CN-122020767-A - Modeling method of intelligent station data model machine

CN122020767ACN 122020767 ACN122020767 ACN 122020767ACN-122020767-A

Abstract

The invention relates to the technical field of intelligent station data model machine modeling methods, in particular to an intelligent station data model machine modeling method; when the modeling method of the intelligent station data model machine is used, basic information such as equipment performance, running state and the like is mainly focused, a constructed model possibly lacks in visualization and interactivity, and interaction and dynamic simulation of a complex scene are difficult to realize; compared with the traditional intelligent station data model modeling method, the intelligent station data model modeling method mainly focuses on basic information such as equipment performance and running state, and the built model possibly lacks in visualization and interactivity, generally only two-dimensional drawings or simple three-dimensional display can be provided, interaction and dynamic simulation of complex scenes are difficult to realize, and the intelligent station data model modeling method can integrate more data dimensions through BIM technology, and meanwhile, the BIM model also has strong interactivity.

Inventors

HE ZHANYOU
XU WENLONG
REN XIAORONG
LI ERYANG
Chai rui
HUANG BIN
WANG XIAOMING
XU BIN
JIANG ZHIGANG
ZHAO XIAOCHUN
XIA XING
XU ZIQIANG

Assignees

中国石油天然气股份有限公司

Dates

Publication Date: 20260512
Application Date: 20241111

Claims (10)

1. The modeling method of the intelligent station data model machine comprises the following steps: S11, firstly, collecting data required by intelligent station data model construction, cleaning the collected original data, removing noise, errors and redundant data, and carrying out data standardization and normalization processing; S12, extracting characteristics useful for model construction from the original data, analyzing the association relation between different data sources, mining rules and information hidden behind the data, and providing depth insight for model construction; S13, capturing more data features and rules according to specific business requirements of the intelligent station, and realizing synchronization and interaction of a station physical entity and a digital model by constructing the digital twin model; s14, training and verifying the model by utilizing historical data and real-time data, and continuously adjusting model parameters and structures to improve the accuracy and robustness of the model; s15, deploying the trained model into a management system of an intelligent station to realize functions of real-time monitoring, early warning, decision support and the like; And S16, evaluating the application effect of the model, including accuracy, stability, response speed and the like, and continuously optimizing and improving the model according to the evaluation result.
2. The method for modeling an intelligent terminal data modeling machine according to claim 1, wherein the method comprises the steps of: s21, determining the type and the range of required data according to the specific requirements of the intelligent station; S22, selecting proper data sources, such as an own database, open source data, sensor data and the like; S23, collecting data from a data source by utilizing technologies such as SQL query, API call, crawler and the like; S24, processing missing values, abnormal values, repeated data and the like, and ensuring the data quality.
3. The method for modeling an intelligent site data modeling machine as defined in claim 2, wherein the method comprises the following steps of: A11, deeply knowing the operation flow, service demand and existing problems of the intelligent station; A12, definitely modeling boundaries such as station facilities, track layout, signal systems and the like; a13, planning the whole architecture of the data model, including data structures, relations and the like.
4. The method for modeling an intelligent terminal data modeling machine according to claim 3, comprising the steps of: S31, identifying key entities in the intelligent station, such as tracks, signal equipment, buildings and the like; s32, defining relevant attributes for each entity, such as the length of a track, the type of signal equipment and the like; S33, defining the relation between entities, such as 'one track connects two stations'.
5. The modeling method of intelligent station data modeling machine according to claim 4, comprising the steps of, when converting the conceptual model: s41, converting the conceptual model into a logic model, and defining a data table, a field, a data type and the like; S42, ensuring that the data table accords with a database design formula, and reducing data redundancy; and S43, defining an index for the common query field, and improving the query efficiency.
6. The modeling method of an intelligent station data modeling machine as defined in claim 5, wherein the modeling method comprises the following steps: s51, selecting a proper database system, such as MySQL, oracle and the like, according to requirements; S52, deploying a database on a server and configuring related parameters; S53, creating a physical database and a table structure according to the logic model.
7. The method for modeling an intelligent site data modeling machine as defined in claim 6, wherein the method comprises the following steps when constructing the BIM model: s61, selecting proper BIM software such as Autodesk Revit, bentley and the like; S62, importing data in a database into BIM software to serve as a modeling basis; And S63, building a three-dimensional model of the intelligent station by using BIM software, wherein the three-dimensional model comprises buildings, tracks and the like.
8. The method for modeling an intelligent station data modeling machine as defined in claim 6, wherein the method comprises the following steps: S71, ensuring data synchronization and consistency between the BIM model and the database; s72, checking the BIM model, and checking whether the model meets actual conditions and business requirements; and S73, optimizing and adjusting the model according to the verification result.
9. The method for modeling an intelligent station data modeling machine as defined in claim 6, wherein the method comprises the following steps: S71, ensuring data synchronization and consistency between the BIM model and the database; s72, checking the BIM model, and checking whether the model meets actual conditions and business requirements; and S73, optimizing and adjusting the model according to the verification result.
10. The method for modeling an intelligent site data modeling machine as defined in claim 6, wherein the method comprises the steps of, when maintaining and updating the model: S91, updating data in a database regularly, and keeping timeliness of the model; S92, optimizing and upgrading the model according to the service requirements and the technical development; s93, ensuring the security of the database and the BIM model and preventing data leakage and illegal access.

Description

Modeling method of intelligent station data model machine Technical Field The invention relates to the technical field of intelligent station data model machine modeling methods, in particular to an intelligent station data model machine modeling method. Background The modeling of the intelligent station data model machine refers to the process of modeling various devices, operation data and business processes in the intelligent station, such as an intelligent substation, an intelligent pump station and the like, by utilizing a data model and technical means, but when the intelligent station data model machine modeling method is used, the data collection and processing of functionality and operability are usually focused, the data dimension may be single, the basic information of device performance, operation state and the like is mainly focused, the constructed model may be deficient in visualization and interactivity, only two-dimensional drawing or simple three-dimensional display can be provided, and the interaction and dynamic simulation of complex scenes are difficult to realize. Disclosure of Invention In order to overcome the problems that when an intelligent station data modeling method is used, data collection and processing are focused on functionality and operability, data dimension is single, basic information such as equipment performance and running state is focused mainly, a built model is possibly deficient in visualization and interactivity, two-dimensional drawings or simple three-dimensional display can be provided, and interaction and dynamic simulation of complex scenes are difficult to realize. The technical scheme of the invention is that the modeling method of the intelligent station data model machine comprises the following steps: S11, firstly, collecting data required by intelligent station data model construction, cleaning the collected original data, removing noise, errors and redundant data, and carrying out data standardization and normalization processing; S12, extracting characteristics useful for model construction from the original data, analyzing the association relation between different data sources, mining rules and information hidden behind the data, and providing depth insight for model construction; S13, capturing more data features and rules according to specific business requirements of the intelligent station, and realizing synchronization and interaction of a station physical entity and a digital model by constructing the digital twin model; s14, training and verifying the model by utilizing historical data and real-time data, and continuously adjusting model parameters and structures to improve the accuracy and robustness of the model; s15, deploying the trained model into a management system of an intelligent station to realize functions of real-time monitoring, early warning, decision support and the like; And S16, evaluating the application effect of the model, including accuracy, stability, response speed and the like, and continuously optimizing and improving the model according to the evaluation result. Preferably, when collecting data required for constructing the intelligent station data model, the method comprises the following steps: s21, determining the type and the range of required data according to the specific requirements of the intelligent station; S22, selecting proper data sources, such as an own database, open source data, sensor data and the like; S23, collecting data from a data source by utilizing technologies such as SQL query, API call, crawler and the like; S24, processing missing values, abnormal values, repeated data and the like, and ensuring the data quality. Preferably, in performing the demand analysis and modeling planning, the following aspects are included: A11, deeply knowing the operation flow, service demand and existing problems of the intelligent station; A12, definitely modeling boundaries such as station facilities, track layout, signal systems and the like; a13, planning the whole architecture of the data model, including data structures, relations and the like. Preferably, in designing the conceptual model of the intelligent station model, the method comprises the following steps: S31, identifying key entities in the intelligent station, such as tracks, signal equipment, buildings and the like; s32, defining relevant attributes for each entity, such as the length of a track, the type of signal equipment and the like; S33, defining the relation between entities, such as 'one track connects two stations'. Preferably, when converting the conceptual model, the method comprises the following steps: s41, converting the conceptual model into a logic model, and defining a data table, a field, a data type and the like; S42, ensuring that the data table accords with a database design formula, and reducing data redundancy; and S43, defining an index for the common query field, and improving the query efficiency. Preferably, the