CN113986968B - Scheme intelligent proofreading method based on electric power standard standardization datamation - Google Patents
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Abstract
The application discloses a scheme intelligent proofreading method based on electric power standard standardization datamation, wherein the method comprises the following steps: constructing a document/equipment standard library, wherein the document/equipment standard library is used for storing standard description modes of documents/equipment, and is stored in a relational database; inputting a scheme file to be corrected, and extracting a corresponding correction standard in the document/equipment standard library according to the scheme file to be corrected; comparing the scheme file to be corrected with the correction standard to obtain a correction result; and generating a proofreading result file according to the proofreading result, and outputting the proofreading result file. The intelligent learning algorithm is adopted to intelligently check the configuration files of the power secondary equipment, a document/equipment standard library is obtained after a large amount of configuration data are trained, and the intelligent checking is carried out on the configuration files of different types through the document/equipment standard library; the working efficiency and the accuracy are improved, and the workload of manual checking is reduced.
Description
Technical Field
The application relates to the field of electric power, in particular to an intelligent scheme proofreading method based on electric power standard standardization datamation.
Background
At present, with the development of the power industry, a large number of construction schemes and secondary equipment exist in a power grid, and in the process of power grid construction, whether the construction schemes meet the standards and whether the configuration of the secondary equipment meets the standards needs to be checked manually, but workers need to be familiar with a large number of standards and standard files for checking, and also need to read and compare a large number of schemes and configuration files to manually find out places which do not meet the standards. This makes the whole check-up consume huge manpower, and work efficiency and accuracy are all lower.
Disclosure of Invention
The application provides an intelligent verification method based on a scheme of power standard standardization and datamation, which comprises the steps of intelligently verifying configuration files of power secondary equipment by adopting an intelligent learning algorithm, obtaining a document/equipment standard library after training a large amount of configuration data, and intelligently verifying different types of configuration files through the document/equipment standard library; the working efficiency and the accuracy are improved, and the workload of manual checking is reduced.
The application provides a scheme intelligent proofreading method based on electric power standard standardization datamation, which comprises the following steps:
constructing a document/equipment standard library, wherein the document/equipment standard library is used for storing standard description modes of documents/equipment, and is stored in a relational database;
inputting a scheme file to be corrected, and extracting a corresponding correction standard in the document/equipment standard library according to the scheme file to be corrected;
comparing the scheme file to be corrected with the correction standard to obtain a correction result;
and generating a proofreading result file according to the proofreading result, and outputting the proofreading result file.
Optionally, the constructing a document/device standard library includes:
inputting a standard scheme file, and constructing a data model according to the standard scheme file;
extracting standard index data according to the standard scheme file;
and combining the standard index data and the data model to construct a document/equipment standard library.
Optionally, the comparing the scheme file to be collated with the collation standard to obtain the collation result includes:
analyzing the scheme file to be corrected to obtain index data corresponding to the scheme file to be corrected; matching and checking the index data according to the checking standard to obtain a standard value;
and obtaining a correction result by correcting the standard value.
Analyzing the scheme file to be corrected to obtain the index data corresponding to the scheme file to be corrected comprises the following steps:
performing first round index data analysis by adopting a standard and standard index extraction mode, and realizing first round matching based on a standard library main body object;
checking the index matching rate with a standard library and the scheme text entry utilization rate, and directly comparing the scheme file to be corrected with the correction standard to obtain a correction result when the text entry utilization rate is 100%; otherwise, continuing the circular traversal scheme, analyzing the remaining text entries through semantics and a K-means algorithm, and acquiring index data matched with the standard data model; and stopping circulation when N cycles of circulation or the index rate matching rate is 100 percent.
Optionally, the document/device standard library includes standard index parameters, the standard index parameters are constructed by combining semantics and a word library, performing word segmentation processing through natural language processing by using grammatical structure characteristics, and combining a file structure outline.
Optionally, the analyzing the scheme file to be corrected to obtain the index data corresponding to the scheme file to be corrected includes:
and analyzing the scheme file to be corrected through a cache technology to obtain index data corresponding to the scheme file to be corrected.
Optionally, the performing matching and proofreading on the index data according to the proofreading standard to obtain a standard value includes:
and matching and correcting the correction standard and the index data through a text clustering related algorithm to obtain a standard value.
The application provides a scheme intelligent proofreading method based on electric power standard standardization datamation, which comprises the following steps: constructing a document/equipment standard library, wherein the document/equipment standard library is used for storing standard description modes of documents/equipment, and is stored in a relational database; inputting a scheme file to be corrected, and extracting a corresponding correction standard in the document/equipment standard library according to the scheme file to be corrected; comparing the scheme file to be corrected with the correction standard to obtain a correction result; and generating a proofreading result file according to the proofreading result, and outputting the proofreading result file. The intelligent learning algorithm is adopted to intelligently check the configuration files of the power secondary equipment, a document/equipment standard library is obtained after a large amount of configuration data are trained, and the intelligent checking is carried out on the configuration files of different types through the document/equipment standard library; the working efficiency and the accuracy are improved, and the workload of manual checking is reduced.
Drawings
Fig. 1 is a schematic flow chart of an embodiment of an intelligent calibration method for a power standard-based normative datamation scheme in the present application.
Detailed Description
The application provides an intelligent verification method based on a scheme of power standard standardization and datamation, which comprises the steps of intelligently verifying configuration files of power secondary equipment by adopting an intelligent learning algorithm, obtaining a document/equipment standard library after training a large amount of configuration data, and intelligently verifying different types of configuration files through the document/equipment standard library; the working efficiency and the accuracy are improved, and the workload of manual checking is reduced.
Referring to fig. 1, an embodiment of an intelligent calibration method based on a power standard normalized datamation scheme in the embodiment of the present application includes:
101. inputting a standard scheme file, and constructing a data model according to the standard scheme file;
in this embodiment, the process of constructing the data model is as follows:
and 1, inputting the standard scheme file into a system, and designing a basic model by analyzing the standard and standardizing the document structure of the standard scheme file and the description mode of the document to the electric power construction object and the electric power equipment by using a relational database. The basic model comprises a word stock, semantics, document information, a document text and an object standard library.
And 2, further initializing a semantic base, wherein the semantics conform to the characteristics of Chinese word segmentation, and main, predicate, object, definite, shape and complementary sentence structures. The method has the advantages that the method can better assist NLP operation to analyze text content, and accurately acquire data such as noun objects and standard index parameters in the document.
And 3, after the semantic base is initialized, initializing the word bank, wherein the word bank is continuously improved in the index extraction process, and the first step of initialization is to establish algorithm basic data. From the "terms/definitions" section in the standard scheme file structure, lexicon initialization can be initially completed, and the obtained proper names are basically subject objects for later comparison, such as: a dispatch data network, a comprehensive data network, a core router, a convergence router, etc.
And 4, finally, constructing by using general technical indexes, and in the southern power grid data network technical specification analysis, firstly analyzing chapter directories of standard scheme files to obtain data network construction index parameters, wherein the parameters comprise: the network management system comprises a network technology basic principle, network coverage and networking, upper and lower level integrated data network interconnection, network bandwidth and network performance, a routing protocol, VPN (virtual private network) setting, network security, an IP (Internet protocol) address, equipment type selection technology basic requirements, a power supply and environment, a core router technology, a convergence router technology, an access router technology, a core switch technology, a convergence switch technology, an access switch and a network management system, wherein index parameters are suitable for the technical standard requirements of power grid data network construction. The router/switch equipment metrics include: power supply mode, main control board redundancy, Ethernet interface, user protocol, Vlan, routing protocol-unicast, routing protocol-multicast, IPv6, manageability, quality of service QoS, traffic monitoring, port mirroring, network security, service isolation, reliability, interoperability. The general indexes can be obtained by adding a configured word stock and a semantic pair imported standard and specification through a calculation tool and performing NLP processing.
The basic data model construction is completed through the four steps, and the structure of the data model is stored in a relational database, wherein a standard and standard document data transformation table and an equipment standard configuration data transformation table exist in the relational database, as shown in table 1 and table 2:
table 1 is a standard, normalized document data transformation table; table 2 is a device standard configuration datamation table.
TABLE 1
TABLE 2
102. Extracting standard index data according to the standard scheme file;
after the data model is constructed, the system further extracts standard index data, specifically:
and 1, storing the text analysis content in a system cache through the imported document corresponding to the standard and normative standard scheme file, and performing repeated operation analysis. The data model structure analyzed and refined in the utilization step 101 is utilized, and then the technical index content is sequentially analyzed according to the model data hierarchy structure as the content of the standard index data.
And 2, each standard file is a root node of an object main body, the standard files are sequentially expanded according to the data model structure, the main body object and the attribute are nodes, and the attribute content is a leaf. The extraction of standard index data is mainly the extraction of contents, taking southern power grid data network technical specification as an example, the data contents obtained by a calculation tool are stored in a relational database, and a calculation tool interface program also visualizes the datamation result of the data contents. Wherein the data content stored in the relational data is as shown in table 3:
TABLE 3
103. And combining the standard index data and the data model to construct a document/equipment standard library.
After the constructed index data is extracted, the standard data is cached in the relational database, and at this time, the main object, the attribute and the content can be verified, so that the main object and the attribute can not be subjected to word segmentation in principle, and the single word group is obtained. The content of the index should satisfy non-null, contain some keywords (e.g. voltage should contain V, bandwidth contains Mbit/s, etc.). Further, a preliminary automatic verification may be accomplished via a computing tool, and the image of step 102 may be presented to a user interface for manual verification by a power professional.
Further, the basic document information corresponding to the standard scheme file is stored in a warehouse, the hash value of the document, the set version and the basic document file information are calculated and stored in a relational database, and document version management is achieved. And (4) storing the construction subject object and the attribute data of the document/equipment standard library in a warehouse, wherein the data are the construction object described in the standard and the specification and the technical standard requirement description of the electric power equipment. Storing the attribute and value modes into a relational database, establishing a top-bottom and level relation through a father ID, and carrying out friendly display in a brain graph mode through a webpage component when an interface is presented. Wherein the equipment standard indexes are shown in table 4:
TABLE 4
104. Inputting a scheme file to be corrected, and extracting a corresponding correction standard in a document/equipment standard library according to the scheme file to be corrected;
after the document/equipment standard library is constructed, a scheme file to be corrected is input into the system, wherein the scheme file to be corrected can be a construction scheme or an equipment configuration list, and the system can find out a correction standard and a standard library which can be used for index correction through document name or equipment name matching. In a computing tool interface, standard libraries for matching can be artificially added or deleted, and the standard specification catalogues are determined so as to quickly construct target data model content and realize that the error comparison rate of the quick matching standard data model is reduced.
105. Analyzing the scheme file to be corrected through a cache technology to obtain index data corresponding to the scheme file to be corrected; matching and checking the checking standard and the index data through a text clustering correlation algorithm to obtain a standard value;
in order to obtain a final proofreading result of a scheme file to be proofread, a standard value needs to be obtained first, wherein different construction schemes are different from an equipment configuration list, and equipment configuration can be rapidly corresponded through standard library index attributes. The structure of the content document of the construction scheme is not necessarily the same as the standard specification, and the index attribute matched with the content document needs to be found by circularly traversing the document for multiple times through indexes of the standard library. Specifically, the method comprises the following steps:
1, firstly, a standard and standard index extraction mode in the first method is adopted to analyze index data in a first round, and first-round matching can be quickly realized based on a main object of a standard library. For example, the construction of the root node scheduling data network is matched first, and then the network technical indexes and the equipment indexes are matched in sequence.
And 2, after the first round of index matching is completed, checking the index matching rate with the standard library and the scheme text entry utilization rate (namely the number of entries/total number of entries successfully corresponding to the scheme content and the standard library). When the text entry usage is 100%, step 106 is performed directly.
And 3, continuing a circular traversal scheme, analyzing the remaining text entries through algorithms such as semantics and K-means and the like, and acquiring index data matched with the standard data model. And stopping circulation when N circulation rounds are carried out or the index rate matching rate is 100%.
106. And obtaining a correction result by correcting the standard value.
After the standard value of the scheme file to be corrected is obtained, performing secondary matching on the index data in the step 105 to ensure the uniqueness of the standard value correction; if the unmatched items are successfully matched, the items are presented on a system interface, manually intervened and corrected, and deleted and corrected according to actual conditions.
After the uniqueness of the standard value is further determined, the standard value is corrected to obtain a correction result, specifically:
and 1, correcting by taking an index value in a standard library, wherein a text clustering matching algorithm set (K-means, ClaRANS and other algorithms) is required to be used for calculating text similarity.
2> equipment configuration index since the standard value of the standard library is a standard value range, the proofreading equipment is configured to be a unique value, and the method adopts text to contain matching. The standard values of the multiple items all meet the requirement that the indexes need to calculate the similarity of the indexes, and the standard indexes are included in the proofreading index content text.
And 3, sequentially finishing index comparison according to the data hierarchy structure, and calculating the matching degree of each index, wherein one standard comparison is the similarity average value of all indexes under the standard and the standard comparison. Circularly completing the matching calculation of all standard indexes to obtain a result; and after all indexes are calibrated, storing the calibration result into the relational database.
107. And generating a proofreading result file according to the proofreading result, and outputting the proofreading result file.
And using a calculation tool to present the proofreading result according to the index hierarchical structure by adopting a mode of an image interface for more results. The proofreading result comprises index matching success rate, matching accuracy rate, overall matching rate and the like. And labeling and prompting the items which do not meet the index standard, and giving error prompts. And mainly carrying out secondary check (correcting algorithm matching parameters) aiming at unmatched and non-compliant index results. And after the secondary automatic correction is finished, manual correction is carried out. If the comparison result is wrong, the index parameter library needs to be manually corrected. If the same type of errors are more, matching and checking are needed again.
Filing the matching result and storing the matching result into a relational database, reading the data from the relational database, and outputting a proofreading result report with a guiding function, such as a standard and standard proofreading record model, by adopting a report template; standard and standard proofreading result models; the device configuration proofreading record model and the device configuration proofreading result model. In this embodiment, the standard and normative proofreading record model is shown in table 5; the standard and normative proofreading result model is shown in table 6; the device configuration collation record model is shown in table 7; the device configuration collation result model is shown in table 8:
TABLE 5
TABLE 6
TABLE 7
TABLE 8
The intelligent learning algorithm is adopted to intelligently check the configuration files of the power secondary equipment, a document/equipment standard library is obtained after a large amount of configuration data are trained, and the intelligent checking is carried out on the configuration files of different types through the document/equipment standard library; the working efficiency and the accuracy are improved, and the workload of manual checking is reduced.
It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described systems, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the several embodiments provided in the present application, it should be understood that the disclosed system, apparatus and method may be implemented in other manners. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units is only one logical division, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application may be substantially implemented or contributed to by the prior art, or all or part of the technical solution may be embodied in a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a read-only memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and the like.
Claims (5)
1. A scheme intelligent proofreading method based on electric power standard specification datamation is characterized by comprising the following steps:
constructing a document/equipment standard library, wherein the document/equipment standard library is used for storing standard description modes of documents/equipment, and is stored in a relational database;
inputting a scheme file to be proofread, and extracting a corresponding proofreading standard in the document/equipment standard library according to the scheme file to be proofread;
comparing the scheme file to be corrected with the correction standard to obtain a correction result;
generating a proofreading result file according to the proofreading result, and outputting the proofreading result file;
the comparing the scheme file to be collated with the collation standard to obtain the collation result includes:
analyzing the scheme file to be corrected to obtain index data corresponding to the scheme file to be corrected; matching and checking the index data according to the checking standard to obtain a standard value;
obtaining a calibration result by calibrating the standard value;
analyzing the scheme file to be collated to obtain the index data corresponding to the scheme file to be collated comprises the following steps:
performing first-round index data analysis by adopting a standard and standard index extraction mode, and realizing first-round matching based on a main object of a standard library;
checking the index matching rate with a standard library and the scheme text entry utilization rate, and directly comparing the scheme file to be corrected with the correction standard to obtain a correction result when the text entry utilization rate is 100%; otherwise, continuing the circular traversal scheme, analyzing the remaining text entries through semantics and a K-means algorithm, and acquiring index data matched with the standard data model; and stopping circulation when N cycles of circulation or the index rate matching rate is 100 percent.
2. The intelligent proofreading method of solutions according to claim 1, wherein the constructing a document/device standard library comprises:
inputting a standard scheme file, and constructing a data model according to the standard scheme file;
extracting standard index data according to the standard scheme file;
and combining the standard index data and the data model to construct a document/equipment standard library.
3. The intelligent proof reading method for the scheme according to any one of claims 1 to 2, characterized in that the document/equipment standard library comprises standard index parameters, the standard index parameters are combined with a word library by semantics, word segmentation processing is performed by natural language processing by using grammatical structure characteristics, and then the standard index parameters are constructed by combining with a file structure outline.
4. The intelligent solution proofreading method according to claim 1, wherein the analyzing the solution file to be proofread to obtain index data corresponding to the solution file to be proofread includes:
and analyzing the scheme file to be corrected through a cache technology to obtain index data corresponding to the scheme file to be corrected.
5. The intelligent solution proofreading method according to claim 1, wherein the performing matching proofreading on the index data according to the proofreading criterion to obtain a criterion value comprises:
and matching and correcting the correction standard and the index data through a text clustering correlation algorithm to obtain a standard value.
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| CN114819565B (en) * | 2022-04-14 | 2024-03-22 | 中国南方电网有限责任公司 | Verification method of system specification description file, control equipment and intelligent substation |
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