CN114742600B - Content analysis method based on industrial internet and computer storage medium - Google Patents
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Abstract
A content analysis method and computer storage medium based on industrial Internet relates to the technical field of industrial Internet, the method comprises: acquiring product model data, order data, material data and process data of a target product; establishing sub-information models corresponding to product model data, order data, material data and process data of a target product; performing data clustering processing and data association processing on sub information models corresponding to product model data, order data, material data and process data of a target product respectively to generate a digital object model; receiving a content analysis request which is sent by terminal equipment and points to a target drawing file corresponding to a target product; acquiring a content analysis result corresponding to the content analysis request from the digital object model; and returning the content analysis result to the terminal equipment. The scheme provided by the application can better meet the requirement that a user knows the information of other aspects of the product except the structural information.
Description
Technical Field
The present invention relates to the field of industrial internet technologies, and in particular, to a content parsing method and a computer storage medium based on an industrial internet.
Background
At present, various drawing software such as CAD (computer aided design) and the like are often applied to drawing of product drawings, generally, only structural information of a product can be known through a drawing file drawn by the drawing software, and information of other aspects of the product is difficult to obtain, so that the requirement of a user for knowing the information of the other aspects of the product cannot be met.
Disclosure of Invention
The embodiment of the application provides a content analysis method based on an industrial internet and a computer storage medium, so as to solve the technical problems.
According to a first aspect of embodiments of the present application, there is provided an industrial internet-based content parsing method, including:
acquiring product model data, order data, material data and process data of a target product;
establishing sub-information models corresponding to the product model data, the order data, the material data and the process data of the target product;
performing data clustering processing and data association processing on sub information models corresponding to the product model data, the order data, the material data and the process data of the target product respectively to generate a digital object model;
receiving a content analysis request which is sent by first terminal equipment and points to a target drawing file corresponding to the target product;
acquiring a content analysis result corresponding to the content analysis request from the digital object model;
and returning the content analysis result obtained from the digital object model to the first terminal equipment.
In an optional example, the obtaining product model data, order data, material data and process data of the target product includes:
sending design requirement information for the target product to a second terminal device associated with the first predetermined object;
receiving a target drawing file returned by the second terminal device based on the design requirement information;
determining product model data of the target product based on the target drawing file;
acquiring order data of the target product;
determining a product quantity of the target product based on the order data of the target product;
and determining material data of the target product based on the product model data and the product quantity of the target product.
In an optional example, the management node stores digital description information of the target product corresponding to each of a plurality of product stages obtained from the digital object model, wherein different product stages in the plurality of product stages correspond to different query ports;
the method further comprises the following steps:
receiving a call request which is forwarded by the edge side semantic processing device and is used for a query port corresponding to a target product stage in the plurality of product stages;
acquiring at least part of information in the target digital description information corresponding to the target product stage from the management node based on the calling request;
and sending at least part of information in the target digital description information to the edge side semantic processing device, so that the edge side semantic processing device returns at least part of information in the target digital description information to the initiator of the call request.
In an optional example, the content parsing request includes a user identifier and a target identifier, where the target identifier is an industrial internet identifier bound to the target drawing file, or an industrial internet of things identifier corresponding to the target drawing file;
after receiving the content analysis request which is sent by the first terminal device and points to the target drawing file corresponding to the target product, the method further includes:
judging whether the content analysis request is legal or not based on the user identification and the target identification;
if the judgment result is yes, agreeing to the content analysis request, and executing the step of obtaining a content analysis result corresponding to the content analysis request from the digital object model;
and if the judgment result is negative, rejecting the content analysis request.
In an optional example, the content analysis request includes a target identifier, where the target identifier is an industrial internet identifier bound to the target drawing file, or an industrial internet of things identifier corresponding to the target drawing file;
after receiving the content analysis request which is sent by the first terminal device and points to the target drawing file corresponding to the target product, the method further includes:
judging whether the designated area stores a content analysis result corresponding to the target identifier;
if the judgment result is yes, acquiring a content analysis result stored corresponding to the target identifier from the designated area, and returning the content analysis result acquired from the designated area to the first terminal equipment;
and if the judgment result is negative, executing the step of obtaining the content analysis result corresponding to the content analysis request from the digital object model, and storing the content analysis result obtained from the digital object model in the appointed area corresponding to the target identification.
In an optional example, before the creating a sub information model corresponding to each of the product model data, the order data, the material data, and the process data of the target product, the method further includes:
acquiring a preset value interval corresponding to the parameter type of a target parameter value in target data; wherein the target data is any one of the following four: product model data, order data, material data and process data of the target product;
if the target parameter value is outside the preset value interval, determining a target value which is closer to the target parameter value in the maximum value and the minimum value of the preset value interval;
comparing the target parameter value with the target value to obtain a comparison result;
and acquiring a correctness checking result of the target data based on the comparison result.
In an optional example, the comparison result includes a ratio of a target difference to the target value, where the target difference is an absolute value of a difference between the target parameter value and the target value;
the obtaining a correctness checking result of the target data based on the comparison result includes:
if the ratio is smaller than or equal to a preset ratio, acquiring a correctness checking result of the target data based on parameter values in the target data except the target parameter value;
if the ratio is larger than the preset ratio, sending a correction request aiming at the target parameter value to third terminal equipment associated with a second preset object, after receiving update data returned by the third terminal equipment in response to the correction request, acquiring the updated target parameter value based on the update data, and acquiring a correctness checking result of the target data based on parameter values in the target data except the target parameter value and the updated target parameter value.
In one optional example, the method further comprises:
acquiring historical reading condition data of an object associated with the first terminal device;
determining reading habit information based on the historical reading condition data;
the returning of the content analysis result obtained from the digital object model to the first terminal device includes:
adjusting the arrangement sequence of a plurality of digital description information in the content analysis result obtained from the digital object model according to the reading habit information;
and returning the content analysis result obtained after the arrangement sequence of the plurality of digital description information is adjusted to the first terminal equipment.
According to a second aspect of embodiments of the present application, there is provided a computer storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of the method according to the first aspect as described above.
According to a third aspect of embodiments of the present application, there is provided an electronic device comprising one or more processors, and memory for storing one or more programs; the one or more programs, when executed by the one or more processors, implement the method as described in the first aspect above.
In the scheme provided by the embodiment of the application, sub-information models corresponding to product model data, order data, material data and process data of the target product can be established, and the digital object model is generated by performing data clustering processing and data association processing on the sub-information models corresponding to the product model data, the order data, the material data and the process data of the target product. Therefore, when a user initiates a content analysis request pointing to a target drawing file corresponding to a target product through the first terminal device, a content analysis result corresponding to the content analysis request can be returned to the first terminal device based on the digital object model, and the user can know information of the target product in multiple dimensions by looking up the content analysis result, so that the user can better meet the requirement of knowing information of other aspects of the product except structure information.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the application and together with the description serve to explain the application and not to limit the application. In the drawings:
fig. 1 shows one of the flow diagrams of the industrial internet-based content parsing method provided in the embodiment of the present application;
FIG. 2 illustrates a logical framework diagram of an industrial Internet identity resolution system;
FIG. 3 is a second flow chart of the content parsing method based on industrial Internet provided in the embodiment of the present application;
FIG. 4 is a schematic diagram illustrating the creation of a digital model of an object in an embodiment of the present application;
fig. 5 is a third flowchart illustrating an industrial internet-based content parsing method provided in an embodiment of the present application;
FIG. 6 is a fourth flowchart illustrating an industrial Internet-based content parsing method provided in an embodiment of the present application;
fig. 7 shows a schematic structural diagram of an electronic device provided in an embodiment of the present application.
Detailed Description
Referring to fig. 1, a flowchart of a content parsing method based on the industrial internet according to an embodiment of the present application is shown. As shown in fig. 1, the method includes step 110, step 120, step 130, step 140, step 150, and step 160.
It should be noted that the target product may be any type of product used in industry, and the "target" in the target product does not constitute any limitation on the target product.
It should be noted that a first database for storing product data may be preset, and the product data may include data related to the full life cycle of the product.
In step 110, product model data, order data, material data and process data of the target product can be obtained from the first database; wherein the product model data may include data related to a product model (e.g., a product CAD model) of the target product, including but not limited to size data, model data, etc. of the product model, as drawn using the drawing software; order data includes, but is not limited to, order quantity, order receipt time, etc.; the material data includes but is not limited to material type, material amount, blanking time and the like; the process data includes, but is not limited to, process flow diagrams, the length of time each process involved in the process flow diagrams takes, process parameters of each process involved in the process flow diagrams, and the like.
Alternatively, product model data may be provided by a product designer of an enterprise (which is subsequently referred to as a target enterprise) and uploaded to the first database for storage; order data can be provided by a production planner of the target enterprise and uploaded to a first database for storage; the material data can be provided by a material supplier of the target enterprise and uploaded to the first database for storage.
And step 120, establishing sub information models corresponding to the product model data, the order data, the material data and the process data of the target product.
In step 120, sub-information models corresponding to the product model data, the order data, the material data and the process data of the target product are established based on OPC UA to obtain four sub-information models; wherein, the English name of OPC is OLE for Process Control, the Chinese meaning of OPC is used for object connection and embedding of Process Control, and the object connection and embedding can be understood as interface; the English name of UA is Unified architecture, and the Chinese meaning of UA is Unified architecture.
It should be noted that the sub-information model corresponding to the product model data may include the relevant storage logic architecture and information of the target product in the product model dimension; the sub-information model corresponding to the order data can comprise related storage logic architecture and information of the target product in order dimensions; the sub-information model corresponding to the material data can comprise related storage logic architecture and information of the target product in the material dimension; the sub-information model corresponding to the process data can include the relevant storage logic architecture and information of the target product in the process dimension.
And step 130, performing data clustering processing and data association processing on the sub-information models corresponding to the product model data, the order data, the material data and the process data of the target product respectively to generate a digital object model.
In step 130, the data clustering of the four sub-information models obtained in step 120 may be performed through a data clustering algorithm, each sub-information model has a unique ID (Identity document, Identity identification number) assigned to the identification resolution system, for example, a unique ID assigned by an identification assignment management system in an industrial internet identification resolution system (the logical framework of which can refer to fig. 2 specifically), functions contained in related product model data, order data and the like are all given to secondary IDs by virtue of query and association capability of the identification resolution system, if the rotating speed matching function of the controller in the process data is ID1, the controller power in the rotating speed matching function is ID11, the controller rotating speed is ID12, and further associating data with a flow series relation in the four sub-information models through ID association of the identification analysis system, thereby constructing a complete digital object model.
It should be noted that, the digital object model may include a large amount of digital description information, for example, digital description information of each of a product model dimension, an order dimension, a material dimension, and a process dimension; the digital description information can be understood as data information in the digital world converted from physical information of a target product in the real world.
Optionally, the first terminal device may be a fixed terminal device such as a desktop computer, or may also be a mobile terminal device such as a mobile phone and a tablet computer.
Optionally, the content analysis request may include an industrial internet identifier bound to the target drawing file, or an industrial internet of things identifier corresponding to the target drawing file, so as to represent that the content analysis request points to the target drawing file corresponding to the target product.
Optionally, the industrial internet identifier bound to the target drawing file may be an industrial internet identifier distributed to the target product by the first distribution management system, and the first distribution management system may be an identifier distribution management system in an industrial internet identifier resolution system; the industrial internet of things identifier corresponding to the target drawing file can be an industrial internet of things identifier distributed to the target product by the second distribution management system.
In step 150, the digitized description information of the product model dimension, the order dimension, the material dimension, and the process dimension may be extracted from the digital object model through ID query, and the content parsing result is composed of the extracted digitized description information.
Optionally, the first terminal device may display the content parsing result through its own display screen.
In the embodiment of the application, sub-information models corresponding to product model data, order data, material data and process data of the target product can be established, and the digital object model is generated by performing data clustering processing and data association processing on the sub-information models corresponding to the product model data, the order data, the material data and the process data of the target product. Therefore, when a user initiates a content analysis request pointing to a target drawing file corresponding to a target product through the first terminal device, a content analysis result corresponding to the content analysis request can be returned to the first terminal device based on the digital object model, and the user can know the information of the target product in multiple dimensions by looking up the content analysis result, so that the requirement of the user for knowing the information of other aspects of the product except the structural information can be well met.
In an alternative example, as shown in fig. 3, step 110 includes step 1101, step 1102, step 1103, step 1104, step 1105, and step 1106.
Optionally, the first predetermined object may be a product designer of a target enterprise, the second terminal device associated with the first predetermined object may be a terminal device used by the product designer, and the second terminal device may be a fixed terminal device or a mobile terminal device.
Alternatively, the target product may be an automobile, and the design requirement information for the target product may include a maximum load capacity requirement of the automobile, a wheel base requirement of the automobile, and the like.
Optionally, the target drawing file returned by the second terminal device may be: and designing the product by a product designer according to the design requirement information, and drawing the drawing by using drawing software to obtain a drawing file.
In step 1103, product model data for the target product may be determined by mapping and analyzing the target drawing file.
In step 1104, order data for the target product is obtained.
In step 1105, the product quantity of the target product may be determined based on the order quantity in the order data of the target product, for example, the order quantity may be directly determined as the product quantity of the target product, or the sum of the order quantity and a certain preset quantity may be set as the product quantity of the target product.
And step 1106, determining material data of the target product based on the product model data and the product quantity of the target product.
In step 1106, the material type and the material amount required for manufacturing a single target product may be estimated based on the product model data of the target product, and the total material amount required for the product amount determined in step 1105 may be further estimated, so as to determine the material data including the material type and the total material amount.
In the embodiment of the application, the design requirement information of the target product can be provided for the first predetermined object, so that the first predetermined object draws the target drawing file according to the design requirement information, the product model data of the target product can be determined based on the target drawing file, and the material data of the target product can be efficiently and reliably determined by combining the product quantity determined by the order data of the target product, so that the subsequent model building step can be executed based on the product model data, the order data and the material data.
In one optional example, the management node stores digitized descriptive information obtained from the digital object model for the target product corresponding to each of a plurality of product phases, different ones of the plurality of product phases corresponding to different ones of the query ports.
Alternatively, the management node may be a management server.
Optionally, the multiple product phases include, but are not limited to, a research and development design phase, a production planning phase, a material supply phase and a manufacturing phase shown in fig. 4, and a production control phase; the digital description information of the research and development design stage can comprise digital description information of product model dimensions in a digital object model; the digital description information of the production planning stage can comprise digital description information of order dimensions in the digital object model; the digital description information of the material supply stage can comprise digital description information of material dimensions in the digital object model; the digital description of the manufacturing stage may include digital description of the process dimensions in the digital object model.
As shown in fig. 5, the method further includes step 170, step 180, and step 190.
It should be noted that the edge side semantic processing device may be a device for providing a plurality of query ports corresponding to a plurality of product phases one to one, and the edge side semantic processing device may forward the received call request in a case of receiving a call request corresponding to the target query request.
It should be noted that the target product stage may be any one of a plurality of product stages, and the "target" in the target product stage does not constitute any limitation on the target product stage.
And step 180, acquiring at least part of information in the target digital description information corresponding to the target product stage from the management node based on the calling request.
In step 180, by analyzing the received invocation request, it may be determined what information of the target product phase is required by the requester of the invocation request, and accordingly, the information may be obtained from the management node, where the information may include all information in the target digital description information corresponding to the target product phase, or may include only part of information in the target digital description information corresponding to the target product phase, that is, the edge-side semantic processing apparatus may provide query functions with different granularities.
In step 190, at least a part of the target digital description information may be provided to the initiator of the call request through a forwarding operation of the edge side semantic processing device.
In the embodiment of the application, based on the digital object model, the digital description information of the target product corresponding to each stage can be stored in the management node, and the edge side semantic processing device can provide the query port, so that a user can query the digital description information of the target product corresponding to the corresponding product stage by initiating a call request to the edge side semantic processing device according to actual needs, and the edge side semantic processing device can provide query functions with different granularities.
In an optional example, the content analysis request includes a user identifier and a target identifier, and the target identifier is an industrial internet identifier bound to the target drawing file or an industrial internet of things identifier corresponding to the target drawing file;
after receiving a content analysis request which is sent by the terminal device and points to a target drawing file corresponding to a target product, the method further comprises the following steps:
judging whether the content analysis request is legal or not based on the user identifier and the target identifier;
if yes, agreeing to the content analysis request, and executing a step of obtaining a content analysis result corresponding to the content analysis request from the digital object model;
and if the judgment result is negative, rejecting the content analysis request.
Alternatively, the user identification may be a user name or a user number.
It should be noted that, correspondence between multiple products and multiple access white lists may be preset, each product in the correspondence may be characterized by an industrial internet identifier or an industrial internet of things identifier of the product, and each access white list in the correspondence may include a plurality of user identifiers.
After receiving the content parsing request sent by the first terminal device, the user identifier and the target identifier may be extracted from the content parsing request, and whether the content parsing request is legal or not may be determined based on the user identifier and the target identifier extracted from the content parsing request. Alternatively, an access white list corresponding to the target identifier extracted from the content parsing request may be determined based on a preset correspondence, and it may be determined whether the user identifier extracted from the content parsing request is located in the determined access white list, and if so, it may be determined that the content parsing request is legal, and if not, it may be determined that the content parsing request is illegal.
Of course, the manner of determining whether the content analysis request is legal is not limited to this, for example, the content analysis request may be determined to be legal if the user identifier extracted from the content analysis request is located in the determined access white list and the user with the user identifier is an employee of the target enterprise, otherwise the content analysis request is determined to be illegal.
In the embodiment of the application, the user identification and the target identification in the content analysis request of the target drawing file can be referred to, the legality of the content analysis request is verified, and a corresponding content analysis result is provided for an initiator of the content analysis request only under the condition that the content analysis request is legal, so that information leakage caused by response to the content analysis request initiated by an illegal user can be avoided.
In an optional example, the content analysis request includes a target identifier, where the target identifier is an industrial internet identifier bound to the target drawing file, or an industrial internet identifier corresponding to the target drawing file;
after receiving a content analysis request which is sent by the terminal device and points to a target drawing file corresponding to a target product, the method further comprises the following steps:
judging whether the designated area stores a content analysis result corresponding to the target identifier;
if the judgment result is yes, acquiring a content analysis result stored corresponding to the target identifier from the designated area, and returning the content analysis result acquired from the designated area to the first terminal equipment;
if the judgment result is negative, the step of obtaining the content analysis result corresponding to the content analysis request from the digital object model is executed, and the content analysis result obtained from the digital object model is stored in the designated area corresponding to the target identification.
It should be noted that the designated area may be a preset area for storing the content parsing request, and optionally, the designated area may be a power-down non-lost storage area.
In the embodiment of the application, after the content analysis request is received, whether the designated area stores the content analysis result corresponding to the target identifier or not can be judged. If the judgment result is negative, the received content analysis request can be considered as the first content analysis request pointing to the target drawing file, then the content analysis result corresponding to the content analysis request can be obtained from the digital object model, the content analysis result obtained from the digital object model is returned to the first terminal device, and the content analysis result obtained from the digital object model is stored in the designated area corresponding to the target identification. If the judgment result is yes, the received content analysis request can be considered to be a non-first content analysis request pointing to the target drawing file, and the content analysis result for the first content analysis request pointing to the target drawing file is stored in the designated area, so that the content analysis result stored in the designated area can be directly returned to the first terminal device without obtaining information from the digital object model again, and the content analysis result required by the user can be provided for the user relatively quickly.
In an alternative example, as shown in fig. 6, before step 120, the method further includes step 111, step 112, step 113, and step 114.
Optionally, the target parameter value is a temperature value (unit may be celsius), and then the parameter type of the target parameter value is a temperature type; the target parameter value is a power value (which may be in watts), and the parameter type of the target parameter value is a power type.
It should be noted that, the corresponding relationship between the parameter type and the preset value interval may be preset, wherein the preset value interval corresponding to the temperature type may be-50 to 100; the preset value interval corresponding to the power type may be 0 to 2000. In this way, in step 111, according to the preset corresponding relationship, the preset value interval corresponding to the parameter type of the target parameter value can be very conveniently determined.
In step 112, if the target parameter value is outside the preset value interval, a target value closer to the target parameter value in the maximum value and the minimum value of the preset value interval is determined.
In step 112, the target parameter value may be compared with the preset value interval to determine a value closer to the target parameter value from the maximum value and the minimum value of the preset value interval, and the value may be used as the target value. For example, the target parameter value is a temperature value, the temperature value is 110, and the preset value interval corresponding to the temperature type is-50 to 100, then 100 can be taken as the target value because 100 is closer to-50 and 110.
And 113, comparing the target parameter value with the target value to obtain a comparison result.
In step 113, a difference between the target parameter value and the target value may be calculated, and a comparison result between the target parameter value and the target value may be determined based on the difference between the target parameter value and the target value.
And step 114, acquiring a correctness checking result of the target data based on the comparison result.
In a specific embodiment, the comparison result includes a ratio of a target difference to a target value, where the target difference is an absolute value of a difference between the target parameter value and the target value;
based on the comparison result, obtaining a correctness checking result of the target data, which comprises the following steps:
if the ratio is smaller than or equal to the preset ratio, acquiring a correctness checking result of the target data based on the parameter values except the target parameter value in the target data;
if the ratio is larger than the preset ratio, sending a correction request aiming at the target parameter value to third terminal equipment associated with the second preset object, after receiving update data returned by the third terminal equipment in response to the correction request, acquiring the updated target parameter value based on the update data, and acquiring a correctness checking result of the target data based on the parameter values except the target parameter value in the target data and the updated target parameter value.
Alternatively, the predetermined ratio may be 10%, 12%, 15% or other values, which are not listed here.
Optionally, the target data is product model data of the target product, and the second predetermined object may be a product designer of the target enterprise; the target data is order data of the target product, and the second predetermined object can be a production planner of the target enterprise; the target data is material data of a target product, and the second predetermined object can be a material supplier of a target enterprise; the target data is process data of the target product, and the second predetermined object may be a process designer of the target enterprise. The third terminal device associated with the second predetermined object may be a terminal device used by the second predetermined object, and the third terminal device may be a fixed terminal device or a mobile terminal device.
If the ratio is smaller than or equal to the preset ratio, it can be considered that the target parameter value does not exceed the preset value interval corresponding to the parameter type of the target parameter value much, and at this time, the parameter values except the target parameter value in the target data can be referred to obtain the correctness checking result of the target data. Optionally, if the remaining parameter values in the target data are respectively located in the corresponding preset value intervals, it may be determined that the correctness verification of the target data passes; if the parameter values exceeding a certain proportion in the rest parameter values in the target data are respectively positioned outside the corresponding preset value interval, the correctness verification of the target data can be determined not to pass.
If the ratio is greater than the preset ratio, it can be considered that the target parameter value exceeds the preset value interval corresponding to the parameter type of the target parameter value more, a correction request for the target parameter value can be sent to the third terminal device, the correction request is referred to, the second predetermined object can know that the target parameter value is incorrect and needs to be corrected, in response to the correction request, update data can be returned through the third terminal device, the update data can include a new target parameter value, then, the new target parameter value can be used for replacing the previous target parameter value, so as to obtain an updated target parameter value, and a correctness checking result of the target data is obtained based on the parameter value except the target parameter value in the target data and the updated target parameter value. Optionally, if the parameter values of the target data except the target parameter value and the updated target parameter value are respectively located in the corresponding preset value interval, it may be determined that the correctness of the target data is verified; otherwise, it may be determined that the correctness check of the target data fails.
In this embodiment, the accuracy check result of the target data may be obtained in a suitable manner by referring to the degree that the target parameter value exceeds the preset value interval corresponding to the parameter type of the target parameter value.
It should be noted that, the manner of obtaining the correctness checking result of the target data based on the comparison result is not limited to this, for example, the comparison result may only include the target difference, if the target difference is smaller than or equal to a preset value, the correctness checking result of the target data may be obtained based on the parameter values of the target data except the target parameter value, and if the target difference is larger than the preset value, the second predetermined object may be caused to provide the updated data by sending the modification request, so as to obtain the updated target parameter value by using the updated data, and obtain the correctness checking result of the target data based on the parameter values of the target data except the target parameter value and the updated target parameter value.
In the embodiment of the application, before the sub-information model is established, the correctness check result of the target data can be obtained by referring to the degree that the value of the target parameter exceeds the preset value interval corresponding to the parameter type of the target parameter, so that the sub-information model is established by referring to the correct data, the correctness of the information in the sub-information model can be well ensured, and the correctness of the information in the digital object model obtained based on the sub-information model is ensured.
In one optional example, the method further comprises:
acquiring historical reading condition data of an object associated with a first terminal device;
determining reading habit information based on historical reading condition data;
returning the content analysis result obtained from the digital object model to the first terminal equipment, comprising:
adjusting the arrangement sequence of a plurality of digital description information in the content analysis result obtained from the digital object model according to the reading habit information;
and returning the content analysis result obtained after the arrangement sequence of the plurality of digital description information is adjusted to the first terminal equipment.
Alternatively, the object associated with the first terminal device may be an object using the first terminal device.
It should be noted that a second database for storing historical reading request data may be preset, so that historical reading condition data of the object associated with the first terminal device may be obtained from the second database, where the historical reading condition data includes, but is not limited to, a reading start time, a reading end time, a reading duration, a typesetting manner selected during reading, and the like. In this way, by analyzing the historical reading condition data, reading habit information can be determined, and the reading habit information is used for representing habits of the object associated with the first terminal device when reading information.
Then, the order of the plurality of pieces of digital description information in the content analysis result obtained from the digital object model may be adjusted according to the reading habit information, for example, if the reading habit information represents that the object habit associated with the first terminal device reads the information of the order dimension first, then reads the information of the product model dimension, then reads the information of the process dimension, and finally reads the information of the material dimension, the order of the plurality of pieces of digital description information in the content analysis result may be adjusted, so that the plurality of pieces of digital description information are arranged in the following order: digital description information of order dimension → digital description information of product model dimension → digital description information of process dimension → digital description information of material dimension. Then, the content parsing result obtained by adjusting the arrangement order of the included plurality of pieces of digital description information may be returned to the first terminal device, so that the object associated with the first terminal device refers to the content parsing request.
In the embodiment of the application, before the content analysis result is returned to the first terminal device, the arrangement sequence of the plurality of pieces of digital description information in the content analysis result is adjusted according to the reading habit information of the object associated with the first terminal device, so that the information arrangement sequence in the content analysis result presented to the user can be ensured to be consistent with the reading habit of the user, and the reading experience of the user is ensured.
In an alternative example, as shown in fig. 4, the product model data, the order data, the material data, and the process data of the target product may be obtained, and the obtained product model data, order data, material data, and process data may be used for building the digital object model, so as to implement coordination of different businesses of research and development, production, management, and the like in the target enterprise. In this way, the digital object model may include product model data a, order data b, material data c, and process data d, and information in the product model data a, the order data b, the material data c, and the process data d is digital description information, that is, the digital object model may include digital description information of each stage from research, development, design to production management and control of the target product.
Optionally, the digital description information in the digital object model may be stored in a plurality of industrial software systems inside the target enterprise to implement data integration across systems, so that the digital description information of the order, design, material, production, and the like corresponding to the target drawing file may be obtained from the enterprise side to help the user to know information between the product and the finished product from the order.
Alternatively, the management node may store the digital description information in the digital object model, and build a retrieval directory for the digital description information, and provide a query port for a user to query through the edge side semantic processing device. When the retrieval catalog is established, the industrial internet of things identification can be set for the target product, the digital description information corresponding to all processes from research, development, design to production management and control of the target product is sequenced according to the time sequence relation, and a query port of each process is provided.
Optionally, edge-side semantic processing means may be used for semantic conversion mapping to achieve an understanding of domain-specific data within the target enterprise.
In summary, in the embodiment of the present application, a user can know information of a target product in multiple dimensions by referring to a content analysis result corresponding to a content analysis request, so that a requirement of the user for knowing information of other aspects of the product except for structural information can be better met.
Based on the same inventive concept, an embodiment of the present application provides a computer storage medium, where a computer program is stored on the computer storage medium, and when the computer program is executed by a processor, the computer program implements the following steps:
acquiring product model data, order data, material data and process data of a target product;
establishing sub-information models corresponding to product model data, order data, material data and process data of a target product;
performing data clustering processing and data association processing on sub information models corresponding to product model data, order data, material data and process data of a target product respectively to generate a digital object model;
receiving a content analysis request which is sent by first terminal equipment and points to a target drawing file corresponding to a target product;
acquiring a content analysis result corresponding to the content analysis request from the digital object model;
and returning the content analysis result obtained from the digital object model to the first terminal equipment.
In an alternative example, the computer program when executed by the processor embodies the steps of:
sending design requirement information for the target product to a second terminal device associated with the first predetermined object;
receiving a target drawing file returned by the second terminal device based on the design requirement information;
determining product model data of a target product based on a target drawing file;
acquiring order data of a target product;
determining a product quantity of the target product based on the order data of the target product;
and determining material data of the target product based on the product model data and the product quantity of the target product.
In an optional example, the management node stores digital description information of a target product corresponding to each of a plurality of product stages obtained from the digital object model, wherein different product stages in the plurality of product stages correspond to different query ports;
the computer program when executed by the processor further implements the steps of:
receiving a call request which is forwarded by a semantic processing device at an edge side and is used for a query port corresponding to a target product stage in a plurality of product stages;
based on the calling request, acquiring at least part of information in the target digital description information corresponding to the target product stage from the management node;
and sending at least part of information in the target digital description information to the edge side semantic processing device so that the edge side semantic processing device returns at least part of information in the target digital description information to the initiator of the call request.
In an optional example, the content analysis request includes a user identifier and a target identifier, and the target identifier is an industrial internet identifier bound to the target drawing file or an industrial internet of things identifier corresponding to the target drawing file;
the computer program when executed by the processor further implements the steps of:
after receiving a content analysis request which is sent by first terminal equipment and points to a target drawing file corresponding to a target product, judging whether the content analysis request is legal or not based on a user identifier and a target identifier;
if the judgment result is yes, agreeing to the content analysis request, and executing the step of obtaining the content analysis result corresponding to the content analysis request from the digital object model;
and if the judgment result is negative, rejecting the content analysis request.
In an optional example, the content analysis request includes a target identifier, where the target identifier is an industrial internet identifier bound to the target drawing file, or an industrial internet of things identifier corresponding to the target drawing file;
the computer program when executed by the processor further implements the steps of:
after receiving a content analysis request which is sent by first terminal equipment and points to a target drawing file corresponding to a target product, judging whether a designated area stores a content analysis result corresponding to a target identifier;
if the judgment result is yes, acquiring a content analysis result stored corresponding to the target identifier from the designated area, and returning the content analysis result acquired from the designated area to the first terminal equipment;
if the judgment result is negative, the step of obtaining the content analysis result corresponding to the content analysis request from the digital object model is executed, and the content analysis result obtained from the digital object model is stored in the designated area corresponding to the target identification.
In an alternative example, the computer program when executed by the processor further implements the steps of:
before sub-information models corresponding to product model data, order data, material data and process data of a target product are established, a preset value interval corresponding to a parameter type of a target parameter value in the target data is obtained; wherein the target data is any one of the following four: product model data, order data, material data and process data of the target product;
if the target parameter value is outside the preset value interval, determining a target value which is closer to the target parameter value in the maximum value and the minimum value of the preset value interval;
comparing the target parameter value with the target value to obtain a comparison result;
and acquiring a correctness checking result of the target data based on the comparison result.
In an optional example, the comparison result includes a ratio of a target difference to a target value, where the target difference is an absolute value of a difference between the target parameter value and the target value;
the computer program when executed by a processor embodies the steps of:
if the ratio is smaller than or equal to the preset ratio, acquiring a correctness checking result of the target data based on the parameter values except the target parameter value in the target data;
if the ratio is larger than the preset ratio, sending a correction request aiming at the target parameter value to third terminal equipment associated with the second preset object, after receiving update data returned by the third terminal equipment in response to the correction request, acquiring the updated target parameter value based on the update data, and acquiring a correctness checking result of the target data based on the parameter values except the target parameter value in the target data and the updated target parameter value.
In one alternative example of this, the user may,
the computer program when executed by the processor further implements the steps of:
acquiring historical reading condition data of an object associated with a first terminal device;
determining reading habit information based on historical reading condition data;
the computer program when executed by a processor embodies the steps of:
adjusting the arrangement sequence of a plurality of digital description information in the content analysis result obtained from the digital object model according to the reading habit information;
and returning the content analysis result obtained after the arrangement sequence of the plurality of digital description information is adjusted to the first terminal equipment.
Based on the same inventive concept, the present embodiment provides an electronic device, referring to fig. 7, including a memory 701, a processor 702, a bus 703 and a computer program stored on the memory 701 and executable on the processor 702, where the processor 702 implements the following steps when executing the computer program:
acquiring product model data, order data, material data and process data of a target product;
establishing sub-information models corresponding to product model data, order data, material data and process data of a target product;
performing data clustering processing and data association processing on sub information models corresponding to product model data, order data, material data and process data of a target product respectively to generate a digital object model;
receiving a content analysis request which is sent by first terminal equipment and points to a target drawing file corresponding to a target product;
acquiring a content analysis result corresponding to the content analysis request from the digital object model;
and returning the content analysis result obtained from the digital object model to the first terminal equipment.
In an alternative example, the processor 702, when executing the computer program, implements the steps of:
sending design requirement information for the target product to a second terminal device associated with the first predetermined object;
receiving a target drawing file returned by the second terminal device based on the design requirement information;
determining product model data of a target product based on a target drawing file;
acquiring order data of a target product;
determining a product quantity of the target product based on the order data of the target product;
and determining material data of the target product based on the product model data and the product quantity of the target product.
In an optional example, the management node stores digital description information of a target product corresponding to each of a plurality of product stages obtained from the digital object model, wherein different product stages in the plurality of product stages correspond to different query ports;
the processor 702, when executing the computer program, further performs the steps of:
receiving a call request which is forwarded by the edge side semantic processing device and is used for a query port corresponding to a target product stage in the multiple product stages;
based on the calling request, acquiring at least part of information in the target digital description information corresponding to the target product stage from the management node;
and sending at least part of information in the target digital description information to the edge side semantic processing device so that the edge side semantic processing device returns at least part of information in the target digital description information to the initiator of the call request.
In an optional example, the content analysis request includes a user identifier and a target identifier, and the target identifier is an industrial internet identifier bound to the target drawing file or an industrial internet of things identifier corresponding to the target drawing file;
the processor 702, when executing the computer program, further performs the steps of:
after receiving a content analysis request which is sent by first terminal equipment and points to a target drawing file corresponding to a target product, judging whether the content analysis request is legal or not based on a user identifier and a target identifier;
if the judgment result is yes, agreeing to the content analysis request, and executing the step of obtaining the content analysis result corresponding to the content analysis request from the digital object model;
and if the judgment result is negative, rejecting the content analysis request.
In an optional example, the content analysis request includes a target identifier, where the target identifier is an industrial internet identifier bound to the target drawing file, or an industrial internet of things identifier corresponding to the target drawing file;
the processor 702, when executing the computer program, further performs the steps of:
after receiving a content analysis request which is sent by first terminal equipment and points to a target drawing file corresponding to a target product, judging whether a designated area stores a content analysis result corresponding to a target identifier;
if the judgment result is yes, acquiring a content analysis result stored corresponding to the target identifier from the designated area, and returning the content analysis result acquired from the designated area to the first terminal equipment;
if the judgment result is negative, the step of obtaining the content analysis result corresponding to the content analysis request from the digital object model is executed, and the content analysis result obtained from the digital object model is stored in the designated area corresponding to the target identification.
In an alternative example, the processor 702, when executing the computer program, further performs the steps of:
before sub-information models corresponding to product model data, order data, material data and process data of a target product are established, a preset value interval corresponding to a parameter type of a target parameter value in the target data is obtained; wherein the target data is any one of the following four: product model data, order data, material data and process data of the target product;
if the target parameter value is outside the preset value interval, determining a target value which is closer to the target parameter value in the maximum value and the minimum value of the preset value interval;
comparing the target parameter value with the target value to obtain a comparison result;
and acquiring a correctness checking result of the target data based on the comparison result.
In an optional example, the comparison result includes a ratio of a target difference to a target value, where the target difference is an absolute value of a difference between the target parameter value and the target value;
the processor 702, when executing the computer program, implements the following steps:
if the ratio is smaller than or equal to the preset ratio, acquiring a correctness checking result of the target data based on the parameter values except the target parameter value in the target data;
if the ratio is larger than the preset ratio, sending a correction request aiming at the target parameter value to third terminal equipment associated with the second preset object, after receiving update data returned by the third terminal equipment in response to the correction request, acquiring the updated target parameter value based on the update data, and acquiring a correctness checking result of the target data based on the parameter values except the target parameter value in the target data and the updated target parameter value.
In one alternative example of this, the user may,
the processor 702, when executing the computer program, further performs the steps of:
acquiring historical reading condition data of an object associated with a first terminal device;
determining reading habit information based on historical reading condition data;
the processor 702, when executing the computer program, implements the following steps:
adjusting the arrangement sequence of a plurality of digital description information in the content analysis result obtained from the digital object model according to the reading habit information;
and returning the content analysis result obtained after the arrangement sequence of the plurality of digital description information is adjusted to the first terminal equipment.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
While the preferred embodiments of the present application have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, it is intended that the appended claims be interpreted as including the preferred embodiment and all changes and modifications that fall within the scope of the present application.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present application without departing from the spirit and scope of the application. Thus, if such modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is intended to include such modifications and variations as well.
Claims (10)
1. A content parsing method based on industrial Internet is characterized by comprising the following steps:
acquiring product model data, order data, material data and process data of a target product;
establishing sub-information models corresponding to the product model data, the order data, the material data and the process data of the target product;
performing data clustering processing and data association processing on sub information models corresponding to the product model data, the order data, the material data and the process data of the target product respectively to generate a digital object model; each sub information model has a unique ID distributed by an identification analysis system, functions contained in the product model data, the order data, the material data and the process data are endowed with secondary IDs, and data with a flow series relation in the four sub information models are associated through ID association of the identification analysis system, so that the digital object model is constructed;
receiving a content analysis request which is sent by first terminal equipment and points to a target drawing file corresponding to the target product;
acquiring a content analysis result corresponding to the content analysis request from the digital object model;
and returning a content analysis result obtained from the digital object model to the first terminal equipment.
2. The method of claim 1, wherein the obtaining product model data, order data, material data, and process data for the target product comprises:
sending design requirement information for the target product to a second terminal device associated with the first predetermined object;
receiving a target drawing file returned by the second terminal device based on the design requirement information;
determining product model data of the target product based on the target drawing file;
acquiring order data of the target product;
determining a product quantity of the target product based on the order data of the target product;
and determining material data of the target product based on the product model data and the product quantity of the target product.
3. The method of claim 1, wherein a management node stores the digital description information obtained from the digital object model for each of a plurality of product phases corresponding to the target product, different ones of the plurality of product phases corresponding to different query ports;
the method further comprises the following steps:
receiving a call request which is forwarded by the edge side semantic processing device and is used for a query port corresponding to a target product stage in the plurality of product stages;
acquiring at least part of information in the target digital description information corresponding to the target product stage from the management node based on the calling request;
and sending at least part of information in the target digital description information to the edge side semantic processing device, so that the edge side semantic processing device returns at least part of information in the target digital description information to the initiator of the call request.
4. The method according to claim 1, wherein the content analysis request includes a user identifier and a target identifier, and the target identifier is an industrial internet identifier bound to the target drawing file or an industrial internet of things identifier corresponding to the target drawing file;
after receiving the content analysis request which is sent by the first terminal device and points to the target drawing file corresponding to the target product, the method further includes:
judging whether the content analysis request is legal or not based on the user identification and the target identification;
if the judgment result is yes, agreeing to the content analysis request, and executing the step of obtaining a content analysis result corresponding to the content analysis request from the digital object model;
and if the judgment result is negative, rejecting the content analysis request.
5. The method according to claim 1, wherein the content parsing request includes a target identifier, and the target identifier is an industrial internet identifier bound to the target drawing file or an industrial internet of things identifier corresponding to the target drawing file;
after receiving the content analysis request which is sent by the first terminal device and points to the target drawing file corresponding to the target product, the method further includes:
judging whether the designated area stores a content analysis result corresponding to the target identifier;
if the judgment result is yes, acquiring a content analysis result stored corresponding to the target identifier from the designated area, and returning the content analysis result acquired from the designated area to the first terminal equipment;
and if the judgment result is negative, executing the step of obtaining the content analysis result corresponding to the content analysis request from the digital object model, and storing the content analysis result obtained from the digital object model in the appointed area corresponding to the target identification.
6. The method of claim 1, wherein before establishing the sub-information model corresponding to each of the product model data, the order data, the material data, and the process data of the target product, the method further comprises:
acquiring a preset value interval corresponding to the parameter type of a target parameter value in target data; wherein the target data is any one of the following four: product model data, order data, material data and process data of the target product;
if the target parameter value is outside the preset value interval, determining a target value which is closer to the target parameter value in the maximum value and the minimum value of the preset value interval;
comparing the target parameter value with the target value to obtain a comparison result;
and acquiring a correctness checking result of the target data based on the comparison result.
7. The method of claim 6, wherein the comparison result comprises a ratio of a target difference to the target value, wherein the target difference is an absolute value of a difference between the target parameter value and the target value;
the obtaining a correctness checking result of the target data based on the comparison result includes:
if the ratio is smaller than or equal to a preset ratio, acquiring a correctness checking result of the target data based on parameter values in the target data except the target parameter value;
if the ratio is larger than the preset ratio, sending a correction request aiming at the target parameter value to third terminal equipment associated with a second preset object, after receiving update data returned by the third terminal equipment in response to the correction request, acquiring the updated target parameter value based on the update data, and acquiring a correctness checking result of the target data based on parameter values in the target data except the target parameter value and the updated target parameter value.
8. The method of claim 1, further comprising:
acquiring historical reading condition data of an object associated with the first terminal device;
determining reading habit information based on the historical reading condition data;
the returning of the content analysis result obtained from the digital object model to the first terminal device includes:
adjusting the arrangement sequence of a plurality of digital description information in the content analysis result obtained from the digital object model according to the reading habit information;
and returning the content analysis result obtained after the arrangement sequence of the plurality of digital description information is adjusted to the first terminal equipment.
9. A computer storage medium, characterized in that a computer program is stored thereon, which computer program, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 8.
10. An electronic device comprising one or more processors, and memory for storing one or more programs; the one or more programs, when executed by the one or more processors, implement the method of any of claims 1-8.
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