CN112232031A - Method and device for verifying edge data model of power internet of things and storage medium - Google Patents
Method and device for verifying edge data model of power internet of things and storage medium Download PDFInfo
- Publication number
- CN112232031A CN112232031A CN202011118301.6A CN202011118301A CN112232031A CN 112232031 A CN112232031 A CN 112232031A CN 202011118301 A CN202011118301 A CN 202011118301A CN 112232031 A CN112232031 A CN 112232031A
- Authority
- CN
- China
- Prior art keywords
- data
- model
- verification
- edge
- public
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000013499 data model Methods 0.000 title claims abstract description 155
- 238000000034 method Methods 0.000 title claims abstract description 47
- 238000012795 verification Methods 0.000 claims abstract description 179
- 238000004458 analytical method Methods 0.000 claims description 26
- 238000005259 measurement Methods 0.000 claims description 16
- 238000010200 validation analysis Methods 0.000 claims description 7
- 230000008569 process Effects 0.000 claims description 6
- 238000004590 computer program Methods 0.000 claims description 4
- 238000013507 mapping Methods 0.000 claims description 4
- 230000007812 deficiency Effects 0.000 claims description 2
- 230000006855 networking Effects 0.000 claims 1
- 239000000126 substance Substances 0.000 claims 1
- 238000012545 processing Methods 0.000 abstract description 32
- 230000000694 effects Effects 0.000 abstract description 9
- 238000011157 data evaluation Methods 0.000 abstract 1
- 238000012827 research and development Methods 0.000 description 11
- 238000010586 diagram Methods 0.000 description 6
- 230000003287 optical effect Effects 0.000 description 6
- 230000006870 function Effects 0.000 description 4
- 230000003014 reinforcing effect Effects 0.000 description 4
- 238000005516 engineering process Methods 0.000 description 2
- 238000012544 monitoring process Methods 0.000 description 2
- 239000013307 optical fiber Substances 0.000 description 2
- 230000002093 peripheral effect Effects 0.000 description 2
- 230000000644 propagated effect Effects 0.000 description 2
- 238000012502 risk assessment Methods 0.000 description 2
- 238000003491 array Methods 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 238000004891 communication Methods 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
- 238000007405 data analysis Methods 0.000 description 1
- 238000012217 deletion Methods 0.000 description 1
- 230000037430 deletion Effects 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000011156 evaluation Methods 0.000 description 1
- 238000007499 fusion processing Methods 0.000 description 1
- 230000014509 gene expression Effects 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 238000007689 inspection Methods 0.000 description 1
- 238000009434 installation Methods 0.000 description 1
- 230000003993 interaction Effects 0.000 description 1
- 238000005457 optimization Methods 0.000 description 1
- 230000008707 rearrangement Effects 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 239000004065 semiconductor Substances 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F40/00—Handling natural language data
- G06F40/10—Text processing
- G06F40/12—Use of codes for handling textual entities
- G06F40/14—Tree-structured documents
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F40/00—Handling natural language data
- G06F40/20—Natural language analysis
- G06F40/205—Parsing
- G06F40/226—Validation
Abstract
The invention discloses a method for verifying an edge data model of an electric power Internet of things, which comprises the steps of acquiring first public data based on a logic model in the edge data model; acquiring second public data based on a physical model in the edge data model; respectively generating corresponding data in an XML format according to the first public data and the second public data; respectively verifying the first public data in the XML format and the second public data in the XML format based on the XML verification rule to obtain a first verification result; verifying the physical model based on a data consistency verification rule to obtain a second verification result; verifying the physical model based on a model rule to obtain a third verification result; and acquiring a final checking result of the edge data model based on the first checking result, the second checking result and the third checking result. The technical scheme provided by the embodiment of the invention can realize the effect of processing the edge side data by the edge data evaluation model.
Description
Technical Field
The embodiment of the invention relates to the technical field of power internet of things, in particular to a method and a device for verifying an edge data model of a power internet of things and a storage medium.
Background
In recent years, with the rapid development of informatization and intelligent technology, sensor technology has taken a leading position in the field of substation inspection business.
The power grid equipment carries out remote state monitoring through the installation sensor, and relieves the working pressure of workers. However, most sensors do not have the capability of edge data interaction and processing, the application scenarios are relatively single, and the problems that interface protocols are not uniform and data models are various cannot be solved, so that technical personnel design an edge data model which can process data in each application scenario, but whether the result of data fusion processing of terminal equipment in each application scenario by the edge data model is accurate or not needs to be judged, and a method capable of verifying the edge data model is urgently needed.
Disclosure of Invention
The invention provides a method and a device for verifying an edge data model of an electric power Internet of things and a storage medium, and aims to achieve the technical effect of monitoring whether the data processing result of the edge data model on edge side terminal equipment in different scenes is accurate or not.
In a first aspect, an embodiment of the present invention provides a method for verifying an edge data model of an electric power internet of things,
acquiring first public data based on a logic model in an edge data model;
acquiring second public data based on a physical model in the edge data model;
respectively generating corresponding data in an XML format according to the first public data and the second public data;
respectively verifying the first public data in the XML format and the second public data in the XML format based on the XML verification rule to obtain a first verification result;
verifying the physical model based on a data consistency verification rule to obtain a second verification result;
verifying the physical model based on the model rule to obtain a third verification result;
and acquiring a final verification result of the edge data model based on the first verification result, the second verification result and the third verification result.
In a second aspect, an embodiment of the present invention further provides an apparatus for verifying an edge data model of an electric power internet of things, where the apparatus includes:
the first public data acquisition module is used for acquiring first public data based on a logic model in the edge data model;
the second public data acquisition module is used for acquiring second public data based on the physical model in the edge data model;
the XML format data generation module is used for respectively generating corresponding data in an XML format according to the first public data and the second public data;
the first verification result acquisition module is used for respectively verifying the first public data in the XML format and the second public data in the XML format based on the XML verification rule to obtain a first verification result;
the second check result acquisition module is used for checking the physical model based on the data consistency verification rule to obtain a second check result;
the third verification result acquisition module is used for verifying the physical model based on the model rule to obtain a third verification result;
and the final verification result acquisition module is used for acquiring a final verification result of the edge data model based on the first verification result, the second verification result and the third verification result.
In a third aspect, an embodiment of the present invention further provides an edge data model checking device, where the device includes:
one or more processors;
a storage device for storing one or more programs,
when the one or more programs are executed by the one or more processors, the one or more processors implement the method for verifying the data model of the edge of the power internet of things according to any one of the embodiments of the present invention.
In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the method for verifying an edge data model of an electric power internet of things according to any one of the embodiments of the present invention.
According to the technical scheme provided by the embodiment of the invention, the first public data and the second public data are respectively obtained based on the logic model and the physical model in the edge data model, the first public data and the second public data are respectively generated into data in an XML format, and the first public data and the second public data which are generated in the XML format are verified through an XML verification rule to obtain a first verification result; and verifying the second public data through a data consistency principle to obtain a second verification result, verifying the physical model in the edge data model through a model principle to obtain a third verification result, and obtaining a final verification result of the edge data model through the three verification results. The verification method of the edge data model provided by the embodiment of the invention can realize the effect of evaluating the edge data model processing edge side data in the power internet of things, and assists research and development personnel in optimizing and reinforcing the edge data model.
Drawings
In order to more clearly illustrate the technical solutions of the exemplary embodiments of the present invention, a brief description is given below of the drawings used in describing the embodiments. It should be clear that the described figures are only views of some of the embodiments of the invention to be described, not all, and that for a person skilled in the art, other figures can be derived from these figures without inventive effort.
Fig. 1 is a schematic flowchart of a method for verifying an edge data model of an electric power internet of things according to a first embodiment of the present invention;
fig. 2 is a schematic flow chart illustrating verification of an edge data model of an electric power internet of things according to different scenarios according to a first embodiment of the present invention;
fig. 3 is a schematic flowchart of a method for verifying an edge data model of an electric power internet of things according to a second embodiment of the present invention;
fig. 4 is a schematic flow chart of a verification method for an edge data model of an electric power internet of things according to a second embodiment of the present invention in practical application;
fig. 5 is a schematic structural diagram of a verification apparatus for an edge data model of an electric power internet of things according to a third embodiment of the present invention;
fig. 6 is a schematic structural diagram of an edge data model checking device according to a fourth embodiment of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not limiting of the invention. It should be further noted that, for the convenience of description, only some of the structures related to the present invention are shown in the drawings, not all of the structures.
Example one
Fig. 1 is a schematic flow diagram of a method for verifying an edge data model of an electric power internet of things according to an embodiment of the present invention, where the method is applicable to a situation that different edge data of different scenes are faced to verify whether the edge data model of the electric power internet of things can perform data unified processing, and the method can be executed by an electric power internet of things edge data model verifying apparatus, and the apparatus can be implemented in a form of software and/or hardware.
As shown in fig. 1, the method of this embodiment includes:
and S110, acquiring first public data based on a logic model in the edge data model.
The edge side data model comprises a logic model and a physical model, wherein the logic model comprises attribute fields and mutual association relation of data of the edge side equipment. The edge side device includes a device in the station area, a terminal device of the substation, and the like. The first public data is logic parameter information for edge devices in the power internet of things, and comprises (Enterprise architecture, EA) help documents, and the EA file comprises the logic parameter information for the edge side devices. The logic parameter information of the edge equipment in the power internet of things can be obtained through the logic model.
And S120, acquiring second public data based on the physical model in the edge data model.
The physical model is a specific application of the logic model, the second public data comprises an EA file, and the EA file comprises physical parameter information in the edge side data. And acquiring the EA file with the physical parameter information of the edge device through a physical model in the edge data model.
S130, respectively generating corresponding data in an XML format according to the first public data and the second public data.
Specifically, the first public data with the logic parameter information and the second public data with the physical parameter information are respectively generated into data in an XML format, so that the subsequent verification process according to the XML rule is facilitated.
S140, respectively checking the first public data in the XML format and the second public data in the XML format based on the XML verification rule to obtain a first checking result.
Wherein the XML validation rules include: XML format verification, element uniqueness verification, element nesting relation verification, element attribute name uniqueness verification, deficiency verification of element optional attributes, and range constraint verification of element contents and attribute values. The XML verification rule is preset and can be replaced by a JSON rule, the first public data and the second public data can be converted into a JSON format, and then the first public data and the second public data in the JSON format are verified respectively through the JSON rule to obtain a first verification result.
Specifically, the XML validation rule is applied to validate the XML format, the element uniqueness, the element nesting relation, the element attribute name uniqueness, the element mandatory attribute deletion, the element content and the attribute value range constraint in the first public data in the XML format and the second public data in the XML format, so as to obtain a first validation result. Correspondingly, the element uniqueness verification may be used to verify whether each element in the first common data and the second common data has uniqueness, for example, any element may be compared with other elements to determine whether the same element exists, and if so, the same element is marked or the same element is subjected to deduplication processing. The elements in the first public data and the second public data should be correctly nested, each layer of nesting relation in the first public data of the logic model and the second public data of the physical model should meet strict regulations of standards, and correspondingly, element nesting relation verification is used for verifying the nesting relation between the elements in the first public data and the second public data based on the nesting relation standards. The attribute name contained in each element in the first public data and the second public data has uniqueness, and accordingly, the attribute name uniqueness of the element can be used for verifying whether the attribute name contained in each element in the first public data and the second public data has uniqueness, for example, when the attribute names of any two elements are the same, the element with the same attribute name is marked or a verification result is output as "no". The elements in the first public data and the second public data are distinguished by optional attributes and optional attributes, wherein the optional attributes cannot be lost in the first public data or the second public data, the content and the attribute value of the elements cannot exceed standard range constraints (including length, maximum and minimum values, regular expressions and other constraints), and when any element in the first public data or the second public data lacks the optional attributes, the element is marked or a verification result is output to be 'no'. For example, the naming case of the first public data of the logical model and the second public data of the physical model should be normalized, the attribute names begin with lower case letters, the element names begin with upper case letters, and the data types defined by the < DataTypeTemplates > defined by the data type template of the edge data model are checked to see if the data types have the same content and different names. It should be noted that, during actual task processing, after the XML verification is finished, the first verification result may be directly output, or after all the verifications are finished, the unified result output may be performed. For example, when any one of the XML rules is not successfully verified, the verification result is negative, the error position and the error rule are indicated, and the verification of the edge data model is continued.
Illustratively, when the corresponding data in the XML format is respectively generated according to the first public data and the second public data, the corresponding data in the SQL format is respectively generated according to the first public data and the second public data. The SQL validation rules are preset and comprise field names, main key names and the like, so that the XML and SQL validation rules are validated respectively aiming at two kinds of public data, and the physical model and the logic model can be validated more accurately.
S150, verifying the physical model based on the data consistency verification rule to obtain a second verification result.
The data consistency rule is preset, and the data consistency rule is verified against a physical model table, a field comparison table and the like in the physical model to obtain a second verification result. The data consistency verification is the same as the verification of the XML verification rule, the verification result can be output in real time in the verification process, and the verification result can also be output after all verification is finished. Therefore, the overall verification speed can be improved, the edge data model can be analyzed on the whole, and research and development personnel can analyze and improve the edge data model conveniently. Of course, the setting may also be performed according to the actual situation, for example, the research and development staff participates in the edge data model verification process, and when any one verification rule is not met, the output verification result is "no" and the detailed information of the corresponding error is set, and the verification is stopped, so that the research and development staff can adjust the edge data model in time.
And S160, verifying the physical model based on the model rule to obtain a third verification result.
Wherein the model rules are set for model properties of the physical model itself. The programming language of the model rules of the present invention includes the standard SQL language, but of course, other languages may be used for programming. And verifying the physical model in the edge data model according to the model rule to obtain a third verification result.
S170, obtaining a final verification result of the edge data model based on the first verification result, the second verification result and the third verification result.
It should be noted that, the verification of the edge data model of the present invention is performed after the edge data model performs the first edge side data processing, and according to the edge side data processing result, the verification of the edge data model is performed to evaluate the data processing effect of the edge data model.
Illustratively, in order to verify the data processing effect of the edge data model on different application scenarios, an embodiment of the present invention provides a method for verifying the edge data model for different scenarios, as shown in fig. 2, the edge data model is verified based on data of a metrology scenario, an analysis decision scenario, and a practice processing scenario; verifying the edge data model based on the data of the measurement scene and the analysis decision scene, and determining whether the edge data model covers the measurement scene and the analysis decision scene; and if so, verifying the edge data model based on the data of the transaction class scene. If the edge data model does not cover the measurement scene and/or the analysis decision scene, expanding the edge data model based on a known expansion model, and verifying the expanded edge data model based on the data of the transaction scene.
The measurement scene, the analysis decision scene and the transaction processing scene are divided during data calculation of the edge side equipment in the power internet of things. Because the scenes of the measurement scene and the analysis decision scene are complex relative to the scenes of the transaction processing scene, the invention firstly verifies the edge data model based on the data in the measurement scene and the analysis decision scene, verifies whether the edge data model can realize the edge data processing under various conditions in the complex scene, then verifies the edge data model based on the data in the scenes of the transaction processing, and evaluates the data processing effect of the edge data model. Known extended models include models that have been developed today that can perform data processing on edge-side data.
Specifically, data of the measurement scene is acquired, the edge data model performs data processing according to the data of the measurement scene, a data processing result is acquired, and the edge data model is checked according to the data processing result. Similarly, the edge data model is verified based on the data of the analysis decision scene and the data of the transaction processing scene, and when the verification result of the edge data model based on the data of the measurement scene and the data of the classification decision scene is yes, the edge data model can cover the measurement scene and the analysis decision scene. At this time, the verification of the edge data model of the transaction class scene is performed. When the edge data model is verified based on the data of the transaction type scene, the compliance degree of the edge data model is verified, the model compliance degree is a verification rule (XML verification rule, data consistency verification rule, model rule and the like) for evaluating whether the edge data model accords with the edge data model, the evaluation range comprises [0-1], the model compliance degree is set to be larger than 0.7, the edge data model is qualified, the edge data model is verified through the data based on the transaction type scene, and a verification result, namely the output model compliance degree, is output.
When the edge data model does not cover the measurement scene or analyze the edge data in the decision scene, the edge data model is expanded based on the known expansion model, if the expansion model and the edge data model thereof are the expansion model, the expanded edge data model can cover the measurement scene and the analysis decision scene, and the expanded edge data model is verified based on the data of the transaction scene, so that the compliance degree of the edge data model is verified. When the extended edge data model cannot cover the measurement scene and the analysis decision scene, the verification process of the edge data model is finished, and a verification result is output and fed back to related research and development personnel for the research and development personnel to improve the edge data model.
It should be noted that, the edge data model checking order of the data of the three scenes according to the present invention may be set differently according to circumstances.
According to the technical scheme provided by the embodiment of the invention, the first public data and the second public data are respectively obtained based on the logic model and the physical model in the edge data model, the first public data and the second public data are respectively generated into data in an XML format, and the first public data and the second public data which are generated in the XML format are verified through an XML verification rule to obtain a first verification result; and verifying the second public data through a data consistency principle to obtain a second verification result, verifying the physical model in the edge data model through a model principle to obtain a third verification result, and obtaining a final verification result of the edge data model through the three verification results. The verification method of the edge data model provided by the embodiment of the invention can realize the effect of evaluating the edge data model processing edge side data in the power internet of things, and assists research and development personnel in optimizing and reinforcing the edge data model.
Example two
Fig. 3 is a schematic flow chart of a method for verifying an edge data model of an electric power internet of things according to an embodiment of the present invention, where the embodiment is an optimization based on the above embodiment, and technical terms the same as or corresponding to the above embodiment will not be described again. The method of the embodiment of the invention comprises the following steps:
and S310, acquiring first public data based on a logic model in the edge data model.
And S320, acquiring second public data based on the physical model in the edge data model.
S330, respectively generating corresponding data in an XML format according to the first public data and the second public data.
S340, respectively checking the first public data in the XML format and the second public data in the XML format based on the XML verification rule to obtain a first checking result.
S350, constructing an edge data model checking database based on the second public data, wherein the edge data model checking database comprises: the data resource manual comprises a data table, an association relation table, a data table comparison table and a field comparison table.
The edge data model checking database is constructed based on second public data, and is second public data obtained by converting acquired result data after data processing is performed on data of edge side equipment by an edge data model, wherein the result data can be stored in a local cache queue file and can be directly called when needed.
And S360, performing data consistency check on the second public data through a data table, an association relation table, a data table comparison table and a field comparison table in the data resource manual to obtain a second check result.
And verifying the data consistency of the second public data of the physical model for the four tab tables, namely the data table, the association relation table, the data table comparison table and the field comparison table in the data resource manual.
Exemplarily, the data consistency check of the second public data is performed through a data table, an association table, a data table comparison table and a field comparison table in the data resource manual, and includes: verifying whether the second public data, the data table in the data resource manual, the association relation table, the data table comparison table and the physical model table name and field information in the field comparison table are consistent; carrying out correctness verification and integrity verification on the association relation; carrying out correctness verification and integrity verification on information in the data table comparison table and the field comparison table; and verifying whether the table-level association relationship exists in the one-to-many field mapping in the field comparison table.
Specifically, whether the data table information, the association relation, the data table comparison table and the field comparison table in the data resource manual are completely consistent or not is checked, whether the association relation of the physical model table in the association relation tab table in the data resource manual is complete or not is checked, whether the physical model table name and the field information in the data resource manual, the source end service system, the source end table and the source end table corresponding to the data table comparison table and the field comparison table 2 are correct or not is checked, and whether the one-to-many field mapping in the field comparison table in the data resource manual provides table-level association relation or not is checked. When any one of the verification results is 'no' and the data consistency result is 'no', the verification result can be output in real time, and the verification result can also be output after the overall verification of the edge data model is finished.
And S370, performing consistency check on the physical model based on the second public data, the analysis domain data resource manual, the physical model manual and the Gbase8a library establishing script to obtain a third check result.
The model rules comprise second public data, an analysis domain data resource manual, a physical model manual and a rule for verifying the physical model by using a Gbase8a library establishing script, wherein the Gbase8a library establishing script is pre-established and is a standard script which is used as a standard for verifying the consistency of the physical model. The analysis domain data resource manual can be constructed based on the second public data.
Illustratively, checking whether the information of the physical model table and the table field in the second public data, the analysis domain data resource manual, the physical model manual and the Gbase8a library establishing script is consistent; checking whether the field lengths and types in the physical model and the Gbase8a library establishing script are consistent; and checking whether the identifiers in the physical model and the Gbase8a library establishing script are consistent.
And S380, acquiring a final verification result of the edge data model based on the first verification result, the second verification result and the third verification result.
Fig. 4 is a schematic flow chart of the verification method for the edge data model of the power internet of things provided by the embodiment of the invention in practical application. And constructing a verification model of the edge data model through a UML modeling tool. The method comprises the steps of data acquisition, verification of an edge data model and subsequent data analysis.
Various data of the edge side device are acquired from any edge side data source (including one of a measurement type scene, an analysis decision type scene and a transaction type scene), and it should be understood that the data is the result data of the edge data model after the edge side data processing is performed once. And extracting a part of result data from the edge data model as data for verifying the edge data model, performing data transmission, and transmitting the data to a physical model and a logic model of the edge data model.
The method comprises the steps of obtaining respective first public data and second public data based on two logic models and two physical models, converting the first public data and the second public data into first public data and second public data in an XML format, verifying the two data according to an XML verification rule to obtain a first verification result, and verifying the physical model according to a data consistency rule and a model rule to obtain a second verification result and a third verification result. The data of the logic model can be subjected to model verification according to the data consistency rule and the model rule.
And risk analysis is respectively carried out on the verification results of the logic model and the physical model, and the verification results are stored in respective cache queue files, so that subsequent research personnel can conveniently check the verification results of the edge data model. The verification result of the physical model can be added to the model verification analysis result set after being processed by local cache, so that the subsequent research and development improvement of the edge data model can be conveniently analyzed, and the verification result of the logic model is issued through an external interface after being subjected to risk analysis and directly informed to research and development personnel.
The method for checking the edge data model of the power internet of things comprises the steps of obtaining first public data and second public data, generating an XML format, checking the first public data in the XML format and the second public data in the XML format respectively based on XML verification rules to obtain a first checking result, building an edge data model checking database, checking the data consistency of the second public data according to a data table, an association relation table, a data table comparison table and a field comparison table in a data resource manual, and checking the consistency of a physical model through the second public data, an analysis domain data resource manual, the physical model manual and a Gbase8a building script. The three verification results are combined together as a final verification result. The verification method of the edge data model provided by the embodiment of the invention can realize the effect of evaluating the edge data model processing edge side data in the power internet of things, and assists research and development personnel in optimizing and reinforcing the edge data model.
EXAMPLE III
Fig. 5 is a block diagram of an apparatus for inspecting an edge data model of an electrical power internet of things according to an embodiment of the present invention, where the apparatus is configured to perform the method for inspecting an edge data model of an electrical power internet of things according to any of the embodiments described above, and the apparatus may be implemented as software and/or hardware. The device includes:
a first common data obtaining module 510, configured to obtain first common data based on a logic model in the edge data model;
a second common data obtaining module 520, configured to obtain second common data based on the physical model in the edge data model;
an XML format data generating module 530, configured to generate corresponding data in an XML format according to the first public data and the second public data;
a first verification result obtaining module 540, configured to verify, based on an XML verification rule, the first public data in the XML format and the second public data in the XML format, respectively, to obtain a first verification result;
a second check result obtaining module 550, configured to check the physical model based on the data consistency verification rule, to obtain a second check result;
a third verification result obtaining module 560, configured to verify the physical model based on the model rule to obtain a third verification result;
and a final verification result obtaining module 570, configured to obtain a final verification result of the edge data model based on the first verification result, the second verification result, and the third verification result.
Further, the second verification result obtaining module 550 includes:
a database construction sub-module, configured to construct an edge data model check database based on second public data, where the edge data model check database includes: a data table, an association relation table, a data table comparison table and a field comparison table in the data resource manual;
and the second check result acquisition submodule is used for carrying out data consistency check on the second public data through a data table, an association relation table, a data table comparison table and a field comparison table in the data resource manual so as to acquire a second check result.
Further, the second verification result obtaining sub-module includes:
the first information checking unit is used for verifying whether the second public data, the data table in the data resource manual, the association relation table, the data table comparison table and the physical model table name and the field information in the field comparison table are consistent or not;
the incidence relation verifying unit is used for verifying the correctness and the integrity of the incidence relation;
the comparison table verification unit is used for carrying out correctness verification and integrity verification on information in the data table comparison table and the field comparison table;
and the incidence relation determining unit is used for verifying whether the table-level incidence relation exists in the one-to-many field mapping in the field comparison table.
Further, the third verification result obtaining module 560 includes:
and the model consistency checking submodule is used for carrying out consistency checking on the physical model based on the second public data, the analysis domain data resource manual, the physical model manual and the Gbase8a library establishing script so as to obtain a third checking result.
Further, the model consistency check submodule includes:
the second information checking unit is used for checking whether the information of the physical model table and the table field in the second public data, the analysis domain data resource manual, the physical model manual and the Gbase8a library establishing script is consistent or not;
the field checking unit is used for checking whether the field lengths and the types in the physical model and the Gbase8a library establishing script are consistent or not;
and the identifier checking unit is used for checking whether the identifiers in the physical model and the Gbase8a library establishing script are consistent or not.
According to the technical scheme provided by the embodiment of the invention, the first public data and the second public data are respectively obtained based on the logic model and the physical model in the edge data model, the first public data and the second public data are respectively generated into data in an XML format, and the first public data and the second public data which are generated in the XML format are verified through an XML verification rule to obtain a first verification result; and verifying the second public data through a data consistency principle to obtain a second verification result, verifying the physical model in the edge data model through a model principle to obtain a third verification result, and obtaining a final verification result of the edge data model through the three verification results. The verification method of the edge data model provided by the embodiment of the invention can realize the effect of evaluating the edge data model processing edge side data in the power internet of things, and assists research and development personnel in optimizing and reinforcing the edge data model.
It should be noted that, the units and modules included in the apparatus are merely divided according to functional logic, but are not limited to the above division as long as the corresponding functions can be implemented; in addition, specific names of the functional units are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the embodiment of the invention.
Example four
Fig. 6 is a schematic structural diagram of an edge data model checking device according to an embodiment of the present invention. FIG. 6 illustrates a block diagram of an exemplary device 60 suitable for use in implementing embodiments of the present invention. The device 60 shown in fig. 6 is only an example and should not bring any limitation to the function and scope of use of the embodiments of the present invention.
As shown in FIG. 6, device 60 is embodied in a general purpose computing device. The components of the device 60 may include, but are not limited to: one or more processors or processing units 601, a system memory 602, and a bus 603 that couples various system components including the system memory 602 and the processing unit 601.
Device 60 typically includes a variety of computer system readable media. Such media may be any available media that is accessible by device 60 and includes both volatile and nonvolatile media, removable and non-removable media.
The system memory 602 may include computer system readable media in the form of volatile memory, such as Random Access Memory (RAM)604 and/or cache memory 605. The device 60 may further include other removable/non-removable, volatile/nonvolatile computer system storage media. By way of example only, storage system 606 may be used to read from and write to non-removable, nonvolatile magnetic media (not shown in FIG. 6, commonly referred to as a "hard drive"). Although not shown in FIG. 6, a magnetic disk drive for reading from and writing to a removable, nonvolatile magnetic disk (e.g., a "floppy disk") and an optical disk drive for reading from or writing to a removable, nonvolatile optical disk (e.g., a CD-ROM, DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to the bus 603 by one or more data media interfaces. Memory 602 may include at least one program product having a set (e.g., at least one) of program modules that are configured to carry out the functions of embodiments of the invention.
A program/utility 608 having a set (at least one) of program modules 607 may be stored, for example, in memory 602, such program modules 607 including, but not limited to, an operating system, one or more application programs, other program modules, and program data, each of which examples or some combination thereof may comprise an implementation of a network environment. The program modules 607 generally perform the functions and/or methods of the described embodiments of the invention.
Device 60 may also communicate with one or more external devices 609 (e.g., keyboard, pointing device, display 610, etc.), with one or more devices that enable a user to interact with device 60, and/or with any devices (e.g., network card, modem, etc.) that enable device 60 to communicate with one or more other computing devices. Such communication may occur via an input/output (I/O) interface 611. Also, device 60 may communicate with one or more networks (e.g., a Local Area Network (LAN), a Wide Area Network (WAN), and/or a public network, such as the internet) via network adapter 612. As shown, a network adapter 612 communicates with the other modules of device 60 via bus 603. It should be appreciated that although not shown in FIG. 6, other hardware and/or software modules may be used in conjunction with device 60, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, among others.
The processing unit 601 executes various functional applications and data processing by running a program stored in the system memory 602, for example, implementing the verification method for the edge data model of the power internet of things provided by the embodiment of the present invention.
EXAMPLE five
Embodiments of the present invention also provide a storage medium containing computer-executable instructions, which when executed by a computer processor, are configured to perform a power internet of things edge data model verification method.
Computer storage media for embodiments of the invention may employ any combination of one or more computer-readable media. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: an electrical connection having 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. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
A computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.
Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
Computer program code for carrying out operations for embodiments of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).
It is to be noted that the foregoing is only illustrative of the preferred embodiments of the present invention and the technical principles employed. It will be understood by those skilled in the art that the present invention is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, although the present invention has been described in greater detail by the above embodiments, the present invention is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the present invention, and the scope of the present invention is determined by the scope of the appended claims.
Claims (11)
1. A method for verifying an edge data model of an electric power Internet of things is characterized by comprising the following steps:
acquiring first public data based on a logic model in an edge data model;
acquiring second public data based on a physical model in the edge data model;
respectively generating corresponding data in an XML format according to the first public data and the second public data;
respectively verifying the first public data in the XML format and the second public data in the XML format based on the XML verification rule to obtain a first verification result;
verifying the physical model based on a data consistency verification rule to obtain a second verification result;
verifying the physical model based on a model rule to obtain a third verification result;
and acquiring a final checking result of the edge data model based on the first checking result, the second checking result and the third checking result.
2. The method of claim 1, wherein the XML validation rules comprise: XML format verification, element uniqueness verification, element nesting relation verification, element attribute name uniqueness verification, deficiency verification of element optional attributes, and range constraint verification of element contents and attribute values.
3. The method of claim 1, wherein verifying the physical model based on the data consistency validation rule, and obtaining the second verification result comprises:
constructing an edge data model check database based on the second public data, wherein the edge data model check database comprises: a data table, an association relation table, a data table comparison table and a field comparison table in the data resource manual;
and performing data consistency check on the second public data through a data table, an association relation table, a data table comparison table and a field comparison table in the data resource manual to obtain a second check result.
4. The method of claim 3, wherein performing a data consistency check on the second public data through a data table, an association table, a data table lookup table, and a field lookup table in a data resource manual comprises:
verifying whether the second public data, the data table in the data resource manual, the association relation table, the data table comparison table and the physical model table name and field information in the field comparison table are consistent;
carrying out correctness verification and integrity verification on the association relation;
carrying out correctness verification and integrity verification on information in the data table comparison table and the field comparison table;
and verifying whether the table-level association relationship exists in the one-to-many field mapping in the field comparison table.
5. The method of claim 1, wherein the verifying the physical model based on the model rule, and obtaining the third verification result comprises:
and performing consistency check on the physical model based on the second public data, the analysis domain data resource manual, the physical model manual and the Gbase8a library establishing script to obtain a third check result.
6. The method of claim 5, wherein the consistency check of the physical model based on the second public data, the analysis domain data resources manual, the physical model manual, and the Gbase8a library-building script comprises:
checking whether the information of the physical model table and the table field in the second public data, the analysis domain data resource manual, the physical model manual and the Gbase8a library establishing script is consistent;
checking whether the field lengths and types in the physical model and the Gbase8a library establishing script are consistent;
and checking whether the identifiers in the physical model and the Gbase8a library establishing script are consistent.
7. The method of claim 1, wherein the edge data model is validated based on data from a metrology class scenario, an analytical decision class scenario, and a business process class scenario; wherein the content of the first and second substances,
verifying the edge data model based on the data of the measurement scene and the analysis decision scene, and determining whether the edge data model covers the measurement scene and the analysis decision scene;
and if so, verifying the edge data model based on the data of the transaction class scene.
8. The method of claim 7, wherein if the edge data model does not cover the metrology class scenario and/or the analysis decision class scenario, then extending the edge data model based on a known extension model, and validating the extended edge data model based on data of the transaction class scenario.
9. The utility model provides an electric power thing networking edge data model calibration equipment which characterized in that includes:
the first public data acquisition module is used for acquiring first public data based on a logic model in the edge data model;
the second public data acquisition module is used for acquiring second public data based on the physical model in the edge data model;
the XML format data generation module is used for respectively generating corresponding data in an XML format according to the first public data and the second public data;
the first verification result acquisition module is used for respectively verifying the first public data in the XML format and the second public data in the XML format based on the XML verification rule to obtain a first verification result;
the second check result acquisition module is used for checking the physical model based on the data consistency verification rule to obtain a second check result;
the third verification result acquisition module is used for verifying the physical model based on the model rule to obtain a third verification result;
and the final verification result acquisition module is used for acquiring a final verification result of the edge data model based on the first verification result, the second verification result and the third verification result.
10. An edge data model verification apparatus, characterized in that the apparatus comprises:
one or more processors;
a storage device for storing one or more programs,
when executed by the one or more processors, cause the one or more processors to implement the power internet of things edge data model verification method of any of claims 1-8.
11. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, implements the method for verifying an edge data model of an electric power internet of things according to any one of claims 1 to 8.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011118301.6A CN112232031A (en) | 2020-10-19 | 2020-10-19 | Method and device for verifying edge data model of power internet of things and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011118301.6A CN112232031A (en) | 2020-10-19 | 2020-10-19 | Method and device for verifying edge data model of power internet of things and storage medium |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN112232031A true CN112232031A (en) | 2021-01-15 |
Family
ID=74117542
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202011118301.6A Pending CN112232031A (en) | 2020-10-19 | 2020-10-19 | Method and device for verifying edge data model of power internet of things and storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112232031A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113726616A (en) * | 2021-11-04 | 2021-11-30 | 国网江苏省电力有限公司信息通信分公司 | Method, device and system for detecting abnormal data in real time based on power internet of things |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20060167905A1 (en) * | 2005-01-27 | 2006-07-27 | Peiya Liu | Method and system for template data validation based on logical constraint specifications |
| CN105589886A (en) * | 2014-10-24 | 2016-05-18 | 国家电网公司 | Power network public information model construction method and power network public information model construction device |
| CN111079284A (en) * | 2019-12-12 | 2020-04-28 | 北京中电普华信息技术有限公司 | Power grid global logic data model verification method, device, server and medium |
| CN111258998A (en) * | 2020-01-16 | 2020-06-09 | 北京字节跳动网络技术有限公司 | Data verification method, device, medium and electronic equipment |
-
2020
- 2020-10-19 CN CN202011118301.6A patent/CN112232031A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20060167905A1 (en) * | 2005-01-27 | 2006-07-27 | Peiya Liu | Method and system for template data validation based on logical constraint specifications |
| CN105589886A (en) * | 2014-10-24 | 2016-05-18 | 国家电网公司 | Power network public information model construction method and power network public information model construction device |
| CN111079284A (en) * | 2019-12-12 | 2020-04-28 | 北京中电普华信息技术有限公司 | Power grid global logic data model verification method, device, server and medium |
| CN111258998A (en) * | 2020-01-16 | 2020-06-09 | 北京字节跳动网络技术有限公司 | Data verification method, device, medium and electronic equipment |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113726616A (en) * | 2021-11-04 | 2021-11-30 | 国网江苏省电力有限公司信息通信分公司 | Method, device and system for detecting abnormal data in real time based on power internet of things |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Zendel et al. | How good is my test data? Introducing safety analysis for computer vision | |
| US20160315823A1 (en) | Enabling real-time operational environment conformity within an enterprise architecture model dashboard | |
| EP2533180A1 (en) | Systems and methods for creating intuitive context for analysis data | |
| US20080155335A1 (en) | Graphical analysis to detect process object anomalies | |
| KR101774878B1 (en) | The method for errors detecting of digitalmap | |
| CN107357970B (en) | Data mining-based building information model abnormal element detection device and method | |
| CN111061833A (en) | Data processing method and device, electronic equipment and computer readable storage medium | |
| US20200210401A1 (en) | Proactive automated data validation | |
| CN103150647B (en) | Report file disposal route, server and system | |
| US20180096038A1 (en) | Model-driven profiling job generator for data sources | |
| CN112445866A (en) | Data processing method and device, computer readable medium and electronic equipment | |
| CN114090556B (en) | Electric power marketing data acquisition method and system | |
| US20160378817A1 (en) | Systems and methods of identifying data variations | |
| CN113806332B (en) | Heterogeneous system integrated data processing method and device and computer equipment | |
| CN105739979B (en) | A kind of workflow choosing method based on probability service procedure | |
| CN112232031A (en) | Method and device for verifying edge data model of power internet of things and storage medium | |
| CN110647523A (en) | Data quality analysis method and device, storage medium and electronic equipment | |
| CN110471912B (en) | Employee attribute information verification method and device and terminal equipment | |
| CN111079284A (en) | Power grid global logic data model verification method, device, server and medium | |
| Weber et al. | Detecting inconsistencies in multi-view uml models | |
| US9330115B2 (en) | Automatically reviewing information mappings across different information models | |
| Jiang et al. | A BIM-based code checking approach for green construction | |
| CN113703739A (en) | Cross-language fusion computing method, system and terminal based on omiga engine | |
| CN113238940A (en) | Interface test result comparison method, device, equipment and storage medium | |
| KR102411292B1 (en) | Method of mamaging quality of smart factory data |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |