1. A major network equipment image device based on label technique, characterized by that includes:

the information access module is used for collecting equipment information and meteorological information of multiple systems;

the data cleaning module is connected with the information access module, cleans the equipment information and the meteorological information and constructs the association between the meteorological information and the equipment information;

the application scene definition module is used for carrying out scene definition;

the label definition module is connected with the application scene definition module, acquires required information from the application scene definition module and realizes the hierarchical classification definition of the corresponding scene labels;

the characteristic extraction module is respectively connected with the data cleaning module and the label definition module and is used for extracting the characteristics of the data output by the data cleaning module on the basis of label definition;

the label generation module is respectively connected with the label definition module and the feature extraction module and generates a label of the equipment by matching feature information with a label value;

and the equipment portrait display module is respectively connected with the application scene definition module and the label generation module and is used for displaying portraits of corresponding equipment of the concerned equipment type in different application scenes.

2. A master network device imaging apparatus based on tag technology according to claim 1, wherein: the equipment information comprises equipment model information and management information of an OMS (operation management system), equipment operation information and equipment topology information of an EMS (energy management system), and equipment position information and monitoring information of a video monitoring system; the weather information comprises equipment operation environment information of the weather system.

3. A master network device imaging apparatus based on tag technology according to claim 1, wherein: the data cleaning module cleans the equipment information and the meteorological information on the basis of univariate data identification and cross data identification rules, so that the access information meets the requirements of consistency, normalization, integrity and timeliness.

4. The tag technology-based primary network device imaging apparatus according to claim 1, wherein the contextualized definition includes: scene name, scene description, scene effective time, scene service object, attention device type and scene layout; the concerned equipment type is used for matching associated equipment of the label, namely equipment of a corresponding type; the scene layout is used for confirming the display position of the label.

5. A master network device imaging apparatus based on tag technology according to claim 1, wherein: the label definition comprises a label name, an application scene, effective starting time, effective ending time, associated equipment, a label type, a label hierarchy and a label value; when the labels are defined hierarchically, the hierarchical division of the labels comprises static labels, dynamic labels and prediction labels; when the labels are defined in a classified mode, the type division of the labels comprises model labels, overhaul labels, alarm labels, disposal labels and early warning labels.

6. A main network device image device based on label technology according to claim 5, characterized in that: the feature extraction module identifies similar device information descriptions as corresponding features based on the tag name in the tag definition.

7. A main network device image device based on label technology according to claim 5, characterized in that: the tag generation module is used for generating tags serving the equipment portrait, realizing matching of tag names, associated equipment types and equipment features based on feature extraction of cleaned data, completing generation of tags, timely revoking tags exceeding effective end time, and simultaneously timely confirming validity of the tags under the conditions of equipment attribute change and meteorological environment change.

8. A master network device imaging apparatus based on tag technology according to claim 7, wherein: the equipment attribute change comprises the change of the equipment attribute caused by equipment change, equipment overhaul, equipment commissioning and equipment retirement conditions.

9. A method for drawing an image of a main network device based on a label technology is characterized by comprising the following steps:

collecting equipment information and meteorological information of multiple systems by using an information access module;

cleaning the equipment information and the meteorological information by using a data cleaning module, and constructing the association between the meteorological information and the equipment information;

performing scene definition by using an application scene definition module;

acquiring required information from an application scene definition module by using a label definition module to realize hierarchical classification definition of corresponding scene labels;

performing feature extraction on the data output by the data cleaning module by using a feature extraction module based on the label definition;

generating a label of the equipment by matching the characteristic information with the label value by using a label generation module;

and utilizing the equipment portrait showing module to show the portrait of the corresponding equipment of the type of the equipment concerned under different application scenes.

10. A method as claimed in claim 9, wherein the method comprises: the content of the scene definition comprises: scene name, scene description, scene effective time, scene service object, attention device type and scene layout; the concerned equipment type is used for matching associated equipment of the label, namely equipment of a corresponding type; the scene layout is used for confirming the display position of the label.

11. A method as claimed in claim 9, wherein the method comprises: the label definition comprises a label name, an application scene, effective starting time, effective ending time, associated equipment, a label type, a label hierarchy and a label value; when the labels are defined hierarchically, the hierarchical division of the labels comprises static labels, dynamic labels and prediction labels; when the labels are defined in a classified mode, the type division of the labels comprises model labels, overhaul labels, alarm labels, disposal labels and early warning labels.

12. A method as claimed in claim 11, wherein the method comprises: the tag generation module is used for generating tags serving the equipment portrait, realizing matching of tag names, associated equipment types and equipment features based on feature extraction of cleaned data, completing generation of tags, timely revoking tags exceeding effective end time, and simultaneously timely confirming validity of the tags under the conditions of equipment attribute change and meteorological environment change.

13. A method as claimed in claim 11, wherein the method comprises: the feature extraction module identifies similar device information descriptions as corresponding features based on the tag name in the tag definition.

Background

With the gradual expansion of the scale of the power grid and the continuous improvement of the intelligent level, the number of power grid devices which need to be monitored and controlled by professional operation personnel in the field of regulation and control is gradually increased, so that the problem that management personnel and operation personnel in the complex power grid operation environment lack means and system support for sensing the operation state of the devices, intelligent decision cannot be made, and effective measures are further lacked for early warning and pre-control of power grid risks.

The chinese patent application with application number 201910981737.9 discloses a method for device portrait based on monitoring alarm signal, but this method for device portrait only relies on monitoring alarm signal to portrait the device, its data source is limited, no device model information, device management information and other auxiliary information are introduced, and the signal normalization will severely restrict the accuracy and applicability of the device portrait.

The application number 202010219516.0 of the invention is China patent application, which discloses a power distribution network equipment portrait method and system based on multidimensional data analysis application, the application scenario is mainly a power distribution network architecture, and the method has limited applicability to power grid equipment because the difference between a main network architecture and the power distribution network architecture is large, and the equipment portrait method, especially factors needing to be considered by a prediction label, are greatly different.

The Chinese patent application with the application number of 201911119359.X provides the basis for equipment portrait, which is mainly to determine familial defects and equipment maintenance conditions through the analysis of equipment types, manufacturers and models, and is mainly served for maintenance personnel.

Although the above three methods all refer to equipment portrayal, the data sources for equipment portrayal reference are limited, the data sources are not fully accessed to the information of the production system and the management system in the current power grid regulation and control field, and meanwhile, the application scenes of the methods are not adaptive, and the requirements of relevant professionals on equipment portrayal cannot be fully met. On the other hand, the updating consideration factors of the label are few, so that the timeliness of the label is low, and related personnel cannot be guided to carry out power grid operation.

Disclosure of Invention

In order to solve the problems, the invention provides a main network equipment portrayal device and a main network equipment portrayal method based on a label technology, which can access multi-source service data and portray power grid equipment based on an application scene, so that related personnel can be assisted to make intelligent decisions, accurate recommendation, intelligent retrieval and the like.

In order to achieve the technical purpose and achieve the technical effects, the invention is realized by the following technical scheme:

in a first aspect, the present invention provides a primary network device portrait apparatus based on tag technology, including:

the information access module is used for collecting equipment information and meteorological information of multiple systems;

the data cleaning module is connected with the information access module, cleans the equipment information and the meteorological information and constructs the association between the meteorological information and the equipment information;

the application scene definition module is used for carrying out scene definition;

the label definition module is connected with the application scene definition module, acquires required information from the application scene definition module and realizes the hierarchical classification definition of the corresponding scene labels;

the characteristic extraction module is respectively connected with the data cleaning module and the label definition module and is used for extracting the characteristics of the data output by the data cleaning module on the basis of label definition;

the label generation module is respectively connected with the label definition module and the feature extraction module and generates a label by matching feature information with a label value;

and the equipment portrait display module is respectively connected with the application scene definition module and the label generation module and is used for displaying portraits of corresponding equipment of the concerned equipment type in different application scenes.

Optionally, the device information includes device model information and management information of the OMS system, device operation information and device topology information of the EMS system, and device location information and monitoring information of the video monitoring system; the weather information comprises equipment operation environment information of the weather system.

Optionally, the data cleaning module cleans the equipment information and the meteorological information based on univariate data identification and cross data identification rules, so that the access information meets the requirements of consistency, normalization, integrity and timeliness.

Optionally, the contextualized definition includes: scene name, scene description, scene effective time, scene service object, attention device type and scene layout; the concerned equipment type is used for matching associated equipment of the label, namely equipment of a corresponding type; the scene layout is used for confirming the display position of the label.

Optionally, the tag definition includes a tag name, an application scenario, a valid start time, a valid end time, an associated device, a tag type, a tag hierarchy, and a tag value; when the labels are defined hierarchically, the hierarchical division of the labels comprises static labels, dynamic labels and prediction labels; when the labels are defined in a classified mode, the type division of the labels comprises model labels, overhaul labels, alarm labels, disposal labels and early warning labels.

Optionally, the feature extraction module confirms similar device information descriptions as corresponding features based on tag names in the tag definitions.

Optionally, the tag generation module is configured to generate a tag serving the equipment portrait, perform feature extraction on the cleaned data, implement matching between a tag name, a related equipment type, and an equipment feature, complete generation of the tag, disable the tag that has exceeded an effective end time in time, and confirm validity of the tag in time under the condition of equipment attribute change and weather environment change.

Optionally, the device attribute change includes a change of a device attribute caused by a device change, a device overhaul, a device commissioning, and a device decommissioning condition.

In a second aspect, the present invention provides a method for imaging a master network device based on a tag technology, including:

collecting equipment information and meteorological information of multiple systems by using an information access module;

cleaning the equipment information and the meteorological information by using a data cleaning module, and constructing the association between the meteorological information and the equipment information;

performing scene definition by using an application scene definition module;

acquiring required information from an application scene definition module by using a label definition module to realize hierarchical classification definition of corresponding scene labels;

performing feature extraction on the data output by the data cleaning module by using a feature extraction module based on the label definition;

generating a label by matching the characteristic information with the label value by using a label generation module;

and utilizing the equipment portrait showing module to show the portrait of the corresponding equipment of the type of the equipment concerned under different application scenes.

Optionally, the contextualized definition includes: scene name, scene description, scene effective time, scene service object, attention device type and scene layout; the concerned equipment type is used for matching associated equipment of the label, namely equipment of a corresponding type; the scene layout is used for confirming the display position of the label.

Optionally, the tag definition includes a tag name, an application scenario, a valid start time, a valid end time, an associated device, a tag type, a tag hierarchy, and a tag value; when the labels are defined hierarchically, the hierarchical division of the labels comprises static labels, dynamic labels and prediction labels; when the labels are defined in a classified mode, the type division of the labels comprises model labels, overhaul labels, alarm labels, disposal labels and early warning labels.

Optionally, the tag generation module is configured to generate a tag serving the equipment portrait, perform feature extraction on the cleaned data, implement matching between a tag name, a related equipment type, and an equipment feature, complete generation of the tag, disable the tag that has exceeded an effective end time in time, and confirm validity of the tag in time under the condition of equipment attribute change and weather environment change.

Optionally, the feature extraction module confirms similar device information descriptions as corresponding features based on tag names in the tag definitions.

Compared with the prior art, the invention has the beneficial effects that:

the invention fully accesses the data of the multisource service system, including the equipment maintenance information of an OMS system, the equipment alarm information, the equipment remote measurement information, the equipment state information and the like of an EMS system, the image acquisition information and the image analysis result information of a video monitoring system, and the historical weather and weather forecast of a weather system; 2) the configuration of the application scene is realized, the equipment portrait result is more in line with the requirements of each specialty through the configuration, and the redundant display of irrelevant labels is reduced; 3) by considering information such as tag timeliness, equipment attributes and weather environment changes, the tags are updated, so that the equipment portrait result timeliness is higher, and intelligent decision and accurate pushing of business personnel are facilitated.

Drawings

In order that the present disclosure may be more readily and clearly understood, reference is now made to the following detailed description of the present disclosure taken in conjunction with the accompanying drawings, in which:

FIG. 1 is a schematic diagram of an apparatus imaging device according to an embodiment of the present invention;

FIG. 2 is a functional diagram of an application scenario definition module according to an embodiment of the present invention;

FIG. 3 is a flow chart illustrating timely tag update according to an embodiment of the present invention;

FIG. 4 is a flow chart illustrating a method for rendering a primary network device in an embodiment of the present invention.

Detailed Description

In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail with reference to the following embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and do not limit the scope of the invention.

The following detailed description of the principles of the invention is provided in connection with the accompanying drawings.

Example 1

As shown in fig. 1, an embodiment of the present invention provides a primary network device representation apparatus based on tag technology, including:

the information access module 1 is used for collecting basic information of equipment derived from an OMS system, an EMS system and the like and auxiliary information of other systems, including equipment model information, equipment operation information, meteorological information and the like. Specifically, the equipment operation information comprises a monitoring alarm signal, equipment defect information, equipment operation information and equipment maintenance information; device model information device type, device name, device voltage class, device production date, etc.; video surveillance information and weather environment information. Which provides a data source for the data cleansing module 2.

And the data cleaning module 2 is used for cleaning the accessed equipment information to ensure that the data meets the requirements of consistency, normalization, integrity and timeliness, and the cleaning rule comprises a univariate data identification rule and a cross data identification rule. This module provides a data source for the feature extraction module 3.

The application scene definition module 3 is configured to perform scene definition based on a scene that needs service for the device representation and service personnel, as shown in fig. 2, configure a scene name, a scene description, a scene validity time, applicable service personnel, a type of concerned device, and a scene layout, and store a corresponding configuration result in a database. This module provides configuration information for the tag definition module 4 and the device representation presentation module 8.

The label definition module 4 is used for realizing the hierarchical classification definition of the labels, and the hierarchical classification of the labels comprises static labels, dynamic labels and prediction labels; the type division comprises a model label, a maintenance label, an alarm label, a disposal label, an early warning label and the like. The static label is mainly equipment model information, such as equipment manufacturer, equipment type, equipment voltage grade, equipment model, equipment commissioning date and the like; the dynamic labels are mainly equipment maintenance times, equipment alarm information quantity, equipment state change times, equipment defect quantity and the like; the prediction label is mainly used for predicting the risk level of equipment, the service life of the equipment, the fault of the equipment and the like. This module provides configuration information to the feature extraction module 5.

And the feature extraction module 5 is used for performing feature extraction on the cleaned data so as to serve for label generation. The feature extraction technology comprises a word segmentation technology, a semantic recognition technology, clustering analysis and the like, if the general description mode of the monitoring information is 'time + object + information description + behavior', the word segmentation technology is adopted to recognize one by one, and feature identification is respectively carried out on the recognition. Which provides a data source for the tag generation module 6.

A tag generation module 6 for generating a tag serving the device representation. The module forms attributes of the label, such as label name, application scene, effective start time, effective end time, associated equipment, label type, label hierarchy, label value and the like, based on the feature extraction result, and realizes timely update of the label according to effective timeliness of the label, equipment attribute change and meteorological environment change. The tag timeliness mainly judges the relation between the equipment image display time and the tag effective starting time and tag effective ending time; the equipment attribute change comprises the change of equipment parameters caused by equipment change, equipment overhaul, equipment commissioning, equipment decommissioning and the like. As shown in fig. 3, by gradually determining the tag timeliness, the device attribute change, and the external environment change, the device tag is changed if the above occurs. Which provides a data source for the device representation rendering module 7.

And the device portrait display module 7 is used for displaying the portrait of the device in different application scenes. The module displays the device portrait by applying the information such as the scene layout, the scene name, the scene description, the attention device type and the like output by the scene definition module.

As shown in fig. 4, the primary network device representation method of the present invention includes the following steps:

step 1: and connecting the multi-source business system to obtain equipment information. The embodiment of the invention is connected through a configuration database and then accessed into basic information of equipment such as an OMS system and an EMS system; and simultaneously, the information of the video monitoring system and the meteorological system is obtained in a service mode.

Step 2: and carrying out data cleaning on the equipment information by adopting univariate data identification and cross data identification rules.

The univariate data identification rule is configured based on a single data source, so that the data is cleaned; the cross data identification rule is configured based on a plurality of data sources, and the data is cleaned.

And step 3: extracting device features from the cleaning result based on the application scenario definition and the data tag definition, specifically:

acquiring a scene name, a scene description, scene effective time, applicable service personnel, a type of concerned equipment and a scene layout from an application scene definition;

acquiring a label name, an application scene, effective start time, effective end time, associated equipment, a label type and a label hierarchy from the data label definition;

the way of extracting the device features from the data cleaning results includes several ways:

in the method (1), equipment features are extracted based on the name of a data field, such as an equipment manufacturer field, an equipment model field, an equipment type field, an equipment voltage level field and the like, and the extractable equipment features comprise characteristic information of the equipment manufacturer, the equipment model, the equipment type, the equipment voltage level and the like;

in the mode (2), a word segmentation technology is adopted to identify cleaning results, such as monitoring information, and the device name and the device behavior are matched by segmenting the contents such as time, objects, information description and behaviors;

in the mode (3), the cleaning result, such as equipment defect description information, is identified by clustering analysis, and the familial defect information is identified by clustering analysis on the manufacturer, the equipment model, the equipment type and the like;

and 4, step 4: and matching the label with the equipment is realized on the feature extraction result by adopting a manual labeling mode and an automatic labeling mode, so that label generation is realized. Specifically, the manual labeling mode mainly depends on expert experience, if a certain main transformer equipment commissioning time field is '2016, 5, 1 and', the equipment commissioning time length is 5 years by extracting the equipment characteristics based on the name of the data field, and further, the equipment service life label can be identified as 'young equipment' by summarizing and analyzing the historical operation conditions of the equipment of a manufacturer and the same manufacturer by experts; the automatic labeling mode is based on a data mining analysis means, such as the equipment service life prediction and the like through the analysis of data such as equipment commissioning time, equipment maintenance conditions, equipment defect conditions and the like. Meanwhile, the tags that have exceeded the valid end time are revoked in time, and the validity of the tags is confirmed in time under the conditions of the equipment attribute change and the weather environment change, and the specific updating flow is shown in fig. 3.

And 5, updating the tag in time based on the timeliness of the tag, the equipment attribute, the change of the meteorological environment and the like. Specifically, whether the validity period of the tag meets the requirements of an application scene is judged based on the timeliness of the tag; specifically, the method comprises the following steps:

the judgment of the equipment attribute change comprises the change of the equipment attribute caused under the conditions of equipment change, equipment overhaul, equipment commissioning, equipment retirement and the like;

the equipment change mainly comprises the replacement of equipment parts;

changes in equipment servicing times can cause changes in the servicing attribute tags, including non-serviced, small number of overhauls, frequent overhauls.

Changes in the device commissioning time can cause changes in the device operational age tags, including a run time of less than 5 years, a run time of greater than or equal to 5 years and less than 10 years, a run time of greater than or equal to 10 years and less than 20 years, and a run time of greater than or equal to 20 years.

Changes in the decommissioning state of the equipment can cause changes in the operational state labels of the equipment, including planning, under-construction, in-service, and decommissioning.

Step 6: the method comprises the following steps of realizing portrait of main network equipment based on an application scene and a tag set, specifically:

confirming a scene name, a scene description, scene effective time, applicable service personnel, an attention device type and a scene layout based on application scene setting;

the method comprises the steps that a label subset required to be selected by each scene is confirmed through the adaptation of the attribute value of each label application scene in a label set and a specific application scene;

and describing the position information of each type of label in each hierarchy by scene layout, and further realizing the portrait and visual display of the power grid equipment.

Example 2

The embodiment of the invention provides a main network equipment image drawing method based on a label technology, which comprises the following steps:

collecting equipment information and meteorological information of multiple systems by using an information access module;

cleaning the equipment information and the meteorological information by using a data cleaning module, and constructing the association between the meteorological information and the equipment information; the equipment information comprises equipment model information and equipment operation information;

performing scene definition by using an application scene definition module;

acquiring required information from an application scene definition module by using a label definition module to realize hierarchical classification definition of corresponding scene labels;

performing feature extraction on the data output by the data cleaning module by using a feature extraction module based on the label definition;

generating a label by matching the characteristic information with the label value by using a label generation module;

and utilizing the equipment portrait showing module to show the portrait of the corresponding equipment of the type of the equipment concerned under different application scenes.

In a specific implementation manner of the embodiment of the present invention, the device information includes device model information and management information of an OMS system, device operation information and device topology information of an EMS system, and device location information and monitoring information of a video monitoring system; the weather information comprises equipment operation environment information of the weather system.

In a specific implementation manner of the embodiment of the present invention, the data cleaning module cleans the device information and the weather information based on univariate data identification and cross data identification rules, so that the access information meets the requirements of consistency, normalization, integrity and timeliness.

In a specific implementation manner of the embodiment of the present invention, the content of the scenizal definition includes: scene name, scene description, scene effective time, scene service object, attention device type and scene layout; the concerned equipment type is used for matching associated equipment of the label, namely equipment of a corresponding type; the scene layout is used for confirming the display position of the label.

In a specific implementation manner of the embodiment of the present invention, the tag definition includes a tag name, an application scenario, an effective start time, an effective end time, associated equipment, a tag type, a tag hierarchy, and a tag value; when the labels are defined hierarchically, the hierarchical division of the labels comprises static labels, dynamic labels and prediction labels; when the labels are defined in a classified mode, the type division of the labels comprises model labels, overhaul labels, alarm labels, disposal labels and early warning labels.

In a specific implementation manner of the embodiment of the present invention, the tag generation module is configured to generate a tag serving an equipment portrait, perform feature extraction on the cleaned data, implement matching between a tag name, an associated equipment type, and an equipment feature, complete generation of the tag, disable the tag that has exceeded a valid end time in time, and confirm validity of the tag in time under the conditions of equipment attribute change and weather environment change.

In a specific implementation manner of the embodiment of the present invention, the feature extraction module confirms similar device information descriptions as corresponding features based on tag names in the tag definitions.

The method in the embodiment of the present invention can be implemented based on the apparatus set forth in embodiment 1.

The foregoing shows and describes the general principles and broad features of the present invention and advantages thereof. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, which are described in the specification and illustrated only to illustrate the principle of the present invention, but that various changes and modifications may be made therein without departing from the spirit and scope of the present invention, which fall within the scope of the invention as claimed. The scope of the invention is defined by the appended claims and equivalents thereof.