CN117874306B - Engineering data source processing method and device, electronic equipment and storage medium - Google Patents
Engineering data source processing method and device, electronic equipment and storage medium Download PDFInfo
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Abstract
The invention discloses a method, a device, electronic equipment and a storage medium for processing engineering data sources, and relates to the technical field of high-speed rail data processing, wherein the method comprises the following steps: acquiring a preset data abstraction model corresponding to a data source to be identified; determining a target engineering data area in the data source to be identified according to preset keywords configured by the preset data abstraction model; and determining the data object of the target engineering data area, and creating a logic corresponding relation between the data object and the target engineering data area. The embodiment of the invention realizes standardized processing of the data sources, reduces data difference caused by different data sources through the data objects, can improve the data regularity, can effectively reduce the data processing time, and is beneficial to improving the production efficiency of the high-speed rail signal train control data products.
Description
Technical Field
The present invention relates to the field of high-speed rail data processing technologies, and in particular, to a method and apparatus for processing engineering data sources, an electronic device, and a storage medium.
Background
In recent years, with the development of passenger special lines and high-speed railways, CTCS-2/3 level train control systems are widely applied to passenger special lines and high-speed railways, and comprise core equipment vehicle-mounted equipment, wireless block center equipment, train control center equipment, temporary speed limiting equipment and the like, and ground equipment sends parameter information such as gradient, camber, speed limiting, target distance and the like of a line to the core equipment vehicle-mounted equipment for calculation and generation of a continuous target distance braking curve for ensuring driving safety, wherein the sources of the parameter information are design units which are submitted to equipment manufacturers according to the general management regulations of iron according to engineering investigation data. Thus, the data sources are required to be processed correctly and efficiently according to the current form of providing the data sources.
At present, data source processing is carried out on ground equipment, equipment manufacturers basically carry out the data source processing in a mode of combining manpower and tools, the tools are used for carrying out preliminary processing to obtain a regular data format, and then the data format is used for ground product equipment after verification and confirmation are carried out manually. However, the tool processes the data source, and the engineering investigation data provided by the design has more problems in automatic processing of the data source due to the difference generated in the advancing of standardization and standardization, including but not limited to large limitation, frequent iteration, more manual participation and the like, so that the processing efficiency of the current railway signal engineering data source is low. Therefore, a new solution is needed to be provided, which can solve the problem that the data source provided by the user shielding design investigation is inaccurate in matching due to factors such as engineering project differences, data template use differences and the like, and simultaneously, the data source processing is more efficient, convenient and flexible, so that in the whole production period of the product, the processing time is shortened by improving the accuracy of data acquisition in the link of the data source processing, and finally, the production efficiency of the product is improved.
Disclosure of Invention
The invention provides an engineering data source processing method, an engineering data source processing device, electronic equipment and a storage medium, so that standardized processing of data sources is realized, data differences caused by different data sources can be reduced, the data regularity degree can be improved, the data processing time is shortened, and the production efficiency of products is improved.
According to an aspect of the present invention, there is provided an engineering data source processing method, wherein the method includes:
Acquiring a preset data abstraction model corresponding to a data source to be identified;
Determining a target engineering data area in the data source to be identified according to preset keywords configured by the preset data abstraction model;
And determining the data object of the target engineering data area, and creating a logic corresponding relation between the data object and the target engineering data area.
According to another aspect of the present invention, there is provided an engineering data source processing apparatus, wherein the apparatus includes:
The model determining module is used for acquiring a preset data abstraction model corresponding to the data source to be identified;
The region matching module is used for determining a target engineering data region in the data source to be identified according to the preset keywords configured by the preset data abstraction model;
and the logic relation module is used for determining the data object of the target engineering data area and creating a logic corresponding relation between the data object and the target engineering data area.
According to another aspect of the present invention, there is provided an electronic apparatus including:
At least one processor; and
A memory communicatively coupled to the at least one processor; wherein,
The memory stores a computer program executable by the at least one processor to enable the at least one processor to perform the engineering data source processing method according to any one of the embodiments of the present invention.
According to another aspect of the present invention, there is provided a computer readable storage medium storing computer instructions for causing a processor to execute the engineering data source processing method according to any embodiment of the present invention.
According to the technical scheme, the preset data abstraction models of different data sources to be identified are obtained, the target engineering data area is determined in the data sources to be identified according to the preset keywords configured by the preset data abstraction models, the data object of the target engineering data area is generated, the logic corresponding relation is set for the data object and the target engineering data area, standardized processing of the data sources is achieved, data differences caused by different data sources are reduced through the data object, the data regularity degree can be improved, the data processing time can be effectively reduced, and the production efficiency of data products is improved.
It should be understood that the description in this section is not intended to identify key or critical features of the embodiments of the invention or to delineate the scope of the invention. Other features of the present invention will become apparent from the description that follows.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for the description of the embodiments will be briefly described below, and it is apparent that the drawings in the following description are only some embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of a method for processing engineering data sources according to a first embodiment of the present invention;
FIG. 2 is a schematic diagram of an engineering data structure according to a first embodiment of the present invention;
FIG. 3 is a schematic diagram of a configuration of engineering interface data according to a first embodiment of the present invention;
FIG. 4 is a flowchart of another engineering data source processing method according to a second embodiment of the present invention;
Fig. 5 is an exemplary diagram of a preset keyword provided according to a second embodiment of the present invention;
Fig. 6 is an exemplary diagram of another preset keyword provided according to the second embodiment of the present invention;
FIG. 7 is a flow chart of a method for processing engineering data sources according to a third embodiment of the present invention;
FIG. 8 is an exemplary diagram of a method for processing engineering data sources according to a fourth embodiment of the present invention;
FIG. 9 is a diagram of an abstract example of an engineering data structure provided according to a fourth embodiment of the invention;
FIG. 10 is a diagram of an abstract example of an interface data structure provided according to a fourth embodiment of the invention;
FIG. 11 is an exemplary diagram of an engineering data cross-redundancy abstraction provided in accordance with a fourth embodiment of the present invention;
FIG. 12 is an exemplary diagram of an interface data cross-redundancy abstraction provided in accordance with a fourth embodiment of the invention;
FIG. 13 is an exemplary diagram of a data source field key group number format provided in accordance with a fourth embodiment of the present invention;
FIG. 14 is a schematic diagram of a data source content abstraction structure according to a fourth embodiment of the invention;
FIG. 15 is an exemplary diagram of a data source provided in accordance with a fourth embodiment of the present invention;
FIG. 16 is an exemplary diagram of a data source set correspondence table page provided in accordance with a fourth embodiment of the present invention;
FIG. 17 is a flowchart illustrating a data source process according to a fourth embodiment of the present invention;
fig. 18 is an exemplary diagram of a keyword matching process provided according to a fourth embodiment of the present invention;
FIG. 19 is a schematic diagram of an engineering data source processing apparatus according to a fifth embodiment of the present invention;
Fig. 20 is a schematic structural diagram of an electronic device implementing the engineering data source processing method according to an embodiment of the present invention.
Detailed Description
In order that those skilled in the art will better understand the present invention, a technical solution in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in which it is apparent that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present invention without making any inventive effort, shall fall within the scope of the present invention.
It should be noted that the terms "first," "second," and the like in the description and the claims of the present invention and the above figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the invention described herein may be implemented in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
Example 1
Fig. 1 is a flowchart of an engineering data source processing method according to an embodiment of the present invention, where the method may be implemented by an engineering data source processing device, and the engineering data source processing device may be implemented in hardware and/or software, and the engineering data source processing device may be configured in a server or a terminal. As shown in fig. 1, the method includes:
step 110, acquiring a preset data abstraction model corresponding to the data source to be identified.
The data source to be identified may be a data source to be subjected to data specification processing, and may be provided by different data manufacturers, for example, when column control data is in the data source to be identified, the data source to be identified may be column control data provided by different exploration hospitals. The preset data abstract model may be a data standardized processing model generated according to the service condition of the data source to be identified, the preset data abstract model may include a data processing specification, a standard data format and the like of the data in the data source to be identified, and the preset data abstract model may at least include keywords used for extracting the data, a data object template of the specification and the like.
In the embodiment of the invention, the data source to be identified can be obtained, and the matched preset data abstraction model can be selected according to the data source to be identified, and the preset data abstraction model can be preconfigured on a local or cloud server.
And 120, determining a target engineering data area in the data source to be identified according to preset keywords configured by the preset data abstraction model.
The preset keywords may be keywords for identifying a data area in the data source to be identified, may be preconfigured in a preset data abstraction model, may be a single keyword or a group of keywords, may be preset according to service requirements of the data source to be identified, and may include project engineering keywords, line keywords, data source keywords, and the like.
In the embodiment of the invention, the preset keywords can be preconfigured in the preset data abstraction model, one or more preset keywords configured in the preset data abstraction model can be extracted, data matched with the preset keywords can be searched in a data source to be identified according to the preset keywords, and the area where the data are located can be used as a target engineering data area. For example, the preset keyword may be a field name, a data field containing the field name in the preset keyword may be included in the data source to be identified, and a location where the data field is located may be used as a target engineering data area.
And 130, determining a data object of the target engineering data area, and creating a logic corresponding relation between the data object and the target engineering data area.
The data object may be an abstract object for performing unified operation on data in the data source to be identified, where the data object includes at least a data type of associated data and a keyword of the associated data. The logical correspondence may be a binding relationship between the data object and the target engineering data area, and the logical correspondence includes, but is not limited to, the data object and the target engineering data area having the same identification information, the index of the data object and the target engineering data area being stored in the same area, and the like.
In the embodiment of the invention, the data type and the keywords of each target engineering data area can be determined, the data type and the keywords can be stored as abstract objects, and a logical corresponding relation is created for the abstract objects and the corresponding target engineering data areas, for example, the data objects and the target engineering data areas can be set with the same identification information, so that the target engineering data areas can be acquired through the data objects for data operation. Further, the generation mode of the abstract object can be configured by a configuration file track or a preset data abstract model.
According to the embodiment of the invention, the preset data abstraction models of different data sources to be identified are obtained, the target engineering data area is determined in the data sources to be identified according to the preset keywords configured by the preset data abstraction models, the data object of the target engineering data area is generated, the logic corresponding relation is set for the data object and the target engineering data area, the standardized processing of the data sources is realized, the data difference caused by different data sources is reduced through the data object, the data regularity degree can be improved, the data processing time can be effectively reduced, and the production efficiency of data products can be improved.
Furthermore, on the basis of the embodiment of the invention, the data source to be identified at least comprises a column control data source, wherein engineering data sources in the column control data source form a data set by taking a line as a unit, and the engineering data sources in the column control data source form the data set by taking engineering as a unit.
In the embodiment of the invention, the data source to be identified may include a train control data source, where the train control data source may include an engineering data source and an interface data source, where the engineering data source may be data parameters required by various signal devices provided by a current signal design unit after the engineering line is surveyed, and the data parameters are basic data of the signal devices for working, and are used as basis for computing various application logics by various system products, for example, driving permission parameters, speed limiting, static speed curves, gradient curves, line conditions, link information and the like. Thus, as part of the software of the signal equipment, it needs to be solidified into the software by a configuration mode, whether it is correct or not directly relates to whether the command sent by the signal equipment is accurate or not, and directly influences the safety and reliability of the operation of the railway equipment, see fig. 2, the engineering data source can form data sets in units of lines, and each data set can comprise an information table of the line. While the interface data sources are provided in the form of device relationships, and can be implemented based on application protocols, the data content of the interface data sources is defined by engineering content, the interface data sources are provided by device manufacturers according to the whole engineering, referring to fig. 3, the interface data sources take one engineering as a building unit, and one or more data sets corresponding to the interface data sources can be included in each engineering.
Example two
Fig. 4 is a flowchart of another engineering data source processing method according to a second embodiment of the present invention, where the embodiment of the present invention is implemented on the basis of the foregoing embodiment of the present invention, and a process for determining a preset data abstraction model and a target engineering data area is described in detail, with reference to fig. 4, and the method provided by the embodiment of the present invention specifically includes the following steps:
step 210, reading the data source to be identified.
In the embodiment of the invention, the data source to be identified can be read from one or more files, different reading modes can be adopted for file carriers of different data sources to be identified, for example, the data source to be identified in a database form can be read through interface call, and the data source to be identified in an EXCEL form can be read through a file loading mode.
Step 220, extracting a configuration file of a preset data abstraction model, wherein the configuration file comprises at least one of the following: the user needs the configuration file and the auxiliary configuration file.
In the embodiment of the invention, the preset abstract model can exist in the form of a configuration file, the configuration file can comprise a data standardization processing process and a matching keyword specified by the preset abstract model, the configuration file can at least comprise a user demand configuration file and an auxiliary configuration file, wherein the user demand configuration file can be a configuration parameter which is uploaded by a user in a self-defined mode according to service demands, and the auxiliary configuration file can be a configuration parameter set by a service provider for realizing data standardization processing, and when a data source to be identified is processed, the configuration file can be read to form the preset data abstract model.
Step 230, extracting preset keywords in a configuration file of the preset data abstraction model, wherein the preset keywords at least comprise engineering interface keywords and engineering data keywords, and the engineering data keywords comprise at least one of file carrier keywords, data set keywords and data field keywords.
Specifically, the configuration file of the preset data abstraction model may include a preset keyword, where the preset keyword may be used to search an engineering interface or engineering data in a data source to be identified, and correspondingly, the preset keyword may be configured with an engineering interface keyword, an engineering data keyword, and the like, where the engineering data keyword may search information such as an engineering project, an engineering line, a file carrier, a data set, and a data field, and different vocabularies may be set as preset keywords for the data source to be identified of different service types, and it may be understood that, for different service requirements, the engineering data keyword set in the configuration file may include one or more of a file carrier keyword, a data set keyword, and a data field keyword.
In the embodiment of the present invention, a configuration file of a preset data abstraction model may be extracted, and engineering interface keywords, engineering data keywords and the like may be read from the configuration file, where the engineering interface keywords and the engineering data keywords may be keywords in an atomic form, and each keyword is related independently, or may be a keyword group having a hierarchical structure, and keywords in each keyword group have a hierarchical relationship, and referring to fig. 5, the preset keywords may be abstract determination keywords according to a structure of "project engineering-line-dataset-data", where each file corresponds to one or more datasets of dataset pages, and each page is named by an table name containing the keywords; the content of each data set page is the specific content of the data source and is divided into field identification and data content. The field identification is named by a name containing a keyword and is used for identifying the meaning of data; the data content is specific data. While fig. 6 shows an example of keywords in a file carrier-data source set-data hierarchy, showing the relationship between the hierarchy of data sources and preset keywords, it may be in the form of physical storage of data or keywords for data protection, where any name containing the keywords is given in the form of a string, and the process keyword matching is actually the matching of the string. What is important is that the keyword matching form of engineering data conforming to the signal characteristics is required to be constructed so as to conveniently locate, search, filter and process the data.
Step 240, matching the target engineering data area in the data source to be identified according to the engineering interface keywords and the engineering data keywords.
In the embodiment of the invention, the engineering interface keywords and the engineering data keywords can be used in the data source to be identified to search the target engineering data area, and if one data area comprises the engineering interface keywords or the engineering interface data keywords, the data area is used as the target engineering data area.
Step 250, determining a data object of the target engineering data area, and creating a logical correspondence between the data object and the target engineering data area.
According to the embodiment of the invention, the configuration files corresponding to the data sources to be identified are extracted by reading the different data sources to be identified, the engineering interface keywords and the engineering data keywords in the configuration files are extracted, the target engineering data area is determined in the data sources to be identified according to the engineering interface keywords and the engineering data keywords, the data object of the target engineering data area is determined, and the logic corresponding relation between the data object and the target engineering data area is created, so that unified processing of the data sources can be realized, the data difference caused by different data sources is reduced, the data regularity degree can be improved through the data object, the data processing time can be reduced, and the production efficiency of data products is enhanced.
Further, on the basis of the above embodiment of the present invention, matching, according to the engineering interface keyword and the engineering data keyword, the target engineering data area in the to-be-identified data source includes:
when the data source to be identified comprises engineering interface data, searching a target data interface matched with the engineering interface keywords in the data source to be identified, and taking the position information of the target data interface as a target engineering data area;
when the data source to be identified comprises engineering data, searching target data fields in the data source to be identified layer by layer according to the engineering data keywords comprising file carrier keywords, data set keywords and data field keywords, and taking the position information of the target data fields as target engineering data areas.
In the embodiment of the invention, when the data source to be identified is engineering interface data, the data in the data source to be identified can be matched according to the engineering interface keywords, when the data comprises the engineering interface keywords, the matched data can be used as a target data interface, the position information corresponding to the target data interface can be used as a target engineering data area, and the position information can be determined by the storage path, the data position and other information of the target data interface. When the data to be identified is engineering data, matching can be performed according to a file carrier keyword, a data set keyword and a data field keyword in the engineering data keyword, wherein the file carrier keyword and the data set keyword can be atomic keywords, the data field keyword can be a hierarchical keyword group, the data field keyword can comprise a plurality of keywords with hierarchical relations, a target data field can be matched in the data to be identified through the file carrier keyword, the data set keyword and the data field keyword, and the position where the target data field is located is used as a target engineering data area.
Example III
Fig. 7 is a flowchart of a method for processing engineering data sources according to a third embodiment of the present invention, where the embodiment of the present invention is embodied on the basis of the above embodiment of the present invention, and referring to fig. 7, the method provided by the embodiment of the present invention specifically includes the following steps:
step 310, a preset data abstraction model corresponding to the data source to be identified is obtained.
Step 320, determining a target engineering data area in the data source to be identified according to the preset keywords configured by the preset data abstraction model.
Step 330, crossing engineering data in different target engineering data areas; and removing the repeated target engineering data area according to the crossing result of the engineering data.
In the embodiment of the invention, the collected different target engineering data areas can be subjected to cross comparison, whether the engineering data in the different target engineering data areas are duplicated or not is judged, and the duplicated target engineering data areas can be removed when the engineering data are determined to be in the duplicated target engineering data areas, wherein the removal of the duplicated target engineering data areas can comprise the whole duplication removal of the duplicated target engineering data areas, the removal of the duplicated engineering data in the duplicated target engineering data areas, and the like.
Step 340, determining the data type of the target engineering data area and the preset keywords.
The data type may be information reflecting the attribute of the engineering data in the target engineering data area, the data type may include a device type, a line type, an engineering type, etc., and the preset keywords may be preset keywords used for determining the target engineering data in the data source to be identified, where each target engineering data area matches with a corresponding preset keyword.
In the embodiment of the invention, engineering data can be extracted in the target engineering data area, the data type of the engineering data can be determined, and preset keywords used when the target engineering data area is extracted from a data source to be identified can be determined.
And step 350, packaging the data type and the preset keywords into a data object, and setting association identification information for the data object and the target engineering data area.
In the embodiment of the invention, the data type and the preset keyword can be packaged into the data object according to the preset format, the preset format can be determined in advance through negotiation, the packaged data object and the corresponding target engineering data area can be provided with the same associated identification information, and the associated identification information can comprise that the data object and the target engineering data area have the same number or are stored in the same storage area and the like.
Example IV
Fig. 8 is an exemplary diagram of a method for processing engineering data sources according to a fourth embodiment of the present invention, referring to fig. 8, a process for a user to normalize acquired original engineering data, so as to acquire a unified logical object may include the following parts:
1. Abstraction of data sources: for railway signal products, the functional logic of a certain product is relatively uniform in different project projects, and the difference is mainly reflected in the difference of design inputs, namely, the difference of data configuration. The application function and the data are combined to completely embody the logic function realized by the specific product under the engineering scheme. The different design inputs will eventually be presented in the form of data sources, so that in railway signal products the release is actually to match the engineering data sources. Thus, the accuracy of the data source is directly related to whether the software function can be correctly represented, and thus, the safety of the product.
In the signal field, for the current train control system, the data sources provided by the design survey are mainly divided into two main categories, namely train control engineering data and train control interface data. These data are all provided in a digitized form of a spreadsheet. In addition, the design basis of interlocking products is also increasingly urgent to digital, especially overseas engineering projects, and electronic interlocking tables are also provided in digital form. Because the input of the interlocking is not standardized at present, the data of the train control engineering are considered firstly:
1) Abstraction of column control engineering data:
The train control engineering data are data parameters required by operation of various signal equipment provided by the current signal design unit after the engineering line is surveyed, and are basic data of the signal equipment operation, and are used as basis for calculating various application logics by various system products, such as driving permission parameters, speed limiting parameters, speed limits, static speed curves, gradient curves, line conditions, link information and the like. Therefore, the signal equipment software is required to be solidified into the software in a configuration mode, and whether the signal equipment is correct or not directly depends on whether an externally-sent instruction of the signal equipment is accurate or not, so that the safety and the reliability of railway equipment operation are directly affected. The train control engineering data has important function on the signal equipment, the provided form and standardization are the problems that signal equipment manufacturers have to solve in the links of product research, production and maintenance, because the production of the signal equipment is to develop corresponding work around the train control engineering data source, the work of inputting, checking, reading, processing, outputting, maintaining and the like of the data source is the basis and foundation of other subsequent links. Typically, the source of the column control engineering data is provided in units of lines. The data source of the train control engineering data is abstracted in the form shown in fig. 9 according to the form of the data source provided by the design unit by taking one engineering unit as an example to provide to the equipment manufacturer.
2) Abstraction of column control interface data:
The interaction of information between the signal devices is required to be regulated by an application protocol, and specific data contents are required to be defined according to the train control engineering data. Therefore, the interface data is the basis of information interaction between the signal devices, whether the solidification form is through compiling or configuration, the interface data source is needed to be solidified into software delivered by the devices, and is output outwards according to an application protocol, so that the correctness of the interface data is also related to the safety and reliability of the functions of the signal devices. The column control interface data source is provided in the form of a device relationship provided by the device manufacturer according to the whole project. At present, the form of the data table of the interface is standardized, and the standardization of the data according to interconnection and interworking among different factories is restricted. With an engineering as an abstraction, the data source of the column control interface data is abstracted in an interface data structure as shown in fig. 10.
3) Abstraction of data interleaving: data redundancy processing is a common problem in the signal field for processing data sources, and is also a reference indicator for in-circuit discrimination criteria and hubs. Namely, the junction engineering has the line crossing condition, and can be finely classified according to the complex crossing condition, while the standard engineering generally has no line crossing condition, and is simple to extend or penetrate even if the line crossing condition exists, and is relatively simple. And the line crossing condition of the hinge engineering is relatively complex. The difficulty of the data crossing condition directly influences the difficulty of the data source processing. Referring to fig. 11, the engineering data may be classified according to data types, check and repeat matching may be performed in each classification, merging and splicing are performed corresponding to repeated engineering data, and repeated data portions are removed, thereby completing data cross abstraction. Referring to fig. 12, for the interface data, check and re-match may be performed on all the interface data at the same time, and duplicate interface data may be directly removed, so as to output discrete interface data.
2. Data keyword abstraction
1) Keyword abstraction and structure of data: the data key can be generated after multi-bit integration abstraction of project engineering-line-file carrier-data source set-data. Referring to fig. 5, the file corresponding to the specific data source is currently an excel file. Files are named by file names containing keywords; each file corresponds to a dataset of one or more dataset pages, each page being named by an outer page name containing a key; the content of each data set page is the specific content of the data source and is divided into field identification and data content. The field identification is named by a name containing a keyword and is used for identifying the meaning of data; the data content is specific data. Referring to FIG. 6, a specific hierarchical structure of data sources is shown in relation to keywords, which may represent both the physical storage form of the data and the form of the keywords it contains. Where any name containing a keyword is given in the form of a string, the processing keyword match is actually a match of the string. What is important is that the keyword matching form of engineering data conforming to the signal characteristics is required to be constructed so as to conveniently locate, search, filter and process the data. Referring to fig. 13, an abstract field key may have multiple levels, each level may have one or more keys under it, and the scope of use of the key of the next level is attributed to the scope of use of the key of the previous level. The field keys of the data source may have the following characteristics:
1. the number of the first layer of matching piles is 1;
2. the field keywords are combined according to the hierarchy, and the names of the matching piles containing the keywords of other layers must be within the range of the matching pile of the previous layer, for example, the vertical range of the matching pile 2-i must be contained within the range of the matching pile 1-1;
3. each layer has a number of matching posts containing keywords, e.g., keyword 2-i is the i-th matching post.
2) Data content abstraction within a data source:
Referring to fig. 14, the data contents include an identification area for defining the meaning of the column data (generally, the data are all given by columns from top to bottom), and a data area given in specific chinese character or english character string containing keywords; the data region is a specific data source, sometimes ordered, and sometimes unordered, according to its data attributes. For example, the data contents in the line data table are ordered and the data contents in the route information table are unordered. The identification area name is generally fixed, but since the old engineering is not executed according to the new specification in the process of standardization promotion, there is a case that the key word is greatly different. In any event, the type attribute of the data is identified by a name containing a key. For example, in fig. 15, a route information table of a station of a certain project may be identified by a field name and a data content area as a data area. It follows from this that one of the plurality of pages in a data source is formed by a common combination of the identification area and the data area. As already explained above, the identification area is a combination containing key names for identifying specific signal properties of the data content. More than 70% of these names and formats are fixed according to statistics. However, different design investigation units can also make some adjustments according to the actual situation of the design investigation units, even if the same design investigation unit is used by designers, differential adjustments can exist due to the use habit of the designers, for example, in terms of format, the area of the whole data source content does not start from the leftmost upper end of the file; for another example, the "transponder group unit number/link distance" of the identification region may be abbreviated as "number/distance". This results in a further 30% of the cases, i.e. the case where the name of the identification area does not contain a keyword. For such a case where data cannot be acquired due to a keyword matching failure, special processing is required.
3. And (3) data source processing:
On the basis of the abstraction, the engineering data table and the interface data table can be processed as follows according to the form of the content, the actually provided form and the abstracted structure:
a) Engineering data sources are in sequential form in units of lines. Each engineering project is provided according to the structure, and each line is provided with a set of engineering data table according to the lines;
b) The interface data source is in discrete form in engineering units. Namely, interface data are shared among different engineering lines, each engineering is formulated according to interface conditions, and if no corresponding interface conditions exist, the interface data are not provided;
c) The file names of the data sources are not fixed, but all contain keywords. For example, some file names have date added to the suffix and some descriptive text added to the suffix, but all include a key of the attribute of the data before the name, and this key is generally fixed;
d) The file content of the data source may be provided in a single page or in multiple pages, with page names not fixed, but each containing keywords; referring to FIG. 16, the data source content is presented in collections, one for each table page. An example of a line data table is given by 4 pages, each with fixed keys, such as "up", "down", "forward", "reverse". Sometimes the page name may carry other auxiliary descriptive text, but generally contains the keywords described above.
In performing data source processing, the data source may be processed in two steps:
1. data source matching, engineering project matching, engineering line matching, file carrier matching, data set matching and data content field identification area matching. After the engineering project and the engineering line are matched, namely, the name of the wanted data file, the corresponding table pages of the data sets and all fields of each data set are identified, the image is called an anchoring process, and once the anchoring is successful, the data content can be identified according to the anchoring range. Classifying according to function types, wherein the matching of the file carrier and the data set is single-level matching, and the matching of the data content is multi-level matching;
2. after the identification area is identified by the data source, the data area can be identified according to the anchoring position, and the data can be read, analyzed and processed after being read.
Referring to fig. 17, the above two-step process can be implemented by the following scheme:
1. For matching of file carriers and matching of data sets, defining an atomic keyword of a signal characteristic to perform direct matching of targets, namely single-layer matching;
2. setting a general identification area field name combination identification processing algorithm, namely field combination anchoring processing, carrying out multi-level matching according to keywords, obtaining identification areas for all data source fields in FIG. 6 after the field matching in all field combinations is completed, reading the data areas according to the range, and then carrying out processing of specific contents;
3. And matching, namely matching the character strings containing the keywords. The matching key may be configured in advance by the user as a basis for the matching process as an input for matching with the data source, and the rule of matching is implemented in an algorithmic form. Specifically, the keyword matching process may be illustrated by fig. 18.
4. The matching process is the process of establishing the internal logic abstract data after the data source processing, in the constructed data abstraction, the identification area and the data area have corresponding relations, and the data area object contains all the attributes of the data, the atomic key words, the data types and the like. In addition, the data objects also construct internal logical relationships with each other.
After the above processing is completed, logic data corresponding to the original engineering data is obtained, the logic data has a unified format, and is convenient for standardization operation, and the logic data can comprise the following parts:
1. Raw data. This is the original data content that is retained during the software process, possibly with some read attributes (e.g., number of lines, data type, etc.), typically provided in log form, for problem localization;
2. abstract data objects. The method is characterized in that after matching, data are built into an internal object of two parts of an identification area and a data area, and the internal object is not provided outside generally;
3. Logical data objects. The data objects are directly accessed by the user after the abstraction is finished, the data objects have all attributes in the matching process, such as atomic keywords, data types and the like, and the mutual relations are established according to the logical relations among the data objects, namely the data objects appointed by the user can be searched from one data object in the data abstraction process, so that the logical operation directly used for the user is convenient and quick, and the user only needs to care about the applied logical operation, and does not carry out the logical processing of the data due to the requirement of the application calculation. For example, the user can directly trace back and acquire any parameters (name, kilometer sign, etc.) of the line start-end signal machine to obtain all parameters of the line number, the intermediate passing transponder, the signal machine (including name, milepost, etc.), the covered equipment (including name, equipment number), the length, the milepost system, broken link, etc. which are concerned by the upper layer application, and directly apply to calculation.
Example five
Fig. 19 is a schematic structural diagram of an engineering data source processing apparatus according to a fifth embodiment of the present invention. As shown in fig. 19, the apparatus includes:
the model determining module 501 is configured to obtain a preset data abstraction model corresponding to a data source to be identified.
The region matching module 502 is configured to determine a target engineering data region in the data source to be identified according to the preset keywords configured by the preset data abstraction model.
A logic relationship module 503, configured to determine a data object of the target engineering data area, and create a logic correspondence between the data object and the target engineering data area.
According to the embodiment of the invention, the model determining module is used for obtaining the preset data abstraction models of different data sources to be identified, the region matching module is used for determining the target engineering data region in the data sources to be identified according to the preset keywords configured by the preset data abstraction models, the logic relation module is used for generating the data object of the target engineering data region and setting the logic corresponding relation for the data object and the target engineering data region, the standardized processing of the data sources is realized, the data difference caused by different data sources is reduced through the data object, the data regularity degree can be improved, the data processing time can be effectively reduced, and the production efficiency of data products is improved.
Further, on the basis of the above embodiment of the present invention, the model determining module 501 includes:
and the data source reading unit is used for reading the data source to be identified.
The configuration reading unit is used for extracting a configuration file of the preset data abstraction model, wherein the configuration file comprises at least one of the following components: the user needs the configuration file and the auxiliary configuration file.
Further, based on the above embodiment of the present invention, the region matching module 502 includes:
The keyword extraction unit is used for extracting the preset keywords in the configuration file of the preset data abstraction model, wherein the preset keywords at least comprise engineering interface keywords and engineering data keywords, and the engineering data keywords comprise at least one of project keywords, engineering line keywords, file carrier keywords, data set keywords and data field keywords.
And the matching processing unit is used for matching the target engineering data area in the data source to be identified according to the engineering interface keywords and the engineering data keywords.
Furthermore, on the basis of the embodiment of the present invention, the matching processing unit is specifically configured to: when the data source to be identified comprises engineering interface data, searching a target data interface matched with the engineering interface key word in the data source to be identified, and taking the position information of the target data interface as the target engineering data area; when the data source to be identified comprises engineering data, searching a target data field in the data source to be identified layer by layer according to the engineering data keywords comprising the project keywords, the engineering line keywords, the file carrier keywords, the data set keywords and the data field keywords, and taking the position information of the target data field as the target engineering data area.
Further, on the basis of the above embodiment of the present invention, the logical relationship module 503 includes:
And the attribute extraction unit is used for determining the data type of the target engineering data area and the preset keywords.
And the relation establishing unit is used for packaging the data type and the preset keyword into the data object and setting association identification information for the data object and the target engineering data area.
Further, on the basis of the above embodiment of the present invention, the apparatus further includes: the cross duplicate removal module is used for crossing engineering data in different target engineering data areas; and removing the repeated target engineering data area according to the crossing result of the engineering data.
Furthermore, on the basis of the embodiment of the invention, the data source to be identified in the device at least comprises a column control data source, engineering data sources in the column control data source form a data set by taking a circuit as a unit, and the engineering data sources in the column control data source form the data set by taking engineering as a unit.
The engineering data source processing device provided by the embodiment of the invention can execute the engineering data source processing method provided by any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the execution method.
Example six
Fig. 20 shows a schematic diagram of the structure of an electronic device 10 that may be used to implement an embodiment of the invention. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. Electronic equipment may also represent various forms of mobile devices, such as personal digital processing, cellular telephones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be exemplary only, and are not meant to limit implementations of the inventions described and/or claimed herein.
As shown in fig. 20, the electronic device 10 includes at least one processor 11, and a memory such as a Read Only Memory (ROM) 12, a Random Access Memory (RAM) 13, etc., communicatively connected to the at least one processor 11, wherein the memory stores a computer program executable by the at least one processor, and the processor 11 can perform various appropriate actions and processes according to the computer program stored in the Read Only Memory (ROM) 12 or the computer program loaded from the storage unit 18 into the Random Access Memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 may also be stored. The processor 11, the ROM 12 and the RAM 13 are connected to each other via a bus 14. An input/output (I/O) interface 15 is also connected to bus 14.
Various components in the electronic device 10 are connected to the I/O interface 15, including: an input unit 16 such as a keyboard, a mouse, etc.; an output unit 17 such as various types of displays, speakers, and the like; a storage unit 18 such as a magnetic disk, an optical disk, or the like; and a communication unit 19 such as a network card, modem, wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information/data with other devices via a computer network, such as the internet, and/or various telecommunication networks.
The processor 11 may be a variety of general and/or special purpose processing components having processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various specialized Artificial Intelligence (AI) computing chips, various processors running machine learning model algorithms, digital Signal Processors (DSPs), and any suitable processor, controller, microcontroller, etc. The processor 11 performs the various methods and processes described above, such as engineering data source processing methods.
In some embodiments, the engineering data source processing method may be implemented as a computer program tangibly embodied on a computer-readable storage medium, such as the storage unit 18. In some embodiments, part or all of the computer program may be loaded and/or installed onto the electronic device 10 via the ROM 12 and/or the communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the engineering data source processing method described above may be performed. Alternatively, in other embodiments, the processor 11 may be configured to perform the engineering data source processing method in any other suitable manner (e.g., by means of firmware).
Various implementations of the systems and techniques described here above may be implemented in digital electronic circuitry, integrated circuit systems, field Programmable Gate Arrays (FPGAs), application Specific Integrated Circuits (ASICs), application Specific Standard Products (ASSPs), systems On Chip (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs, the one or more computer programs may be executed and/or interpreted on a programmable system including at least one programmable processor, which may be a special purpose or general-purpose programmable processor, that may receive data and instructions from, and transmit data and instructions to, a storage system, at least one input device, and at least one output device.
A computer program for carrying out methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the computer programs, when executed by the processor, cause the functions/acts specified in the flowchart and/or block diagram block or blocks to be implemented. The computer program may execute entirely on the machine, partly on the machine, as a stand-alone software package, partly on the machine and partly on a remote machine or entirely on the remote machine or server.
In the context of the present invention, a computer-readable storage medium may be a tangible medium that can contain, or store a computer program for use by or in connection with an instruction execution system, apparatus, or device. The computer readable storage medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. Alternatively, the computer readable storage medium may be a machine readable signal medium. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
To provide for interaction with a user, the systems and techniques described here can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and a pointing device (e.g., a mouse or a trackball) through which a user can provide input to the electronic device. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic input, speech input, or tactile input.
The systems and techniques described here can be implemented in a computing system that includes a background component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such background, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), wide Area Networks (WANs), blockchain networks, and the internet.
The computing system may include clients and servers. The client and server are typically remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server can be a cloud server, also called a cloud computing server or a cloud host, and is a host product in a cloud computing service system, so that the defects of high management difficulty and weak service expansibility in the traditional physical hosts and VPS service are overcome.
It should be appreciated that various forms of the flows shown above may be used to reorder, add, or delete steps. For example, the steps described in the present invention may be performed in parallel, sequentially, or in a different order, so long as the desired results of the technical solution of the present invention are achieved, and the present invention is not limited herein.
The above embodiments do not limit the scope of the present invention. It will be apparent to those skilled in the art that various modifications, combinations, sub-combinations and alternatives are possible, depending on design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the scope of the present invention.
Claims (10)
1. A method of engineering data source processing, the method comprising:
Acquiring a preset data abstraction model corresponding to a data source to be identified;
Determining a target engineering data area in the data source to be identified according to preset keywords configured by the preset data abstraction model, wherein the preset keywords at least comprise keywords for identifying the data area in the data source to be identified, the preset keywords are pre-configured in the preset data abstraction model, the preset keywords at least comprise engineering interface keywords and engineering data keywords, and the engineering data keywords comprise project keywords, engineering line keywords, file carrier keywords, data set keywords and data field keywords;
Determining a data object of the target engineering data area, and creating a logic corresponding relation between the data object and the target engineering data area, wherein the data object comprises an abstract object for carrying out unified operation on data in the data source to be identified, the data object at least comprises a data type associated with the data and a keyword associated with the data, the logic corresponding relation comprises the data object and the target engineering data area with the same identification information, and indexes of the data object and the target engineering data area are stored in the same area.
2. The method of claim 1, wherein the obtaining a preset data abstraction model corresponding to the data source to be identified comprises:
Reading the data source to be identified;
extracting a configuration file of the preset data abstraction model, wherein the configuration file comprises at least one of the following: the user needs the configuration file and the auxiliary configuration file.
3. The method of claim 1, wherein the determining the target engineering data area within the data source to be identified according to the preset keywords configured by the preset data abstraction model comprises:
extracting the preset keywords in the configuration file of the preset data abstraction model;
and matching the target engineering data area in the data source to be identified according to the engineering interface keywords and the engineering data keywords.
4. A method according to claim 3, wherein said matching said target project data area at said data source to be identified according to said project interface key and said project data key comprises:
when the data source to be identified comprises engineering interface data, searching a target data interface matched with the engineering interface key word in the data source to be identified, and taking the position information of the target data interface as the target engineering data area;
When the data source to be identified comprises engineering data, searching a target data field in the data source to be identified layer by layer according to the engineering data keywords comprising the project keywords, the engineering line keywords, the file carrier keywords, the data set keywords and the data field keywords, and taking the position information of the target data field as the target engineering data area.
5. The method of claim 1, wherein the determining the data object of the target engineering data area and creating the logical correspondence of the data object to the target engineering data area comprises:
determining the data type of the target engineering data area and the preset keywords;
and packaging the data type and the preset keyword into the data object, and setting associated identification information for the data object and the target engineering data area.
6. The method as recited in claim 1, further comprising:
Crossing engineering data in different target engineering data areas;
and removing the repeated target engineering data area according to the crossing result of the engineering data.
7. The method of claim 1, wherein the data sources to be identified comprise at least a column control data source, engineering data sources within the column control data source form a data set in units of lines, and engineering data sources within the column control data source form a data set in units of engineering.
8. An engineering data source processing apparatus, the apparatus comprising:
The model determining module is used for acquiring a preset data abstraction model corresponding to the data source to be identified;
The region matching module is used for determining a target engineering data region in the data source to be identified according to preset keywords configured by the preset data abstraction model, wherein the preset keywords at least comprise keywords for identifying the data region in the data source to be identified, the preset keywords are configured in the preset data abstraction model in advance, the preset keywords at least comprise engineering interface keywords and engineering data keywords, and the engineering data keywords comprise project keywords, engineering line keywords, file carrier keywords, data set keywords and data field keywords;
The logic relation module is used for determining a data object of the target engineering data area and creating a logic corresponding relation between the data object and the target engineering data area, wherein the data object comprises an abstract object for carrying out unified operation on data in the data source to be identified, the data object at least comprises a data type associated with the data and a keyword associated with the data, the logic corresponding relation comprises identification information which is the same as that of the target engineering data area, and indexes of the data object and the target engineering data area are stored in the same area.
9. An electronic device, the electronic device comprising:
At least one processor; and
A memory communicatively coupled to the at least one processor; wherein,
The memory stores a computer program executable by the at least one processor to enable the at least one processor to perform the engineering data source processing method of any one of claims 1-7.
10. A computer readable storage medium, characterized in that the computer readable storage medium stores computer instructions for causing a processor to implement the engineering data source processing method of any one of claims 1 to 7 when executed.
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