CN112800024A - Ontology-based assembly system knowledge base and construction method thereof - Google Patents
Ontology-based assembly system knowledge base and construction method thereof Download PDFInfo
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Abstract
The invention discloses an assembly system knowledge base based on a body and a construction method thereof, belongs to the application field of the body knowledge base, and particularly relates to an assembly system knowledge base based on the body and a construction method thereof. The method comprises the steps of extracting a concept in the assembly system field and assembly related knowledge, expressing and reasoning in the assembly body, obtaining the assembly system body which is combined with the assembly object body and the assembly characteristic body and has knowledge inquiry reasoning and updating functions, improving the sharing and reusability of the assembly system knowledge in the assembly field, and providing a foundation for subsequent knowledge decision and assembly process generation.
Description
Technical Field
The invention belongs to the application field of ontology knowledge bases, and particularly relates to a knowledge base of an assembly system and a construction method thereof.
Background
At present, precision micro-structures are widely used in various fields, and with the change of various and variable-batch research and development and production modes, the assembly of the precision micro-structures is gradually transited from manual assembly of workers to automatic assembly of an assembly system, and the assembly precision, efficiency, reliability and consistency are improved.
The assembly system contains rich knowledge information, and the knowledge information is combined with the assembly object information, so that the assembly system has important significance for assembly process decision and generation. However, the knowledge information of the current assembly system lacks semantic association, and is difficult to interact with knowledge bodies such as assembly objects, assembly actions and the like, so that good records and applications are obtained. On the other hand, the ontology is defined as 'formal specification of shared concept model', and semantic representation and knowledge reuse in a true sense can be realized. Therefore, it is necessary to integrate and sort the knowledge information of the assembly system to form an ontology-based knowledge base capable of recognizing and reasoning.
Disclosure of Invention
Aiming at the defects of the prior art, the invention aims to provide an assembly system knowledge base system construction method based on an ontology, which integrates and combs the structural function and the associated attribute parameters of an assembly system, uniformly models the assembly system, and instantiates the ontology by using a self-adaptive assembly system facing a micro fuse, so that the correctness of the method is verified, and the sharing and reusability of the assembly system in the field of assembly process are improved.
The establishment environment of the ontology model can be selectively set according to actual conditions. The ontology model related by the invention is established based on the prot g e software platform.
The invention provides a method for constructing an assembly system knowledge base system based on an ontology, which mainly comprises the steps of establishing a semantic frame and related attributes of an assembly system element and establishing and instantiating a rule base, and comprises the following specific steps:
s10, summarizing and arranging the functional structure and each attribute type concept of the assembly system;
s20, acquiring assembly element keywords based on the assembly system field concept, and establishing a related attribute and assembly system element semantic framework in the body;
s30, merging the assembly object ontology base and the assembly feature ontology base to instantiate an assembly system element semantic framework to obtain an assembly knowledge ontology;
s40, collecting traditional assembly experience and finding specific assembly experience in an assembly system and an assembly process, expressing the acquired assembly knowledge in the form of If … Then …, and converting the assembly knowledge expressed in the form of If … Then … into a SWRL rule base form which can be understood by an ontology.
The beneficial effects are that: the invention expresses in the knowledge body by mining the data of the assembly system and extracting the related assembly knowledge, instantiates the knowledge body by the self-adaptive assembly system facing the microminiature fuze, infers and updates the knowledge by defining different inference rules, can effectively solve the problems that the information knowledge of the existing assembly system is difficult to be effectively managed and applied, and is difficult to be combined with other assembly information knowledge to realize the intelligent decision and generation of the assembly process, and is beneficial to realizing the expression and reuse of the assembly system knowledge, thereby improving the assembly efficiency and shortening the production period.
Drawings
1: assembly platform overall structure
Fig. 1 is a general structure of a platform for a microminiature fuze-oriented adaptive assembly system, which instantiates an ontology in the third step in the method provided by the present invention. The automatic assembling and disassembling device comprises a loading and unloading carrying mechanical arm, an auxiliary operating platform, an auxiliary supporting subsystem, a precise motion control and adjustment subsystem, an assembling and executing subsystem, a multi-scale self-adaptive clamping subsystem, a high-precision alignment subsystem and a rapid image processing and identifying subsystem.
2: flow chart
FIG. 2The flow chart describes the flow of the method for constructing the ontology-oriented assembly system knowledge base system in detail, and finally the method with knowledge query reasoning and updating is obtainedAnd assembling a system body library.
3: assembly system element semantic framework
FIG. 3 is a semantic framework of assembly elements built from structural functional modules of the assembly system in a second step of the method of the present invention;
4: related attributes in an assembly system ontology
FIG. 4 is a diagram of the related attributes, including object attributes and data attributes, established according to the assembly system in the second step of the method provided by the present invention;
5: assembly ontology element semantic framework
Fig. 5 is a semantic frame of an assembly ontology library obtained by combining an assembly system ontology library, an assembly object ontology library and an assembly feature ontology library in the third step of the method provided by the present invention;
6: relationship inference of fixture and parts
Fig. 6 is a diagram illustrating the relationship between the fixture and the part, which is generated by inference after the assembly system library and the assembly object library are combined and instantiated in the third step of the method of the present invention.
7: new knowledge after SWRL inference
Fig. 7 shows new knowledge of example housing part 21201 obtained in the body after SWRL inference in the fourth step of the method of the present invention.
8: assemble ontology after instantiation
Fig. 8 is an assembly knowledge ontology conceptual diagram of the adaptive assembly system of the micro-fuse.
Detailed Description
The method of the present invention is described in detail below with reference to the accompanying drawings and examples.
The present embodiment provides an adaptive assembly system for a micro fuse, referring to fig. 1, including: the automatic feeding and discharging device comprises a feeding and discharging carrying mechanical arm, an auxiliary operating platform, an auxiliary supporting subsystem, a precise motion control and adjustment subsystem, an assembly execution subsystem, a multi-scale self-adaptive clamping subsystem, a high-precision alignment subsystem and a rapid image processing and identifying subsystem.
Referring to fig. 2, a flow chart of a method for constructing an ontology-based assembly system knowledge base system according to the present invention is shown.
Step S10, referring to fig. 1, generalizing and acquiring the functional structure and various attribute type concepts of the automatic assembly system for precision fine components, and dividing the functional structure and various attribute type concepts into seven modules, namely, a loading and unloading module, a flexible clamping module, a precision linear motion module, an assembly platform module, an assembly execution module, a visual alignment module, and an auxiliary assembly module. And mining and integrating and summarizing main structures, main functions, precision parameters and the like contained in each module.
Step S20, acquiring assembly system element keywords based on the assembly system domain concept, and establishing an assembly system semantic frame and related attributes in the ontology, as shown in fig. 3 and 4.
The assembly system semantic framework is divided into seven modules, namely a feeding and discharging module, a flexible clamping module, a precise linear motion module, an assembly platform module, an assembly execution module, a visual alignment module and an auxiliary assembly module, under the microstructure automatic tool assembly system; each module is divided into assembling parts or systems; for example, a microscopic optical alignment system, a common optical alignment system and a flight camera system are included under the visual alignment module; a subclass six-station substrate holder is arranged below the flexible clamping module, a subclass clamp is arranged below the flexible clamping module, and the clamp can be divided into an adsorption clamp and a clamping jaw clamp.
The related attributes in the ontology are divided into two categories, namely object attributes and data attributes, wherein the object attributes are used for mutually associating different semantic elements, and the data attributes are used for assigning values to corresponding semantic elements. Object attributes such as "used jig" and "for holding part" may correlate the assembled part and the assembled jig; and data attributes such as 'whether visual alignment is needed' and 'measuring range' are assigned to the contents such as whether the assembly object needs visual alignment and the measuring range of the measuring tool respectively.
And step S20, merging the assembly system semantic framework ontology base established in the step S20 with the assembly object and the assembly characteristic ontology base, and instantiating an assembly system element semantic framework to obtain a knowledge ontology. The merged ontology semantic framework is shown in fig. 5, and it can be seen that the ontology takes assembly objects, assembly features, and assembly systems as three major central classes, and there are sub-classes below the ontology. The knowledge ontology is instantiated by taking a self-developed micro-miniature fuse self-adaptive assembly system as an example. The various types and the examples are connected through attributes to form a whole with mutual correlation, and simple knowledge reasoning can be carried out through a reasoning machine carried by the prot g e based on the relation correlation among the elements. As shown in fig. 6, the data attribute "for holding a part" and the data attribute "used jig" are in "inverse of" relationship with each other, that is, they are in inverse attribute with each other, and new knowledge can be inferred by an example "spring jig 21201" having attribute "for holding a part spring 21201" under the jig class, and an example "spring 21201" having attribute "used jig spring jig 21201".
Step S40, collecting traditional assembly experience and finding specific assembly experience in the assembly system and the assembly process, and expressing the acquired assembly knowledge in the form of If … Then …. As to the choice of assembly alignment, in general,
the precision of the IF assembly position is required to be 2-5 microns, and THEN selects a common optical alignment system;
the precision requirement of the IF assembly position is less than 2 microns, and THEN selects a microscopic optical alignment system;
the precision of the IF assembly position is required to be 5-10 microns, the assembly time is within a certain threshold value, and THEN selects a flight camera system;
the IF assembly position precision is required to be more than 20 microns, and THEN does not need assembly alignment.
Further, on the basis of assembly knowledge, the knowledge expressed in the natural language form is converted into an SWRL rule base form, and the selection of assembly alignment is still taken as an example:
s1 is part (
S2 is part (
S3 parts (
S4 parts (
S5 parts (
Referring to fig. 7, for the example "housing part 21201", which has data attribute "mounting position accuracy 3", new knowledge can be obtained by inference from the HermiT inference engine under the above-mentioned SWRL rule, that "housing part 21201" has object attribute "visual alignment 21201 for visual alignment system and object attribute" clamp double V-shaped jaws 21201 "for object attribute and data attribute" whether visual alignment true is required ".
Referring to fig. 8, it is a conceptual diagram of an assembly knowledge body of the adaptive assembly system of the micro fuse.
The invention constructs the assembly ontology knowledge base of the assembly system based on the ontology technology, integrates and classifies different assembly system functional structures, excavates the common characteristics of the assembly system, considers the combination of the assembly ontology knowledge base and the assembly characteristic ontology knowledge base, instantiates a self-developed micro-type fuze self-adaptive assembly system as an example, expresses the knowledge of manual assembly experience in the ontology, obtains new assembly knowledge through the inquiry and reasoning of the knowledge, better guides the assembly process, and has practical value.
In summary, the above description is only a preferred embodiment of the present invention, and is not intended to limit the scope of the present invention. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (5)
1. An assembly system knowledge base based on a body and a construction method thereof are characterized in that the main structure of the assembly system knowledge base based on the body comprises a semantic frame concept class of a microstructure automatic assembly system, wherein the semantic frame concept class comprises seven major center classes of a feeding and discharging module, a flexible clamping module, a precise linear motion module, an assembly platform module, an assembly execution module, a visual alignment module and an auxiliary assembly module, and is used for representing object attributes and data attributes of relationships among the concept classes and examples and an SWRL rule for reasoning new knowledge; the construction method comprises the following steps:
s10, summarizing and arranging the functional structure and each attribute type concept of the assembly system;
s20, acquiring assembly element keywords based on the assembly system field concept, and establishing a related attribute and assembly system element semantic framework in the body;
s30, combining the assembly object ontology and the assembly characteristic ontology to obtain an assembly knowledge ontology;
s40, establishing an assembly process rule in an SWRL form in the knowledge ontology through the production rule, and reasoning to obtain new assembly knowledge to form an assembly system ontology with knowledge inquiry reasoning and updating.
2. The ontology-based assembly system knowledge base and the construction method thereof according to claim 1, wherein in step S10, the functional structure modules of the assembly system are sorted and analyzed to obtain the attribute data such as assembly function, structure composition, motion and position parameters.
3. The ontology-based assembly system knowledge base and the construction method thereof according to claim 1, wherein in step S20, based on the assembly system domain concept and the assembly system data, an assembly system semantic framework is constructed, and the correlation attributes are established, so as to form an assembly system ontology base model.
4. The ontology-based assembly system knowledge base and the construction method thereof according to claim 1, wherein in step S30, the merged assembly knowledge ontology comprises an assembly object attribute description module, an assembly characteristic attribute description module, and an assembly system attribute description module; each module is used for describing different assembling information; the assembly object attribute description module is used for describing the assembly object, namely the information of the assembly product and the parts; the assembly characteristic attribute description module is used for describing characteristic information such as a contact surface, a contact mode and the like in the assembly process of an assembly product; the assembly system attribute description module is used for describing information such as an assembly function, an assembly structure and the like of the automatic assembly system.
5. The assembly system knowledge base based on ontology and its construction method according to claim 1, characterized in that, according to general or specific assembly experience, the assembly process rule in SWRL form is established in the knowledge ontology through production rule, new assembly knowledge is obtained by inference, forming an assembly system ontology base with knowledge query inference and update.
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Patent Citations (8)
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