A device information description and storage method based on multi-dimensional classification of meta-attribute tags

Abstract

The present invention discloses a device information description and storage method based on multi-dimensional classification of meta-attribute tags. First, the device information is collected; then the dimensions are determined, and the device meta-attributes are extracted from the device information according to the determined dimensions; then the meta-attribute tags are defined according to the extracted meta-attributes; the device information is described using the device meta-attribute tags; and finally, the device information is stored in a relational database. The present invention extracts the collected device information as device meta-attributes, binds meta-attributes to the device, and checks the device meta-attributes, i.e., the device information in the actual device summary information table, which is similar to the relationship between points, lines, and surfaces. This method effectively solves the problem of reserving a large number of fields in the early stage of table creation in traditional methods, and is more convenient for the integration, management, and analysis of device data.

Description

Technical Field

[0001] The present invention belongs to the field of device information description, and in particular relates to a novel device information description method, and provides a database modeling method based on the device information description method. Background Art

[0002] Device information description is key to equipment management and data integration across various industries, providing crucial technical support for integrating business systems and deploying big data applications. Due to the diverse and uncertain nature of device attributes, device descriptions vary across different companies, and even within a single company, different departments may describe similar devices differently. This leads to numerous issues when storing device information, hindering subsequent applications. Adding data to the database can even lead to problems like inability to add data and system crashes. Furthermore, information silos can exist when integrating and analyzing device data.

[0003] Although many device description and database modeling methods have been developed in recent years, these problems have not been effectively addressed. Traditional methods generally reserve a large number of fields when initially creating a table, but this method wastes a large amount of storage space and significantly reduces the efficiency of data operations when operating on the database. Summary of the Invention

[0004] The purpose of the present invention is to address the deficiencies of existing device information description and storage, and to propose a device information description and storage method based on multi-dimensional classification of meta-attribute tags.

[0005] To address the above problems, the present invention provides a method for describing and storing device data: 1. Using a new device description language to make device information description clearer. 2. Providing a modeling method for the new device description language to simplify device information maintenance.

[0006] The method of the present invention can dynamically and multi-dimensionally describe and classify device information, better adapt to the diversified requirements of device attributes, make the storage of device information more systematic, and avoid problems such as database crash, inability to store, and difficulty in maintenance.

[0007] A device information description and storage method based on multi-dimensional classification of meta-attribute tags, the specific method is as follows:

[0008] Step (1), collecting device information;

[0009] Step (2), determine the dimension;

[0010] Equipment information can be classified from different perspectives, with each perspective being a dimension. The choice of dimension should be based on the department's actual focus on equipment information.

[0011] Step (3), extracting device meta-attributes from the device information according to the determined dimensions;

[0012] Step (4), defining meta-attribute labels based on the extracted meta-attributes;

[0013] The characteristics of assigning labels to device meta-attributes are called device meta-attribute labels.

[0014] Step (5), using device meta-attribute tags to describe device information;

[0015] Step (6), device information storage;

[0016] A relational database is used to store device information.

[0017] The database model is built using a relational database, which is an improvement on the star model. The database model includes five types of tables: dimension information table, meta-attribute table, actual device attribute table, actual device summary information table, and device historical information change record table.

[0018] Furthermore, the device information described herein refers to information generated during device management activities. This information includes both general and specific device attributes. General attributes are common to all devices, but may differ in their values ​​across devices. Specific device attributes are obtained based on the device type.

[0019] Furthermore, the device meta-attribute refers to an abstract data unit that describes the definition, identification, representation, and allowed values ​​of various types of devices. It is an abstract definition of the attributes possessed by actual devices, namely, device information. It includes the device meta-attribute name, code, value, data type, data length, and dimension information: the name is the title of the content described by the device information; the code is a string of letters and numbers used to identify the device meta-attribute name; the value is the information value of the content described by the device information; the data type and data length are characteristics that describe the value, namely the data class type to which the value belongs, and the data length slightly greater than the maximum length of the value; and the dimension information is the classification information belonging to each dimension. In other words, the device meta-attribute is the conceptual expression of a certain attribute of the device, and the actual device information is the concretization and instantiation of the device meta-attribute.

[0020] The extraction of device meta-attributes complies with the following requirements:

[0021] (1) Standardize the device metadata attributes according to the national standards published on the National Standard Information Public Service Platform and the standards specified by the user itself;

[0022] (2) Clarify the category to which the device meta-attributes belong in each dimension;

[0023] (3) Meta-attribute values ​​must comply with national data standards.

[0024] Each device meta-attribute is described from multiple dimensions. Different device meta-attributes can be in the same dimension, and different devices can have the same device meta-attribute. Each dimension can be expanded or set to a fixed length.

[0025] Furthermore, step (5) is specifically implemented as follows:

[0026] By utilizing the device's meta-attribute tags and multi-dimensionally classifying them, a multi-dimensional description of the device is achieved. Devices are located and described from multiple dimensions. Through tag attachment (binding device meta-attribute tags), tag overwriting (changing device meta-attribute tag values), tag removal (unbinding device meta-attribute tags), and tag history monitoring, a real-time description of the device's current information and the ability to query and trace historical device information are achieved.

[0027] Furthermore, the dimension information table is used to store the dimension information determined in step (2), each dimension is a table, and the information in each table is the classification information under the corresponding dimension; the meta-attribute table is used to store the device meta-attribute information extracted in step (3) and the dimension information to which the device meta-attribute belongs; the actual device attribute table is used to store the device meta-attribute information and meta-attribute values ​​bound to the device in step (5); the actual device summary information table is used to store the current information of the device; and the device history information change record table is used to store the historical dynamic information of the device description.

[0028] A device information description and storage system based on multi-dimensional classification of meta-attribute tags includes a device information collection module, a dimension determination module, a device meta-attribute extraction module, a tag definition module, a device information description module, and a relational database:

[0029] The device information collection module is used to collect device information. This information refers to information generated during device management activities and includes both general and specific device attributes. General attributes are common to all devices, but may differ in their values ​​across devices. Specific device attributes are obtained based on the device type.

[0030] The dimension determination module is used to determine dimensions; it classifies device information from different perspectives, with each perspective being a dimension. The selection of dimensions should be based on the department's actual focus on device information.

[0031] The device meta-attribute extraction module extracts device meta-attributes from device information based on determined dimensions. These device meta-attributes are abstract data units that describe the definition, identification, representation, and allowed values ​​of various types of devices. They are abstract definitions of the attributes possessed by actual devices, namely, device information. These attributes include the device meta-attribute name, code, value, data type, data length, and dimension information: The name is the title of the content described by the device information; the code is a string of characters containing only letters and numbers used to identify the device meta-attribute name; the value is the information value of the content described by the device information; the data type and data length are characteristics that describe the value, namely, the data class type to which the value belongs, and a data length slightly greater than the maximum length of the value; and dimension information is the classification information belonging to each dimension. In other words, a device meta-attribute is a conceptual expression of a device attribute, and actual device information is the concretization and instantiation of the device meta-attribute.

[0032] The extraction of device meta-attributes complies with the following requirements:

[0033] (1) Standardize the device metadata attributes according to the national standards published on the National Standard Information Public Service Platform and the standards specified by the user itself;

[0034] (2) Clarify the category to which the device meta-attributes belong in each dimension;

[0035] (3) Meta-attribute values ​​must comply with national data standards.

[0036] Each device meta-attribute is described from multiple dimensions. Different device meta-attributes can be in the same dimension, and different devices can have the same device meta-attribute. Each dimension can be expanded or set to a fixed length.

[0037] The tag definition module defines the meta-attribute tag according to the extracted meta-attribute; after the device meta-attribute is given the characteristics of the tag, it is called the device meta-attribute tag.

[0038] The device information description module uses device meta-attribute tags to describe device information. This module utilizes device meta-attribute tags and implements multi-dimensional description of devices through multi-dimensional classification. It locates and describes devices from multiple dimensions, and through tag attachment (binding device meta-attribute tags), tag overwriting (changing device meta-attribute tag values), tag removal (unbinding device meta-attribute tags), and tag history monitoring, it enables real-time description of current device information and tracing of historical device information.

[0039] The relational database is used to store device information;

[0040] A relational database is used to store device information. Modeling is done using a relational database, improving upon the star model. The database model includes five tables: dimension information table, meta-attribute table, actual device attribute table, actual device summary information table, and device history information change record table.

[0041] The dimension information table is used to store the dimension information determined by the dimension determination module, each dimension is a table, and the information in each table is the classification information under the corresponding dimension; the meta-attribute table is used to store the device meta-attribute information extracted by the device meta-attribute extraction module and the dimension information to which the device meta-attribute belongs; the actual device attribute table is used to store the device meta-attribute information and meta-attribute values ​​bound to the device by the device information description module; the actual device summary information table is used to store the current information of the device; the device historical information change record table is used to store the historical dynamic information of the device description.

[0042] The beneficial effects of the present invention are as follows:

[0043] This database modeling method saves a lot of space and solves the problem of fixed fields and lack of flexibility in traditional database table building.

[0044] This device information description and storage method, based on multidimensional classification of meta-attribute tags, extracts collected device information as device meta-attributes. These meta-attributes are then bound to devices. Viewing device meta-attributes reveals the device information in the actual device summary information table, similar to the relationship between points, lines, and surfaces. This method effectively addresses the issue of reserving a large number of fields during initial table creation, facilitating the integration, management, and analysis of device data. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 It is a logical relationship diagram of device information in a relational database;

[0046] Figure 2 、 Figure 3 It is a schematic diagram of multi-dimensional description of device meta-attributes. DETAILED DESCRIPTION

[0047] The present invention will be further analyzed below in conjunction with specific embodiments.

[0048] A device information description and storage method based on multi-dimensional classification of meta-attribute tags, the specific method is as follows:

[0049] Step (1), collecting device information;

[0050] Device information refers to the information generated during device management activities. It includes both common and unique device attributes. Common attributes are common to all devices, but may differ in their values ​​across devices. Unique device attributes are obtained based on the device type.

[0051] The main information of the equipment can be obtained from the equipment supplier, including equipment manuals or drawings, maintenance and operation guides, and related information on troubleshooting; relevant information can be obtained from documents and materials such as mechanical completion reports, single-machine and system commissioning reports, supervision reports, special equipment inspection reports, and fire inspection acceptance reports.

[0052] Step (2), determine the dimension;

[0053] In the present invention, device information is classified from different perspectives, each of which is a dimension. The choice of dimension should be based on the actual emphasis of the department on device information.

[0054] Theoretically, there is no limit to the number of dimensions, but too many dimensions will lead to dimensional disaster. This paper recommends using 3-5 dimensions. This paper provides the following dimensions from the aspects of device information management, device information life cycle, device-related services, and device managers:

[0055] 1. Equipment information management dimension: From the perspective of equipment information management, the present invention divides equipment information into equipment basic data information, equipment daily maintenance information, equipment status monitoring information, equipment repair information, and equipment spare parts information.

[0056] 1) Equipment basic data information includes basic equipment information, equipment drawing information, and equipment asset information. Among them, basic equipment information includes basic information such as equipment number, name, specifications, production date, manufacturer, and installation unit; equipment drawing information includes equipment installation drawings, equipment parts drawings and assembly drawings, equipment design changes, etc.; equipment asset information includes equipment inventory information, equipment rental information, equipment scrapping information, and equipment property insurance information;

[0057] 2) Equipment daily maintenance information includes equipment inspection information (including inspection standards, plans, data and reports) and equipment maintenance information (including maintenance standards, plans and records);

[0058] 3) Equipment status monitoring information includes production parameter information, operating status information, energy and environmental protection information, and comprehensive evaluation information (evaluation information includes OEE evaluation, status evaluation, etc.);

[0059] 4) Equipment maintenance information includes maintenance plan information, maintenance scheme information, spare parts consumption information, and maintenance record information;

[0060] 5) Equipment spare parts information includes spare parts procurement information (including spare parts procurement plan, spare parts bidding information and spare parts supplier information), spare parts inventory information (including spare parts in and out information, spare parts inventory count information).

[0061] 2. Equipment information life cycle dimension: The present invention divides equipment information into equipment early planning information, equipment mid-term operation information, and equipment late maintenance information from the perspective of equipment information life cycle.

[0062] 1) Equipment pre-planning information refers to information obtained before equipment installation and acceptance. Equipment is categorized as either domestically manufactured or purchased, depending on whether the equipment is domestically manufactured. Pre-planning information for domestically manufactured equipment includes equipment planning, design, and manufacturing information; while pre-planning information for purchased equipment includes equipment selection and procurement information.

[0063] 2) Equipment mid-term operation information includes equipment installation information, equipment debugging information, equipment operation information and equipment maintenance information.

[0064] 3) Equipment post-maintenance information includes equipment failure and diagnosis information, equipment maintenance information, equipment improvement and update information, and equipment scrapping information.

[0065] 3. Equipment-related business dimensions: Basic ledger, equipment procurement ledger, equipment parts ledger, equipment fault diagnosis ledger, equipment maintenance ledger, equipment inspection ledger, and equipment scrapping ledger. The specific classification of business dimensions can be based on the business structure of the user unit.

[0066] 4. Equipment Manager Dimension: In this invention, the equipment manager refers to the relevant personnel involved in the equipment information. Based on the operation of the equipment by different personnel, the equipment information is classified into equipment procurement manager information, equipment operation manager information, equipment maintenance manager information, equipment repair manager information, etc. For example, the manager of the purchase price information of a certain equipment is Mr. Chen from the procurement department. Since the purchase price information is not accessible to only one device or one company, but is shared by all devices, each device owner can define the purchase price information of their own device. Therefore, the purchase price information belongs to the default manager (that is, all managers have permission).

[0067] Effective analysis of the equipment information lifecycle and effective control of the relationship between equipment and people, or the human-machine relationship, help improve overall equipment efficiency and optimize equipment asset costs. This article recommends that the Equipment Information Lifecycle and Manager dimensions be mandatory. If a department already has a comprehensive equipment information management framework or is preparing to establish an equipment information management system, the Equipment Information Management dimension can be selected. If a department focuses on equipment ledger information, the Equipment Business dimension can be selected. The choice of dimension should be based on the department's specific focus on equipment information.

[0068] Step (3), extracting device meta-attributes from the device information according to the determined dimensions;

[0069] Device meta-attributes are abstract data units that describe the definition, identification, representation, and allowed values ​​of various devices. They are abstract definitions of the attributes of actual devices, namely, device information. These include the device meta-attribute name, code, value, data type, data length, and dimension information: The name is the title of the content described by the device information; the code is a string containing only letters and numbers that identifies the device meta-attribute name; the value is the information value of the content described by the device information; the data type and data length are characteristics that describe the value, namely the data class type to which the value belongs, and the data length slightly greater than the maximum length of the value; and dimension information is the classification information within each dimension. In other words, a device meta-attribute is a conceptual expression of a device attribute, while actual device information is the concretization and instantiation of the device meta-attribute.

[0070] The extraction of device meta-attributes complies with the following requirements:

[0071] (1) Standardize meta-attributes based on the national standards published on the National Standard Information Public Service Platform and the standards specified by the user organization itself;

[0072] (2) Clarify the category to which the device meta-attributes belong in each dimension;

[0073] (3) Meta-attribute values ​​must comply with national data standards.

[0074] The above three requirements require that device meta-attributes be both universal and flexible enough to adapt to the individualized device data management needs of different users. Therefore, the traditional approach of standardizing device meta-attributes based on a single dimension cannot meet these requirements. Each device meta-attribute is described across multiple dimensions. Different device meta-attributes can be described in the same dimension, and different devices can have the same device meta-attribute. This significantly reduces the complexity of description and subsequent database storage space. Each dimension can be expanded or set to a fixed length.

[0075] Device meta-attribute extraction methods include manual entry, automatic extraction, and semi-automated methods. Choosing the appropriate method requires comprehensive consideration of the number of meta-attributes, extraction accuracy and cost, and the quality and complexity of the data source. Manual entry is labor-intensive and time-consuming and is not recommended. The latter two methods are generally used to quickly extract and modify device meta-attributes.

[0076] Step (4), defining meta-attribute tags based on the extracted device meta-attributes;

[0077] A tag consists of a name and a value, and is typically used to describe or indicate the characteristics of an object. The device meta-attributes extracted in the previous step also have names and values. When these device meta-attributes are given the characteristics of a tag, they are called device meta-attribute tags.

[0078] Step (5), using device meta-attribute tags to describe device information;

[0079] By utilizing the device's meta-attribute tags and multi-dimensionally classifying them, a multi-dimensional description of the device is achieved. Devices are located and described from multiple dimensions. Through tag attachment (binding device meta-attribute tags), tag overwriting (changing device meta-attribute tag values), tag removal (unbinding device meta-attribute tags), and tag history monitoring, a real-time description of the device's current information and the ability to query and trace historical device information are achieved.

[0080] Step (6), device information storage;

[0081] A relational database is used to store device information. Traditional modeling and table creation methods are too rigid due to fixed fields, which can easily lead to redundancy, system instability and other problems.

[0082] The method of the present invention adopts relational database modeling and improves on the star model. The database model of the present invention establishes five types of tables: dimension information table, meta-attribute table, actual device attribute table, actual device summary information table and device history information change record table.

[0083] The dimension information table is used to store the dimension information determined in step (2), each dimension is a table, and the information in each table is the classification information under the corresponding dimension; the meta-attribute table is used to store the device meta-attribute information extracted in step (3) and the dimension information to which the device meta-attribute belongs; the actual device attribute table is used to store the device meta-attribute information and meta-attribute values ​​bound to the device in step (5); the actual device summary information table is used to store the current information of the device, which can realize the description of the device information; the device history information change record table is used to store the historical dynamic information of the device description, which can realize the query and tracing of the device history information description. Figure 1 shown.

[0084] A device information description and storage system based on multi-dimensional classification of meta-attribute tags includes a device information collection module, a dimension determination module, a device meta-attribute extraction module, a tag definition module, a device information description module, and a relational database:

[0085] The device information collection module is used to collect device information. Device information refers to information generated during device management activities. Device information includes both common and unique device attributes. Common attributes are common to all devices, but may differ in their values ​​across devices. Device-specific attributes are obtained based on the device type.

[0086] The main information of the equipment can be obtained from the equipment supplier, including equipment manuals or drawings, maintenance and operation guides, and related information on troubleshooting; relevant information can be obtained from documents and materials such as mechanical completion reports, single-machine and system commissioning reports, supervision reports, special equipment inspection reports, and fire inspection acceptance reports.

[0087] The dimension determination module is used to determine dimensions; it categorizes device information from different perspectives, with each perspective being a dimension. Dimension selection should be based on the department's actual focus on device information.

[0088] Theoretically, there is no limit to the number of dimensions, but too many dimensions will lead to dimensional disaster. This paper recommends using 3-5 dimensions. This paper provides the following dimensions from the aspects of device information management, device information life cycle, device-related services, and device managers:

[0089] 1. Equipment information management dimension: From the perspective of equipment information management, the present invention divides equipment information into equipment basic data information, equipment daily maintenance information, equipment status monitoring information, equipment repair information, and equipment spare parts information.

[0090] 1) Equipment basic data information includes basic equipment information, equipment drawing information, and equipment asset information. Among them, basic equipment information includes basic information such as equipment number, name, specifications, production date, manufacturer, and installation unit; equipment drawing information includes equipment installation drawings, equipment parts drawings and assembly drawings, equipment design changes, etc.; equipment asset information includes equipment inventory information, equipment rental information, equipment scrapping information, and equipment property insurance information;

[0091] 2) Equipment daily maintenance information includes equipment inspection information (including inspection standards, plans, data and reports) and equipment maintenance information (including maintenance standards, plans and records);

[0092] 3) Equipment status monitoring information includes production parameter information, operating status information, energy and environmental protection information, and comprehensive evaluation information (evaluation information includes OEE evaluation, status evaluation, etc.);

[0093] 4) Equipment maintenance information includes maintenance plan information, maintenance scheme information, spare parts consumption information, and maintenance record information;

[0094] 5) Equipment spare parts information includes spare parts procurement information (including spare parts procurement plan, spare parts bidding information and spare parts supplier information), spare parts inventory information (including spare parts in and out information, spare parts inventory count information).

[0095] 2. Equipment information life cycle dimension: The present invention divides equipment information into equipment early planning information, equipment mid-term operation information, and equipment late maintenance information from the perspective of equipment information life cycle.

[0096] 1) Equipment pre-planning information refers to information obtained before equipment installation and acceptance. Equipment is categorized as either domestically manufactured or purchased, depending on whether the equipment is domestically manufactured. Pre-planning information for domestically manufactured equipment includes equipment planning, design, and manufacturing information; while pre-planning information for purchased equipment includes equipment selection and procurement information.

[0097] 2) Equipment mid-term operation information includes equipment installation information, equipment debugging information, equipment operation information and equipment maintenance information.

[0098] 3) Equipment post-maintenance information includes equipment failure and diagnosis information, equipment maintenance information, equipment improvement and update information, and equipment scrapping information.

[0099] 3. Equipment-related business dimensions: Basic ledger, equipment procurement ledger, equipment parts ledger, equipment fault diagnosis ledger, equipment maintenance ledger, equipment inspection ledger, and equipment scrapping ledger. The specific classification of business dimensions can be based on the business structure of the user unit.

[0100] 4. Equipment Manager Dimension: In this invention, the equipment manager refers to the relevant personnel involved in the equipment information. Based on the operation of the equipment by different personnel, the equipment information is classified into equipment procurement manager information, equipment operation manager information, equipment maintenance manager information, equipment repair manager information, etc. For example, the manager of the purchase price information of a certain equipment is Mr. Chen from the procurement department. Since the purchase price information is not accessible to only one device or one company, but is shared by all devices, each device owner can define the purchase price information of their own device. Therefore, the purchase price information belongs to the default manager (that is, all managers have permission).

[0101] Effective analysis of the equipment information lifecycle and effective control of the relationship between equipment and people, or the human-machine relationship, help improve overall equipment efficiency and optimize equipment asset costs. This article recommends that the Equipment Information Lifecycle and Manager dimensions be mandatory. If a department already has a comprehensive equipment information management framework or is preparing to establish an equipment information management system, the Equipment Information Management dimension can be selected. If a department focuses on equipment ledger information, the Equipment Business dimension can be selected. The choice of dimension should be based on the department's specific focus on equipment information.

[0102] The device meta-attribute extraction module extracts device meta-attributes from device information based on defined dimensions. Device meta-attributes are abstract data units that describe the definition, identification, representation, and allowed values ​​of various types of devices. They are abstract definitions of the attributes possessed by actual devices, namely, device information. These attributes include the device meta-attribute name, code, value, data type, data length, and dimension information: The name is the title of the content described by the device information; the code is a string containing only letters and numbers that identifies the device meta-attribute name; the value is the information value of the content described by the device information; the data type and data length are characteristics that describe the value, namely the data class type to which the value belongs, and the data length slightly greater than the maximum length of the value; and dimension information is the classification information within each dimension. In other words, a device meta-attribute is a conceptual expression of a device attribute, while actual device information is the concretization and instantiation of the device meta-attribute.

[0103] The extraction of device meta-attributes complies with the following requirements:

[0104] (1) Standardize meta-attributes based on the national standards published on the National Standard Information Public Service Platform and the standards specified by the user organization itself;

[0105] (2) Clarify the category to which the device meta-attributes belong in each dimension;

[0106] (3) Meta-attribute values ​​must comply with national data standards.

[0107] The above three requirements require that device meta-attributes be both universal and flexible enough to adapt to the individualized device data management needs of different users. Therefore, the traditional approach of standardizing device meta-attributes based on a single dimension cannot meet these requirements. Each device meta-attribute is described across multiple dimensions. Different device meta-attributes can be described in the same dimension, and different devices can have the same device meta-attribute. This significantly reduces the complexity of description and subsequent database storage space. Each dimension can be expanded or set to a fixed length.

[0108] Device meta-attribute extraction methods include manual entry, automatic extraction, and semi-automated methods. Choosing the appropriate method requires comprehensive consideration of the number of meta-attributes, extraction accuracy and cost, and the quality and complexity of the data source. Manual entry is labor-intensive and time-consuming and is not recommended. The latter two methods are generally used to quickly extract and modify device meta-attributes.

[0109] The tag definition module defines the meta-attribute tags according to the extracted meta-attributes; after the device meta-attributes are given the characteristics of the tags, they are called device meta-attribute tags.

[0110] The device information description module uses device meta-attribute tags to describe device information. This module leverages device meta-attribute tags and implements multi-dimensional descriptions of devices through multi-dimensional classification. Devices are located and described from multiple dimensions. Through tag attachment (binding device meta-attribute tags), tag overwriting (changing device meta-attribute tag values), tag removal (unbinding device meta-attribute tags), and tag history monitoring, it enables real-time descriptions of current device information and allows for querying and tracing of historical device information.

[0111] Relational database is used to store device information;

[0112] A relational database is used to store device information. Modeling is done using a relational database, improving upon the star model. The database model includes five tables: dimension information table, meta-attribute table, actual device attribute table, actual device summary information table, and device history information change record table.

[0113] The dimension information table is used to store the dimension information determined by the dimension determination module. Each dimension is a table, and the information in each table is the classification information under the corresponding dimension; the meta-attribute table is used to store the device meta-attribute information extracted by the device meta-attribute extraction module and the dimension information to which the device meta-attribute belongs; the actual device attribute table is used to store the device meta-attribute information and meta-attribute values ​​bound to the device by the device information description module; the actual device summary information table is used to store the current information of the device; the device historical information change record table is used to store the historical dynamic information of the device description.

[0114] Example

[0115] 1. Collect device information:

[0116] Obtain key equipment information from the equipment supplier, including equipment manuals or drawings, maintenance and operation guides, and related information on troubleshooting; obtain relevant information from documents and materials such as mechanical completion reports, single-machine and system commissioning reports, supervision reports, special equipment inspection reports, and fire inspection acceptance reports.

[0117] 2. Determine the dimensions:

[0118] This embodiment is described using three dimensions as examples: business dimension, device information life cycle dimension, and manager dimension. For dimension information, refer to step (2). Figure 2 、 3 shown.

[0119] 3. Extract device meta-attributes from device information based on the determined dimensions:

[0120] 1. Extract the device meta-attribute from the device information. For example, if the purchase price of the device is 200 yuan, extract its purchase price meta-attribute. Its meta-attribute value is 200, the meta-attribute unit is yuan, and the meta-attribute data type is floating point.

[0121] 2. Classify equipment meta-attributes from the business dimension. The purchase unit price meta-attribute is present in all equipment procurement information, so the category of the purchase unit price meta-attribute in the business dimension is the equipment procurement ledger.

[0122] 3. Analyze the equipment meta-attributes in the dimension of the equipment information lifecycle. The purchase unit price meta-attribute is the procurement link of the equipment information lifecycle that all equipment has. Therefore, the purchase unit price meta-attribute belongs to the equipment procurement information in the preliminary planning information in this dimension.

[0123] 4. Analyze the device meta-attributes from the manager dimension. For example, if the manager of a device's purchase price meta-attribute is Mr. Chen from the purchasing department, Mr. Chen can bind the purchase price meta-attribute to the device or modify its value.

[0124] Repeat the above steps for a device to extract all the desired device meta-attributes and their dimensions.

[0125] 4. Define meta-attribute tags based on the extracted device meta-attributes:

[0126] A tag consists of a name and a value, and is typically used to describe or indicate the characteristics of an object. The device meta-attributes extracted in the previous step also contain names and values. Giving device meta-attributes the characteristics of a tag is called a device meta-attribute tag. 5. Use device meta-attribute tags to describe device information:

[0127] By utilizing the device's meta-attribute tags and multi-dimensionally classifying them, a multi-dimensional description of the device is achieved. Devices are located and described from multiple dimensions. Through tag attachment (binding device meta-attribute tags), tag overwriting (changing device meta-attribute tag values), tag removal (unbinding device meta-attribute tags), and tag history monitoring, a real-time description of the device's current information and the ability to query and trace historical device information are achieved.

[0128] 6. Device Information Storage:

[0129] When using relational database modeling to build tables and only considering three dimensions of information, the logical relationship is as follows Figure 1 shown.

[0130] in:

[0131] 1. Dimension information tables (in this example, the meta-attribute business information table, the meta-attribute manager information table, and the meta-attribute device lifecycle information table; dimensions can be expanded as needed) include the dimension ID, name, parent category, and notes. Parent categories can be removed depending on the situation. In this example, the device information lifecycle classification ID does not require a parent category, so it is omitted. The parent category primarily resolves nested issues within the same dimension. For example, in the manager information for Company A and its subsidiary B, Company A is the parent category of Subsidiary B.

[0132] 2. The meta-attribute table contains information describing the device meta-attributes, including meta-attribute ID, attribute name, meta-attribute code, length, data type, whether it is not enumerated, each dimension ID, and remarks.

[0133] 3. The actual device attribute table contains: meta-attribute id, value, device id, and remarks.

[0134] 4. The actual device summary information table contains common information in the basic device information (i.e., device code and name, device model, upper-level device classification code and name) and meta-attribute description text. This table construction can reduce the length of the meta-attribute table and the actual device attribute table, facilitating retrieval. This table implements the description of device information.

[0135] 5. The device historical information change record table includes: device ID, meta-attribute ID, operation time, operation record (addition, deletion, and modification), meta-attribute original value (the value of the meta-attribute before the change), meta-attribute value (the value of the meta-attribute after the change, or the value assigned when adding the meta-attribute), which facilitates tracing the device historical description information.

[0136] 7. The association of the above five types of tables records a device meta-attribute as a label, classifies the labels by different dimensions, and then describes the current information of the device by attaching labels to the device. The current information of the device is divided into two types, namely fixed information (immutable information, which refers to the device meta-attribute with a uniquely determined meta-attribute value) and dynamic information (variable information, which refers to the device meta-attribute with a variable meta-attribute value). The device historical information change record table records the changes in dynamic information and is used to query the device historical information description. The device meta-attribute description text in the actual device summary information table is formed by integrating the other three types of tables through multi-table queries using SQL statements. All information in the actual device summary information table is the required device description information.

[0137] The above description is a further detailed description of the present invention in conjunction with specific / preferred embodiments, and the specific implementation of the present invention should not be considered to be limited to these descriptions. Those skilled in the art of the present invention may make various substitutions or modifications to the described embodiments without departing from the scope of the present invention, and such substitutions or modifications should be considered to fall within the scope of protection of the present invention.

[0138] Parts of the present invention that are not described in detail belong to the common knowledge of those skilled in the art.

Claims

1. A device information description and storage method based on multi-dimensional classification of meta-attribute tags, characterized in that: The specific method is as follows: Step (1), collect device information; Step (2), determine the dimension; Classify equipment information from different perspectives, with each perspective being a dimension. The choice of dimension should be based on the department's actual focus on equipment information. Step (3), extracting device meta-attributes from the device information according to the determined dimensions; Step (4), defining meta-attribute labels based on the extracted meta-attributes; The characteristics of labeling device meta-attributes are called device meta-attribute labels; Step (5), using device meta-attribute tags to describe device information; Step (6), device information storage; Use relational database to store device information; The model is built using a relational database, which is an improvement on the star model. The database model has five types of tables: dimension information table, meta-attribute table, actual device attribute table, actual device summary information table, and device historical information change record table. Step (5) is specifically implemented as follows; Utilize the device's meta-attribute tags and achieve multi-dimensional description of the device through multi-dimensional classification of meta-attribute tags; locate and describe the device from multiple dimensions, and achieve real-time description of the device's current information and query and traceability of the device's historical information description through tag attachment, tag overlay, tag removal, and tag history monitoring; The dimension information table is used to store the dimension information determined in step (2), each dimension is a table, and the information in each table is the classification information under the corresponding dimension; The meta-attribute table is used to store the device meta-attribute information extracted in step (3) and the dimension information to which the device meta-attribute belongs; the actual device attribute table is used to store the device meta-attribute information and meta-attribute values ​​bound to the device in step (5); the actual device summary information table is used to store the current information of the device; and the device history information change record table is used to store the historical dynamic information of the device description.

2. The device information description and storage method based on multi-dimensional classification of meta-attribute tags according to claim 1 is characterized in that: The device information refers to the information generated during device management activities, and includes general device attributes and device-specific attributes. The general attributes refer to attributes that all devices have, and the difference between general attributes of different devices is that the attribute values ​​may be different. The device-specific attributes are obtained according to the device type.

3. The device information description and storage method based on multi-dimensional classification of meta-attribute tags according to claim 1 or 2, characterized in that: The device meta-attribute is an abstract data unit that describes the definition, identification, representation and allowed values ​​of various types of devices. It is an abstract definition of the attributes of actual devices, namely, device information, including the device meta-attribute name, code, value, data type, data length, and dimension information: the name is the title of the content described by the device information; the code is a set of strings used to identify the device meta-attribute name, which only contains letters and numbers; the value is the information value of the content described by the device information; the data type and data length are characteristics of the descriptive value, namely, the data class type to which the value belongs, and the data length slightly larger than the maximum length of the value; the dimension information is the classification information under each dimension; that is, the device meta-attribute is the conceptual expression of a certain attribute of the device, and the actual device information is the concretization and instantiation of the device meta-attribute; The extraction of device meta-attributes complies with the following requirements: (1) Standardize the device meta-attributes according to the national standards published on the National Standard Information Public Service Platform and the standards specified by the user itself; (2) Clarify the category to which the device meta-attributes belong in each dimension; (3) Meta-attribute values ​​must comply with national data standards; Each device meta-attribute is described from multiple dimensions. Different device meta-attributes can be in the same dimension, and different devices can have the same device meta-attribute. Each dimension can be expanded or set to a fixed length dimension.

4. A device information description and storage system based on multi-dimensional classification of meta-attribute tags, characterized by: It includes device information collection module, dimension determination module, device meta-attribute extraction module, label definition module, device information description module and relational database: The device information collection module is used to collect device information; the device information refers to information generated during device management activities, and includes general device attributes and device-specific attributes; the general attributes are attributes that all devices have, and the difference between general attributes of different devices is that the attribute values ​​may be different; the device-specific attributes are obtained according to the device type; The dimension determination module is used to determine the dimension; classify the equipment information from different perspectives, each perspective being a dimension; the selection of the dimension should be based on the actual emphasis of the department on the equipment information; The device meta-attribute extraction module extracts device meta-attributes from device information according to the determined dimensions; the device meta-attributes refer to abstract data units that describe the definition, identification, representation and allowed values ​​of various types of devices, and are abstract definitions of the attributes of actual devices, namely, device information, including device meta-attribute name, code, value, data type, data length, and dimension information: the name is the title of the content described by the device information; the code is a set of strings used to identify the device meta-attribute name, which only contains letters and numbers; the value is the information value of the content described by the device information; the data type and data length are characteristics of the descriptive value, namely, the data class type to which the value belongs, and the data length slightly larger than the maximum length of the value; the dimension information is the classification information under each dimension; that is, the device meta-attribute is the conceptual expression of a certain attribute of the device, and the actual device information is the concretization and instantiation of the device meta-attribute; The extraction of device meta-attributes complies with the following requirements: (1) Standardize the device meta-attributes according to the national standards published on the National Standard Information Public Service Platform and the standards specified by the user itself; (2) Clarify the category to which the device meta-attributes belong in each dimension; (3) Meta-attribute values ​​must comply with national data standards; Each device meta-attribute is described from multiple dimensions. Different device meta-attributes can be in the same dimension, and different devices can have the same device meta-attribute. Each dimension can be expanded or set to a fixed length. The tag definition module defines the meta-attribute tag according to the extracted meta-attribute; after the device meta-attribute is given the characteristics of the tag, it is called the device meta-attribute tag; The device information description module uses device meta-attribute tags to describe device information; using the device meta-attribute tags, a multi-dimensional description of the device is achieved through multi-dimensional classification of the meta-attribute tags; the device is located and described from multiple dimensions, and through attaching tags, tag overlays, tag removal, and tag history monitoring, a real-time description of the device's current information is achieved, as well as query and traceability of the device's historical information description; The relational database is used to store device information; Use relational database to store device information; The model is built using a relational database, which is an improvement on the star model. The database model has five types of tables: dimension information table, meta-attribute table, actual device attribute table, actual device summary information table, and device historical information change record table. The dimension information table is used to store the dimension information determined by the dimension determination module. Each dimension is a table, and the information in each table is the classification information under the corresponding dimension. The meta-attribute table is used to store the device meta-attribute information extracted by the device meta-attribute extraction module and the dimension information to which the device meta-attributes belong; the actual device attribute table is used to store the device meta-attribute information and meta-attribute values ​​bound to the device in the device information description module; the actual device summary information table is used to store the current information of the device; the device historical information change record table is used to store the historical dynamic information of the device description.

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