610986160.7A priority Critical patent/CN108073586A/en
Publication of CN108073586A publication Critical patent/CN108073586A/en
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/10—File systems; File servers
    • G06F16/18—File system types
    • G06F16/1805—Append-only file systems, e.g. using logs or journals to store data
    • G06F16/1815—Journaling file systems
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2216/00—Indexing scheme relating to additional aspects of information retrieval not explicitly covered by G06F16/00 and subgroups
    • G06F2216/03—Data mining

Abstract

A kind of crash analysis method for early warning based on oil-gas pipeline SCADA system of the present invention, including：According to the time interval of setting, the profile data and daily record data for the oil-gas pipeline that storage SCADA system collects at regular intervals, form section file and journal file, the profile data includes the real-time running data of each equipment of oil-gas pipeline of SCADA system at a time each data collection point acquisition, and the daily record data includes acquisition delta data and manual operation data；When needing inverting, the section file and journal file of selection are called, plays the profile data that selected section file includes and the daily record data that journal file includes sequentially in time.The present invention can periodically store real-time profile data and daily record data, have compressed data storage capacity, after accident generation, by playing back oil-gas pipeline profile data and daily record data in certain time, the accurate and visual situation of change for reflecting the state of affairs in this period.

Description

Crash analysis method and apparatus based on oil-gas pipeline SCADA system
Technical field
It is more particularly to a kind of to be based on oil-gas pipeline SCADA (Supervisory the present invention relates to oil-gas transportation technical field Control And Data Acquisition, i.e. data acquisition are controlled with monitoring) the crash analysis method and apparatus of system.
Background technology
The long-distance pipe forwarding of the important energy sources goods and materials such as oil, natural gas is rapidly developed, to oil-gas pipeline The intensity of production run scheduling controlling also proposed increasingly higher demands.Centralization regulation and control model causes the production of pipeline Operational management is more and more stronger to the dependence of oil-gas pipeline data acquisition analysis system (SCADA), and artificial intervention is fewer and fewer.
Oil-gas pipeline devices in system is numerous, measurement point distribution is wide, causes oil-gas pipeline SCADA software system data amounts huge Greatly, and data record is at regular intervals with regard to carrying out the whole network state estimation.
It is stored directly at present in oil gas pipe network SCADA inverting data in real-time data base, however as pipeline scale Increasingly huge, SCADA data point quantity bigger, distribution are wider, and huge memory space will be occupied by storing these data, this is undoubtedly The business processing burden of real-time data base can be increased.Current accident inversion data are directly read from real-time data base, can not Deviation effects caused by avoiding real-time database gathered data mistake.Therefore the mechanism of this accident inversion will depend on system to accident The accurate capture of itself and accurate judgement will be unable to as to this in the case of accident is not by accurate captured therefore carry out inverting point Analysis.Therefore, existing accident inversion mechanism cannot support whole pipe network operation states, the main reason is that being limited to memory capacity Etc. reasons the history message of flood tide can not be all saved in database.Analysis understands that traditional accident inversion method uses Real-time data base model and the Hologram Storage inversion method of data are stored, is had the following problems：
1. the real-time data base data of directly storage SCADA can increase the business processing burden of real-time data base.
2. being directly based upon real-time data base data carries out accident inversion, it is not easy to find that relatively large deviation wherein that may be present is surveyed Magnitude.
3. traditional method can only carry out data readback, localized accident occurrence cause rely on the manual analysis of specialty, it is necessary to Abundant domain knowledge, and intelligentized analysis prediction cannot be carried out.
The content of the invention
In order to solve the technical issues of above-mentioned, the present invention provides a kind of crash analysis based on oil-gas pipeline SCADA system Method and apparatus is effectively compressed data storage capacity.
Specifically, including following technical solution：
A kind of crash analysis method based on oil-gas pipeline SCADA system, including：
According to the section number of the time interval of setting, the at regular intervals oil-gas pipeline that storage SCADA system collects According to and daily record data, form section file and journal file, the profile data includes SCADA system at a time each number According to the real-time running data of each equipment of oil-gas pipeline of collection point acquisition, the daily record data is including acquisition delta data and manually Operation data；
When needing inverting, the section file and journal file of selection are called, is played sequentially in time selected disconnected The daily record data that the profile data and journal file that face file includes include.
Selectively, it is described that the section file of selection and journal file is called to include：
According to the beginning inverse time of setting and terminate inverse time, the selection record time is starting inverse time and end All section files and journal file between inverse time are as the section file and journal file called.
Selectively, the profile data and journal file for playing selected section file sequentially in time and including Comprising daily record data include：Profile data and daily record data are refreshed according to the inverting step-length of setting during broadcasting.
Selectively, further include：
The extraction acquisition delta data from the daily record data of the journal file of selection, forms acquisition delta data collection；
The collection point alarm delta data and the branch topology relationship of oil-gas pipeline equipment concentrated according to acquisition delta data, The faulty equipment caused the accident is found using data mining.
Selectively, the data mining is that all frequent 1 item collections are found according to the branch topology relationship of oil-gas pipeline, Maximum frequent itemsets are obtained using Apirori algorithms, the corresponding oil of acquisition delta data concentrated according to the maximum frequent set Feed channel equipment positions faulty equipment.
A kind of accident analysis apparatus based on oil-gas pipeline SCADA system, including：
Memory module for the time interval according to setting, stores the oil gas that SCADA system collects at regular intervals The profile data and daily record data of pipeline, form section file and journal file, and the profile data includes SCADA system at certain The real-time running data of each equipment of oil-gas pipeline of one moment each data collection point acquisition, the daily record data include acquisition and become Change data and manual operation data；
Inverting module for when needing inverting, calling the section file of selection and journal file, is broadcast sequentially in time Put the profile data that selected section file includes and the daily record data that journal file includes.
Selectively, in the inverting module section file of selection and journal file is called to include：
According to the beginning inverse time of setting and terminate inverse time, the selection record time is starting inverse time and end All section files and journal file between inverse time are as the section file and journal file called.
Selectively, the profile data that selected section file includes is played in the inverting module sequentially in time Include with the daily record data that journal file includes：According to the inverting step-length of setting, section number is refreshed according to inverting step-length during broadcasting According to and daily record data.
Selectively, further include：
Mining analysis module, for extracting acquisition delta data from the daily record data of the journal file of selection, formation is adopted Ji Bianhuashuojuji；The collection point alarm delta data and the topological correlation of oil-gas pipeline equipment concentrated according to acquisition delta data Relation finds the faulty equipment caused the accident using data mining.
Selectively, the data mining is that all frequent 1 item collections are found according to the branch topology relationship of oil-gas pipeline, Maximum frequent itemsets are obtained using Apirori algorithms, the corresponding oil of acquisition delta data concentrated according to the maximum frequent set Feed channel equipment positions faulty equipment.
The advantageous effect of technical solution provided in an embodiment of the present invention：
1st, real-time profile data and business datum can be periodically stored, using unified management mechanism to profile data and daily record Data are managed, and have compressed data storage capacity, have saved database storage resources, data tune when convenient for inverting and analyzing With.
2nd, after accident generation, by playing back the profile data and daily record data of the oil-gas pipeline in certain time, accurately Intuitively reflect the business datum situation of change in this period；It ensure that the integrality and correctness of data, be dispatcher Crash analysis provide technical guarantee, for further mining analysis provide data support.
3rd, Apirori algorithms are improved by topological correlation rule according to oil-gas pipeline feature and carries out data mining, it can be fast Faulty equipment is accurately positioned in speed, and the security for oil-gas pipeline equipment production run provides decision support, effectively improves scheduling Member's accident treatment efficiency, prevents the generation of pipeline major accident.
Description of the drawings
To describe the technical solutions in the embodiments of the present invention more clearly, make required in being described below to embodiment Attached drawing is briefly described, it should be apparent that, the accompanying drawings in the following description is only some embodiments of the present invention, for For those of ordinary skill in the art, without creative efforts, other are can also be obtained according to these attached drawings Attached drawing.
Fig. 1 is the flow chart of the crash analysis method according to an embodiment of the invention based on oil-gas pipeline SCADA system.
Fig. 2 is the structure of the accident analysis apparatus according to another embodiment of the present invention based on oil-gas pipeline SCADA system Block diagram.
Fig. 3 is the data trend figure of certain valve chamber outlet pressure of transferring natural gas from the west to the east in an example, wherein (a) is actual motion number According to (b) is operation inverting data.
Specific embodiment
To make technical scheme and advantage clearer, embodiment of the present invention is made below in conjunction with attached drawing into One step it is described in detail.
The technical concept of the present invention mainly includes three parts：Accident storage, accident inversion and accident mining analysis.Its In, accident storage part is unified to be stored data file and generates accident scene.Storage class is divided into daily record data storage and breaks Face data storage, daily record data are responsible for storage service data (therefore also by title daily record data), and real-time data base profile data is deposited Store up the function of completion timing interception real-time database profile data.Wherein, delta data of the business datum including acquisition, dispatcher are artificial Data of operation etc..Accident inversion mainly by the database under data section file access pattern to inverting state and parse send day Will file and the processing of responsible inverting instruction.Wherein, inverting instruction processing provides inverting and starts/pause instruction processing, inverting Step-length adjusts.Server-side will empty this all data of inverting example after inverting command for stopping is received, in real-time data base.Thing Therefore mining analysis generates accident set according to oil-gas pipeline equipment incidence relation, by receiving the delta data of time of casualty section, Analysis accident producing cause positions faulty equipment.And analysis result is showed into dispatcher by chart or graphics mode, simultaneously Generation accident knowledge base.
Wherein accident inversion is carried out on the basis of accident storage just provided skill for the crash analysis of dispatcher Art guarantee, it is believed that be a kind of crash analysis.Accident mining analysis is further point carried out using data mining technology Analysis.
Illustrative specific introduction is carried out to the present invention below by two embodiments.
As shown in Figure 1, one embodiment of the invention provides a kind of crash analysis side based on oil-gas pipeline SCADA system Method, including：
Step S1：According to the time interval of setting, the oil-gas pipeline that SCADA system collects is stored at regular intervals Profile data and daily record data form section file and journal file, and according to time sequencing Coutinuous store, the profile data The real-time running data of each equipment of oil-gas pipeline including SCADA system at a time each data collection point acquisition, it is described Daily record data includes acquisition delta data and manual operation data；
Note that profile data not necessarily includes all real-time running datas of a certain moment, and may be preassigned Some real-time running datas；Acquisition delta data refers to the data that can record daily state that acquisition comes.
Oil-gas pipeline SCADA system equipment measuring point is more, the various and substantial amounts of real time data complexity.Therefore the present invention uses Unified storage mode storage real time data.
Step S1, that is, casualty data storage, it is necessary to custom strategies come store and delete the daily creation data of pipeline (such as pressure, Flow, temperature) and real-time change daily record data.The present embodiment is in a manner that timing stores, according to the time set by user Interval preserves the section and daily record data of a SCADA system real-time data base at regular intervals.So as to be specified by generating In the range of data section, achieve the purpose that compress amount of storage.Section recovery can be also carried out in inverting simultaneously, is recovering section When, by searching for the holding time of section the data section recovered is needed to position.
For example, the profile data set according to operating personnel preserves interval t ', the accident of oil-gas pipeline SCADA system is utilized Data storage function obtains the profile data preserved for the real-time data base needs of crash analysis, and profile data is stored in In section information buffering area.Then the data in buffering area are write into section file fi' in, and add and break in real-time data base Face data stored record.So as to which all section files form section file set F ', i.e.,:
F '={ f1′,f2′,f3′,LL}
The information such as oil-gas pipeline SCADA system acquisition delta data, control can not be showed comprehensively by only retaining profile data.Cause This, oil-gas pipeline SCADA system not only stores real-time data base profile data, also preserves acquisition delta data, manually control, behaviour The business diaries information such as work, limit value modification, that is, carry out daily record data storage.The object of daily record data storage is business data flow, Such as business data flow can be stored in the form of binary file in journal file.Configuration is needed to protect by daily record data storage For the business datum deposited using time t as interval, the reading of content business datum from the log buffer area of SCADA system passes through file Journal file l is write in serviceiIn, and journal file stored record is added in real-time data base.Final service data form day Will file set L, i.e.,:
L={ l1,l2,l3,LL}
Therefore, as R, i.e., the real-time data base business processing data relative recording of casualty data storage integrates:
R=F ' UL={ f1′,l1,f2′,l2,f3′,l3,LL}
Accident storage service accident scene triggering mode includes triggering and automatic trigger manually, and triggering manually can trigger morning In the scene e of any time in journal file retention cycle of current timei.Automatic trigger supports setting accident triggering item Part, when the condition is satisfied, triggering accident storage automatically generate scene, in order to the inverting of accident and accident rational analysis.Finally As E, i.e., the accident scene of composition integrates：
E={ e1,e2,e3,LL}(ei∈R)
The casualty data storing step of the embodiment can periodically store real-time profile data and business datum, using unified Administrative mechanism is managed profile data and daily record data, has compressed data storage capacity, has saved database storage resources, just Data call when inverting and analysis.
Step S2：When needing inverting, the section file and journal file of selection are called, sequentially in time selected by broadcasting The daily record data that the profile data and journal file that the section file selected includes include.
Accident inversion server-side is by accident scene eiData carry out playback process, according to the demand of user push inverting knot Fruit ensure that the personalized use of oil-gas pipeline SCADA software systems accident inversion modules, be carried for the crash analysis of dispatcher For technical guarantee.
To ensure that accident inversion does not interfere with oil-gas pipeline real time monitoring, and it can accurately carry out crash analysis, oil-gas pipeline The accident inversion of SCADA system uses inverting state real-time data base.The data structure and SCADA system of inverting state real-time data base Database real time data structure it is identical, but be directed to different application services.Using inverting state real-time data base into Row accident inversion data playback can either avoid influencing real time data displaying, and the purposes of data can be classified exactly And analysis.After accident inversion, which receives, to be started to send broadcast event, accident inversion is (simple according to the inverse time axis step-length of setting Referred to as inverting step-length), periodic refreshing for the data in the real-time data base of casualty data storage to inverting state real-time data base, Can recreating accidents occur front and rear scene.
For example, dispatcher selects inverting scene e by accident inversion interfacei, accident inversion client sends a message to thing Therefore inverting server-side, accident inversion server-side obtain inverting scene eiInverting condition, that is, start inverse time, terminate inverting when Between, the information such as inverse time axis step-length.Above inverting broadcast strategy can ensure dispatcher to inverse time, inverting step-length It is self-defined, improve the availability of accident inversion.
Therefore, the section file of selection and journal file is called to include in the step：
According to the beginning inverse time of setting and terminate inverse time, the selection record time is starting inverse time and end All section files and journal file between inverse time are as the section file and journal file called.
Meanwhile profile data and journal file that selected section file includes are played in the step sequentially in time Comprising daily record data include：Profile data and daily record data are refreshed according to the inverting step-length of setting during broadcasting.
Such as it is realized especially by following measure.
Obtain inverting scene eiAfter information, accident inversion recovers section using profile data correction strategy.Section file The data value of user-defined sart point in time may not recorded with journal file.If without profile data amendment, thing Therefore inverting can not ensure the accuracy of inverting data.Therefore by inverting scene eiIn journal file collection L daily record data recover Data correction is carried out to inverting state real-time data base.The journal file l being successively read in daily record collection Li, judge liRecord end Time teiWith inverting scene start time tsSequencing, by teiEarlier than tsWhole journal files recover to inverting node into Row data correction.After inverting starts, according to inverting scene eiAt the beginning of tsDaily record is read, judges daily record collection L and section successively Whether the file of collection F ' needs to be restored to inverting state real-time database, works as tiIt is later than inverting end time teWhen, then terminate inverting clothes Business.
The accident inversion step of the embodiment is after accident generation, by playing back the oil-gas pipeline section number in certain time According to and daily record data, the business datum situation of change in accurate and visual reflection this period；Ensure that data integrality and Correctness provides technical guarantee for the crash analysis of dispatcher, data branch is provided for further mining analysis It holds.
In order to realize intelligent crash analysis, as shown in Figure 1, the present embodiment still further comprises step S3：From selection Extraction acquisition delta data in the daily record data of journal file, forms acquisition delta data collection；It is concentrated according to acquisition delta data Collection point alarm delta data and oil-gas pipeline equipment branch topology relationship, being found using data mining is caused the accident Faulty equipment.Extraction acquisition delta data, however, the present invention is not limited thereto in the journal file usually called in inverting.This In collection point alarm delta data refer to undergo mutation compared with the data collected before and cause to accuse beyond preset range Alert data.
For example with being associated rule digging based on the sorting technique of support vector machines.The core of association rule mining It is to obtain frequent item set.In the excavation of oil-gas pipeline casualty data, candidate is oil-gas pipeline devices collect data collection AP, I.e.：
AP={ AP1,AP2,AP3,AP4,L L}
But oil-gas pipeline SCADA system equipment is numerous, gathered data amount is generally all more, if data set AP's On the basis of carry out data mining and generate frequent item set, it is higher and the problems such as Result is unreliable it will cause resource is occupied. Accident is all often that the relevant device with topological relation causes in oil-gas pipeline SCADA system, has certain correlation rule, Therefore calculation amount can effectively be reduced to establish candidate according to topological structure relation.Apriori algorithm is suitable for Maximum Frequent In item collection (maximum frequent itemsets are the frequent item sets for meeting no superset condition in each frequent k item collections) relatively small data set Association rule mining, the present embodiment improve the acquisition of Apriori algorithm progress frequent item set using topological correlation rule.
In this step, the basic data of crash analysis is parsing day for the data set D ', D ' after accident inversion pretreatment The acquisition delta data that will file set L is drawn, i.e.,:
According to the collection point alarm variable information in D ', in the maximum frequent itemsets F that data mining is drawnkMiddle analysis is drawn The faulty equipment caused the accident positions faulty equipment, then carries out manual analysis, determine size and the influence of failure, be The security of pipe-line equipment production run provides decision support.
Therefore, data mining here is that all frequent 1 item collections are found according to the branch topology relationship of oil-gas pipeline, profit Maximum frequent itemsets are obtained with Apirori algorithms, the corresponding oil-gas pipeline of acquisition delta data concentrated according to maximum frequent set Equipment positions faulty equipment.The acquisition delta data that maximum frequent set is concentrated is measured by measurement equipment, corresponding to one or more The operation of oil-gas pipeline equipment wherein just there is the faulty equipment that failure is caused to occur, therefore can be concentrated by maximum frequent set Acquisition delta data position faulty equipment, maximum frequent itemsets are simpler, easier positioning.
For example, the pseudocode that oil-gas pipeline accident Mining Frequent Itemsets Based generates algorithm is as follows：
1.K=1
2.Fk=find_freq_itemset_topo (AP) { has found all frequent 1 item collections according to topological relation }
3.repeat
4.k=k+1
5.Ck=apriori_gen (Fk- 1) { generation candidate }
The each affairs t ∈ T do of 6.for
7.Ct=subset (Ck, t) and { identification belongs to all candidates of t }
The each candidate c ∈ C of 8.fort do
9. б (c)=б (c)+1 { support counting increment }
10.end for
11.end for
12 Fk=c | c ∈ Ck∩б({c})≥N*min_sup}
{ extracting frequent k- item collections }
13.until Fk=Φ
14.Result=UFk
Meanwhile the accident knowledge base (accident data obtained after crash analysis, for next time generated after crash analysis Referred to during analysis), available for real-time accident early warning assistant analysis, dispatcher's accident treatment efficiency is effectively improved, prevents pipeline weight The generation of major break down.
The accident mining analysis of the present embodiment improves Apirori by topological correlation rule according to oil-gas pipeline feature and calculates Method carries out data mining, can quick and precisely position faulty equipment, the security for oil-gas pipeline equipment production run provides certainly Plan is supported, is effectively improved dispatcher's accident treatment efficiency, is prevented the generation of pipeline major accident.
Based on the same idea with method, another embodiment of the present invention additionally provides a kind of based on oil-gas pipeline SCADA systems The accident analysis apparatus of system, as shown in Fig. 2, including：
Memory module 1 for the time interval according to setting, stores the oil that SCADA system collects at regular intervals The profile data and daily record data of feed channel, form section file and journal file, and profile data includes SCADA system a certain The real-time running data of each equipment of oil-gas pipeline of moment each data collection point acquisition, daily record data include acquisition delta data With manual operation data；
Inverting module 2, for when needing inverting, calling the section file of selection and journal file, sequentially in time Play the profile data that selected section file includes and the daily record data that journal file includes.
Wherein, the section file of selection and journal file is called to include in inverting module 2：
According to the beginning inverse time of setting and terminate inverse time, the selection record time is starting inverse time and end All section files and journal file between inverse time are as the section file and journal file called.
Profile data and the journal file bag that selected section file includes are played in inverting module 2 sequentially in time The daily record data contained includes：Profile data and daily record data are refreshed according to the inverting step-length of setting during broadcasting.
It is further improved as the embodiment, which further includes：
Mining analysis module 3：For extracting acquisition delta data from the daily record data of the journal file of selection, formation is adopted Ji Bianhuashuojuji；The collection point alarm delta data and the topological correlation of oil-gas pipeline equipment concentrated according to acquisition delta data Relation finds the faulty equipment caused the accident using data mining.
Wherein, the data mining in mining analysis module 3 is all according to the discovery of the branch topology relationship of oil-gas pipeline Frequent 1 item collection obtains maximum frequent itemsets, the acquisition delta data pair that the maximum frequent set is concentrated using Apirori algorithms The oil-gas pipeline equipment answered is faulty equipment.
The module of the present embodiment is corresponded with the step of upper embodiment of the method, and the explanation of a upper embodiment of the method is similary Suitable for the present embodiment, therefore, the details and advantage of the present embodiment will not be described in great detail, and may refer to an embodiment.
Illustrate the effect of the present invention with an example below.
Certain year year in such a month, and on such a day 8:55 points to 9:11/, it is automatic that certain valve chamber main line block valve has occurred in transfering natural gas from the west to the east line Shut-off accident.By oil-gas pipeline SCADA system west_east gas transmission pipeline year year in such a month, and on such a day 10:03 point to 10:18 points of SCADA The real time data bag of system carries out data inversion and failure point using inverting module as actual motion status data to data Analysis, carries out comparison check with actual motion state, and examines the availability of failure analysis result.
SCADA system configuration storage collection point 285, the scene include section file 1, journal file 14.Inverting Data are compared with actual motion business datum, and in actual moving process, business datum number is 23543, inversion result industry Business data amount check is 23535, and the two number is essentially identical, and business datum inverting is consistent with the actual running results.
Inverting data carry out curve comparison with actual motion business datum, pass through certain valve obtained during comparing actual motion The real time execution curve and inversional curve of room outlet pressure, data match rate reach 99%.And equipment operation condition can be more Comprehensively show.The results are shown in Figure 3 for carrying out practically：
By crash analysis reasoning, it was therefore concluded that be since the latter valve chamber main line block valve of the valve chamber accidental switches off Afterwards, engineering staff opens latter valve chamber, the valve chamber outlet pressure is caused to decline very fast, and the thing that the valve chamber is automatically closed has occurred Therefore.
It can be seen that the crash analysis method of the present invention can carry out accident inversion after accident generation, accurately and effectively Position failure occurrence of equipment.
It will be appreciated by those skilled in the art that hardware can be passed through by realizing all or part of step, module of above-described embodiment It completes, relevant hardware can also be instructed to complete by program.Program can be stored in a kind of computer-readable storage medium In matter, storage medium can be read-only memory, disk or CD etc..
The present invention can increase necessary hardware and software in existing oil-gas pipeline SCADA system and realize, effectively profit With existing resource, time and the cost of exploitation are saved.
The above is for only for ease of it will be understood by those skilled in the art that technical scheme, not limiting The present invention.Within the spirit and principles of the invention, any modifications, equivalent replacements and improvements are made should be included in this Within the protection domain of invention.

Claims (10)

  1. A kind of 1. crash analysis method based on oil-gas pipeline SCADA system, which is characterized in that including：
    According to the time interval of setting, store at regular intervals the oil-gas pipeline that SCADA system collects profile data and Daily record data forms section file and journal file, and the profile data includes SCADA system, and at a time each data are adopted The real-time running data of each equipment of oil-gas pipeline of collection point acquisition, the daily record data include acquisition delta data and manual operation Data；
    When needing inverting, the section file and journal file of selection are called, plays selected section text sequentially in time The daily record data that the profile data and journal file that part includes include.
  2. 2. crash analysis method according to claim 1, which is characterized in that the section file for calling selection and daily record File includes：
    According to the beginning inverse time of setting and terminate inverse time, the selection record time is starting inverse time and terminating inverting All section files and journal file between time are as the section file and journal file called.
  3. 3. crash analysis method according to claim 1, which is characterized in that it is described play sequentially in time it is selected The daily record data that the profile data and journal file that section file includes include includes：According to the inverting step-length brush of setting during broadcasting New profile data and daily record data.
  4. 4. according to claim 1-3 any one of them crash analysis methods, which is characterized in that further include：
    The extraction acquisition delta data from the daily record data of the journal file of selection, forms acquisition delta data collection；
    The collection point alarm delta data and the branch topology relationship of oil-gas pipeline equipment concentrated according to acquisition delta data, utilize The faulty equipment caused the accident is found in data mining.
  5. 5. crash analysis method according to claim 4, which is characterized in that
    The data mining is that all frequent 1 item collections are found according to the branch topology relationship of oil-gas pipeline, is calculated using Apirori Method obtains maximum frequent itemsets, and the corresponding oil-gas pipeline equipment of acquisition delta data concentrated according to the maximum frequent set positions Faulty equipment.
  6. 6. a kind of accident analysis apparatus based on oil-gas pipeline SCADA system, which is characterized in that including：
    Memory module for the time interval according to setting, stores the oil-gas pipeline that SCADA system collects at regular intervals Profile data and daily record data, form section file and journal file, the profile data includes SCADA system at certain for the moment The real-time running data of each equipment of oil-gas pipeline of each data collection point acquisition is carved, the daily record data includes acquisition variation number According to manual operation data；
    Inverting module for when needing inverting, calling the section file of selection and journal file, plays institute sequentially in time The daily record data that the profile data and journal file that the section file of selection includes include.
  7. 7. accident analysis apparatus according to claim 6, which is characterized in that the section of selection is called in the inverting module File and journal file include：
    According to the beginning inverse time of setting and terminate inverse time, the selection record time is starting inverse time and terminating inverting All section files and journal file between time are as the section file and journal file called.
  8. 8. accident analysis apparatus according to claim 6, which is characterized in that broadcast sequentially in time in the inverting module Putting the profile data that selected section file includes and the daily record data that journal file includes includes：It is walked according to the inverting of setting It is long, profile data and daily record data are refreshed according to inverting step-length during broadcasting.
  9. 9. according to claim 6-8 any one of them accident analysis apparatus, which is characterized in that further include：
    Mining analysis module for the extraction acquisition delta data from the daily record data of the journal file of selection, forms acquisition and becomes Change data set；The collection point alarm delta data and the topological correlation of oil-gas pipeline equipment concentrated according to acquisition delta data close System, the faulty equipment caused the accident is found using data mining.
  10. 10. accident analysis apparatus according to claim 9, which is characterized in that
    The data mining is that all frequent 1 item collections are found according to the branch topology relationship of oil-gas pipeline, is calculated using Apirori Method obtains maximum frequent itemsets, and the corresponding oil-gas pipeline equipment of acquisition delta data concentrated according to the maximum frequent set positions Faulty equipment.
CN201610986160.7A 2016-11-09 2016-11-09 Crash analysis method and apparatus based on oil-gas pipeline SCADA system Pending CN108073586A (en)

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CN111198853A (en) * 2018-11-16 2020-05-26 北京微播视界科技有限公司 Data processing method and device, electronic equipment and computer readable storage medium
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CN112147459A (en) * 2020-08-12 2020-12-29 国电南瑞科技股份有限公司 Power grid fault analysis device and method based on SCADA system
CN116255570A (en) * 2022-12-22 2023-06-13 新疆敦华绿碳技术股份有限公司 Pipeline monitoring and hidden danger analyzing method and system for carbon dioxide trapping

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