CN116055530A - Object modeling method, system and readable storage medium based on industrial Internet of things - Google Patents
Object modeling method, system and readable storage medium based on industrial Internet of things Download PDFInfo
- Publication number
- CN116055530A CN116055530A CN202310247894.3A CN202310247894A CN116055530A CN 116055530 A CN116055530 A CN 116055530A CN 202310247894 A CN202310247894 A CN 202310247894A CN 116055530 A CN116055530 A CN 116055530A
- Authority
- CN
- China
- Prior art keywords
- data
- things
- object model
- equipment
- target
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Images
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/12—Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
-
- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B21/00—Alarms responsive to a single specified undesired or abnormal condition and not otherwise provided for
- G08B21/18—Status alarms
- G08B21/182—Level alarms, e.g. alarms responsive to variables exceeding a threshold
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L69/00—Network arrangements, protocols or services independent of the application payload and not provided for in the other groups of this subclass
- H04L69/08—Protocols for interworking; Protocol conversion
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04Q—SELECTING
- H04Q9/00—Arrangements in telecontrol or telemetry systems for selectively calling a substation from a main station, in which substation desired apparatus is selected for applying a control signal thereto or for obtaining measured values therefrom
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04Q—SELECTING
- H04Q2209/00—Arrangements in telecontrol or telemetry systems
- H04Q2209/10—Arrangements in telecontrol or telemetry systems using a centralized architecture
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04Q—SELECTING
- H04Q2209/00—Arrangements in telecontrol or telemetry systems
- H04Q2209/20—Arrangements in telecontrol or telemetry systems using a distributed architecture
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]
Abstract
The invention discloses an object modeling method, an object modeling system and a readable storage medium based on industrial Internet of things, wherein the method comprises the following steps: constructing a target object model based on the Internet of things, and binding physical equipment with the target object model, wherein the physical equipment comprises a sensor group, a controller and operation equipment; collecting target data corresponding to the physical equipment, wherein the target data comprises sensing data, control data and operation data; and analyzing based on the target object model and the target data, wherein the analysis content comprises performing equipment parameter mapping analysis based on the target object model and performing function calculation analysis based on the target data. The invention improves the reusability of the industry object model by constructing the industry object model library, can process service data errors in real time, simulate missing service data, improves the service processing accuracy, combines and splits the service processing accuracy with service equipment entities, and reduces service delivery and maintenance cost.
Description
Technical Field
The invention relates to the technical field of the Internet of things, in particular to an object modeling method, an object modeling system and a readable storage medium based on the industrial Internet of things.
Background
Object modeling is a key for realizing industrial data acquisition and is a foundation for realizing industrial Internet. The object modeling based on the industrial Internet of things is realized by constructing a scripting language and unified modeling oriented to physical entities, which shields the bottom terminal difference, standardizes the capability expression and interaction modes of the objects, and greatly reduces the application development and replication cost of the Internet of things. However, the existing object modeling method has the following disadvantages: 1. the data acquisition model is complex to construct, the multiplexing degree of the same equipment object is low, and the maintenance cost is high; 2. the industrial equipment data has the defects and errors, so that the service judgment difficulty is high, and the equipment data can not be simulated and corrected in real time; 3. the industrial site is controlled by a centralized control system, and the output interface is unique but comprises a plurality of devices (powder coating is exemplified by extrusion process comprising an extruder, a tablet press and a crusher). The data acquisition is carried out according to the physical entity, the mechanical modification is needed, the difficulty is high, and the cost is high; the physical entity equipment is split at the edge software, so that delivery personnel often work in different places, and the implementation and maintenance difficulties are high; 4. the industrial equipment is controlled by a distributed control system, the control system respectively comprises respective output interfaces (powder coating is exemplified by a pulverizer control system comprising a frequency converter, a PLC, a temperature controller and the like), data acquisition is carried out according to service entities, and a unified output network is required to be built; the physical entity equipment combination is carried out on the edge software, so that delivery personnel often work in different places, and the real-time maintenance cost is high.
Disclosure of Invention
The invention aims to provide an object modeling method, an object modeling system and a readable storage medium based on the industrial Internet of things, which are used for improving the reusability of an industrial object model by constructing the industrial object model library, processing service data errors in real time, simulating missing service data, improving the service processing accuracy, combining and splitting with service equipment entities and reducing the service delivery and maintenance cost.
The invention provides an object modeling method based on industrial Internet of things, which comprises the following steps:
constructing a target object model based on the Internet of things, and binding physical equipment with the target object model, wherein the physical equipment comprises a sensor group, a controller and operation equipment;
collecting target data corresponding to the physical equipment, wherein the target data comprises sensing data, control data and operation data;
resolving based on the object model and the object data, wherein,
the analysis content comprises equipment parameter mapping analysis based on the target object model and function calculation analysis based on the target data.
In this scheme, the thing networking based object model is constructed, and physical equipment and the object model are bound, specifically includes:
Constructing the target object model based on the Internet of things, wherein the target object model at least comprises a group of equipment object models for industrial manufacturing, and the group of equipment object models for industrial manufacturing at least comprises a sensor group model, a controller model and an operation equipment model;
and based on matching the physical equipment in communication with the current Internet of things with the target object model, binding the successfully identified target object model with the corresponding physical equipment, wherein the number value of the target object model is larger than that of the physical equipment in communication with the current Internet of things.
In this scheme, gather the target data that the physical equipment corresponds, specifically include:
acquiring acquisition data corresponding to physical equipment based on an edge gateway side, and performing protocol conversion on the acquisition data to obtain standard data;
performing equipment type discrimination based on the standard data to obtain the sensing data, the control data and the operation data;
the target data is obtained based on the sensing data, the control data, and the operation data.
In this solution, the performing function calculation and analysis based on the target data specifically includes:
Performing corresponding function calculation analysis on the target data based on different types, wherein,
performing alarm function calculation on the sensing data to judge whether to output alarm reminding;
performing missing function calculation on the control data to judge whether to secondarily output a corresponding control command;
and performing error function calculation on the operation data to judge whether an error exists in the operation data.
In this solution, the performing device parameter mapping analysis based on the object model specifically includes:
identifying field control types of industrial manufacturing, wherein the field control types comprise centralized control types and decentralized control types;
when the centralized control type device is identified, device splitting is carried out based on the physical device, and device parameter mapping is carried out based on the split physical device and a corresponding target object model;
in the mapping process, corresponding target data are loaded for display.
In this scheme, the device parameter mapping analysis based on the object model further includes: and when the decentralized control type device is identified, device combination is carried out based on the physical devices, device parameter mapping is carried out based on the combined physical devices and the corresponding object models, and corresponding object data are loaded and displayed in the mapping process.
The second aspect of the present invention also provides an object modeling system based on the industrial internet of things, including a memory and a processor, where the memory includes an object modeling method program based on the industrial internet of things, and when the object modeling method program based on the industrial internet of things is executed by the processor, the following steps are implemented:
constructing a target object model based on the Internet of things, and binding physical equipment with the target object model, wherein the physical equipment comprises a sensor group, a controller and operation equipment;
collecting target data corresponding to the physical equipment, wherein the target data comprises sensing data, control data and operation data;
resolving based on the object model and the object data, wherein,
the analysis content comprises equipment parameter mapping analysis based on the target object model and function calculation analysis based on the target data.
In this scheme, the thing networking based object model is constructed, and physical equipment and the object model are bound, specifically includes:
constructing the target object model based on the Internet of things, wherein the target object model at least comprises a group of equipment object models for industrial manufacturing, and the group of equipment object models for industrial manufacturing at least comprises a sensor group model, a controller model and an operation equipment model;
And based on matching the physical equipment in communication with the current Internet of things with the target object model, binding the successfully identified target object model with the corresponding physical equipment, wherein the number value of the target object model is larger than that of the physical equipment in communication with the current Internet of things.
In this scheme, gather the target data that the physical equipment corresponds, specifically include:
acquiring acquisition data corresponding to physical equipment based on an edge gateway side, and performing protocol conversion on the acquisition data to obtain standard data;
performing equipment type discrimination based on the standard data to obtain the sensing data, the control data and the operation data;
the target data is obtained based on the sensing data, the control data, and the operation data.
In this solution, the performing function calculation and analysis based on the target data specifically includes:
performing corresponding function calculation analysis on the target data based on different types, wherein,
performing alarm function calculation on the sensing data to judge whether to output alarm reminding;
performing missing function calculation on the control data to judge whether to secondarily output a corresponding control command;
And performing error function calculation on the operation data to judge whether an error exists in the operation data.
In this solution, the performing device parameter mapping analysis based on the object model specifically includes:
identifying field control types of industrial manufacturing, wherein the field control types comprise centralized control types and decentralized control types;
when the centralized control type device is identified, device splitting is carried out based on the physical device, and device parameter mapping is carried out based on the split physical device and a corresponding target object model;
in the mapping process, corresponding target data are loaded for display.
In this scheme, the device parameter mapping analysis based on the object model further includes: and when the decentralized control type device is identified, device combination is carried out based on the physical devices, device parameter mapping is carried out based on the combined physical devices and the corresponding object models, and corresponding object data are loaded and displayed in the mapping process.
A third aspect of the present invention provides a computer readable storage medium, including a machine-based object modeling method program for industrial internet of things, which when executed by a processor, implements the steps of an industrial internet of things-based object modeling method as described in any one of the above.
According to the object modeling method, system and readable storage medium based on the industrial Internet of things, disclosed by the invention, the reusability of the industrial object model is improved by constructing the industrial object model library, the business data errors can be processed in real time, the missing business data is simulated, the business processing accuracy is improved, the business processing accuracy is combined and split with business equipment entities, and the business delivery and maintenance cost is reduced.
Drawings
FIG. 1 shows a flow chart of an object modeling method based on industrial Internet of things of the present invention;
FIG. 2 shows a schematic diagram of an Internet of things platform structure of an object modeling method based on the industrial Internet of things;
FIG. 3 shows a schematic diagram of the alarm function calculation of an object modeling method based on the industrial Internet of things;
FIG. 4 shows a schematic diagram of a device split mapping of an object modeling method based on industrial Internet of things according to the present invention;
FIG. 5 shows a schematic diagram of a device combination map of an object modeling method based on industrial Internet of things in accordance with the present invention;
FIG. 6 shows a block diagram of an object modeling system based on the industrial Internet of things of the present invention.
Detailed Description
In order that the above-recited objects, features and advantages of the present invention will be more clearly understood, a more particular description of the invention will be rendered by reference to the appended drawings and appended detailed description. It should be noted that, in the case of no conflict, the embodiments of the present application and the features in the embodiments may be combined with each other.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, however, the present invention may be practiced in other ways than those described herein, and therefore the scope of the present invention is not limited to the specific embodiments disclosed below.
FIG. 1 shows a flow chart of an object modeling method based on industrial Internet of things.
As shown in fig. 1, the application discloses an object modeling method based on industrial internet of things, which comprises the following steps:
s102, constructing a target object model based on the Internet of things, and binding physical equipment with the target object model, wherein the physical equipment comprises a sensor group, a controller and operation equipment;
s104, collecting target data corresponding to the physical equipment, wherein the target data comprises sensing data, control data and operation data;
s106, analyzing based on the target object model and the target data, wherein the analysis content comprises performing equipment parameter mapping analysis based on the target object model and performing function calculation analysis based on the target data.
It should be noted that, in this embodiment, as shown in fig. 2, for an industrial internet of things platform, one end is an edge side, for example, an edge gateway performs edge settlement to collect data information of the physical device, and one end is a device data side, including multiple object models, where the object model is firstly constructed based on the internet of things, so that binding can be performed based on the object model and a corresponding physical device, correspondingly, the physical device includes a sensor group, a controller and an operation device, acquires collected data corresponding to the physical device based on the edge side and performs industrial protocol conversion to obtain corresponding standard data, classifies the standard data to obtain the sensing data, the control data and the operation data, so as to obtain the target data, and after obtaining the target data, performs analysis based on the object model and the target data, where specific analysis includes analysis based on function calculation analysis based on the target data, including deletion, error analysis, and function calculation judgment of whether the data is overrun or not; the specific analysis content further comprises performing device parameter mapping analysis based on the object model, wherein when performing device parameter mapping, the control types of the corresponding control system of the industrial field need to be considered, wherein the control types comprise a centralized control type and a decentralized control type, different mapping modes are adopted according to different control types, for example, when the control type corresponding to the industrial field is the centralized control type, the physical device of the entity needs to be split, then the parameter mapping is performed on the object model corresponding to the split physical device binding, and then the data analysis is performed based on a single split device.
According to the embodiment of the invention, the method for constructing the object model based on the internet of things and binding the physical equipment with the object model specifically comprises the following steps:
constructing the target object model based on the Internet of things, wherein the target object model at least comprises a group of equipment object models for industrial manufacturing, and the group of equipment object models for industrial manufacturing at least comprises a sensor group model, a controller model and an operation equipment model;
and based on matching the physical equipment in communication with the current Internet of things with the target object model, binding the successfully identified target object model with the corresponding physical equipment, wherein the number value of the target object model is larger than that of the physical equipment in communication with the current Internet of things.
It should be noted that, in this embodiment, when the object model is built based on the internet of things, the corresponding number value is greater than the number value of the physical devices currently in communication with the internet of things, so that when model matching and binding are performed, it is ensured that each physical device connected to the current internet of things can be bound to one object model, and therefore, the object model at least includes a set of industrial manufacturing device object models, and accordingly, a set of industrial manufacturing device object models at least includes a sensor group model, a controller model, and an operation device model, and other element models, such as a hard disk storage model. Correspondingly, the object model is a digital representation of an entity (such as a sensor, a vehicle-mounted device, a building, a factory and the like) in a physical space at the cloud end, and can be understood as a set of function definitions of equipment, so that complex equipment modeling in an actual scene is solved, and equipment under different products can perform different function definitions without mutual influence.
According to an embodiment of the present invention, the collecting target data corresponding to the physical device specifically includes:
acquiring acquisition data corresponding to physical equipment based on an edge gateway side, and performing protocol conversion on the acquisition data to obtain standard data;
performing equipment type discrimination based on the standard data to obtain the sensing data, the control data and the operation data;
the target data is obtained based on the sensing data, the control data, and the operation data.
In this embodiment, the foregoing embodiment describes that the edge side is used to perform edge settlement to collect the data information of the physical device, and correspondingly, the collected data is acquired based on the edge gateway side, and then the industrial protocol conversion is performed on the collected data to obtain corresponding standard data, so that the standard data is divided according to types to obtain the corresponding sensing data, the control data, the operation data and other data, and the divided standard data is used as the target data.
According to an embodiment of the present invention, the function calculation and analysis based on the target data specifically includes:
Performing corresponding function calculation analysis on the target data based on different types, wherein,
performing alarm function calculation on the sensing data to judge whether to output alarm reminding;
performing missing function calculation on the control data to judge whether to secondarily output a corresponding control command;
and performing error function calculation on the operation data to judge whether an error exists in the operation data.
It should be noted that, in the above embodiment, the function calculation analysis is performed based on the target data, which includes performing analysis contents such as deletion, error analysis, and function calculation to determine whether the data exceeds the limit, so in this embodiment, the alarm function calculation is performed on the sensing data to determine whether to output an alarm reminder; performing missing function calculation on the control data to judge whether to secondarily output a corresponding control command; and performing error function calculation on the operation data to determine whether an error exists in the operation data, wherein, taking alarm function calculation as an example, as shown in fig. 3, the acquired acquisition data includes "tem_01:60.23, hum_01:55'; according to the report of the industrial entity physical equipment, searching a corresponding object model 'Tem_01': the temperature, hum_01/10, humidity "is used for carrying out alarm function calculation, and the specific steps are as follows: alert, script: if (Hum > 10) { return true; else { return false } ", the data analysis result obtained by this is" temperature: 60.23, humidity: 55, alarm, true.
According to an embodiment of the present invention, the performing device parameter mapping analysis based on the object model specifically includes:
identifying field control types of industrial manufacturing, wherein the field control types comprise centralized control types and decentralized control types;
when the centralized control type device is identified, device splitting is carried out based on the physical device, and device parameter mapping is carried out based on the split physical device and a corresponding target object model;
in the mapping process, corresponding target data are loaded for display.
It should be noted that, in this embodiment, referring to fig. 4, in the device splitting modeling analysis process, when the centralized control type is identified, device splitting is performed based on the physical device, and device parameter mapping is performed based on the split physical device and the corresponding object model, where the centralized control type is first split, and then object model mapping is performed to obtain parameters of a single data volume, specifically, as shown in fig. 4, the split mapping of the temperature and the humidity on the physical device 1001 corresponds to the temperature obtained on the object model bound by the physical device 1002, and the humidity obtained on the object model bound by the physical device 1003, specifically, the data collected by the device 1001 is "tem_01:60.23 "hum_01:55", and performing device splitting to obtain data on a target object model corresponding to the physical device 1002, wherein the data is "tem_02: temperature ", the corresponding mapping relationship is" tem_01:tem_02", and the corresponding obtained analysis data is" temperature: 60.23"; the data on the object model corresponding to the physical device 1003 obtained by device splitting is "hum_02: humidity ", the corresponding mapping relationship is" hum_01:hum_02", and the corresponding obtained analysis data is" humidity ": 55".
According to an embodiment of the present invention, the performing device parameter mapping analysis based on the object model further includes: and when the decentralized control type device is identified, device combination is carried out based on the physical devices, device parameter mapping is carried out based on the combined physical devices and the corresponding object models, and corresponding object data are loaded and displayed in the mapping process.
In this embodiment, since the device combination is performed, the number of object models needs to be equal to or greater than "2", and when the distributed control type is identified with reference to fig. 5, the data on the collected physical device 1004 is "tem—01:60.23", the collected data on the physical device 1005 is" hum_01:55", device combination is performed, and device parameter mapping is performed based on the combined physical device and the corresponding object model, where the mapping relationship is" tem_01: tem_02 "and" hum_01:hum_02 ", and thus, the mapping data on the object model corresponding to the corresponding physical device 1006 is" tem_02: temperature, hum_02:humidity ", and the analyzed data is" temperature: 60.23, humidity: 55".
It should be noted that the step of performing the missing function calculation on the control data to determine whether to secondarily output the corresponding control command specifically includes:
Acquiring the control data for data capture, wherein,
judging whether the grabbing result is a preset value, if so, outputting a secondary control command, and if not, not outputting the secondary control command.
It should be noted that, in this embodiment, for the control data type in the standard data, it is required to determine whether there is corresponding required data in the corresponding data field, for example, the control data is "acquiring temperature data of the physical device 1001", that is, it indicates that there is corresponding control signal and control object in the current control data, which indicates that the grabbing result is not a preset value, at this time, no secondary control command is output, and if there is no parameter in the control command line, that is, "acquiring x" indicates that there is a control signal but there is no control object in the current control data, it indicates that the grabbing result is a preset value, at this time, the preset value may be set to "0", when the control command is complete, it indicates that the grabbing result of the current control data is not "0", otherwise, when the control command is incomplete, it indicates that the grabbing result of the current control data is "0".
It should be noted that the calculating the error function on the operation data to determine whether there is an error in the operation data specifically includes:
Acquiring acquired sensing data as a reference parameter;
randomly selecting analysis data of the operation equipment in an operation stage to trace the source;
and comparing the result after tracing with the reference parameter to judge whether an error exists.
It should be noted that, in this embodiment, since the analysis data displayed by the operation device in the operation stage is derived from the sensing data, in order to avoid errors in the operation process, tracing the analysis data is needed to determine whether the traced result is consistent with the current sensing data to determine whether errors exist, where the physical device 1002 analyzes the data "temperature: 60.23 "for example, the tracing result corresponding to the current analysis data is the temperature sensing data" tem_01:60.23 "collected by the physical device 1001, and the comparison is performed between the analysis data extraction data" 60.23 "and the temperature sensing data extraction data" 60.23", so that the result is consistent, and if the comparison result is inconsistent, the error is indicated.
It should be noted that, when the function error exists in the operation data, the judgment is performed based on the control data to trace the source error, which specifically includes:
when the function error exists in the operation data, tracing the source result corresponding to the analysis data;
And comparing the control object and/or the control signal based on the control data and the tracing result to trace the source error.
It should be noted that, in this embodiment, when the function error exists in the operation data, the cause may be that the control data is erroneous, so that the control data needs to be compared, for example, the control data is "the temperature data of the collection physical device 1001", the tracing result is "the humidity data corresponding to the physical device 1001 is" hum_01:55", which indicates that the control object and the control signal are different, and the cause of the error may be that the signal transmission of the sensor has a problem of a circuit disorder or that the mapping relationship has an error.
It should be noted that, the determining to trace the source error based on the mapping relation specifically includes:
when the function error exists in the operation data, the mapping relation is extracted for judgment, wherein,
if the mapping objects are consistent in front and back, the current error cause is indicated to be the disturbance of the sensor signal transmission line;
if the mapping objects are inconsistent, indicating that the current mapping relation has errors.
It should be noted that, in this embodiment, since the mapping relationship is preset or input by the user side, there may be an error in the final operation data due to an error in the mapping relationship, and at this time, it is necessary to extract the mapping relationship to perform the mapping object comparison, for example, the mapping relationship "tem—01" in the above embodiment: if the mapping objects before and after the judgment are respectively 'tem_' and 'tem_' or 'hum_' and 'hum_' according to comparison, the mapping objects are consistent before and after the judgment, and the current error is indicated to be caused by disturbance of the signal transmission line of the sensor; if the mapping objects before and after the judgment are respectively "tem_" & "hum_", or "hum_" and "tem_", the comparison indicates that the mapping objects before and after are inconsistent, and at this time, it indicates that the current mapping relationship has errors and needs to be corrected.
FIG. 6 shows a block diagram of an object modeling system based on the industrial Internet of things of the present invention.
As shown in fig. 6, the invention discloses an object modeling system based on industrial internet of things, which comprises a memory and a processor, wherein the memory comprises an object modeling method program based on industrial internet of things, and the object modeling method program based on industrial internet of things realizes the following steps when being executed by the processor:
constructing a target object model based on the Internet of things, and binding physical equipment with the target object model, wherein the physical equipment comprises a sensor group, a controller and operation equipment;
collecting target data corresponding to the physical equipment, wherein the target data comprises sensing data, control data and operation data;
resolving based on the object model and the object data, wherein,
the analysis content comprises equipment parameter mapping analysis based on the target object model and function calculation analysis based on the target data.
It should be noted that, in this embodiment, as shown in fig. 2, for an industrial internet of things platform, one end is an edge side, for example, an edge gateway performs edge settlement to collect data information of the physical device, and one end is a device data side, including multiple object models, where the object model is firstly constructed based on the internet of things, so that binding can be performed based on the object model and a corresponding physical device, correspondingly, the physical device includes a sensor group, a controller and an operation device, acquires collected data corresponding to the physical device based on the edge side and performs industrial protocol conversion to obtain corresponding standard data, classifies the standard data to obtain the sensing data, the control data and the operation data, so as to obtain the target data, and after obtaining the target data, performs analysis based on the object model and the target data, where specific analysis includes analysis based on function calculation analysis based on the target data, including deletion, error analysis, and function calculation judgment of whether the data is overrun or not; the specific analysis content further comprises performing device parameter mapping analysis based on the object model, wherein when performing device parameter mapping, the control types of the corresponding control system of the industrial field need to be considered, wherein the control types comprise a centralized control type and a decentralized control type, different mapping modes are adopted according to different control types, for example, when the control type corresponding to the industrial field is the centralized control type, the physical device of the entity needs to be split, then the parameter mapping is performed on the object model corresponding to the split physical device binding, and then the data analysis is performed based on a single split device.
According to the embodiment of the invention, the method for constructing the object model based on the internet of things and binding the physical equipment with the object model specifically comprises the following steps:
constructing the target object model based on the Internet of things, wherein the target object model at least comprises a group of equipment object models for industrial manufacturing, and the group of equipment object models for industrial manufacturing at least comprises a sensor group model, a controller model and an operation equipment model;
and based on matching the physical equipment in communication with the current Internet of things with the target object model, binding the successfully identified target object model with the corresponding physical equipment, wherein the number value of the target object model is larger than that of the physical equipment in communication with the current Internet of things.
It should be noted that, in this embodiment, when the object model is built based on the internet of things, the corresponding number value is greater than the number value of the physical devices currently in communication with the internet of things, so that when model matching and binding are performed, it is ensured that each physical device connected to the current internet of things can be bound to one object model, and therefore, the object model at least includes a set of industrial manufacturing device object models, and accordingly, a set of industrial manufacturing device object models at least includes a sensor group model, a controller model, and an operation device model, and other element models, such as a hard disk storage model. Correspondingly, the object model is a digital representation of an entity (such as a sensor, a vehicle-mounted device, a building, a factory and the like) in a physical space at the cloud end, and can be understood as a set of function definitions of equipment, so that complex equipment modeling in an actual scene is solved, and equipment under different products can perform different function definitions without mutual influence.
According to an embodiment of the present invention, the collecting target data corresponding to the physical device specifically includes:
acquiring acquisition data corresponding to physical equipment based on an edge gateway side, and performing protocol conversion on the acquisition data to obtain standard data;
performing equipment type discrimination based on the standard data to obtain the sensing data, the control data and the operation data;
the target data is obtained based on the sensing data, the control data, and the operation data.
In this embodiment, the foregoing embodiment describes that the edge side is used to perform edge settlement to collect the data information of the physical device, and correspondingly, the collected data is acquired based on the edge gateway side, and then the industrial protocol conversion is performed on the collected data to obtain corresponding standard data, so that the standard data is divided according to types to obtain the corresponding sensing data, the control data, the operation data and other data, and the divided standard data is used as the target data.
According to an embodiment of the present invention, the function calculation and analysis based on the target data specifically includes:
Performing corresponding function calculation analysis on the target data based on different types, wherein,
performing alarm function calculation on the sensing data to judge whether to output alarm reminding;
performing missing function calculation on the control data to judge whether to secondarily output a corresponding control command;
and performing error function calculation on the operation data to judge whether an error exists in the operation data.
It should be noted that, in the above embodiment, the function calculation analysis is performed based on the target data, which includes performing analysis contents such as deletion, error analysis, and function calculation to determine whether the data exceeds the limit, so in this embodiment, the alarm function calculation is performed on the sensing data to determine whether to output an alarm reminder; performing missing function calculation on the control data to judge whether to secondarily output a corresponding control command; and performing error function calculation on the operation data to determine whether an error exists in the operation data, wherein, taking alarm function calculation as an example, as shown in fig. 3, the acquired acquisition data includes "tem_01:60.23, hum_01:55'; according to the report of the industrial entity physical equipment, searching a corresponding object model 'Tem_01': the temperature, hum_01/10, humidity "is used for carrying out alarm function calculation, and the specific steps are as follows: alert, script: if (Hum > 10) { return true; else { return false } ", the data analysis result obtained by this is" temperature: 60.23, humidity: 55, alarm, true.
According to an embodiment of the present invention, the performing device parameter mapping analysis based on the object model specifically includes:
identifying field control types of industrial manufacturing, wherein the field control types comprise centralized control types and decentralized control types;
when the centralized control type device is identified, device splitting is carried out based on the physical device, and device parameter mapping is carried out based on the split physical device and a corresponding target object model;
in the mapping process, corresponding target data are loaded for display.
It should be noted that, in this embodiment, referring to fig. 4, in the device splitting modeling analysis process, when the centralized control type is identified, device splitting is performed based on the physical device, and device parameter mapping is performed based on the split physical device and the corresponding object model, where the centralized control type is first split, and then object model mapping is performed to obtain parameters of a single data volume, specifically, as shown in fig. 4, the split mapping of the temperature and the humidity on the physical device 1001 corresponds to the temperature obtained on the object model bound by the physical device 1002, and the humidity obtained on the object model bound by the physical device 1003, specifically, the data collected by the device 1001 is "tem_01:60.23 "hum_01:55", and performing device splitting to obtain data on a target object model corresponding to the physical device 1002, wherein the data is "tem_02: temperature ", the corresponding mapping relationship is" tem_01:tem_02", and the corresponding obtained analysis data is" temperature: 60.23"; the data on the object model corresponding to the physical device 1003 obtained by device splitting is "hum_02: humidity ", the corresponding mapping relationship is" hum_01:hum_02", and the corresponding obtained analysis data is" humidity ": 55".
According to an embodiment of the present invention, the performing device parameter mapping analysis based on the object model further includes: and when the decentralized control type device is identified, device combination is carried out based on the physical devices, device parameter mapping is carried out based on the combined physical devices and the corresponding object models, and corresponding object data are loaded and displayed in the mapping process.
In this embodiment, since the device combination is performed, the number of object models needs to be equal to or greater than "2", and when the distributed control type is identified with reference to fig. 5, the data on the collected physical device 1004 is "tem—01:60.23", the collected data on the physical device 1005 is" hum_01:55", device combination is performed, and device parameter mapping is performed based on the combined physical device and the corresponding object model, where the mapping relationship is" tem_01: tem_02 "and" hum_01:hum_02 ", and thus, the mapping data on the object model corresponding to the corresponding physical device 1006 is" tem_02: temperature, hum_02:humidity ", and the analyzed data is" temperature: 60.23, humidity: 55".
It should be noted that the step of performing the missing function calculation on the control data to determine whether to secondarily output the corresponding control command specifically includes:
Acquiring the control data for data capture, wherein,
judging whether the grabbing result is a preset value, if so, outputting a secondary control command, and if not, not outputting the secondary control command.
It should be noted that, in this embodiment, for the control data type in the standard data, it is required to determine whether there is corresponding required data in the corresponding data field, for example, the control data is "acquiring temperature data of the physical device 1001", that is, it indicates that there is corresponding control signal and control object in the current control data, which indicates that the grabbing result is not a preset value, at this time, no secondary control command is output, and if there is no parameter in the control command line, that is, "acquiring x" indicates that there is a control signal but there is no control object in the current control data, it indicates that the grabbing result is a preset value, at this time, the preset value may be set to "0", when the control command is complete, it indicates that the grabbing result of the current control data is not "0", otherwise, when the control command is incomplete, it indicates that the grabbing result of the current control data is "0".
It should be noted that the calculating the error function on the operation data to determine whether there is an error in the operation data specifically includes:
Acquiring acquired sensing data as a reference parameter;
randomly selecting analysis data of the operation equipment in an operation stage to trace the source;
and comparing the result after tracing with the reference parameter to judge whether an error exists.
It should be noted that, in this embodiment, since the analysis data displayed by the operation device in the operation stage is derived from the sensing data, in order to avoid errors in the operation process, tracing the analysis data is needed to determine whether the traced result is consistent with the current sensing data to determine whether errors exist, where the physical device 1002 analyzes the data "temperature: 60.23 "for example, the tracing result corresponding to the current analysis data is the temperature sensing data" tem_01:60.23 "collected by the physical device 1001, and the comparison is performed between the analysis data extraction data" 60.23 "and the temperature sensing data extraction data" 60.23", so that the result is consistent, and if the comparison result is inconsistent, the error is indicated.
It should be noted that, when the function error exists in the operation data, the judgment is performed based on the control data to trace the source error, which specifically includes:
when the function error exists in the operation data, tracing the source result corresponding to the analysis data;
And comparing the control object and/or the control signal based on the control data and the tracing result to trace the source error.
It should be noted that, in this embodiment, when the function error exists in the operation data, the cause may be that the control data is erroneous, so that the control data needs to be compared, for example, the control data is "the temperature data of the collection physical device 1001", the tracing result is "the humidity data corresponding to the physical device 1001 is" hum_01:55", which indicates that the control object and the control signal are different, and the cause of the error may be that the signal transmission of the sensor has a problem of a circuit disorder or that the mapping relationship has an error.
It should be noted that, the determining to trace the source error based on the mapping relation specifically includes:
when the function error exists in the operation data, the mapping relation is extracted for judgment, wherein,
if the mapping objects are consistent in front and back, the current error cause is indicated to be the disturbance of the sensor signal transmission line;
if the mapping objects are inconsistent, indicating that the current mapping relation has errors.
It should be noted that, in this embodiment, since the mapping relationship is preset or input by the user side, there may be an error in the final operation data due to an error in the mapping relationship, and at this time, it is necessary to extract the mapping relationship to perform the mapping object comparison, for example, the mapping relationship "tem—01" in the above embodiment: if the mapping objects before and after the judgment are respectively 'tem_' and 'tem_' or 'hum_' and 'hum_' according to comparison, the mapping objects are consistent before and after the judgment, and the current error is indicated to be caused by disturbance of the signal transmission line of the sensor; if the mapping objects before and after the judgment are respectively "tem_" & "hum_", or "hum_" and "tem_", the comparison indicates that the mapping objects before and after are inconsistent, and at this time, it indicates that the current mapping relationship has errors and needs to be corrected.
A third aspect of the present invention provides a computer-readable storage medium, where the computer-readable storage medium includes an industrial internet of things-based object modeling method program, where the industrial internet of things-based object modeling method program, when executed by a processor, implements the steps of an industrial internet of things-based object modeling method according to any one of the above.
According to the object modeling method, system and readable storage medium based on the industrial Internet of things, disclosed by the invention, the reusability of the industrial object model is improved by constructing the industrial object model library, the business data errors can be processed in real time, the missing business data is simulated, the business processing accuracy is improved, the business processing accuracy is combined and split with business equipment entities, and the business delivery and maintenance cost is reduced.
In the several embodiments provided in this application, it should be understood that the disclosed apparatus and method may be implemented in other ways. The above described device embodiments are only illustrative, e.g. the division of the units is only one logical function division, and there may be other divisions in practice, such as: multiple units or components may be combined or may be integrated into another system, or some features may be omitted, or not performed. In addition, the various components shown or discussed may be coupled or directly coupled or communicatively coupled to each other via some interface, whether indirectly coupled or communicatively coupled to devices or units, whether electrically, mechanically, or otherwise.
The units described above as separate components may or may not be physically separate, and components shown as units may or may not be physical units; can be located in one place or distributed to a plurality of network units; some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in each embodiment of the present invention may be integrated in one processing unit, or each unit may be separately used as one unit, or two or more units may be integrated in one unit; the integrated units may be implemented in hardware or in hardware plus software functional units.
Those of ordinary skill in the art will appreciate that: all or part of the steps for implementing the above method embodiments may be implemented by hardware related to program instructions, and the foregoing program may be stored in a computer readable storage medium, where the program, when executed, performs steps including the above method embodiments; and the aforementioned storage medium includes: a mobile storage device, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk or an optical disk, or the like, which can store program codes.
Alternatively, the above-described integrated units of the present invention may be stored in a computer-readable storage medium if implemented in the form of software functional modules and sold or used as separate products. Based on such understanding, the technical solutions of the embodiments of the present invention may be embodied in essence or a part contributing to the prior art in the form of a software product stored in a storage medium, including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the methods described in the embodiments of the present invention. And the aforementioned storage medium includes: a removable storage device, ROM, RAM, magnetic or optical disk, or other medium capable of storing program code.
Claims (10)
1. The object modeling method based on the industrial Internet of things is characterized by comprising the following steps of:
constructing a target object model based on the Internet of things, and binding physical equipment with the target object model, wherein the physical equipment comprises a sensor group, a controller and operation equipment;
collecting target data corresponding to the physical equipment, wherein the target data comprises sensing data, control data and operation data;
Resolving based on the object model and the object data, wherein,
the analysis content comprises equipment parameter mapping analysis based on the target object model and function calculation analysis based on the target data.
2. The method for modeling an object based on the industrial internet of things according to claim 1, wherein the method for building a target object model based on the internet of things and binding physical equipment with the target object model specifically comprises:
constructing the target object model based on the Internet of things, wherein the target object model at least comprises a group of equipment object models for industrial manufacturing, and the group of equipment object models for industrial manufacturing at least comprises a sensor group model, a controller model and an operation equipment model;
and based on matching the physical equipment in communication with the current Internet of things with the target object model, binding the successfully identified target object model with the corresponding physical equipment, wherein the number value of the target object model is larger than that of the physical equipment in communication with the current Internet of things.
3. The method for modeling an object based on the industrial internet of things according to claim 2, wherein the collecting the target data corresponding to the physical device specifically includes:
Acquiring acquisition data corresponding to physical equipment based on an edge gateway side, and performing protocol conversion on the acquisition data to obtain standard data;
performing equipment type discrimination based on the standard data to obtain the sensing data, the control data and the operation data;
the target data is obtained based on the sensing data, the control data, and the operation data.
4. The method for modeling an object based on the industrial internet of things according to claim 3, wherein the function calculation analysis based on the target data specifically comprises:
performing corresponding function calculation analysis on the target data based on different types, wherein,
performing alarm function calculation on the sensing data to judge whether to output alarm reminding;
performing missing function calculation on the control data to judge whether to secondarily output a corresponding control command;
and performing error function calculation on the operation data to judge whether an error exists in the operation data.
5. The method for modeling an object based on the industrial internet of things according to claim 1, wherein the performing device parameter mapping analysis based on the object model specifically comprises:
Identifying field control types of industrial manufacturing, wherein the field control types comprise centralized control types and decentralized control types;
when the centralized control type device is identified, device splitting is carried out based on the physical device, and device parameter mapping is carried out based on the split physical device and a corresponding target object model;
in the mapping process, corresponding target data are loaded for display.
6. The method for modeling an object based on industrial internet of things according to claim 5, wherein the performing device parameter mapping analysis based on the object model further comprises: and when the decentralized control type device is identified, device combination is carried out based on the physical devices, device parameter mapping is carried out based on the combined physical devices and the corresponding object models, and corresponding object data are loaded and displayed in the mapping process.
7. The object modeling system based on the industrial Internet of things is characterized by comprising a memory and a processor, wherein the memory comprises an object modeling method program based on the industrial Internet of things, and the object modeling method program based on the industrial Internet of things realizes the following steps when being executed by the processor:
Constructing a target object model based on the Internet of things, and binding physical equipment with the target object model, wherein the physical equipment comprises a sensor group, a controller and operation equipment;
collecting target data corresponding to the physical equipment, wherein the target data comprises sensing data, control data and operation data;
resolving based on the object model and the object data, wherein,
the analysis content comprises equipment parameter mapping analysis based on the target object model and function calculation analysis based on the target data.
8. The object modeling system based on the industrial internet of things of claim 7, wherein the building a target object model based on the internet of things and binding physical equipment with the target object model specifically comprises:
constructing the target object model based on the Internet of things, wherein the target object model at least comprises a group of equipment object models for industrial manufacturing, and the group of equipment object models for industrial manufacturing at least comprises a sensor group model, a controller model and an operation equipment model;
and based on matching the physical equipment in communication with the current Internet of things with the target object model, binding the successfully identified target object model with the corresponding physical equipment, wherein the number value of the target object model is larger than that of the physical equipment in communication with the current Internet of things.
9. The object modeling system based on the industrial internet of things according to claim 8, wherein the collecting the target data corresponding to the physical device specifically includes:
acquiring acquisition data corresponding to physical equipment based on an edge gateway side, and performing protocol conversion on the acquisition data to obtain standard data;
performing equipment type discrimination based on the standard data to obtain the sensing data, the control data and the operation data;
the target data is obtained based on the sensing data, the control data, and the operation data.
10. A computer readable storage medium, wherein the computer readable storage medium includes an industrial internet of things based object modeling method program, and when the industrial internet of things based object modeling method program is executed by a processor, the steps of an industrial internet of things based object modeling method according to any one of claims 1 to 6 are implemented.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310247894.3A CN116055530B (en) | 2023-03-15 | 2023-03-15 | Object modeling method, system and readable storage medium based on industrial Internet of things |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310247894.3A CN116055530B (en) | 2023-03-15 | 2023-03-15 | Object modeling method, system and readable storage medium based on industrial Internet of things |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN116055530A true CN116055530A (en) | 2023-05-02 |
| CN116055530B CN116055530B (en) | 2023-06-16 |
Family
ID=86125814
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310247894.3A Active CN116055530B (en) | 2023-03-15 | 2023-03-15 | Object modeling method, system and readable storage medium based on industrial Internet of things |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116055530B (en) |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20120330859A1 (en) * | 2011-06-27 | 2012-12-27 | International Business Machines Corporation | Interactive business process modeling and simulation |
| CN112235326A (en) * | 2020-12-15 | 2021-01-15 | 长沙树根互联技术有限公司 | Internet of things equipment data analysis method and device and electronic equipment |
| CN113138562A (en) * | 2021-06-22 | 2021-07-20 | 武汉慧联无限科技有限公司 | Terminal control system and terminal control method based on Internet of things |
| US20210280325A1 (en) * | 2020-03-05 | 2021-09-09 | International Business Machines Corporation | Decentralized network protected iot query resolution |
| CN113393936A (en) * | 2021-07-06 | 2021-09-14 | 重庆大学 | Disabled elderly health monitoring system based on end-edge-cloud architecture |
| CN114371883A (en) * | 2021-12-29 | 2022-04-19 | 天翼物联科技有限公司 | Construction method and calling system of compound model of Internet of things |
| CN114978925A (en) * | 2022-04-25 | 2022-08-30 | 北京物元数界科技有限公司 | Object model creating method and system |
| CN115002146A (en) * | 2022-03-25 | 2022-09-02 | 冶金自动化研究设计院有限公司 | Application method of object model in industrial Internet of things |
-
2023
- 2023-03-15 CN CN202310247894.3A patent/CN116055530B/en active Active
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20120330859A1 (en) * | 2011-06-27 | 2012-12-27 | International Business Machines Corporation | Interactive business process modeling and simulation |
| US20210280325A1 (en) * | 2020-03-05 | 2021-09-09 | International Business Machines Corporation | Decentralized network protected iot query resolution |
| CN112235326A (en) * | 2020-12-15 | 2021-01-15 | 长沙树根互联技术有限公司 | Internet of things equipment data analysis method and device and electronic equipment |
| CN113138562A (en) * | 2021-06-22 | 2021-07-20 | 武汉慧联无限科技有限公司 | Terminal control system and terminal control method based on Internet of things |
| CN113393936A (en) * | 2021-07-06 | 2021-09-14 | 重庆大学 | Disabled elderly health monitoring system based on end-edge-cloud architecture |
| CN114371883A (en) * | 2021-12-29 | 2022-04-19 | 天翼物联科技有限公司 | Construction method and calling system of compound model of Internet of things |
| CN115002146A (en) * | 2022-03-25 | 2022-09-02 | 冶金自动化研究设计院有限公司 | Application method of object model in industrial Internet of things |
| CN114978925A (en) * | 2022-04-25 | 2022-08-30 | 北京物元数界科技有限公司 | Object model creating method and system |
Non-Patent Citations (3)
| Title |
|---|
| LEIJI ZHU: "Design and Experiment of Smart Fire Electric Power Monitoring System Based on the Cyber-Physical Model", 《2021 IEEE 2ND INTERNATIONAL CONFERENCE ON INFORMATION TECHNOLOGY, BIG DATA AND ARTIFICIAL INTELLIGENCE (ICIBA)》 * |
| 万璐;杜明伟;王雪姣;王森;王林;梁皓;张立祯;李召虎;: "物联网与作物模型在智慧棉花系统中的应用与展望", 中国棉花, no. 08 * |
| 徐超;林友勇;李少利;: "物联数据建模分析框架探讨", 智能物联技术, no. 03 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN116055530B (en) | 2023-06-16 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109587125B (en) | Network security big data analysis method, system and related device | |
| CN115063118B (en) | Intelligent workshop equipment management method and system based on industrial Internet | |
| CN113032868A (en) | Prefabricated part management method and device, electronic equipment and storage medium | |
| CN109389326B (en) | Monitoring event-oriented object modeling method, device and system | |
| CN115330887B (en) | Automatic test system and test method for intelligent substation protection device | |
| CN113410813A (en) | Digital twin distribution network fault-based diagnosis method and related device | |
| CN115661553A (en) | BIM-based rail transit member classification method, system and equipment | |
| CN115328068A (en) | Digital twinning system applied to industrial production | |
| CN107944005B (en) | Data display method and device | |
| CN110609864B (en) | Chemical supply chain-oriented data visualization management method and device | |
| CN115269438A (en) | Automatic testing method and device for image processing algorithm | |
| CN116055530B (en) | Object modeling method, system and readable storage medium based on industrial Internet of things | |
| CN113434425A (en) | Measurement and control system capable of being rapidly developed and measurement and control system billboard | |
| CN108090234A (en) | A kind of information network method for auto constructing of software-oriented defect | |
| CN117110794A (en) | Intelligent diagnosis system and method for cable faults | |
| CN116383742A (en) | Rule chain setting processing method, system and medium based on feature classification | |
| CN111047731A (en) | AR technology-based telecommunication room inspection method and system | |
| CN114241401A (en) | Abnormality determination method, apparatus, device, medium, and product | |
| CN113673797A (en) | Production monitoring method and device and computer readable storage medium | |
| CN113076355A (en) | Method for sensing data security flow situation | |
| CN111859058A (en) | Method and device for acquiring environmental data, storage medium and electronic device | |
| CN116880365B (en) | Method, system and readable storage medium for monitoring equipment production process | |
| CN106998559B (en) | Cell detection method and device | |
| CN116993297B (en) | Task data generation method and system based on electronic conference record | |
| CN112199418B (en) | State identification method, device and equipment for industrial object |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| CB02 | Change of applicant information |
Address after: Room 402, Building 8, Xinyi Lingyu R&D Center, No. 26 Honglang North 2nd Road, Xingdong Community, Xin'an Street, Bao'an District, Shenzhen City, Guangdong Province, 518101 Applicant after: Shenzhen pfiter Information Technology Co.,Ltd. Address before: 518101 1901, Building 1, COFCO Chuangxin R&D Center, 69 District, Xingdong Community, Xin'an Street, Bao'an District, Shenzhen, Guangdong Applicant before: Shenzhen pfiter Information Technology Co.,Ltd. |
|
| CB02 | Change of applicant information | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |