CN111931336B - Complex welding part unit dividing method and device and readable storage medium - Google Patents

Complex welding part unit dividing method and device and readable storage medium Download PDF

Info

Publication number
CN111931336B
CN111931336B CN202010607170.1A CN202010607170A CN111931336B CN 111931336 B CN111931336 B CN 111931336B CN 202010607170 A CN202010607170 A CN 202010607170A CN 111931336 B CN111931336 B CN 111931336B
Authority
CN
China
Prior art keywords
welding
weight
fuzzy
units
characteristic layer
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Active
Application number
CN202010607170.1A
Other languages
Chinese (zh)
Other versions
CN111931336A (en
Inventor
徐劲力
胡云锋
卢杰
吴波
黄丰云
刘晓刚
邹琳
张晓帆
卢佩航
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Wuhan University of Technology WUT
Original Assignee
Wuhan University of Technology WUT
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Wuhan University of Technology WUT filed Critical Wuhan University of Technology WUT
Priority to CN202010607170.1A priority Critical patent/CN111931336B/en
Publication of CN111931336A publication Critical patent/CN111931336A/en
Application granted granted Critical
Publication of CN111931336B publication Critical patent/CN111931336B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00—Computer-aided design [CAD]
    • G06F30/20—Design optimisation, verification or simulation

Landscapes

  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Computer Hardware Design (AREA)
  • Evolutionary Computation (AREA)
  • Geometry (AREA)
  • General Engineering & Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Resistance Welding (AREA)

Abstract

The invention discloses a complex welding part unit dividing method, a complex welding part unit dividing device and a readable storage medium, belongs to the technical field of welding planning, and solves the technical problem that the welding planning efficiency is low in the prior art. A complex weldment unit dividing method comprises the following steps: acquiring the quality, volume, weld joint length, connection quantity, similarity and inclusion of a welding part, and acquiring a fuzzy scale matrix corresponding to a characteristic layer by taking the obtained quality, volume, weld joint length, connection quantity, similarity and inclusion as the characteristic layer; acquiring a weight corresponding to the characteristic layer according to the fuzzy scale matrix corresponding to the characteristic layer, and determining the weight of each welding part relative to the basic part according to the weight corresponding to the characteristic layer and the weight corresponding to the quality, the volume, the length of a welding seam, the number of connections, the similarity and the inclusiveness of the basic part; and determining the number of the welding units, and obtaining the dividing result of the welding part units according to the number of the welding units and the weight of each welding part relative to the base part. The method of the invention improves the efficiency of welding planning.

Description

Complex welding part unit dividing method and device and readable storage medium
Technical Field
The invention relates to the technical field of welding planning, in particular to a complex welding part unit dividing method and device and a readable storage medium.
Background
The current welding planning method adopts the method that the welding sequence of each part is judged by the artificial experience of a process engineer, and the process planning is carried out on the product; the method is simple and easy to implement and is not easy to make mistakes for simple welding parts; however, for complex welding products, the method for planning the combination of different parts is thousands of, if the units of various parts can be divided according to a certain rule to form a few unit combinations, and then the unit groups are planned for welding, the time is greatly saved, and the planning efficiency is improved; meanwhile, the problem of excessive manual experience division can be solved.
Because the number of assembled parts is large, the space complexity is high and the assembled parts have a hierarchical relationship, the existing unit division method is mainly applied to hierarchical division in the assembly field, the welding complexity is gradually increased nowadays, and a unit division method is also needed; the original unit division method mainly comprises a clustering division method, a process information division method, a graph theory division method, an empirical example reasoning method and the like; the clustering method has good application effect but poor pertinence; the graph theory is simple and easy to understand, but is not easy to convert into computer language; because the information of different products is different, the method of process information and empirical reasoning is difficult to be applied to the analysis of other products; the existing unit division methods are only suitable for the assembly field and are not suitable for the welding field; the original method depending on manual experience cannot reasonably divide parts, so that the efficiency of welding planning is low; different parts have different characteristics and different information, and cannot be well applied to different products.
Disclosure of Invention
In view of the above, the present invention provides a method and an apparatus for partitioning a complex weldment unit, and a readable storage medium, so as to solve the technical problem of low welding planning efficiency in the prior art.
In one aspect, the invention provides a complex weldment unit dividing method, which comprises the following steps:
acquiring the quality, the volume, the length of welding seams, the connection quantity, the similarity and the inclusion of the welding parts, and acquiring a fuzzy scale matrix corresponding to a characteristic layer by taking the quality, the volume, the length of the welding seams, the connection quantity, the similarity and the inclusion of the welding parts as the characteristic layer;
acquiring a weight corresponding to the characteristic layer according to the fuzzy scale matrix corresponding to the characteristic layer, and determining the weight of each welding part relative to the basic part according to the weight corresponding to the characteristic layer and the weight corresponding to the quality, the volume, the length of a welding seam, the number of connections, the similarity and the inclusiveness of the basic part;
and determining the number of the welding units, and obtaining the dividing result of the welding part units according to the number of the welding units and the weight of each welding part relative to the base part.
Further, acquiring fuzzy scale values of the parameter characteristics of the ith welding part compared with the parameter characteristics of the jth welding part
Figure GDA0003137836170000021
By passing
Figure GDA0003137836170000022
Forming a fuzzy scale matrix corresponding to the characteristic layer; wherein the content of the first and second substances,
Figure GDA0003137836170000023
Pi mis a parameter characteristic of the i-th weld, Pi mAnd the parameter characteristics of the jth welding part are any one of quality, volume, welding seam length, connection quantity, similarity and inclusion.
Further, acquiring a weight corresponding to the feature layer according to the fuzzy scale matrix corresponding to the feature layer, specifically including acquiring a fuzzy complementary consistent matrix corresponding to the feature layer according to the fuzzy scale matrix corresponding to the feature layer, and acquiring a weight corresponding to the feature layer according to the corresponding fuzzy complementary consistent matrix.
Further, acquiring a fuzzy complementary consistent matrix corresponding to the characteristic layer according to the fuzzy scale matrix corresponding to the characteristic layer, specifically comprising,
obtaining the element r of the ith row and the jth column in the fuzzy complementary consistent matrixijBy the element rijForming a fuzzy complementary consistent matrix corresponding to the characteristic layer, wherein,
Figure GDA0003137836170000024
ri、rjthe sum of each element in the ith and jth rows in the fuzzy scale matrix corresponding to the characteristic layer is respectively.
Further, according to the corresponding fuzzy complementary consistent matrix, obtaining a weight corresponding to the feature layer, specifically including, by a formula
Figure GDA0003137836170000025
Obtaining the weight corresponding to the characteristic layer, omegaiAnd n represents the order of the fuzzy complementary consistent matrix R, and alpha is (n-1)/2.
And further, determining the weight of each welding part relative to the base part according to the weight corresponding to the characteristic layer and the weight corresponding to the quality, the volume, the length of the welding line, the connection number, the similarity and the inclusion of the base part, and specifically, multiplying the weight corresponding to the characteristic layer by the weight corresponding to the base part and the weight corresponding to the quality, the volume, the length of the welding line, the connection number, the similarity and the inclusion of the base part to determine the weight of each welding part relative to the base part.
Further, determining the number of welding units, in particular by inequality
Figure GDA0003137836170000031
Determining the number of welding units NPN is the number of welded parts, NSIs a special welding unit.
Further, obtaining a dividing result of the welding part units according to the number of the welding units and the weight of each welding part relative to the base part, specifically comprising determining the welding units according to the number of the welding units and the weight of each welding part relative to the base part, determining an edge weight between the welding parts according to the weight corresponding to the feature layer and the fuzzy complementary consistent matrix, and obtaining the dividing result of the welding part units according to the edge weights between the welding units and the welding parts.
On the other hand, the invention also provides a complex weldment unit partitioning device, which comprises a processor and a memory, wherein the memory stores a computer program, and when the computer program is executed by the processor, the complex weldment unit partitioning method according to any one of the above technical solutions is realized.
In another aspect, the present invention further provides a computer-readable storage medium, on which a computer program is stored, wherein the computer program is executed by a processor to implement the complex weldment unit partitioning method according to any one of the above technical solutions.
Compared with the prior art, the invention has the beneficial effects that: acquiring the quality, the volume, the length of the welding seam, the connection quantity, the similarity and the inclusion of the welding part, and acquiring a fuzzy scale matrix corresponding to a characteristic layer by taking the quality, the volume, the length of the welding seam, the connection quantity, the similarity and the inclusion of the welding part as the characteristic layer; acquiring a weight corresponding to the characteristic layer according to the fuzzy scale matrix corresponding to the characteristic layer, and determining the weight of each welding part relative to the basic part according to the weight corresponding to the characteristic layer and the weight corresponding to the quality, the volume, the length of a welding seam, the number of connections, the similarity and the inclusiveness of the basic part; determining the number of welding units, and obtaining the dividing result of the welding part units according to the number of the welding units and the weight of each welding part relative to the base part; the division result of the welding part units is obtained quickly, and the welding planning efficiency is improved.
Drawings
Fig. 1 is a schematic flow chart of a complex weldment unit dividing method according to embodiment 1 of the present invention;
FIG. 2 is a hierarchical model of a target layer, a feature layer, and a part layer according to embodiment 1 of the present invention;
FIG. 3 is a schematic diagram illustrating directed weights between weldments according to embodiment 1 of the present invention;
FIG. 4 is a weight diagram of the base member according to embodiment 1 of the present invention;
fig. 5 is a traversal diagram according to embodiment 1 of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
Example 1
The invention provides a complex weldment unit dividing method, which has a flow schematic diagram, and as shown in figure 1, the method comprises the following steps:
s1, acquiring the quality, the volume, the welding seam length, the connection quantity, the similarity and the inclusion of the welding parts, and acquiring a fuzzy scale matrix corresponding to a characteristic layer by taking the quality, the volume, the welding seam length, the connection quantity, the similarity and the inclusion of the welding parts as the characteristic layer;
s2, obtaining weights corresponding to the feature layers according to the fuzzy scale matrixes corresponding to the feature layers, and determining the weights of the welding parts relative to the basic parts according to the weights corresponding to the feature layers and the weights corresponding to the quality, the volume, the length of welding seams, the number of connections, the similarity and the inclusiveness of the basic parts;
and S3, determining the number of welding units, and obtaining the dividing result of the welding part units according to the number of the welding units and the weight of each welding part relative to the base part.
In specific implementation, a hierarchical model of a target layer, a feature layer and a part layer is established, as shown in fig. 2, a first layer is the target layer, a second layer is the feature layer, a third layer is the part (welding part) layer, and the mass (w), the volume (v), the connection quantity (c) of each part (welding part), the length (l) of a welding seam connected between the welding parts, the similarity(s) and the spatial inclusion relationship (inclusiveness, represented by i) between the parts are obtained in advance; the target layer refers to a basic part, in the process of welding a plurality of parts, a welding part is usually selected as a central welding part and is placed at a more important position, a welding robot or a craftsman welds around the central welding part, and other welding parts are welded together until the welding parts are welded into a whole; in the welding unit, a welding part left by removing the welding unit basic part is called as a sub-part of the welding unit, wherein the welding unit consists of the welding unit basic part and the welding unit sub-part;
the connection quantity refers to the quantity of one part (welding part) and other parts which have direct mutual connection relation; the space inclusion relationship refers to whether one part is in the space of the other part, if so, the space inclusion relationship is 1, otherwise, the space inclusion relationship is 0; similarity can be calculated from the mass w, the area a and the centroid b and the euclidean distance,
Figure GDA0003137836170000041
wherein, wiIndicates a weld part PiMass of (d), wmaxIndicates a weld part PiAnd PjMaximum value of mass;
preferably, the fuzzy scale matrix corresponding to the feature layer is obtained, specifically including,
obtaining fuzzy scale value of parameter characteristic of the ith welding piece compared with parameter characteristic of the jth welding piece
Figure GDA0003137836170000042
By passing
Figure GDA0003137836170000051
Forming a fuzzy scale matrix corresponding to the characteristic layer; wherein the content of the first and second substances,
Figure GDA0003137836170000052
Pi mis a parameter characteristic of the i-th weld, Pi mThe parameter characteristic (also called as m characteristic) of the jth welding part is any one of mass, volume, welding seam length, connection quantity, similarity and inclusiveness;
preferably, the method includes acquiring a weight corresponding to the feature layer according to a fuzzy scale matrix corresponding to the feature layer, and specifically includes acquiring a fuzzy complementary consistent matrix corresponding to the feature layer according to the fuzzy scale matrix corresponding to the feature layer, and acquiring a weight corresponding to the feature layer according to the corresponding fuzzy complementary consistent matrix;
preferably, the fuzzy complementary consistent matrix corresponding to the feature layer is obtained according to the fuzzy scale matrix corresponding to the feature layer, and specifically includes,
obtaining the element r of the ith row and the jth column in the fuzzy complementary consistent matrixijDisclosure of the inventionOver element rijForming corresponding fuzzy mutual of characteristic layer
And (c) complementing the consensus matrix, wherein,
Figure GDA0003137836170000053
ri、rjrespectively the sum of each element in the ith and the j row in the fuzzy scale matrix corresponding to the characteristic layer;
according to rijA fuzzy complementary consistent matrix R can be obtained
Figure GDA0003137836170000054
Wherein n represents the order of the fuzzy complementary consistent matrix R;
preferably, the obtaining of the weight corresponding to the feature layer according to the corresponding fuzzy complementary consistent matrix specifically includes obtaining the weight corresponding to the feature layer through a formula
Figure GDA0003137836170000055
Obtaining the weight corresponding to the characteristic layer, omegaiA weight corresponding to a characteristic layer of the ith welding part is represented by n, the order of the fuzzy complementary consistent matrix R is represented by alpha which is (n-1)/2;
preferably, the weight of each welding part relative to the base part is determined according to the weight corresponding to the feature layer and the weight corresponding to the mass, the volume, the length of the welding line, the number of connections, the similarity and the inclusion of the base part, and specifically, the method comprises the step of multiplying the weight corresponding to the feature layer by the weight corresponding to the mass, the volume, the length of the welding line, the number of connections, the similarity and the inclusion of the base part to determine the weight of each welding part relative to the base part.
In specific implementation, the weight corresponding to the feature layer of the welding part is multiplied by the weight corresponding to the feature target layer (the weight corresponding to the mass, the volume, the length of the welding line, the connection quantity, the similarity and the inclusion of the basic part) to obtain the weight Q of each welding part relative to the basic parti＝ωi*ωmWherein，QiThe weight of each welding part relative to the basic part; omegamRepresenting the weight of the characteristic target layer;
preferably, the number of welding units is determined, including, in particular, by inequality
Figure GDA0003137836170000061
Determining the number of welding units NPN is the number of welded parts, NSIs a special welding unit;
the special welding unit is a welding part which can generate great deformation to influence the welding between the following welding units and the overall quality if the special welding unit has larger mass and longer and dense welding seam length when being welded on another part in the welding process;
preferably, the dividing result of the welding part units is obtained according to the number of the welding units and the weight of each welding part relative to the base part, and the method specifically comprises the steps of determining the welding units according to the number of the welding units and the weight of each welding part relative to the base part, determining the edge weight between the welding parts according to the weight corresponding to the characteristic layer and the fuzzy complementary consistent matrix, and obtaining the dividing result of the welding part units according to the edge weight between the welding units and the welding parts;
the weight of each welding part relative to the basic part is divided by using a minimum spanning tree algorithm by using a directed weight graph relation mode and taking the welding basic part as a starting point, wherein the direction of an arrow is taken as that the basic part points to the sub-parts, for example, fig. 3 is a directed weight schematic diagram between the welding parts, the representation forms are 'welding parts (nodes) and weights (edges)', P1, P2 and P3 nodes represent different welding parts, and the edges connected with the nodes represent the weight between the two units; if W12> W13, the fact that P2 has higher probability than P3 and is divided into the same welding unit with P1 at the same time is shown, and the edge weight between the welding parts is determined according to the weight corresponding to the characteristic layer and the fuzzy complementary consistent matrix;
the calculation formula is as follows,
Figure GDA0003137836170000062
w、ωv、ωl、ωc、ωiand ωsThe corresponding weight r in the feature layerw ij、rv ij、rl ij、rc ij、ri ijAnd rs ij、rw ijRespectively representing the features of the part in the ith row and the j column of elements in the fuzzy complementary consistent matrix;
dividing welding units by using a minimum spanning tree algorithm, wherein the direction of an arrow is taken as a basic part and points to a sub-part to obtain a unit division scheme; for example, if the part P9 and the base pieces P5, P6 have a connection relationship, W59 is smaller than W69, the part P9 and the base piece P6 belong to the same welding unit;
in specific implementation, interference detection is carried out on the unit dividing structure, wherein when any one of the welding parts is assembled along any direction of a coordinate system, the contact condition of the welding part and the rest welding parts is expressed in a matrix form, and the matrix form is called as an interference matrix;
during welding, a welding unit performs welding processing with another unit along the direction of a coordinate system (x, y, z), and an interference matrix I based on the coordinate system can be established, wherein the interference checking direction is six directions of +/-x, +/-y and +/-z; in a welded assembly of n welded units U ═ { U1, U2, … …, Un }, the orthogonal interference matrix of the assembly in the direction k (k ═ x, -x, y, -y, z, -z) is IyAs will be shown below, the following,
Figure GDA0003137836170000071
in the above formula, IijyIndicating the interference with part j when part i is assembled in direction y, a value of 1 indicating interference and a value of 0 indicating no interference.
Example 2
The embodiment of the invention provides a complex welding part unit dividing method, taking an auxiliary frame with a frame type closed structure as an example, and the part code information of a frame is shown in a table 1;
TABLE 1
Figure GDA0003137836170000072
Substituting various index parameters of welding parts
Figure GDA0003137836170000073
Performing standardization treatment, and substituting the result
Figure GDA0003137836170000074
The comparison indexes of all characteristic parameters of each welding part are obtained, the quality characteristics are taken as an example, the fuzzy scale matrix of the quality characteristics is shown in the table 2,
TABLE 2
Figure GDA0003137836170000081
The weight of each weld to the feature is obtained according to the fuzzy scale matrix of different features of each weld, as shown in table 3,
TABLE 3
Figure GDA0003137836170000091
The 16 welded parts are used as the welded part layer of the hierarchical structure to be evaluated, and the relative weight of each characteristic of the basic part in the auxiliary frame is shown in table 4,
TABLE 4
Figure GDA0003137836170000092
The weight of the basic parts is P from small to large16、P13、P10、P1、P7、P11、P15、P2、P8、P9、P12、P5、P4、P6、P3And P14A weight map of the base member, as shown in FIG. 4; the subframe containing a welded part which can be formed as a special welding unit and is a support, N S1, the number of available welding units is; therefore P is12、P5、P4、P6、P3And P14Is a basic piece;
traversing by using a minimum spanning tree method according to the weight value by taking the basic element as a starting point, and traversing a schematic diagram, wherein a gray representation is taken as the basic element as shown in FIG. 5; welding the welding units in a certain order, i.e. U1(P4、P1)→U2(P3、P2、P16)→U3(P5、P7、P8、P10)→U4(P6、P9、P11)→U5(P14、P13、P15)→U6(P12)，
By means of the interference matrix it is possible to,
Figure GDA0003137836170000093
learn U1And U2Has an interference value of 1, U in xyz2And U3Has an interference value of 1, U in xyz3And U4Interference value on xy of 1, U4And U5Has an interference value of 1, U in y5And U6The interference value in xyz of (1) is found to be no interference phenomenon, i.e. the weld division is reasonable.
Example 3
The embodiment of the invention provides a complex weldment unit partitioning method, which comprises a processor and a memory, wherein a computer program is stored in the memory, and when the computer program is executed by the processor, the complex weldment unit partitioning method is realized according to any one of the above embodiments.
Example 4
The embodiment of the present invention provides a computer-readable storage medium, on which a computer program is stored, where the computer program is executed by a processor to implement the complex weldment unit partitioning method according to any one of the above embodiments.
The invention discloses a complex welding part unit dividing method, a complex welding part unit dividing device and a readable storage medium, wherein the quality, the volume, the length of a welding seam, the connection quantity, the similarity and the inclusion of a welding part are obtained, and the quality, the volume, the length of the welding seam, the connection quantity, the similarity and the inclusion of the welding part are used as a characteristic layer, so that a fuzzy scale matrix corresponding to the characteristic layer is obtained; acquiring a weight corresponding to the characteristic layer according to the fuzzy scale matrix corresponding to the characteristic layer, and determining the weight of each welding part relative to the basic part according to the weight corresponding to the characteristic layer and the weight corresponding to the quality, the volume, the length of a welding seam, the number of connections, the similarity and the inclusiveness of the basic part; determining the number of welding units, and obtaining the dividing result of the welding part units according to the number of the welding units and the weight of each welding part relative to the base part; by reasonably dividing the welding pieces, the dividing result of the welding piece unit is quickly obtained, and the welding planning efficiency is improved; the welding part unit dividing scheme has universality.
The above-described embodiments of the present invention should not be construed as limiting the scope of the present invention. Any other corresponding changes and modifications made according to the technical idea of the present invention should be included in the protection scope of the claims of the present invention.

Claims (8)

1. A complex weldment unit dividing method is characterized by comprising the following steps:
acquiring the quality, the volume, the length of welding seams, the connection quantity, the similarity and the inclusion of the welding parts, and acquiring a fuzzy scale matrix corresponding to a characteristic layer by taking the quality, the volume, the length of the welding seams, the connection quantity, the similarity and the inclusion of the welding parts as the characteristic layer;
acquiring a fuzzy complementary consistent matrix corresponding to the characteristic layer according to a fuzzy scale matrix corresponding to the characteristic layer, acquiring a weight corresponding to the characteristic layer according to the corresponding fuzzy complementary consistent matrix, and determining the weight of each welding part relative to the basic part according to the weight corresponding to the characteristic layer and the weight corresponding to the quality, the volume, the length of a welding seam, the connection quantity, the similarity and the inclusion of the basic part;
determining the number of welding units, determining the welding units according to the number of the welding units and the weight of each welding piece relative to a base piece, determining the edge weight between the welding pieces according to the weight corresponding to the characteristic layer and the fuzzy complementary consistent matrix, and obtaining the division result of the welding pieces according to the welding units and the edge weight between the welding pieces.
2. The method for partitioning complex weldment units according to claim 1, wherein obtaining a fuzzy scale matrix corresponding to the feature layer comprises,
obtaining fuzzy scale value of parameter characteristic of the ith welding piece compared with parameter characteristic of the jth welding piece
Figure FDA0003137836160000011
By passing
Figure FDA0003137836160000012
Forming a fuzzy scale matrix corresponding to the characteristic layer; wherein the content of the first and second substances,
Figure FDA0003137836160000013
Pi mis a parameter characteristic of the i-th weld, Pi mAnd the parameter characteristics of the jth welding part are any one of quality, volume, welding seam length, connection quantity, similarity and inclusion.
3. The method for partitioning complex weldment units according to claim 2, wherein obtaining fuzzy complementary consistent matrices corresponding to feature layers based on fuzzy scale matrices corresponding to feature layers comprises,
obtaining the element r of the ith row and the jth column in the fuzzy complementary consistent matrixijBy the element rijForming a fuzzy complementary consistent matrix corresponding to the characteristic layer, wherein,
Figure FDA0003137836160000014
ri、rjthe sum of each element in the ith and the jth row in the fuzzy scale matrix corresponding to the characteristic layer is respectively, and n is the order number of the fuzzy complementary consistent matrix.
4. The method of partitioning complex weldment units of claim 3, wherein obtaining weights corresponding to feature layers based on the corresponding fuzzy complementary consistent matrices specifically comprises, via a formula
Figure FDA0003137836160000021
Obtaining the weight corresponding to the characteristic layer, omegaiAnd n represents the order of the fuzzy complementary consistent matrix R, and alpha is (n-1)/2.
5. The method for partitioning the complex weldment units according to claim 1, wherein the weight of each weldment relative to the base is determined according to the weight corresponding to the feature layer and the weight corresponding to the mass, volume, weld length, number of connections, similarity, and inclusiveness of the base, and specifically comprises multiplying the weight corresponding to the feature layer by the weight corresponding to the base, and determining the weight of each weldment relative to the base.
6. The complex weldment unit division method of claim 1, wherein determining the number of weld units comprises, in particular, determining the number of weld units by inequality
Figure FDA0003137836160000022
Determining the number of welding units NPN is the number of welded parts, NSIs a special welding unit.
7. A complex weldment unit partitioning apparatus comprising a processor and a memory, the memory having stored thereon a computer program that, when executed by the processor, implements the complex weldment unit partitioning method of any one of claims 1 to 6.
8. A computer-readable storage medium having stored thereon a computer program, wherein the computer program, when executed by a processor, implements the complex weldment unit partitioning method of any of claims 1-6.
CN202010607170.1A 2020-06-30 2020-06-30 Complex welding part unit dividing method and device and readable storage medium Active CN111931336B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202010607170.1A CN111931336B (en) 2020-06-30 2020-06-30 Complex welding part unit dividing method and device and readable storage medium

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202010607170.1A CN111931336B (en) 2020-06-30 2020-06-30 Complex welding part unit dividing method and device and readable storage medium

Publications (2)

Publication Number Publication Date
CN111931336A CN111931336A (en) 2020-11-13
CN111931336B true CN111931336B (en) 2021-09-24

Family

ID=73316272

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202010607170.1A Active CN111931336B (en) 2020-06-30 2020-06-30 Complex welding part unit dividing method and device and readable storage medium

Country Status (1)

Country Link
CN (1) CN111931336B (en)

Families Citing this family (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113312806B (en) * 2021-07-30 2021-10-19 武汉理工大学 Welding unit dividing method and device

Family Cites Families (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP6070514B2 (en) * 2013-11-07 2017-02-01 Ｊｆｅスチール株式会社 Fatigue life prediction method of laser lap weld joint
CN107784441A (en) * 2017-10-23 2018-03-09 贵州大学 A kind of power distribution network Rolling Planning Post-assessment Method based on Fuzzy AHP
CN109299550B (en) * 2018-09-29 2022-09-27 长安大学 Steel structure bridge manufacturing decision evaluation method
CN110598279A (en) * 2019-08-28 2019-12-20 武汉理工大学 Method and device for planning part machining process route
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

Also Published As

Publication number Publication date
CN111931336A (en) 2020-11-13

Similar Documents

Publication Publication Date Title
CN112927357B (en) 3D object reconstruction method based on dynamic graph network
CN111347429A (en) Collision detection mechanical arm path planning method based on improved ant colony algorithm
CN111931336B (en) Complex welding part unit dividing method and device and readable storage medium
Tabar et al. Evaluating evolutionary algorithms on spot welding sequence optimization with respect to geometrical variation
Li et al. Mobile robot path planning based on improved genetic algorithm with A-star heuristic method
CN110569926A (en) point cloud classification method based on local edge feature enhancement
CN109255141A (en) A kind of body of a motor car forward direction conceptual design cross sectional shape optimization method
CN113506186B (en) Method and device for screening disturbed track of power system, electronic equipment and storage medium
CN106934853A (en) A kind of acquiring method of the automobile workpiece surface normal vector based on point cloud model
CN113885567B (en) Collaborative path planning method for multiple unmanned aerial vehicles based on conflict search
CN115421522A (en) Unmanned aerial vehicle coverage path planning method based on parallel self-adaptive ant colony algorithm
Bhattacharjya et al. A genetic algorithm for intelligent imaging from quantum-limited data
CN114756997A (en) Method and device for detecting self-intersecting line of hull plate curved surface design and storable medium
EP3958180A1 (en) Method for determining an indicator of a technical system, determination unit and construction system
CN114972695A (en) Point cloud generation method and device, electronic equipment and storage medium
Bhaduri et al. Efficient surrogate modeling for turbine blade row cyclic symmetric mode shapes
Wilson et al. Parallel adaptive tetrahedral mesh generation by the advancing front technique
Putra et al. Fuzzy Lightweight CNN for Point Cloud Object Classification based on Voxel
CN117972397B (en) Atmospheric dry-wet sedimentation model simulation optimization monitoring method and medium based on big data
CN104346520A (en) Neural network based data dimension reduction system and dimension reducing method thereof
CN113033034B (en) Mixed order vector finite element electromagnetic field calculation method and system
Huang et al. Path planning for UAV reconnoitring in complex environment based on improved visibility graph and genetic algorithm
Du Analyzing topological changes for structural shape simplification
CN112086135B (en) State analysis method, device and equipment
CN116972826A (en) Multi-unmanned aerial vehicle track planning method, equipment and storage medium

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
CB03 Change of inventor or designer information

Inventor after: Xu Jinli

Inventor after: Hu Yunfeng

Inventor after: Lu Jie

Inventor after: Wu Bo

Inventor after: Huang Fengyun

Inventor after: Liu Xiaogang

Inventor after: Zou Lin

Inventor after: Zhang Xiaofan

Inventor after: Lu Peihang

Inventor before: Xu Jinli

Inventor before: Hu Yunfeng

Inventor before: Lu Jie

Inventor before: Wu Bo

Inventor before: Huang Fengyun

Inventor before: Liu Xiaogang

Inventor before: Zou Lin

Inventor before: Zhang Xiaofan

Inventor before: Lu Peihang

CB03 Change of inventor or designer information
GR01 Patent grant
GR01 Patent grant