CN111460018A - Object ID data link method and system - Google Patents

Abstract

The invention discloses a real object ID data communication method and a real object ID data communication system. For the stock data, due to the existence of historical data, namely data before the establishment of the real object ID, in the establishment process of the real object ID, related data can be gradually recorded, and the data recorded in the later period is matched below the corresponding real object ID through the incidence relation with the corresponding real object ID, so that the integrity of the data related to the corresponding real object ID can be ensured.

Description

Object ID data link method and system

Technical Field

The invention relates to a real object ID data through method and a real object ID data through system, wherein a real object ID, namely a unified identity code of a power grid asset, is a unique and lifelong unchangeable identity code given to real object asset equipment of a national power grid company.

Background

The entity ID runs through each stage of the asset full life cycle such as power grid entity asset planning plan, purchasing construction, operation and maintenance overhaul, retirement disposal and the like, and is used for realizing the associated sharing of information such as asset full life cycle project coding, WBS (Work Breakdown Structure), material coding, asset coding, equipment coding and the like. The purpose is to realize the interconnection and intercommunication of information such as states, costs, defects and the like of the power grid physical assets in the whole life cycle of planning design, purchasing construction, operation and maintenance overhaul and retirement scrapping by taking physical ID as a link, and promote the management level of company assets to be a new step.

The national network company carries out object ID construction nationwide from 2018, the object ID construction mainly comprises stock object ID generation and traceability, and the whole flow of the incremental object ID is communicated with related data maintenance.

With the continuous development of big data technology and the continuous expansion of power systems, a full-service data center is built and starts to be applied in each province, and the data sharing degree of each service system is improved. Trying to link PMS2.0 equipment data, project, material, equipment, asset and micro-application related data in an ERP system and engineering construction parameter data; however, the data integration level of an information system in each operation of the existing electric power is not high, and the problems of high difficulty in data calculation and display among systems, difficulty in rule making and the like exist. In view of this, it is necessary to communicate the relevant data of each link of the power system.

Note: PMS 2.0: the Power Production management System 2.0 is a national network equipment (asset) operation and maintenance lean management system.

2. ERP: the national network ERP suite software is an enterprise management solution (systems applications and Products) of SI EPU, Germany.

Since the physical ID is built from 2018, the power system is a huge system, and the update cycle of the equipment is also long, the related data includes not only incremental equipment data, but also existing equipment data and equipment data which is being built and is not yet recorded into the database, and because the periods of the related equipment are different, the same kind of equipment is described by using different fields, and even the naming rules of the equipment IDs are different. In particular, the power grid management hierarchy is lower at an earlier time, such as a county level and a regional level, and the management of the equipment is different in each place, and the generated data is relatively complicated.

For example, the chinese patent document CN110689214A background art describes that in different application scenarios, the same entity may have multiple identifiers, and the physical ID also has the same problem, in different scenarios, different fields, even different identifiers and names, are used for description, and in a purchasing link, a construction link, and an operation state, the same device, for example, uses different fields for description. Even if the operation state is pure, different fields are used for description in different systems, for example, the same device is described in a PMS and an ERP by using different fields.

To achieve data communication, chinese patent document CN110689214A determines whether at least two real IDs can be fused in a manner of data registration under different time and space, and if so, the two real IDs can be fused. The fusion of the real object ID and the grid real object ID has the premise that whether at least two real object IDs point to the same equipment or not and then data communication is carried out, so that the data communication of the real object IDs of the grid has guiding significance, but the applicable objects are different, the complexity of the real object IDs of the grid is higher, and especially a large amount of historical data exists.

The unified physical ID has a strong meaning in the aspect of power grid data management and control, and data link-up takes the physical ID as a core, and can link-up all links of a power grid project.

Disclosure of Invention

Therefore, the invention aims to provide a data through method based on the physical ID by taking the physical ID as a core for effectively passing through power grid service data, and also provides a physical ID data through system.

In an embodiment of the present invention, a real object ID data traversal method is provided, which includes the following steps:

extracting, namely extracting data in the PMS and the ERP by adopting a preset extraction method;

the first storage is to store the extracted data to a designated position in a classified manner, wherein the classification is divided into incremental data and stock data according to whether the corresponding equipment is connected to the power grid or not;

processing, namely providing a virtual real object ID for the incremental data, and mapping the incremental data related to the virtual real object ID to a first storage area by taking the virtual real object ID as an incidence relation; mapping the stock data related to the real object ID to a second storage area by taking the real object ID as an incidence relation for the stock data, and uniformly describing a rule through a preset matching relation for the residual stock data, further mapping the residual stock data to the second storage area and including the residual stock data below the given real object ID;

wherein, PMS is Power Production Management System, namely the operation and maintenance lean Management System of national network equipment (assets);

ERP is System Applications and Products, an enterprise management System.

Optionally, the incremental data are classified and stored according to different sources of the corresponding devices, and each type of incremental data is described by using a respective field;

and a determined mapping relation exists between corresponding fields of different types of incremental data.

Optionally, providing an additional field library for adding a description of the incremental data;

providing a rule base, calling corresponding rules from the rule base to check the incremental data when the equipment receives the incremental data, and accessing the corresponding equipment to the power grid after the check is passed;

after the equipment is connected to the power grid, the virtual real object ID is newly established through the equipment to form the real object ID, and the incremental data are matched through the field to generate stock data.

Optionally, the inventory data comprises normalized inventory data and traced inventory data;

when the traced stock data is processed, whether the traced stock data is abnormal or not needs to be verified, if yes, abnormal information is fed back to a node reporting the traced stock data;

if not, the traced stock data generates normalized stock data according to the field matching.

Optionally, the extracting step is extracting at a given time every day; and/or

Fetching of the corresponding external instruction.

Optionally, all fields of data related to the ERP and the PMS are extracted for the first time;

the subsequent extraction is all the current fields of the data related to the ERP and the PMS at the extraction time; or

Subsequent extraction extracts only all fields in ERP and PMS that are used to describe the added data or to generate updated data.

Optionally, the method of determining addition or update is:

generating an increase mark when data is increased, and generating an update mark when the data is updated;

accordingly, the addition or update of the data is determined by the addition flag and the update flag.

Alternatively, the predetermined extraction method is an extraction method using ET L or E L T;

wherein ET L is Extract-Transform-L oad, i.e. used to describe the process of extracting-converting-loading-data from source end to destination end;

e L T is Extract-L oad-Transform, which is used to describe the process of extracting-loading-converting data from a source end to a destination end;

e, extract, T, transform, and L, load.

Optionally, in the processing step, account card key field matching screening is performed on the extracted data, and abnormal data is generated on the screened data which cannot be matched.

In an embodiment of the present invention, a real object ID data pass-through system is further provided, including:

the extraction unit is used for extracting data in the PMS and the ERP by adopting a preset extraction method;

the primary storage unit is used for storing the data extracted by the extraction unit to a specified position in a classified manner, wherein the classification is divided into incremental data and stock data according to whether the corresponding equipment is connected to a power grid or not;

the processing unit is used for providing a virtual real object ID for the incremental data stored in the primary storage unit and mapping the incremental data related to the virtual real object ID to a first storage area by taking the virtual real object ID as an incidence relation; mapping the stock data related to the real object ID to a second storage area by taking the real object ID as an incidence relation for the stock data stored in the primary storage unit, and further mapping the residual stock data to the second storage area by a preset matching relation unified description rule and including the residual stock data below the given real object ID;

wherein, PMS is Power Production Management System, namely the operation and maintenance lean Management System of national network equipment (assets);

ERP is System Applications and Products, an enterprise management System.

In the embodiment of the invention, data types are distinguished so as to facilitate data management, wherein incremental data provide virtual real object IDs in advance, and based on the data generated by running through each link in the equipment construction process through the virtual real object IDs, the omission or loss of the incremental data is avoided. For the stock data, due to the existence of historical data, namely data before the establishment of the real object ID, in the establishment process of the real object ID, related data can be gradually recorded, and the data recorded in the later period is matched below the corresponding real object ID through the incidence relation with the corresponding real object ID, so that the integrity of the data related to the corresponding real object ID can be ensured.

Drawings

Fig. 1 is a topological diagram of a power system test data acquisition system in an embodiment.

Fig. 2 is a flow chart illustrating physical ID data communication in an embodiment of the present invention.

Detailed Description

Referring to the attached fig. 1 of the specification, regarding power system test equipment, such as a loop resistance tester, a ground resistance tester, a relay protection tester, a transformation ratio tester, a direct current high voltage generator, a frequency generator, a high voltage switch dynamic characteristic tester, and the like, these test equipment used for testing each link of a power system are used as instruments and meters, generally have ports connected with an upper computer, and can directly upload test data.

Some test data can be manually input by field personnel to, for example, a work area client, which can be seen in fig. 1, and in the figure, the work area client serves as a leaf node for acquiring test data of an electric power system to form an upper computer of an acquisition terminal, which is the aforementioned test equipment.

The incremental data is more often entered by, for example, a handheld terminal after a certain link of the relevant equipment project is completed, and uploaded to, for example, the aforementioned work area client.

In some implementations, the incremental data may be entered directly at the work area client.

The related information is not necessarily device operation data, and may be, for example, current state data, device source data, acceptance check point data, and the like of the device corresponding to the virtual real object ID.

A local area network for acquiring test data is constructed by a plurality of factory clients in a certain factory area, and the local area network can be established on a wired network or a wireless network.

The local area network is connected to the external network through a core network switch, in fig. 1, the province company client forms a father node of the information internal network, and the province company client can be used as an approval end and used for monitoring test data of subordinate nodes of the province company client.

In the network constructed in fig. 1, the data server and the application server may be deployed at a lower hierarchy level, or may be deployed at a higher hierarchy level. When the system is deployed at a lower level, the number of required servers is large, and a server cluster can be constructed.

For higher levels, the test data of all the areas are collected, and the statistical characteristics of the test data are more representative.

The test data can be directly collected by the test equipment and then uploaded, and in more applications, the field equipment is provided with instruments, such as current measuring equipment, voltage measuring equipment and the like. In more applications, based on a centralized and distributed field working condition acquisition system, a monitoring system based on force control software is arranged at a power plant end, and the monitoring system can be used as a work area client.

The terminals located at higher levels in the topology shown in fig. 1 are preferably configured for BI-based experimental data analysis, presentation. Where BI is an abbreviation of Business Intelligence, Business Intelligence. Also known as business intelligence or business intelligence, refers to the realization of business value by data analysis using modern data warehouse technology, on-line analysis processing technology, data mining and data presentation technology. The concept of business intelligence was first introduced by the Gartner Group (Gartner Group) in 1996.

By adopting BI, the dimension data analysis of the test report can be realized, multiple dimensions such as date, property, profession and the like can be defined, free combination and configuration can be performed, test items and test data corresponding to the test report under different conditions can be freely displayed, and two viewing modes of a report form or a chart are supported.

It is to be known that the physical ID needs a service to span multiple service departments such as projects, materials, devices, assets, and the like, the related data relates to multiple informatization systems such as PMS2.0, ERPs, and micro applications, if the related data is checked across service fields and the completion condition is checked, because of different service rules, the department codes do not correspond, the related fields are not uniform, the difficulty of checking the related data and the completion condition is large, the actual requirements of managers on, for example, schedule management and control cannot be met, the workload of statistics personnel is increased because of checking multiple system data, and the online management and control requirements of a management layer cannot be met.

In the embodiment of the invention, one or more independent data servers can be preset to collect and store the service data based on the physical ID to the data servers, and the related service data determines the service control dimensions of different data according to preset service rules and combs the related data. The related data is combed at the data server, so that when the related data is called or further processed, the related data of an online service system does not need to be acquired in real time, the influence of a network state and a transmission rate is avoided, complex data processing is not needed, and the efficiency of related personnel for processing related services is greatly improved.

It should be noted that the related service data are always stored in each service system, and therefore, for the calling or extracting of the related service data, the extracting is feasible and barrier-free under the condition that the authority is satisfied.

Regarding the authority, it is obvious that data management and control are completed under the condition that the authority is satisfied, and a service end of the data management and control necessarily has the authority.

In addition, although the related service data is always stored in each service system, the data corresponding to the external instruction in the whole full-service flow data is extracted and displayed in response to the external instruction, which still faces a great obstacle. Specifically, multiple service systems need to be searched, and due to a data structure and a corresponding (mapping) mode, the control dimensions are different, and the searching is relatively difficult; the searched data corresponding to the external instruction needs to be gathered from each service system to the local, and the response time is long; furthermore, the related data needs to be manually read, and the overall efficiency is low.

It should be noted that even though the management modes and the service management and control dimensions of the service systems are different, the service data corresponding to the physical ID can still be summarized based on the physical ID, processed according to the new service rule, and stored locally, where the local in this paragraph refers to the data server.

After the relevant business data are gathered, the data can be combed according to the given data statistical dimension and the corresponding incidence relation, and then the data are stored in the relevant data server, so that when the data are called again, the data are called directly from the data server instead of being called across business fields, and the data are combed, so that the data can be regularly displayed corresponding to relevant instructions.

It should be noted that, for the same data of each existing service system, if department codes do not correspond and related fields are not uniform, but have a certain association relationship with each other, although it is difficult to comb related data across service fields, the related data are gathered locally, and after mapping is performed based on the association relationship, the difficulty in combing the corresponding relationship of the corresponding service data is greatly reduced.

The structure shown in fig. 2 is a control flow of data in a through process, data sources are a full-service data center and an ODS, that is, a data layer (data level) encapsulates operations on a database, and in an embodiment of the present invention, the data layer is used for adding or transferring service data in a corresponding service system from a PMS and an ERP to an upper layer of the data layer, that is, a logic layer, which is a data extraction process.

The ODS is a national network data center, and the intervention authority is high. The PMS and ERP data are data from each business system, and are data directly extracted in the embodiment of the present invention. Most of data in the national network data center ODS is processed data of a relatively upper layer.

The logical layer in the structure shown in fig. 2 is used to describe the logical structure of the data stored in the database, and the lower layer, that is, the service data transmitted by the data layer, stores the data contained in, for example, the same physical ID into one block with the physical ID as an index based on the existing or determined association relationship between the data and the physical ID.

The logical layer records the total storage before data processing as primary storage, and the storage after data primary processing is secondary storage, and so on.

The data classification storage contributes to subsequent selective processing, and the data management and control efficiency can be improved.

Correspondingly, for primary storage, the extracted data is classified and stored to a designated position, wherein the classification is divided into incremental data and stock data according to whether the corresponding equipment is connected to the power grid or not.

Further, providing a virtual real object ID for the incremental data, and mapping the incremental data related to the virtual real object ID to a first storage area by taking the virtual real object ID as an incidence relation; and mapping the stock data related to the real object ID to a second storage area by taking the real object ID as an incidence relation for the stock data, and uniformly describing a rule through a preset matching relation for the residual stock data, further mapping the residual stock data to the second storage area and including the residual stock data under the given real object ID.

It should be noted that, after the device enters the field, a physical ID tag, for example, may be attached, the physical ID may be determined by means of scanning with a handheld terminal, and then relevant data is recorded and uploaded. The device is not a device directly connected to the power grid, but its relevant data can be uploaded. Because the device is in the non-operation state, the physical ID corresponding to the device in the non-operation state is recorded as a virtual physical ID, for example, the entry device is controlled.

It should be noted that the data may be processed by a single physical ID, or may be processed by the same kind of data included in a plurality of business systems, and the processing may be performed based on local business needs. In further applications, the data that is ultimately stored locally may be described in a variety of fields.

The logic layer reconstructs the data extracted by the data layer so as to be suitable for storage on a specified single device, and the processing of related data is convenient.

Further, the logical layer describes the relevant data using predetermined fields, suitable for combing or suitable for direct presentation.

And storing the processed data of the logic layer into a local database.

In addition, the data link is performed by associating the data related to the device corresponding to the physical ID with the physical ID, and some data cannot be easily associated with some data to be included in the physical ID by the physical ID for various reasons.

The data management and control layer (shown as data management and control in fig. 2) performs statistics on related data, and mainly includes incremental device data (corresponding incremental data) maintenance, stock traceability data exception management and accounting card corresponding data exception management and control.

The method comprises the steps of firstly looking at incremental data, wherein the incremental data mainly relate to the problem of data integrity, and the key of the problem is that as equipment is not involved in a power grid, relevant incremental data are mainly input by manual collection, and the integrity of the incremental data is not easy to guarantee.

In the embodiment of the invention, the technical parameters of the materials are not maintained, the engineering construction parameters are not maintained, the checking and acceptance inventory is not maintained, and the transferring inventory is not maintained. According to given rules, at a certain stage of device intervention, specific work is necessarily required to be completed, relevant incremental data are adapted, and management and control on the site can be ensured through integrity verification of the incremental data in a specific time period.

The incremental data are classified and stored according to different corresponding equipment sources, and each type of incremental data is described by using respective fields;

and a determined mapping relation exists between corresponding fields of different types of incremental data.

For example, the data that the technical parameters of each unit of materials are not maintained is checked, various types such as normal purchasing, e-commerce platform purchasing and the like are maintained and distinguished according to the technical parameters of the required materials, various types of rules are inconsistent, page data need to be combed and formed independently, uploading is performed through a work area client, and the integrity of corresponding incremental data is verified based on the determined rules.

And then, counting the condition that the engineering construction parameters are not maintained, dividing the engineering construction parameters into different engineering construction parameters such as a handover test report, an installation debugging record and the like, combing the engineering construction parameters according to different dimensionalities and different rules, counting the devices of each unit device, which do not complete the engineering construction parameters, forming corresponding incremental data, verifying according to due data of the incremental data at the stage, and ensuring the integrity of the data at the stage.

And the other aspects are the same as the reason that the checking, checking and counting book is not maintained and the fund transferring and counting book is not maintained. The essence is whether the upload data has satisfied all the data that should be at this stage.

In addition, for incremental data, as the entered data increases, the amount of the adapted field also becomes larger, in some implementations, some fields may need to be newly set for new equipment, and for this purpose, an additional field library is provided for increasing the description of the incremental data;

providing a rule base, calling corresponding rules from the rule base to check the incremental data when the equipment receives the incremental data, and accessing the corresponding equipment to the power grid after the check is passed; the rules herein are those that ensure the integrity of the data as described above.

After the equipment is connected to the power grid, the virtual real object ID is newly established through the equipment to form the real object ID, and the incremental data are matched through the field to generate stock data.

In addition, before the device is connected to the power grid, the device needs to be guaranteed to be available, and relevant rules can be provided from the aspect of availability to verify the state of the corresponding device. It should be understood that here, belonging to the acceptance category, the relevant rules have certainty.

The stock data not only comprises stock data generated in an incremental mode after the physical ID is established, but also comprises stock data corresponding to the power grid system equipment which is accessed before the physical ID is established. The relatively big problem of the stock data in data management is the traceability problem of the stock data, and the reason of the traceability problem is mainly that the equipment management is not uniform from place to place.

Subdivided, the volume data comprising normalized inventory data and traced inventory data;

when the traced stock data is processed, whether the traced stock data is abnormal or not needs to be verified, if yes, abnormal information is fed back to a node reporting the traced stock data;

if not, the traced stock data generates normalized stock data according to the field matching.

The more traced stock data is reflected in that project codes are not matched with WBS (Work Breakdown Structure), material types are not matched with equipment types, materials are not matched with equipment voltage levels, material codes are not matched with material descriptions, the first position of a purchase application number is not 1, the first position of a purchase order number is not 4, the first position of a material code is not 5 and the like.

For example, the material code is not 5 at the beginning, and it should be understood that, as incremental data, the data structure thereof determines that whether the relevant material code is correct or not can be determined by simply verifying the first bit. And then whether the first position of the traced data purchase application order number is correct is counted according to rules, whether the traced data purchase application order number is correct can be quickly judged, the number of each unit is counted according to unit dimensions, and functions of inquiring details, exporting and the like are provided.

The same applies to other types of "bit" verification methods.

For example, the item code is not matched with the WBS, which is represented by the fact that the item code has a certain association relationship with the WBS, and the matching condition of the traced data item code and the WBS is counted according to the known rule to find out corresponding abnormal data.

The exception data of the above stages can be sent to the upper layer together and processed by the upper layer node. The related abnormal data can also be fed back to the lower layer, and the lower layer node checks the equipment or the uploaded data according to the abnormal data condition.

The same processing mode is adopted for other unmatched data such as the unmatched material type and the unmatched equipment type.

The mismatching of the data influences the communication of the data, and after the data matching condition is corrected, the related data is communicated.

The main reason of the abnormal data generated about the corresponding abnormal condition of the account card object is that the key fields of the account card object are not matched, and then an empty asset card list or an asset value abnormal list exists. Relevant abnormal data can be screened out through field matching for example, and the abnormal data is fed back to a lower stage for correction, and formed new matched data can be communicated.

For the data extraction, an ET L tool is used for extraction, the data extraction can be carried out at regular time, preferably 0 hour, 0 minute and 0 second every day, the data of each service system is the data of 24 hours till the previous day, and 0 hour, 0 minute and 0 second every day is midnight, the change probability of the physical ID is low, the data updating of each service system based on the existing physical ID is slow, and for the data transmission between the local database and each service system, other service systems are probably in a quasi-idle state at the moment, the related data transmission rate is relatively high.

The method has the advantages that the relevant data are extracted at regular time, particularly in the relatively idle time period of the whole power grid system, and are processed and stored, so that the influences on the large occupation of system resources and the normal operation of the power grid system can be effectively avoided. The processed data can be directly called in the normal time period.

The data obtained by timing extraction is relatively real-time compared with the data of the full-service system, the data of the full-service system has longer duration, the data which is updated every day is relatively less, and the data extracted by timing has better authenticity on the current day or the next day.

In some embodiments, the data distributed at each service system end can be directly called by means of an external command on the basis of the existing data stored locally.

It should be noted that the data of each service system end exists in the conventional data call, and is supplemented in the embodiment of the present invention.

Furthermore, the data distributed at each service system end is extracted by an external instruction as a supplement, and the extraction is necessarily premised on timing extraction.

Further, as described above, the data volume of the data which is updated every day is not large relative to the whole full service system, so that the data which is updated can be extracted only on the basis of the existing data which is stored locally for the extraction of the corresponding external instruction, and the existing data can be directly replaced by the data which is updated after the data which is updated is stored locally, thereby greatly reducing the whole transmission volume and the calculation volume.

In an embodiment of the invention, all fields of the data involved regarding the physical ID that are ERP and PMS2.0 (or further upgraded e.g. PMS 3.0) are extracted at least for the first time. In the subsequent extraction, all fields of the ERP and PMS2.0 relating to the data of the real object ID can be extracted, and all fields of the ERP and PMS for describing added data or generating updated data can also be extracted.

The data generating the update often has definite update time, and the data can be extracted according to the update time.

In some applications, the data that generates the update may be identified directly by way of a timestamp or other digital label, which is a periodic identification that is cancelled after the identified data is extracted.

Regarding the extraction method, there are two main database-based data extraction methods, one is ET L, i.e., Extract-Transform-L oad, which is used to describe the process of extracting-transforming-loading-data from a source end to a destination end, and the other is E L T, i.e., Extract-L oad-Transform, which is used to describe the process of extracting-loading-transforming-data from a source end to a destination end, wherein E, i.e., Extract, T, Transform, and L, i.e., load.

The ET L or E L T can store mapping and conversion rules of the source (source) and destination (destination) by using its built-in metadata function, and developers can develop the data without being familiar with various platforms and data structures.

In contrast, the process described in ET L generally includes ET L or E L T in a mixture, and the more data, complex conversion logic, and the more computationally intensive the destination database, the more preferred is E L T to exploit the parallel processing power of the destination database.

As can be seen from the structure shown in FIG. 1, the data in the local database corresponds to the data in the PMS and the ERP based on the ET L or E L T, and a local data combination association table is formed by locally storing the determined association relationship between the data.

In the local database, the processed data is used as an element to form a local data statistical table, and at least the real object ID is used as an index.

Claims (10)

1. A real object ID data through method is characterized by comprising the following steps:

extracting, namely extracting data in the PMS and the ERP by adopting a preset extraction method;

the first storage is to store the extracted data to a designated position in a classified manner, wherein the classification is divided into incremental data and stock data according to whether the corresponding equipment is connected to the power grid or not;

processing, namely providing a virtual real object ID for the incremental data, and mapping the incremental data related to the virtual real object ID to a first storage area by taking the virtual real object ID as an incidence relation; mapping the stock data related to the real object ID to a second storage area by taking the real object ID as an incidence relation for the stock data, and uniformly describing a rule through a preset matching relation for the residual stock data, further mapping the residual stock data to the second storage area and including the residual stock data below the given real object ID;

wherein, PMS is Power Production Management System, namely the operation and maintenance lean Management System of national network equipment (assets);

ERP is System Applications and Products, an enterprise management System.

2. The real object ID data link-up method according to claim 1, wherein the incremental data are classified and stored according to different sources of the corresponding devices, and each type of incremental data is described by using a respective field;

and a determined mapping relation exists between corresponding fields of different types of incremental data.

3. The real object ID data traversal method according to claim 2, wherein an additional field library is provided for adding description of incremental data;

providing a rule base, calling corresponding rules from the rule base to check the incremental data when the equipment receives the incremental data, and accessing the corresponding equipment to the power grid after the check is passed;

after the equipment is connected to the power grid, the virtual real object ID is newly established through the equipment to form the real object ID, and the incremental data are matched through the field to generate stock data.

4. The real object ID data link method of claim 1, wherein the inventory data includes normalized inventory data and source-traced inventory data;

when the traced stock data is processed, whether the traced stock data is abnormal or not needs to be verified, if yes, abnormal information is fed back to a node reporting the traced stock data;

if not, the traced stock data generates normalized stock data according to the field matching.

5. The real object ID data link method according to claim 4, wherein the extracting step is extracting at a given time every day; and/or

Fetching of the corresponding external instruction.

6. The real object ID data penetration method according to claim 5, wherein all fields related to ERP and PMS are extracted for the first time;

the subsequent extraction is all the current fields of the data related to the ERP and the PMS at the extraction time; or

Subsequent extraction extracts only all fields in ERP and PMS that are used to describe the added data or to generate updated data.

7. The object ID data link-through method of claim 6, wherein the method of determining addition or update is:

generating an increase mark when data is increased, and generating an update mark when the data is updated;

accordingly, the addition or update of the data is determined by the addition flag and the update flag.

8. The object ID data link-up method according to claim 1, wherein the predetermined extraction method is an extraction method using ET L or E L T;

wherein ET L is Extract-Transform-L oad, i.e. used to describe the process of extracting-converting-loading-data from source end to destination end;

e L T is Extract-L oad-Transform, which is used to describe the process of extracting-loading-converting data from a source end to a destination end;

e, extract, T, transform, and L, load.

9. The object ID data link method according to claim 1, wherein in the processing step, the extracted data is subjected to account key field matching screening, and abnormal data is generated from the screened unmatchable data.

10. A kind of material object ID data link up the system, characterized by, comprising:

the extraction unit is used for extracting data in the PMS and the ERP by adopting a preset extraction method;

the primary storage unit is used for storing the data extracted by the extraction unit to a specified position in a classified manner, wherein the classification is divided into incremental data and stock data according to whether the corresponding equipment is connected to a power grid or not;

the processing unit is used for providing a virtual real object ID for the incremental data stored in the primary storage unit and mapping the incremental data related to the virtual real object ID to a first storage area by taking the virtual real object ID as an incidence relation; mapping the stock data related to the real object ID to a second storage area by taking the real object ID as an incidence relation for the stock data stored in the primary storage unit, and further mapping the residual stock data to the second storage area by a preset matching relation unified description rule and including the residual stock data below the given real object ID;

wherein, PMS is Power Production Management System, namely the operation and maintenance lean Management System of national network equipment (assets);

ERP is System Applications and Products, an enterprise management System.

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