CN104573194A - Recognition method for subassembly in assembly sequence planning - Google Patents
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Abstract
The invention discloses a recognition method for a subassembly in assembly sequence planning. The recognition method comprises the steps of building a weighted non-vector connection diagram through a relationship between assemblies, and then determining basic parts; judging the subassembly according to the definition and the association degree of parts; finally, realizing a subassembly recognition algorithm through designing and compiling under a Matlab (matrix laboratory) environment. According to the recognition method disclosed by the invention, an algorithm instance verifies that a great significance in realizing assembly sequence optimization and shortening assembly sequence planning time is obtained by applying the subassembly recognition to the assembly sequence planning, an assembly sequence is simplified, and the assembly difficulty and the assembly cost are reduced.
Description
Technical Field
The invention relates to the field of assembly sequence planning, in particular to a method for identifying a subassembly in the assembly sequence planning.
Background
The problems of combination explosion, overlarge search space, exponential increase of constrained combination and the like can be faced in the assembly of different scales in various environments. In the face of a product which is formed by a large number of parts, complex in structure, high in assembly requirement and difficult in component identification during intelligent sequence planning, the sub-assembly bodies are divided so that the assembly bodies of different scales can be assembled in a structural hierarchy manner, the assembly sequence planning problem is decomposed into a plurality of sub-problems, the assembly difficulty is reduced, the generation process of an assembly sequence is facilitated, and the planning efficiency is improved. The assembly of the product can be better guided, and the assembly cost is reduced.
Many partitioning methods have been proposed at home and abroad with respect to the identification of sub-assemblies. At present, the identification method of the sub-assembly body utilizes the structure information of the assembly body to automatically extract and divide human-computer interaction. Wherein, automatically extracting sub-assemblies generally requires establishing part connection models of the assemblies.
The prior art has the defects of complex assembly sequence, high assembly difficulty and high cost.
Disclosure of Invention
In order to overcome the defects of the prior art, the invention aims to provide an assembly sequence planning neutron assembly body identification method, which simplifies the assembly sequence and reduces the assembly difficulty and cost.
In order to achieve the purpose, the invention adopts the technical scheme that:
a method of identifying a subassembly in an assembly sequence plan, comprising the steps of:
firstly, establishing a right undirected connection diagram through the relation between assemblies, and confirming a basic part;
the assembly body is composed of n parts and is provided withEstablishing an assembly right undirected connection diagram G for the assembly according to the connection relation of the parts,
wherein,representing a collection of component parts in an assembly;
indicating that a fastening connection relationship or a contact connection relationship exists between the parts;
the weight wij represented by the seven-tuple is used for marking that eij is a fastening connection edge or a contact connection edge, and the weight of the contact connection edge is also used for marking the direction of a contact surface;
the weight wij components are defined as follows:
adjacency matrix for weighted undirected connection graphTo show, the element cij in the adjacency matrix is a structural variable, which includes the member variables: r, x0，x1，y0，y1，z0，z1The assignment of the element corresponding to the edge of the graph G in the matrix, that is, the assignment of the weight value of the edge, and the values of all the member variables of the other elements are 0, because the contact connection relationship is established under an orthogonal coordinate system, the matrix element c is defined according to the components of the weight value of the edgeijMiddle member variable x1、y1、z1Can represent part piAnd pjContact coupling relationships in the-x, -y, -z directions;
secondly, judging the sub-assemblies according to the definitions and the incidence matrixes;
the sub-assembly body is a combination of a group of parts, has stability and independence, the number of the parts of the sub-assembly body is more than or equal to 2 and less than the total number of the parts, the parts are mutually and stably matched, at least one assembling or disassembling direction exists, and in order to realize the automatic judgment of the sub-assembly body in the assembly body, the association degree among the parts of the assembly body needs to be determined;
thirdly, generating a recognition algorithm of the sub-assembly body according to the structural characteristics of the sub-assembly body and the assembly process;
because the I-type sub-assembly body can not be spontaneously separated, the sub-assembly loops must contain fastening and connecting edges, a set formed by all vertexes of a minimum loop containing the fastening and connecting edges is called a minimum loop set, the minimum loop is found for each fastening and connecting edge in the undirected connection graph of the assembly body, the minimum loop not containing the base piece in the vertex is selected to generate the minimum loop set, the minimum loop sets containing the common nodes are merged until no common node exists in each final set, the merged set is called a maximum loop set, global interference judgment is carried out on each maximum loop set and all parts outside the set, and if no part with global interference exists, the sub-structure corresponding to the node in the maximum loop set is the I-type sub-assembly body,
the sub-assembly recognition algorithm comprises the following steps:
3.1) selecting X, Y, Z the direction which is not judged, and generating all contact part sets which do not include the base part in the direction which is not judged according to the value of the member variable of each element in the weighted connection undirected graph;
3.2) if a certain part in the contact part set belongs to an I-shaped sub-assembly body, adding the parts in the I-shaped sub-assembly body into the contact part set;
3.3) judging in the undetermined direction according to an adjacency matrix of the weighted connection undirected graph, and if parts do not belong to the contact part set and are not base pieces, adding the zero into the contact part set if any two parts in the contact part set exist in a contact connection relation in the undetermined direction;
3.4) merging the expanded contact part sets obtained in the step 3), and merging the sets containing the common nodes again until the intersection between all the sets is empty, wherein the merged set is called an expanded contact part set;
3.5) judging whether parts which do not belong to the contact part set exist in a certain direction except the undetermined direction according to the interference matrix, wherein the parts which belong to the contact part set have a contact connection relation, and if the parts exist in each direction except the undetermined direction, the substructure corresponding to the expanded contact part set is a II-type sub-assembly body and a support node is output; otherwise, the extended contact part set cannot be used as a II-type sub-assembly in a direction other than the undetermined direction. Setting the current direction as judged;
3.6) judging whether X, Y, Z directions are judged, if yes, finishing the algorithm, otherwise, returning to the step 1);
fourthly, realizing a sub-assembly body recognition algorithm by design and compilation in a Matlab environment;
the method comprises the following steps of applying Matlab software to design and compile a sub-assembly recognition algorithm, wherein the basic flow for realizing sub-assembly recognition in a Matlab environment is as follows: 4.1) inputting a data set and the number of parts of the assembly body; 4.2) initializing the assembly base piece; 4.3) distributing each part to the basic part with the strongest relevance degree to form a part set; 4.4) judging whether convergence occurs, outputting the sub-assembly body when the convergence occurs, and otherwise, returning to the previous step until the convergence occurs.
The invention has the beneficial effects that: the invention verifies that the sub-assembly identification is applied to the assembly sequence planning through the algorithm example, has important significance for realizing the optimization of the assembly sequence and shortening the planning time of the assembly sequence, simplifies the assembly sequence and reduces the assembly difficulty and the cost.
Drawings
FIG. 1 is a relational model of a weighted undirected graph.
FIG. 2 is a basic scheme for identifying sub-assemblies.
FIG. 3 is a detailed flow diagram of a sub-assembly identification algorithm.
Fig. 4 is a basic flow for realizing sub-assembly identification in a Matlab environment.
Fig. 5 is a diagram showing a recognition result of an assembly of an example of a motorcycle.
Detailed Description
The present invention will be described in detail below with reference to the accompanying drawings.
A method of identifying a subassembly in an assembly sequence plan, comprising the steps of:
firstly, establishing a weighted undirected connection diagram according to the relationship among assemblies, and confirming a basic part, wherein a weighted undirected connection diagram relationship model is shown in figure 1;
the assembly body is composed of n parts and is provided withEstablishing an assembly right undirected connection diagram G for the assembly according to the connection relation of the parts,
wherein,representing a collection of component parts in an assembly;
indicating that a fastening connection relationship or a contact connection relationship exists between the parts;
the weight wij represented by the seven-tuple is used for marking that eij is a fastening connection edge or a contact connection edge, and the weight of the contact connection edge is also used for marking the direction of a contact surface;
the weight wij components are defined as follows:
adjacency matrix for weighted undirected connection graphTo show, the element cij in the adjacency matrix is a structural variable, which includes the member variables: r, x0，x1，y0，y1，z0，z1The assignment of the element corresponding to the edge of the graph G in the matrix, that is, the assignment of the weight value of the edge, and the values of all the member variables of the other elements are 0, because the contact connection relationship is established under an orthogonal coordinate system, the matrix element c is defined according to the components of the weight value of the edgeijMiddle member variable x1、y1、z1Can represent part piAnd pjContact coupling relationships in the-x, -y, -z directions,
secondly, judging the sub-assemblies according to the definitions and the incidence matrixes;
the sub-assembly body is a combination of a group of parts and has stability and independence, the number of the parts of the sub-assembly body is more than or equal to 2 and less than the total number of the parts, the parts are mutually and stably matched, at least one assembling or disassembling direction exists,
the parts in a product can be integrally assembled or disassembled as an assembly body, the parts are sub-assembly bodies obtained by comprehensively analyzing factors such as matching conditions, fastening conditions, space association conditions and the like among the parts in the product according to experience and human beings, and in order to realize the automatic judgment of the sub-assembly bodies in the assembly bodies, the association degree among the parts of the assembly bodies needs to be determined;
thirdly, generating a recognition algorithm of the sub-assembly body according to the structural characteristics of the sub-assembly body and the assembly process; because the I-type sub-assembly body can not be spontaneously separated, the sub-assembly loops must contain fastening and connecting edges, a set formed by all vertexes of a minimum loop containing the fastening and connecting edges is called a minimum loop set, the minimum loop is found for each fastening and connecting edge in the undirected connection graph of the assembly body, the minimum loop not containing the base piece in the vertex is selected to generate the minimum loop set, the minimum loop sets containing the common nodes are merged until no common node exists in each final set, the merged set is called a maximum loop set, global interference judgment is carried out on each maximum loop set and all parts outside the set, and if no part with global interference exists, the sub-structure corresponding to the node in the maximum loop set is the I-type sub-assembly body,
the sub-assembly recognition algorithm comprises the following steps:
3.1) selecting X, Y, Z the direction which is not judged, and generating all contact part sets which do not include the base part in the direction which is not judged according to the value of the member variable of each element in the weighted connection undirected graph;
3.2) if a certain part in the contact part set belongs to an I-shaped sub-assembly body, adding the parts in the I-shaped sub-assembly body into the contact part set;
3.3) judging in the undetermined direction according to an adjacency matrix of the weighted connection undirected graph, and if parts do not belong to the contact part set and are not base pieces, adding the zero into the contact part set if any two parts in the contact part set exist in a contact connection relation in the undetermined direction;
3.4) merging the expanded contact part sets obtained in the step 3), and merging the sets containing the common nodes again until the intersection between all the sets is empty, wherein the merged set is called an expanded contact part set;
3.5) judging whether parts which do not belong to the contact part set exist in a certain direction except the undetermined direction according to the interference matrix, wherein the parts which belong to the contact part set have a contact connection relation, and if the parts exist in each direction except the undetermined direction, the substructure corresponding to the expanded contact part set is a II-type sub-assembly body and a support node is output; otherwise, the extended contact part set cannot be used as a II-type sub-assembly in a direction other than the undetermined direction. Setting the current direction as judged;
3.6) judging whether X, Y, Z directions are judged, if yes, finishing the algorithm, otherwise, returning to the step 1);
the basic flow for identifying sub-assemblies is shown in figure 2,
generating a sub-assembly recognition algorithm according to the weighted undirected join diagram, the structural characteristics of the sub-assembly and the assembly process, wherein the specific flow of the generated sub-assembly recognition algorithm is shown in FIG. 3;
fourthly, realizing a sub-assembly body recognition algorithm by design and compilation in a Matlab environment;
the method comprises the following steps of applying Matlab software to design and compile a sub-assembly recognition algorithm, wherein the basic flow for realizing sub-assembly recognition in a Matlab environment is as follows: 4.1) inputting a data set and the number of parts of the assembly body; 4.2) initializing the assembly base piece; 4.3) distributing each part to the basic part with the strongest relevance degree to form a part set; 4.4) judging whether convergence occurs, outputting the sub-assembly body when the convergence occurs, and otherwise, returning to the previous step until the convergence occurs.
The basic flow for realizing the sub-assembly recognition in the Matlab environment is shown in fig. 4.
Dat is stored in motorcycle, and the data is identified by using a subassembly identification algorithm, and the result of subassembly identification obtained after the data of the motorcycle is operated by a program is shown in fig. 5.
Claims (7)
1. A method of identifying a subassembly in an assembly sequence plan, comprising the steps of:
firstly, establishing a right undirected connection diagram through the relation between assemblies, and confirming a basic part;
secondly, judging the sub-assemblies according to the definitions and the incidence matrixes;
thirdly, generating a recognition algorithm of the sub-assembly body according to the structural characteristics of the sub-assembly body and the assembly process;
and fourthly, realizing a sub-assembly body recognition algorithm by designing and compiling in a Matlab environment.
2. A method of identifying sub-assemblies in an assembly sequence plan as recited in claim 1, wherein: establishing a directed undirected connection diagram, specifically comprising:
the assembly body is composed of n parts and is provided withEstablishing an assembly right undirected connection diagram G for the assembly according to the connection relation of the parts,
wherein,representing a collection of component parts in an assembly;
indicating that a fastening connection relationship or a contact connection relationship exists between the parts;
the weight wij represented by the seven-tuple is used for marking that eij is a fastening connection edge or a contact connection edge, and the weight of the contact connection edge is also used for marking the direction of a contact surface;
the weight wij components are defined as follows:
adjacency matrix for weighted undirected connection graphTo show, the element cij in the adjacency matrix is a structural variable, which includes the member variables: r, x0，x1，y0，y1，z0，z1The assignment of the element corresponding to the edge of the graph G in the matrix, that is, the assignment of the weight value of the edge, and the values of all the member variables of the other elements are 0, because the contact connection relationship is established under an orthogonal coordinate system, the matrix element c is defined according to the components of the weight value of the edgeijMiddle member variable x1、y1、z1Can represent part piAnd pjContact coupling relationships in the-x, -y, -z directions.
3. A method of identifying sub-assemblies in an assembly sequence plan as recited in claim 1, wherein: judging the sub-assemblies according to the sub-assembly definitions and the incidence matrixes;
the sub-assembly body is a combination of a group of parts, has stability and independence, the number of the parts of the sub-assembly body is more than or equal to 2 and less than the total number of the parts, the parts are mutually and stably matched, and at least one assembling or disassembling direction exists; in order to realize automatic discrimination of sub-assemblies in the assemblies, the association degree between the parts of the assemblies needs to be determined.
4. A method of identifying sub-assemblies in an assembly sequence plan as recited in claim 1, wherein: the sub-assembly recognition algorithm is;
since the I-shaped sub-assembly body can not be separated spontaneously, a fastening connecting edge is necessarily included in the sub-assembly loop.
5. The method comprises the following steps that a set consisting of all vertexes of a minimum loop comprising fastening connection edges is called as a minimum loop set, the minimum loop is found for each fastening connection edge in a non-directional connection diagram of an assembly body, the minimum loop not comprising a base piece in each vertex is selected to generate the minimum loop set, the minimum loop sets comprising common nodes are merged until no common node exists in each final set, the merged set is called as a maximum loop set, global interference judgment is carried out on each maximum loop set and all parts outside the set, and if no part with global interference exists, a substructure corresponding to the node in the maximum loop set is an I-type sub-assembly body;
the sub-assembly recognition algorithm comprises the following steps:
3.1) selecting X, Y, Z the direction which is not judged, and generating all contact part sets which do not include the base part in the direction which is not judged according to the value of the member variable of each element in the weighted connection undirected graph;
3.2) if a certain part in the contact part set belongs to an I-shaped sub-assembly body, adding the parts in the I-shaped sub-assembly body into the contact part set;
3.3) judging in the undetermined direction according to an adjacency matrix of the weighted connection undirected graph, and if parts do not belong to the contact part set and are not base pieces, adding the zero into the contact part set if any two parts in the contact part set exist in a contact connection relation in the undetermined direction;
3.4) merging the expanded contact part sets obtained in the step 3), and merging the sets containing the common nodes again until the intersection between all the sets is empty, wherein the merged set is called an expanded contact part set;
3.5) judging whether parts which do not belong to the contact part set exist in a certain direction except the undetermined direction according to the interference matrix, wherein the parts which belong to the contact part set have a contact connection relation, and if the parts exist in each direction except the undetermined direction, the substructure corresponding to the expanded contact part set is a II-type sub-assembly body and a support node is output; otherwise, the extended contact part set cannot be used as a II-type sub-assembly in a direction other than the undetermined direction.
6. Setting the current direction as judged;
3.6) judging X, Y, Z whether the directions are judged, if yes, finishing the algorithm, otherwise, returning to the step 1).
7. A method of identifying sub-assemblies in an assembly sequence plan as recited in claim 1, wherein: the basic flow for realizing sub-assembly identification in the Matlab environment is as follows:
4.1) inputting a data set and the number of parts of the assembly body; 4.2) initializing the assembly base piece; 4.3) distributing each part to the basic part with the strongest relevance degree to form a part set; 4.4) judging whether convergence occurs, outputting the sub-assembly body when the convergence occurs, and otherwise, returning to the previous step until the convergence occurs.
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Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106204317A (en) * | 2016-07-12 | 2016-12-07 | 桂林电子科技大学 | Subassembly detection method based on body |
| CN106203696A (en) * | 2016-07-08 | 2016-12-07 | 桂林电子科技大学 | A kind of hybrid precast sequence generating method based on symbol |
| CN106372393A (en) * | 2016-08-26 | 2017-02-01 | 江苏科技大学 | Assembly sequence planning method of complex assembly on the basis of assembly matrix |
| CN108710733A (en) * | 2018-05-04 | 2018-10-26 | 河海大学常州校区 | A kind of rule-based dynamical assemble CAD model overall situation symmetry recognition methods |
| CN109784263A (en) * | 2019-01-09 | 2019-05-21 | 大连理工大学 | A kind of sub-assemblies extracting method based on interference with connection relationship |
| CN110889173A (en) * | 2019-10-15 | 2020-03-17 | 广西汽车集团有限公司 | Assembly unit division method based on assembly relation grading |
| CN111192156A (en) * | 2019-12-25 | 2020-05-22 | 安徽工程大学 | Assembly body disassembly sequence generation method and device |
| CN117648730A (en) * | 2024-01-26 | 2024-03-05 | 北京适创科技有限公司 | Method, device, equipment and storage medium for determining state of assembly |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101311966A (en) * | 2008-06-20 | 2008-11-26 | 浙江大学 | Three-dimensional human face animations editing and synthesis a based on operation transmission and Isomap analysis |
| CN101794334A (en) * | 2010-02-11 | 2010-08-04 | 天津理工大学 | Method for detaching products based on connected piece level network diagram |
| CN102521843A (en) * | 2011-11-28 | 2012-06-27 | 大连大学 | Three-dimensional human body motion analysis and synthesis method based on manifold learning |
| CN102664787A (en) * | 2012-04-01 | 2012-09-12 | 华为技术有限公司 | Generation method of decision tree and device thereof |
| CN103021009A (en) * | 2012-12-14 | 2013-04-03 | 大连大学 | Motion diagram transition point selecting method based on nonlinearity manifold learning |
-
2014
- 2014-12-20 CN CN201410794761.9A patent/CN104573194A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101311966A (en) * | 2008-06-20 | 2008-11-26 | 浙江大学 | Three-dimensional human face animations editing and synthesis a based on operation transmission and Isomap analysis |
| CN101794334A (en) * | 2010-02-11 | 2010-08-04 | 天津理工大学 | Method for detaching products based on connected piece level network diagram |
| CN102521843A (en) * | 2011-11-28 | 2012-06-27 | 大连大学 | Three-dimensional human body motion analysis and synthesis method based on manifold learning |
| CN102664787A (en) * | 2012-04-01 | 2012-09-12 | 华为技术有限公司 | Generation method of decision tree and device thereof |
| CN103021009A (en) * | 2012-12-14 | 2013-04-03 | 大连大学 | Motion diagram transition point selecting method based on nonlinearity manifold learning |
Non-Patent Citations (2)
| Title |
|---|
| 刘华等: "装配序列规划问题的 Benchmark生成算法", 《桂林电子科技大学学报》 * |
| 张勐等: "基于带权无向连接图的子装配体识别方法研究", 《桂林电子科技大学学报》 * |
Cited By (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106203696B (en) * | 2016-07-08 | 2019-04-16 | 桂林电子科技大学 | A kind of hybrid precast sequence generating method based on symbol |
| CN106203696A (en) * | 2016-07-08 | 2016-12-07 | 桂林电子科技大学 | A kind of hybrid precast sequence generating method based on symbol |
| CN106204317A (en) * | 2016-07-12 | 2016-12-07 | 桂林电子科技大学 | Subassembly detection method based on body |
| CN106372393A (en) * | 2016-08-26 | 2017-02-01 | 江苏科技大学 | Assembly sequence planning method of complex assembly on the basis of assembly matrix |
| CN108710733B (en) * | 2018-05-04 | 2022-03-01 | 河海大学常州校区 | Rule-based dynamic assembly CAD model global symmetry recognition method |
| CN108710733A (en) * | 2018-05-04 | 2018-10-26 | 河海大学常州校区 | A kind of rule-based dynamical assemble CAD model overall situation symmetry recognition methods |
| CN109784263A (en) * | 2019-01-09 | 2019-05-21 | 大连理工大学 | A kind of sub-assemblies extracting method based on interference with connection relationship |
| CN109784263B (en) * | 2019-01-09 | 2020-09-11 | 大连理工大学 | Sub-assembly body extraction method based on interference and connection relation |
| CN110889173A (en) * | 2019-10-15 | 2020-03-17 | 广西汽车集团有限公司 | Assembly unit division method based on assembly relation grading |
| CN110889173B (en) * | 2019-10-15 | 2023-07-07 | 广西汽车集团有限公司 | Assembly unit classification method based on assembly relation grading |
| CN111192156A (en) * | 2019-12-25 | 2020-05-22 | 安徽工程大学 | Assembly body disassembly sequence generation method and device |
| CN117648730A (en) * | 2024-01-26 | 2024-03-05 | 北京适创科技有限公司 | Method, device, equipment and storage medium for determining state of assembly |
| CN117648730B (en) * | 2024-01-26 | 2024-04-19 | 北京适创科技有限公司 | Method, device, equipment and storage medium for determining state of assembly |
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