CN104978405A - Human error data processing method ans system - Google Patents
Human error data processing method ans system Download PDFInfo
- Publication number
- CN104978405A CN104978405A CN201510311836.8A CN201510311836A CN104978405A CN 104978405 A CN104978405 A CN 104978405A CN 201510311836 A CN201510311836 A CN 201510311836A CN 104978405 A CN104978405 A CN 104978405A
- Authority
- CN
- China
- Prior art keywords
- data
- people
- mistake
- database
- check
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/21—Design, administration or maintenance of databases
- G06F16/211—Schema design and management
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/21—Design, administration or maintenance of databases
- G06F16/215—Improving data quality; Data cleansing, e.g. de-duplication, removing invalid entries or correcting typographical errors
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/24—Querying
- G06F16/245—Query processing
- G06F16/2458—Special types of queries, e.g. statistical queries, fuzzy queries or distributed queries
- G06F16/2462—Approximate or statistical queries
Abstract
The present invention discloses a human error data processing method and system. The human error data processing method comprises: a data reception step, which is used for collecting and receiving source data to be analyzed, wherein the source data is human error data in a human-computer interaction process, and importing the source data into a human error database; a data management step, which is used for managing the source data and carrying out maintenance on codes of the human error database; and a data application step, which is used for performing statistical analysis and data mining on the source data based on a component technology. According to the human error data processing method provided by the present invention, the human error data generated in the human-computer interaction process is collected and imported into the human error database, and the statistical analysis and mining of the source data are implemented by using the component technology, so that supporting the data statistical analysis and mining and the effective collection of the human error data of a digital control system are simultaneously implemented, and the reliability and efficiency of the human error data processing are significantly improved.
Description
Technical field
The present invention relates to Human Engineering and infotech crossing domain, especially, relate to a kind of people for nuclear power plant's Digitizing And Control Unit data mart modeling disposal route and system by mistake.
Background technology
In the scale complex systems such as nuclear power, Aero-Space, petrochemical complex, the importance of man-machine interaction receives general concern day by day.On the one hand, effective man-machine interaction can promote reliability and the security of system; On the other hand, man-machine interaction is again the direct sources causing human-equation error, once man-machine interaction goes wrong, then task may be caused to lose efficacy or catastrophic failure.The event report that core operator association of the world (World Association of Nuclear Operators, WANO) issues every year is thousands of part nearly, is a kind of unstructured data presented with html web page form.For a long time, researchist is saved in EXCEL document win useful data from webpage after mainly with the mode of artificial treatment, contrast WANO coded system greatly again, work numerous and diverse and the visualization of data is not high, extendability is strong, accuracy also can not be guaranteed, cause the inefficiency of research work, flow process chaotic, be unfavorable for carrying out and carrying out of research work.
Therefore the system building a kind of WANO of support people mistake statistic analysis has seemed particularly urgent, but not yet exist in prior art and be applied to the automatic processing and treating method that field of human-computer interaction people misses data (i.e. human-equation error data), need artificial treatment mode to carry out processing process, the extendability of not only inefficiency and reliability and follow-up data application all can not be guaranteed.
Summary of the invention
The invention provides a kind of people data mart modeling disposal route and system by mistake, systematically cannot miss to people the technical matters that data carry out statistical study and excavation process to solve existing field of human-computer interaction.
The technical solution used in the present invention is as follows:
According to an aspect of the present invention, provide a kind of people data mart modeling disposal route by mistake, the people for the generation of digital control system interactive process misses the processing process of data, and people by mistake data mart modeling disposal route comprises:
Data reception step, for gathering and receiving source data to be analyzed, source data is the people's data by mistake in interactive process, and source data is imported people's database by mistake;
Data management step, for managing source data and safeguarding the coding of people's mistake database;
Market demand step, carries out statistical study and data mining based on component technology to source data.
Further, data reception step comprises:
Data inputting, for gathering and receiving people's by mistake data of history,
Data check and examination & verification, carry out data check and data examination & verification for missing data to the people received;
Wherein, data check is used for mating the people the received coding scheme that data miss database by verification static class method with people by mistake, by the database by mistake of the data importing people by verification, data examination & verification is used for carrying out authority supervision with the security ensureing data to the data variation in people by mistake database.
Further, data inputting comprises:
Receive formatted document data and formatted document data are carried out secondary encapsulation and build static class and import people's database by mistake;
Receive html document data and import people's database by mistake;
By interface accessing background data base so that the data importing people in background data base is missed database.
Further, data management step comprises:
Data source manages, and for managing the data structure of source data, is convenient to miss from people the Data View that database obtains customization;
Code Maintainability, increases for data encoding people being missed to database, check, revises and soft delete;
Data maintenance, for modifying to the incident report data stored in people by mistake database, check and soft delete;
Assembly management, for increasing the various application component information missing database based on people, check, revise and delete,
Template Manager, for managing applying template, comprising and increasing applying template, check, revises and delete, and applying template is used for statistical conversion or report output.
Further, market demand step comprises:
Statistical study, obtains statistic analysis result for carrying out statistical study based on component technology;
Data mining, obtains data mining results for carrying out data mining based on component technology;
Statistical conversion, for becoming formatted document by the statistical conversion in people by mistake database;
Report output, for becoming data sheet by the statistical conversion in people by mistake database.
According to a further aspect in the invention, also provide a kind of people data mart modeling disposal system by mistake, the people for the generation of digital control system interactive process misses the processing process of data, and people by mistake data mart modeling disposal system comprises:
Data reception module, for gathering and receiving source data to be analyzed, source data is the people's data by mistake in interactive process, and source data is imported people's database by mistake;
Data management module, for managing source data and safeguarding the coding of people's mistake database;
Market demand module, for carrying out statistical study and data mining based on component technology to source data.
Further, data reception module comprises:
Data entry element, for gathering and receiving people's by mistake data of history,
Data check and examination & verification unit, data check and data examination & verification is carried out for missing data to the people received, wherein, data check is used for mating the people the received coding scheme that data miss database by verification static class method with people by mistake, by the database by mistake of the data importing people by verification, data examination & verification is used for carrying out authority supervision with the security ensureing data to the data variation in people by mistake database.
Further, data entry element comprises:
First receives subelement, builds static class for receiving formatted document data and formatted document data being carried out secondary encapsulation and imports people's database by mistake;
Second receives subelement, for receiving html document data and importing people's database by mistake;
3rd receives subelement, for passing through interface accessing background data base so that the data importing people in background data base is missed database.
Further, data management module comprises:
Data source administrative unit, for managing the data structure of source data, is convenient to miss from people the Data View that database obtains customization;
Code Maintainability unit, increases for data encoding people being missed to database, check, revises and soft delete;
Data maintenance unit, for modifying to the incident report data stored in people by mistake database, check and soft delete;
Assembly management unit, for increasing the various application component information missing database based on people, check, revise and delete,
Template Manager unit, for managing applying template, comprising and increasing applying template, check, revises and delete, and applying template is used for statistical conversion or report output.
Further, market demand template comprises:
Statistical analysis unit, obtains statistic analysis result for carrying out statistical study based on component technology;
Data mining unit, obtains data mining results for carrying out data mining based on component technology;
Statistical conversion unit, for becoming formatted document by the statistical conversion in people by mistake database;
Report output unit, for becoming data sheet by the statistical conversion in people by mistake database.
The present invention has following beneficial effect:
The present inventor is data mart modeling disposal route and system by mistake, gather by missing data to the people produced in interactive process and import people's database by mistake, component technology is adopted to realize the statistics of source data, analysis and excavation, achieve the statistics of supported data while effectively gathering digital control system people mistake data, analyze and excavate, reliability and the treatment effeciency of the process of people's mistake data mart modeling are all significantly improved.
Except object described above, feature and advantage, the present invention also has other object, feature and advantage.Below with reference to figure, the present invention is further detailed explanation.
Accompanying drawing explanation
The accompanying drawing forming a application's part is used to provide a further understanding of the present invention, and schematic description and description of the present invention, for explaining the present invention, does not form inappropriate limitation of the present invention.In the accompanying drawings:
Fig. 1 is the schematic flow sheet that preferred embodiment of the present invention people misses data mart modeling disposal route; And
Fig. 2 is the structural representation that preferred embodiment of the present invention people misses data mart modeling disposal system.
Embodiment
Below in conjunction with accompanying drawing, embodiments of the invention are described in detail, but the multitude of different ways that the present invention can be defined by the claims and cover is implemented.
It should be noted that, term " first ", " second " etc. in instructions of the present invention and claims and above-mentioned accompanying drawing are for distinguishing similar object, and need not be used for describing specific order or precedence.Should be appreciated that the data used like this can be exchanged in the appropriate case, to understand the embodiments of the invention described.In addition, term " comprises " and " having " and their any distortion, intention is to cover not exclusive comprising, such as, contain those steps or unit that the process of series of steps or unit, method, system, product or equipment is not necessarily limited to clearly list, but can comprise clearly do not list or for intrinsic other step of these processes, method, product or equipment or unit.
The preferred embodiments of the present invention provide a kind of people for nuclear power plant's electronic control system data mart modeling disposal route by mistake, people for producing this digital control system interactive process misses data and carries out processing process, and the present embodiment people by mistake data mart modeling disposal route comprises:
Data reception step, for gathering and receiving source data to be analyzed, source data is the people's data by mistake in interactive process, and people herein by mistake data refers to human-equation error data, and source data is imported people's database by mistake; The nuclear power plant accident report of the present embodiment by issuing every year WANO, adopts various ways to carry out effective data acquisition to it, sets up WANO people's database by mistake;
Data management step, for managing source data and safeguarding the coding of people's mistake database; Managed and Code Maintainability by source data WANO people being missed to database, the readability of system data and intelligibility are improved;
Market demand step, carries out statistical study and data mining based on component technology to source data.The present embodiment carries out statistical study to source data and data mining comprises: one, the selection of data mining algorithm and realization, and particularly, the application component set by means of VS development platform forms; Two, the preparation of data source, calls for subsequent applications; Three, the integration of application component and system, calling and parameter configuration of application component.
The present embodiment gathers by missing data to the people produced in interactive process and imports people's database by mistake, component technology is adopted to realize the statistics of source data, analysis and excavation, achieve the statistics of supported data while effectively gathering digital control system people mistake data, analyze and excavate, reliability and the treatment effeciency of the process of people's mistake data mart modeling are all significantly improved.
With reference to Fig. 1, particularly, the present embodiment data reception step comprises:
Data inputting, for gathering and receiving people's by mistake data of history, wherein, the people of history by mistake data mainly comprises the human-equation error data in nuclear power plant's accident report that WANO issues;
Data check and examination & verification, carry out data check and data examination & verification for missing data to the people received; Wherein, data check is used for mating the people the received coding scheme that data miss database by verification static class method with people by mistake, by the database by mistake of the data importing people by verification, data examination & verification is used for carrying out authority supervision with the security ensureing data to the data variation in people by mistake database.
In the present embodiment, the source of source data mainly comprises: the background data base of formatted document data, html document data and WANO exploitation.Accordingly, data inputting comprises:
1, receive formatted document data and formatted document data carried out secondary encapsulation structure static class and import people's database by mistake; Formatted document for be accumulate in long-term WANO people by mistake research work, through standardization processing, the data that database format requires can be met, main forms is EXCEL document, and the needs simultaneously for meeting expanding of system function additionally provide the type text document data such as TXT, WORD.Data importing function realizes based on COM (common component model) technology of .NET platform intergration, for to EXCEL format file data importing functional realiey: Microsoft.Office.Interop.Excel.dll procedure set is that the .NET to Excel COM that Microsoft provides encapsulates, its inside defines various method of operating and the document properties of EXCEL document object, can realize operating the major part of EXCEL document object by it.Native system is on the basis of quoting Microsoft.Office.Interop.Excel.dll procedure set, with .NET code, secondary encapsulation is carried out to some EXCEL document methods of operating that native system is conventional and construct ExcelHelper static class, to provide the support to EXCEL document operation, then just at the Business Logic of system, the data manipulation of EXCEL document object can be realized by the method for packing called in static class.
2, receive html document data and import people's database by mistake; The document for be the event report of the html web page form that WANO issues in its official website, due to html document form lack of standard and interior data also present with unformatted form, for this system provides two kinds of modes, interior data is collected.It is a kind of automatic data accquisition based on html document data mining technology and processing mode that document is resolved, and can reduce the workload of Data Collection to a great extent, improves the accuracy of data.Manual data collection is based on the understanding of individual to document, and contrast WANO coding schedule extracts data, thus reaches the method for Data Collection object, and its advantage is strong adaptability, and adjustable amplitude is large.Its principle realized is, by individual from html document, the information needed for extraction, comprise WANO coding, the date occurs event, Report Type etc., then the database format automatically realizing data according to WANO data encoding by system is changed.
3, by interface accessing background data base with by the by mistake database of the data importing people in background data base, its background data base API Access interface developed by WANO, thus reach the object of Data Collection.
The safety and reliability of data is foundation stones that WANO people studies by mistake, and be the key drawing correct statistic analysis result, the present embodiment is provided safeguard to data safety and reliability by these two flow processs.Wherein, data check flow process is mated with WANO coding scheme by the data check static class method of call definition in Business Logic in earlier stage collecting the data obtained, and identify the data item that it fails to match, for data processing provides support, the data only having verification to pass through could stored in WANO people's database by mistake.Data auditing flow exercises supervision to system data change (comprising data maintenance, data inputting), and the data variation only having examination & verification to pass through just can be reflected in market demand effect.Preferably, also comprise log management, log management defines checking and deletion action flow process system journal, and daily record is derived and defined user according to the function self needed daily record guiding system.
Database occupies very important status in an infosystem, the quality of database structure has an impact direct to the efficiency of application system and the effect of realization, the design of rational database structure can improve the efficiency that data store, and ensures the integrality of data, consistance and security and reduces the difficulty of system application and development.Access function of the present invention completes under the support of the Autocad PowerDesigner of Sysbase company exploitation, first structure concept model is needed, the relation between definition entity attributes field, entity and the identification field of entity based on WANO coding scheme and practical application.Secondly on the basis of conceptual model, derived the logical model of its correspondence by PowerDesigner, in logical model, refinement is carried out to the substantial definition in conceptual model and entity relationship definition.Third by Autocad, architecture model and concrete database (native system select be SQL2008) are combined, form corresponding physical model.Last structure script of automatically deriving database on the basis of physical model, with the Account login DBMS configured, performs above-mentioned script in query analyzer, finally completes Basic Design and realization that WANO people misses database.
The present embodiment data management step is used for, for applying the support providing data, assembly and template, specifically comprising:
Data source manages, and for managing the data structure of source data, is convenient to miss from people the Data View that database obtains customization.Particularly, managed the Data View of system by data source management, obtain source data based on WANO Database Events coding, then edit and process it, the query statement of shape paired data storehouse fact table, for market demand;
Code Maintainability, increases for data encoding people being missed to database, check, revises and soft delete;
Data maintenance, for modifying to the incident report data stored in people by mistake database, check and soft delete;
Assembly management, for increasing the various application component information missing database based on people, check, revise and delete, because the application function of native system has all come based on component technology, so assembly management is most important, each assembly can provide some standards and simple application interface, allows user to arrange and adjusts parameter and attribute.By component technology, multiple assemblies of separate sources can organically combine by user, form complexity (large-scale) application program of correspond to actual needs (and relative low price) fast.Based on the needs of system component management, developer component management control, achieves to change the additions and deletions of system component and looks into operation.Particularly, in the present embodiment, assembly management interface forms primarily of three TAB pages, wherein, increases assembly TAB page and is mainly used in increasing module information in system component configuration file (adopting XML document to preserve configuration information in the present system); The component list TAB page the mode of list can browse the module information of having added, and deletes module information by it; Editing files TAB page display module information in the format of a xml document, can edit-modify configuration information greatly by it.The calling function of assembly realizes based on the procedure set reflection technology of .NET, just can build an entity object for correlation analysis by following code segment:
Wherein: the memory location of what AssemblyPath represented the is procedure set of definitions component; The NameSpace of what ClassNamespace represented is component definition; What WANO.DataMinning.RelevancyAlgorithm represented is the correlation analysis class defined in NameSpace.In general, this part is made up of business function and external interface two parts.Business function provides many system built-in services, as function of statistic analysis, data mining capability, data visualization function etc.; External interface mainly provides some and accesses the interface of other application program as SPSS, SAS, EXCEL etc., thus some powers using other application program realize system extension.
Template Manager, for managing applying template, comprising and increasing applying template, check, revises and delete, and applying template is used for statistical conversion or report output.
In the present embodiment, market demand step comprises:
Statistical study, obtains statistic analysis result for carrying out statistical study based on component technology; Be exemplified below:
Default scene: basic data statistics and data visualization are WANO people's parts that research work is indispensable by mistake, conveniently easily expands and the exploration of effect of visualization well for data rule is most important.The present embodiment for most basic statistics operation (personel accident impact and consequence distribution statistics) in WANO people by mistake research in WANO people by mistake statistical analysis system realize thought and step is introduced.
Solution: first with suitable identity authority accessing system, choose the data source needed for operation after entering system statistical analysis operation interface, then the data item in data source is screened.Need to get out applying template according to task and set the corresponding attribute of template, data statistics task can be completed.Concrete steps are as follows:
(1) with suitable identity authority accessing system, the data source needed for operation is chosen (to choose and got out data source " 2001-2010 event consequence statistics " after entering system statistical analysis operation interface here, step 1), in tables of data, certain screening (removing distracter or incoherent item, step 2) is carried out to the data item in data source.
(2) determine that the type of task (selects " data statistics " here, step 3), then prepare and select then corresponding applying template (to select the test template " histogram 001 " of the then system integration here, step 4), in the forms ejected, set the attribute of applying template simultaneously, Data distribution8 statistical graph can be obtained.
(3) Corpus--based Method chart carries out data analysis (data visualization that system support is real-time, the data namely in the form of amendment top can be reflected in current statistical graph in real time).
Data mining, obtains data mining results for carrying out data mining based on component technology; Be exemplified below:
Preset scene: association rule mining is widely used in recent years as a core application of DM technology, this is because correlation rule is not many times proven by traditional causality analysis or reasoning as the recessive relation existed between a kind of things, but but outwardness and the life and work on people produce the impact (typical apply of this respect has market basket analysis, customer loyalty analysis etc.) that can not be ignored to this relation rule.Same Association Rule Analysis also can be the research of WANO people's mistake as a kind of practical technique and contributes, the excavation of the correlation rule between event related personnel is for instructing nuclear power station staff training, managing to improve personnel's cooperation efficiency, reduction people by mistake probability of happening has important directive significance, and this part of research will introduce the data analysis operation step missing statistical analysis system with example based on WANO people with the analytical work of event related personnel correlation rule.
Solution: the data analysis work missing statistical analysis system based on WANO people relates generally to three aspect core contents.The selection of first data mining algorithm and realization, the action need of this part completes outside system, realization (generation of applying template) for algorithm native system needs to realize by means of the procedure set technology of VS development platform (best configuration is VS 2010, NET4.0 version).It two is preparations of data source, existingly before this part operation introduces, and concrete operations are similar, skip over here.It three is integration of applying template and system, calling and parameter configuration of applying template.Concrete operation steps is as follows:
(1) the assessment of algorithm, selection and analysis (this research, based on familiarity and the consideration that easily realizes, selects the association rules mining algorithm of these classics of Apriori exemplarily).In existing all kinds of association rule algorithm, Apriori algorithm be wherein affected the most extensive the most basis boolean association rule Frequent Itemsets Mining Association Rules Algorithm, other association rule algorithm is derived from Apriori algorithm mostly.Its core concept is from Candidate Set C
k-1in by scanning affairs collection T, find out the Item Sets I being not less than minimum support
1, be called Frequent Set F
k-1; Again with Frequent Set F
k-1by generating new Candidate Set C from connection and beta pruning computing
k, Candidate Set C
kfrequent Set L is found out again by scanning affairs collection
k, so circulation is until cannot concentrate in affairs and find Frequent Set.Its internal processes is as follows:
Whole flow process is made up of five parts, wherein, and input: affairs collection T, minimum support Min; Export: the Frequent Set L existed in affairs collection T; Process one: find and generate the concentrated Frequent Set of things (first to produce Frequent Set L
1, then produce L
2, so circulation is until L
kin no longer contain item till.); Process two: generate Candidate Set and (call process three, by L
k-1certainly connecting of Frequent Set produces Candidate Set and carries out beta pruning.Because theoretical according to the Item Sets of Agrawal, Frequent Item Sets can not be the subset of Infrequent item-set.); Process three: connect and beta pruning.
By arthmetic statement we can find Apriori algorithm realize two committed steps be respectively connect and beta pruning.Wherein the step of attended operation refers to and passes through L
k-1produce Candidate Set C from connecting
k.Specific rules is: suppose L
k-1in include l
1and l
2two item collection, the identical and item collection I of their front n item
1(n+1)th be greater than I
2, then two item collection can be merged together.Cut operator is then the Candidate Set C produced for attended operation
k, again scan affairs collection, obtain C
kin support of each collection, remove the item collection that those do not meet support restriction, thus obtain Frequent Set F
k.
(2) the generation of applying template, namely sets of applications exploitation (C# language realizes Apriori algorithm) under VS development platform, corresponding with code analysis result, its core code is also generated by frequent item set, candidate generates and correlation rule generates three main disposal routes and forms, and function structure is as follows:
(3) enter system component administration module with suitable identity authority (system manager), applying template is loaded in system environments.Choose the procedure set that institute's previous step generates) (step 1), add (step 2) after improving descriptor successively, then exit administration module (step 3)
(4) data source prepares, and gets the first five items called after SJY001 (before concrete steps, existing introduction is no longer burdensome) of the event related personnel field in 2013 annual event reports here
(5) enter system statistical analysis operation interface, the data source needed for operation is chosen (to select data full " SJY001 " here, step 1), in tables of data, certain screening (removing distracter or incoherent item, step 2) is carried out to the data item in data source.
(6) determine that the type of task (selects " data analysis " here, step 3), then prepare and select then corresponding applying template (to select the test template " association rules mining algorithm " of the then system integration here, step 4), in the forms ejected, set corresponding attribute, corresponding analysis result can be obtained in viewing area.
(7) the analysis result based on viewing area makes corresponding interpretation work.
Statistical conversion, for becoming formatted document by the statistical conversion in people by mistake database;
Report output, for becoming data sheet by the statistical conversion in people by mistake database.
In the present embodiment, with reference to Fig. 1, statistical study and data mining, under the support of component technology, realize carrying out statistical study and data mining capability (as correlation analysis, cluster analysis etc.) to data source.
Preferably, the present embodiment people by mistake data mart modeling disposal route also comprise: connect other data statisticss and analysis software by external interface and realize statistics to Human Factor in Nuclear Power Plant mistake data, analyze and excavate.Such as, external interface mainly provides other application program as the access of SPSS, SAS, EXCEL etc., thus some powers using other application program are to realize the expansion of systemic-function.Like this, setting up WANO people by mistake after database, user both can by having called existing assembly or exploitation Custom component, can connect other data statisticss and analysis software again realize statistics to Human Factor in Nuclear Power Plant mistake data, analyze and excavate by external interface.
According to a further aspect in the invention, a kind of people is also provided data mart modeling disposal system by mistake, people for the generation of digital control system interactive process misses the processing process of data, with reference to Fig. 2, data mart modeling disposal route is corresponding by mistake for the people of the present embodiment people mistake data mart modeling disposal system and above-described embodiment, and it comprises:
Data reception module 100, for gathering and receiving source data to be analyzed, source data is the people's data by mistake in interactive process, and source data is imported people's database by mistake;
Data management module 200, for managing source data and safeguarding the coding of people's mistake database;
Market demand module 300, for carrying out statistical study and data mining based on component technology to source data.
In the present embodiment, data reception module 100 comprises:
Data entry element 101, for gathering and receiving people's by mistake data of history,
Data check and examination & verification unit 103, data check and data examination & verification is carried out for missing data to the people received, wherein, data check is used for mating the people the received coding scheme that data miss database by verification static class method with people by mistake, by the database by mistake of the data importing people by verification, data examination & verification is used for carrying out authority supervision with the security ensureing data to the data variation in people by mistake database.
In the present embodiment, data entry element 101 comprises:
First receives subelement, builds static class for receiving formatted document data and formatted document data being carried out secondary encapsulation and imports people's database by mistake;
Second receives subelement, for receiving html document data and importing people's database by mistake;
3rd receives subelement, for passing through interface accessing background data base so that the data importing people in background data base is missed database.
In the present embodiment, data management module 200 comprises:
Data source administrative unit 201, for managing the data structure of source data, is convenient to miss from people the Data View that database obtains customization;
Code Maintainability unit 203, increases for data encoding people being missed to database, check, revises and soft delete;
Data maintenance unit 205, for modifying to the incident report data stored in people by mistake database, check and soft delete;
Assembly management unit 207, for increasing the various application component information missing database based on people, check, revise and delete,
Template Manager unit 209, for managing applying template, comprising and increasing applying template, check, revises and delete, and applying template is used for statistical conversion or report output.
In the present embodiment, market demand template 300 comprises:
Statistical analysis unit 301, obtains statistic analysis result for carrying out statistical study based on component technology;
Data mining unit 303, obtains data mining results for carrying out data mining based on component technology;
Statistical conversion unit 305, for becoming formatted document by the statistical conversion in people by mistake database;
Report output unit 307, for becoming data sheet by the statistical conversion in people by mistake database.
The present embodiment people by mistake data mart modeling disposal system also comprises auxiliary power module 400, service is provided for the main body module for system, to improve operability and the Consumer's Experience sense of system, particularly, auxiliary power module 400 comprises: file management unit 401, window management module unit 403 and text editing unit 405 etc., wherein, file management unit 401 manages for the file relevant to system, window management module unit 403 is for carrying out unified management to the window of system, and text editing unit 405 is for editing some function scripted codes.
The present embodiment method and system, based on WANO coding scheme, component technology is adopted to realize the statistics of data source, analysis and data mining duty, the collection of event data that Human Factor in Nuclear Power Plant is caused delay, to analyze and excavation is integrated in an infosystem, and external interface layer is provided, use the expansion that some powerful external applications realize systemic-function; Comparatively classic method, system involved in the present invention can be convenient to people to a great extent and to cause delay the gather and analysis of event data, greatly improves the efficiency of research work.
It should be noted that, can perform in the computer system of such as one group of computer executable instructions in the step shown in the process flow diagram of accompanying drawing, and, although show logical order in flow charts, but in some cases, can be different from the step shown or described by order execution herein.
Obviously, those skilled in the art should be understood that, above-mentioned of the present invention each module or each step can realize with general calculation element, they can concentrate on single calculation element, or be distributed on network that multiple calculation element forms, alternatively, they can realize with the executable program code of calculation element, thus, they can be stored and be performed by calculation element in the storage device, or they are made into each integrated circuit modules respectively, or the multiple module in them or step are made into single integrated circuit module to realize.Like this, the present invention is not restricted to any specific hardware and software combination.
The foregoing is only the preferred embodiments of the present invention, be not limited to the present invention, for a person skilled in the art, the present invention can have various modifications and variations.Within the spirit and principles in the present invention all, any amendment done, equivalent replacement, improvement etc., all should be included within protection scope of the present invention.
Claims (10)
1. people's data mart modeling disposal route by mistake, the people for the generation of digital control system interactive process misses the processing process of data, it is characterized in that, described people by mistake data mart modeling disposal route comprises:
Data reception step, for gathering and receiving source data to be analyzed, described source data is the people's data by mistake in interactive process, and described source data is imported people's database by mistake;
Data management step, for managing described source data and safeguarding the coding of described people's mistake database;
Market demand step, carries out statistical study and data mining based on component technology to described source data.
2. people according to claim 1 data mart modeling disposal route by mistake, it is characterized in that, described data reception step comprises:
Data inputting, for gathering and receiving people's by mistake data of history,
Data check and examination & verification, carry out data check and data examination & verification for missing data to the described people received;
Wherein, described data check is used for mating the described people the received coding scheme that data miss database by verification static class method with described people by mistake, by the database by mistake of people described in the data importing by verification, described data examination & verification is used for carrying out authority supervision with the security ensureing data to the data variation in described people by mistake database.
3. people according to claim 2 data mart modeling disposal route by mistake, it is characterized in that, described data inputting comprises:
Receive formatted document data and described formatted document data are carried out secondary encapsulation and build static class and import described people database by mistake;
Receive html document data and import described people database by mistake;
By interface accessing background data base so that people described in the data importing in described background data base is missed database.
4. people according to claim 1 data mart modeling disposal route by mistake, it is characterized in that, described data management step comprises:
Data source manages, and for managing the data structure of described source data, is convenient to miss from described people the Data View that database obtains customization;
Code Maintainability, increases for the data encoding described people being missed to database, check, revises and soft delete;
Data maintenance, for modifying to the incident report data stored in described people by mistake database, check and soft delete;
Assembly management, for increasing the various application component information missing database based on described people, check, revise and delete,
Template Manager, for managing applying template, comprising and increasing applying template, check, revises and delete, and described applying template is used for statistical conversion or report output.
5. people according to claim 1 data mart modeling disposal route by mistake, it is characterized in that, described market demand step comprises:
Statistical study, obtains statistic analysis result for carrying out statistical study based on component technology;
Data mining, obtains data mining results for carrying out data mining based on component technology;
Statistical conversion, for becoming formatted document by the statistical conversion in described people by mistake database;
Report output, for becoming data sheet by the statistical conversion in described people by mistake database.
6. people's data mart modeling disposal system by mistake, the people for the generation of digital control system interactive process misses the processing process of data, it is characterized in that, described people by mistake data mart modeling disposal system comprises:
Data reception module, for gathering and receiving source data to be analyzed, described source data is the people's data by mistake in interactive process, and described source data is imported people's database by mistake;
Data management module, for managing described source data and safeguarding the coding of described people's mistake database;
Market demand module, for carrying out statistical study and data mining based on component technology to described source data.
7. people according to claim 6 data mart modeling disposal system by mistake, it is characterized in that, described data reception module comprises:
Data entry element, for gathering and receiving people's by mistake data of history,
Data check and examination & verification unit, data check and data examination & verification is carried out for missing data to the described people received, wherein, described data check is used for mating the described people the received coding scheme that data miss database by verification static class method with described people by mistake, by the database by mistake of people described in the data importing by verification, described data examination & verification is used for carrying out authority supervision with the security ensureing data to the data variation in described people by mistake database.
8. people according to claim 7 data mart modeling disposal system by mistake, it is characterized in that, described data entry element comprises:
First receives subelement, builds static class for receiving formatted document data and described formatted document data being carried out secondary encapsulation and imports described people database by mistake;
Second receives subelement, for receiving html document data and importing described people database by mistake;
3rd receives subelement, for passing through interface accessing background data base so that people described in the data importing in described background data base is missed database.
9. people according to claim 6 data mart modeling disposal system by mistake, it is characterized in that, described data management module comprises:
Data source administrative unit, for managing the data structure of described source data, is convenient to miss from described people the Data View that database obtains customization;
Code Maintainability unit, increases for the data encoding described people being missed to database, check, revises and soft delete;
Data maintenance unit, for modifying to the incident report data stored in described people by mistake database, check and soft delete;
Assembly management unit, for increasing the various application component information missing database based on described people, check, revise and delete,
Template Manager unit, for managing applying template, comprising and increasing applying template, check, revises and delete, and described applying template is used for statistical conversion or report output.
10. people according to claim 6 data mart modeling disposal system by mistake, it is characterized in that, described market demand template comprises:
Statistical analysis unit, obtains statistic analysis result for carrying out statistical study based on component technology;
Data mining unit, obtains data mining results for carrying out data mining based on component technology;
Statistical conversion unit, for becoming formatted document by the statistical conversion in described people by mistake database;
Report output unit, for becoming data sheet by the statistical conversion in described people by mistake database.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201510311836.8A CN104978405A (en) | 2015-06-08 | 2015-06-08 | Human error data processing method ans system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201510311836.8A CN104978405A (en) | 2015-06-08 | 2015-06-08 | Human error data processing method ans system |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN104978405A true CN104978405A (en) | 2015-10-14 |
Family
ID=54274909
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201510311836.8A Pending CN104978405A (en) | 2015-06-08 | 2015-06-08 | Human error data processing method ans system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN104978405A (en) |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105676831A (en) * | 2016-04-25 | 2016-06-15 | 湖南工学院 | System for reducing failure probability of maintenance personnel and method thereof |
| CN105915403A (en) * | 2015-12-15 | 2016-08-31 | 乐视网信息技术（北京）股份有限公司 | Traffic import method and device |
| CN106217968A (en) * | 2016-07-15 | 2016-12-14 | 常熟市赛蒂镶嵌玻璃制品有限公司 | A kind of high abrasion implosion guard |
| CN106775689A (en) * | 2016-12-05 | 2017-05-31 | 广发证券股份有限公司 | A kind of system and method for big data application and development |
| CN111241184A (en) * | 2020-02-17 | 2020-06-05 | 湖南工学院 | High-throughput-rate data processing method for multi-source database of power distribution network |
-
2015
- 2015-06-08 CN CN201510311836.8A patent/CN104978405A/en active Pending
Non-Patent Citations (6)
| Title |
|---|
| (英)JOHN SHARP著；周靖译: "《Visual C# 2010从入门到精通》", 30 August 2010, 清华大学出版社 * |
| 国家质检总局信息中心组编: "《中国林业信息化顶层设计》", 29 February 2012, 中国林业出版社 * |
| 张力等: "WANO人因事件统计及分析", 《核动力工程》 * |
| 李波，等: "《Android 4.X从入门到精通》", 31 December 2012 * |
| 郑龙等: "WANO人误研究平台", 《计算机系统应用》 * |
| 高文宇等: "人因可靠性数据库基础架构研究", 《中国安全科学学报》 * |
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105915403A (en) * | 2015-12-15 | 2016-08-31 | 乐视网信息技术（北京）股份有限公司 | Traffic import method and device |
| CN105676831A (en) * | 2016-04-25 | 2016-06-15 | 湖南工学院 | System for reducing failure probability of maintenance personnel and method thereof |
| CN105676831B (en) * | 2016-04-25 | 2019-01-15 | 湖南工学院 | A kind of System and method for reducing service personnel's probability of failure |
| CN106217968A (en) * | 2016-07-15 | 2016-12-14 | 常熟市赛蒂镶嵌玻璃制品有限公司 | A kind of high abrasion implosion guard |
| CN106775689A (en) * | 2016-12-05 | 2017-05-31 | 广发证券股份有限公司 | A kind of system and method for big data application and development |
| CN111241184A (en) * | 2020-02-17 | 2020-06-05 | 湖南工学院 | High-throughput-rate data processing method for multi-source database of power distribution network |
| CN111241184B (en) * | 2020-02-17 | 2023-07-04 | 湖南工学院 | High throughput rate data processing method for multi-source database of power distribution network |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN104978405A (en) | Human error data processing method ans system | |
| CN107247788A (en) | A kind of method of the comprehensive regulation service based on government data | |
| CN104572895A (en) | MPP (Massively Parallel Processor) database and Hadoop cluster data intercommunication method, tool and realization method | |
| CN112527774A (en) | Data center building method and system and storage medium | |
| CN108710644A (en) | One kind is about government affairs big data processing method | |
| CN107679977A (en) | A kind of tax administration platform and implementation method based on semantic analysis | |
| CN101739454A (en) | Data processing system | |
| CN103678396B (en) | A kind of data back up method and device based on data model | |
| CN102945628B (en) | Accident consequence information acquiring method, device and training system | |
| CN104766240A (en) | Electronic banking data processing system and method | |
| CN104881462A (en) | Metadata management system | |
| CN115547466A (en) | Medical institution registration and review system and method based on big data | |
| CN104951954A (en) | FMCG research system | |
| CN102023859A (en) | Digital development environment-oriented software integration method with reliability, maintainability and supportability | |
| CN108199862A (en) | A kind of operation system, which reports an error, manages system and method | |
| CN102819616B (en) | Cloud online real-time multi-dimensional analysis system and method | |
| CN111984826B (en) | XML-based data automatic warehousing method, system, device and storage medium | |
| CN114218291A (en) | Portrait generation method, apparatus, device and storage medium based on target object | |
| CN114048188A (en) | Cross-database data migration system and method | |
| CN110019118A (en) | The system and method for database O&M efficiency are promoted based on DevOps | |
| CN110457009A (en) | The implementation method of software security demand recommended models based on data analysis | |
| US20150363711A1 (en) | Device for rapid operational visibility and analytics automation | |
| CN110018815A (en) | Application development system and method based on database and spreadsheet software | |
| CN115422202A (en) | Service model generation method, service data query method, device and equipment | |
| CN103488693A (en) | Data processing device and data processing method |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20151014 |