CN111274757A - Method for realizing automatic layout of multi-branch cable assembly of electromechanical product based on multi-objective optimization - Google Patents
Method for realizing automatic layout of multi-branch cable assembly of electromechanical product based on multi-objective optimization Download PDFInfo
- Publication number
- CN111274757A CN111274757A CN202010061023.9A CN202010061023A CN111274757A CN 111274757 A CN111274757 A CN 111274757A CN 202010061023 A CN202010061023 A CN 202010061023A CN 111274757 A CN111274757 A CN 111274757A
- Authority
- CN
- China
- Prior art keywords
- cable
- layout
- cable assembly
- branch
- section
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 238000005457 optimization Methods 0.000 title claims abstract description 38
- 238000000034 method Methods 0.000 title claims abstract description 27
- 239000002245 particle Substances 0.000 claims abstract description 55
- 238000013461 design Methods 0.000 claims abstract description 10
- 238000000354 decomposition reaction Methods 0.000 claims abstract description 4
- 239000013598 vector Substances 0.000 claims description 9
- NUFBIAUZAMHTSP-UHFFFAOYSA-N 3-(n-morpholino)-2-hydroxypropanesulfonic acid Chemical compound OS(=O)(=O)CC(O)CN1CCOCC1 NUFBIAUZAMHTSP-UHFFFAOYSA-N 0.000 claims description 5
- 238000011161 development Methods 0.000 claims description 5
- 238000005452 bending Methods 0.000 claims description 4
- 238000010586 diagram Methods 0.000 claims description 4
- 238000010845 search algorithm Methods 0.000 claims description 4
- 230000000704 physical effect Effects 0.000 claims description 2
- 238000007781 pre-processing Methods 0.000 claims description 2
- 238000012545 processing Methods 0.000 claims description 2
- 238000005070 sampling Methods 0.000 claims description 2
- 238000010276 construction Methods 0.000 abstract description 2
- 230000000712 assembly Effects 0.000 description 7
- 238000000429 assembly Methods 0.000 description 7
- 238000009826 distribution Methods 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 238000006116 polymerization reaction Methods 0.000 description 2
- 125000000174 L-prolyl group Chemical group [H]N1C([H])([H])C([H])([H])C([H])([H])[C@@]1([H])C(*)=O 0.000 description 1
- 230000001464 adherent effect Effects 0.000 description 1
- 238000013473 artificial intelligence Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 238000011960 computer-aided design Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 230000006698 induction Effects 0.000 description 1
- 238000011900 installation process Methods 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 210000005036 nerve Anatomy 0.000 description 1
- 238000012827 research and development Methods 0.000 description 1
- 238000004904 shortening Methods 0.000 description 1
- 230000002792 vascular Effects 0.000 description 1
Images
Landscapes
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
A method for realizing the automatic layout of a multi-branch cable assembly of an electromechanical product based on multi-objective optimization is characterized by comprising the following steps: and determining a plurality of optimization targets and constraint conditions of the multi-target layout of the cable assembly according to the requirements. And carrying out discretization pretreatment on the cable laying space. The multi-target cable layout problem is solved by using a multi-target particle swarm optimization algorithm based on decomposition, a cable assembly layout scheme solution set meeting multiple targets can be obtained, and the construction and assembly of a cable assembly geometric model can be completed. The method can provide a group of optimal wiring schemes meeting the Pareto criterion through one-time operation, can be used for decision selection of different requirements of designers, and has the advantages of simple algorithm structure, high solving efficiency and great engineering value of recommended schemes. The implementation of the invention can effectively improve the wiring design efficiency and quality of the electromechanical product and reduce the working strength of designers.
Description
Technical Field
The invention relates to a computer aided design and artificial intelligence technology, in particular to a cable wiring technology of an electromechanical product, and specifically relates to a method for realizing automatic layout of a multi-branch cable assembly of the electromechanical product based on multi-objective optimization.
Background
The cable is a 'vascular nerve' of the mechatronic device, is used for energy transmission and signal control of an electrical element, and is widely used in complex mechatronic products such as aerospace, vehicles, electronics, ships and the like, and the unreasonable cable layout not only destroys the stability of the system but also damages electrical elements, so that the product failure rate is increased, for example, the american general company concludes that 50% of failures of engine air parking events are caused by damage to pipelines, cables and sensors. Most cables of complex electromechanical products are bundled cable assemblies, cable layout design relates to multiple optimization targets and multiple engineering constraints, multiple different layout schemes exist, most intelligent optimization algorithms aim at the problem of single-target layout optimization of double-end single cables, the length of the cables is singly used as the optimization target, the traditional mode of combining engineering experience and path search is adopted, the unique cable layout of the scheme is obtained, consideration of factors such as manufacturability, assembly difficulty and the like of the cable assemblies is lacked, and multiple targets such as total weight, manufacturability, assembly difficulty and the like of the cable assemblies are reasonably considered, so that the important significance and necessity for shortening the production research and development period of the electromechanical products are achieved.
Disclosure of Invention
The invention aims to solve the problem of difficult multi-target layout of cable assemblies of electromechanical products, and provides a method for realizing automatic layout of multi-branch cable assemblies of electromechanical products based on multi-target optimization so as to solve the problem of multi-target layout of cable assemblies of electromechanical products.
The technical scheme of the invention is as follows:
a method for realizing the automatic layout of the multi-branch cable assembly of an electromechanical product based on multi-objective optimization is characterized by comprising the following steps:
(1) inputting information of each port, wiring relation and physical attributes of each core wire for electrical connection of a cable assembly to be designed;
(2) determining a plurality of optimization targets and constraint conditions of the cable assembly layout design according to the engineering requirements of the wiring design, and recordingThe number of optimization targets is M, and an optimization function f of the layout scheme is setm(x) M is 1,2, …, M, x is a cable assembly layout scheme, wherein the smaller the respective optimization objective function value, the better the layout scheme;
(3) designing a three-dimensional geometric model based on the structure of an electromechanical product, performing discrete preprocessing on a cable laying space, and generating a cable laying space expressed by a discrete space model;
(4) optimizing and solving the layout of the cable assembly by using a multi-target particle swarm optimization algorithm (MOPSO/D for short) based on decomposition, initializing an initial solution by using the discrete cable laying space generated in the step (2), processing optimization constraints, generating a series of non-dominated cable layout schemes, and storing the schemes by using an XML format respectively;
(5) selecting a cable layout meeting the requirement, reading a corresponding XML file in a CAD environment, automatically generating a cable assembly geometric model by using a secondary development interface, and assembling the cable assembly geometric model into an electromechanical product geometric model.
In the step (1), the information of each port includes a spatial position and a plugging vector direction; the wiring relation is a wiring meter or a wiring diagram which is electrically connected; each core physical property includes core cross-sectional shape, size, and linear density.
In the step (2), the total weight of the cable assembly, the ratio of the main road of the bundling section and the open space on the laying path of the cable assembly are selected as optimization targets, and the objective functions are f1(x)、f2(x) And f3(x) Calculated according to the following formula:
f1(x)＝GB+GS
wherein G isB、GSThe total weight of the binding section and the total weight of the non-binding section;
wherein n is the number of the binding sections; l isiIs the length of the bundling segment; n is a radical ofiThe number of cables included for the bundled section; rhojThe j-th line cable density in the bundling section;
wherein n is the number of non-binding segments; l isiIs the length of the non-bundled section; rhoi(ii) an ith line cable density;
wherein, the contribution is the main road occupation ratio of the binding section; n is the number of the binding sections; l isiThe length of the ith bundling section; n is a radical ofiThe number of cables in the ith bundling section;
wherein Openness is an open space on a cable component laying path; n is the number of nodes on the laying path of the cable assembly; viIs the open space volume around the node;
the requirements of attaching the paths to the wall, avoiding high-temperature and strong electromagnetic regions, port extension length and minimum bending radius of the cable are taken as constraint conditions.
In the step (3), the cable laying space expressed by the discrete space model includes information such as discrete unit positions, topological relations among the discrete units, and spatial attributes of the discrete units. Wherein the spatial attributes include information about whether obstacles are present, temperature, electromagnetic strength, openness, etc.
In the step (4), the specific process for optimizing and solving the cable layout based on the MOPSO/D algorithm is as follows:
the first step is as follows: initializing;
step 1.1, generating W uniform weight vectors according to the target number m and the sampling step length H;
step 1.2, calculating Euclidean distances among the weight vectors of the subproblems, and selecting the smallest B subproblems as neighbors;
step 1.3 Using the number of branching points and null according to the Cable Patch TableThe inter-position encodes the particles, randomly generates W particles, and initializes the particle velocity. For each particle, first, a path between the terminal point and the branch point and a path between the branch points are generated using a path search algorithm; then, constructing a minimum spanning tree of the branch point, and traversing a path from the search terminal to the nearest branch point; finally, the core wires passing through each branch section are determined according to the wiring relation, the attributes such as the diameter and the linear density of the branch sections are calculated according to the core wire attributes, so that the overall wiring harness layout scheme is generated, and the target value f (p) of the particles is calculated according to the schemei)＝(f1(pi),f2(pi),…,fm(pi))，i＝1,2,…,W；；
Step 1.4 initialize reference point z*；
Step 1.5 set the locally and globally optimal particle of the particle to the particle itself, i.e. pbesti＝gbesti＝pi；
The second step is that: population evolution;
step 2.1, calculating the speed and the position of the particle i, and calculating each target value of the new position of the particle;
step 2.2 according to particle piTarget value f (p)i) Updating reference points
Step 2.3 updating the particle piIf the new location is better than the previous location, then pbest is seti＝piOtherwise, the original local optimal position pbest is reservedi；
Step 2.4 Using particles piUpdating the global optimal position of the neighbor particle, for particle piNeighbor particle pbGlobal optimum position gbest ofbIf p isiAs a neighbor pbIs better, then gbest is setb＝piOtherwise, not updating the global optimal position of the neighbor;
and 2.5, judging whether the evolution termination condition is met, if so, respectively storing the global optimal solution of the population and the related physical attributes of the corresponding cable layout into an XML file, and stopping population evolution, otherwise, continuing the second step.
In the step (5), the process of generating and assembling the geometric model of the cable assembly is as follows:
the first step is as follows: reading a cable layout XML file, reconstructing to obtain physical attributes of the cable such as the diameter, the linear density, the minimum bending radius, the looseness and the like of each branch section, and a discrete path point set of each branch section;
the second step is that: setting physical attributes of each branch section of the cable according to the CAD secondary development interface, generating a continuous path of each branch section of the cable assembly according to discrete path points of each branch section and fitting a sample curve, and creating and generating a geometric model of each branch section;
the third step: and setting an assembly coordinate system of the cable assembly according to the position of each port, and completing the assembly of the cable geometric model to the electromechanical product geometric model.
The invention has the beneficial effects that:
the invention provides a method for realizing automatic layout of a multi-branch cable assembly of an electromechanical product based on multi-objective optimization aiming at the automatic design of the multi-objective layout of the cable assembly of the electromechanical product. And determining a plurality of optimization targets and constraint conditions of the multi-target layout of the cable assembly according to the requirements. And carrying out discretization pretreatment on the cable laying space. The multi-target cable layout problem is solved by using a multi-target particle swarm optimization algorithm based on decomposition, a cable assembly layout scheme solution set meeting multiple targets can be obtained, and the construction and assembly of a cable assembly geometric model can be completed. The method can provide a group of optimal wiring schemes meeting the Pareto criterion through one-time operation, can be used for decision selection of different requirements of designers, and has the advantages of simple algorithm structure, high solving efficiency and great engineering value of recommended schemes. The implementation of the invention can effectively improve the wiring design efficiency and quality of the electromechanical product and reduce the working strength of designers.
Drawings
Fig. 1 is a schematic diagram of a spatial structure and a distribution of terminals of a typical electromechanical product.
FIG. 2 is a flow chart of an implementation of automatic layout of a multi-branch cable assembly of an electromechanical product based on multi-objective optimization.
FIG. 3 is a diagram of a multi-target layout effect of the cable assembly of the electromechanical product.
Table 1 is a wiring table of electromechanical products.
Table 2 is the preprocessed discrete spatial data.
Detailed Description
The following further description of the embodiments of the present invention is provided in conjunction with the accompanying drawings to enable those skilled in the art to better understand the present invention.
As shown in fig. 1-3, tables 1-2.
The input conditions of the method for realizing the automatic layout of the multi-branch cable assembly of the electromechanical product based on multi-objective optimization are the mechanical structure, the spatial position of a wiring terminal, the normal vector direction of a connector and an electric wiring table of the electromechanical product. As shown in fig. 1 and table 1.
TABLE 1 electromechanical products wiring table
The multi-target particle swarm algorithm suitable for cable assembly layout design is obtained through fixed-length particle coding based on the decomposed multi-target particle swarm algorithm, and layout optimization of cable assemblies in the mechanical and electrical products and creation and assembly of cable geometric models are achieved.
FIG. 2 is a flow chart of the present invention for implementing automatic layout of multi-branch cable assembly of electromechanical products based on multi-objective optimization. The method comprises the following specific steps:
the first step is as follows: determining a plurality of optimization targets and constraint conditions of the cable assembly layout design, recording the number of the optimization targets as 3, and setting an optimization function f of a layout schemem(x) And m is 1,2 and 3, the smaller the optimization objective function value is, the better the layout scheme is. SelectingThree indexes of the total weight of the cable assembly, the ratio of main roads of the bundling section and the open space on the laying path of the cable assembly are taken as optimization targets, x is a cable assembly layout scheme, and target functions are respectively f1(x)、f2(x) And f3(x) Calculated according to the following formula:
f1(x)＝GB+GS
wherein G isB、GSThe total weight of the binding section and the total weight of the non-binding section;
wherein n is the number of the binding sections; l isiIs the length of the bundling segment; n is a radical ofiThe number of cables included for the bundled section; rhojThe linear density of the jth cable in the bundling section;
wherein n is the number of non-binding segments; l isiIs the length of the non-bundled section; rhoiIs the linear density of the ith cable;
wherein, the contribution is the main road occupation ratio of the binding section; n is the number of the binding sections; l isiThe length of the ith bundling section; n is a radical ofiThe number of cables in the ith bundling section;
wherein Openness is an open space on a cable component laying path; n is the number of nodes on the laying path of the cable assembly; viIs the open space volume around the node.
Adherence of paths, avoidance of high temperature and strong electromagnetic regions, port extension length and minimum cable bend halfThe diameter requirement is used as a constraint condition. The path adherence h (x) ≠ 0, whereas h (x) ≠ 0; the path does not pass through the high temperature region t (x) 0, whereas t (x) is not equal to 0; the path does not pass through the strong electromagnetic region e (x) 0, otherwise e (x) is not equal to 0; the port extension length meets the requirement that N (x) is 0, otherwise, N (x) is not equal to 0; b (x) is not less than bminThe minimum bend radius requirement is met for the path.
The second step is that: firstly, an AABB bounding box CAD model of an assembly body is constructed according to a geometric model of an electromechanical product assembly body, and Boolean subtraction operation is carried out on the bounding box model by combining the distribution of product parts. The method can obtain a cable laying space excluding the obstacle area, and perform volume grid discretization pretreatment on the space to obtain discrete units in the laying space. In the actual cable installation process, different manufacturability requirements are required for the cable structure and path, for example, some electromechanical products require the cable to avoid a heat source, some electromechanical products require the cable to avoid electromagnetic interference or require fixing along the inner wall, and the like. Adding the process attributes related to cabling in the discrete space can obtain the preprocessed discrete space data shown in table 2.
TABLE 2 preprocessed discrete spatial data
Wherein the id column represents a unique identifier of the discrete unit, and the corresponding discrete unit can be retrieved through the identifier; the Geometric list represents discrete spatial Geometric attributes where only the spatial coordinate information (x, y, z) of the discrete cell center point is needed; the Craft column represents the process attribute of the discrete space, and the corresponding volume, T, E and A respectively represent the space volume (mm) of the discrete unit3) Equivalent temperature (K), equivalent magnetic induction (10)-3T) and adherence information (0 indicates that the cell is adherent); the Topology column represents the contiguous cell identification around the discrete cell, where-1 represents null.
The third step: the specific solving process after the MOPSO/D algorithm reads the discrete laying space is as follows:
(1) the number of samples 10 is set, and a set U of sample points with a step size of 0.1 is generated, where U is {0,0.1,0.2, …,1 }. According to the target space dimension m being 3, 45 weight vectors uniformly distributed in the space are generated.
(2) And calculating Euclidean distances between 45 subproblem weight vectors, and selecting the minimum 20 subproblems as neighbors.
(3) According to the cable connection table shown in table 1, the number of connection terminals is 10, the number of branch points does not exceed 8 at most, and the particles can be described as codes with a fixed length of 25. Particle PiCoded in the form of Pi＝(k,x1,y1,z1,x2,y2,z2,…,xk,yk,zk,xk+1,yk+1,zk+1,…,x8,y8,z8) K is the number of branch points constituting the cable structure, and the remaining 8-k are potential branch points that do not participate in constituting the cable structure but may participate in constituting the cable structure in the iterative update of the algorithm. Randomly generating 45 particles with an initial particle velocity of 0, for each particle, firstly, adding a cable constraint condition into a path search algorithm, and generating a path between a terminal point and a branch point and a path between the branch points by using the path search algorithm; then, constructing a minimum tree of the branch point, and further determining a path from the wiring end to the branch point; finally, the core wire attribute of the binding section is determined according to the wiring relation, and the target value f (p) of the particles is calculatedi)＝(f1(pi),f2(pi),f3(pi))，i＝1,2,…,45。
(4) The initial reference point being a larger number, z*＝(1e+10,1e+10,1e+10)。
(5) Setting the locally and globally optimal particles of each particle to the particle itself, i.e., pbesti＝gbesti＝pi，i＝1,2,…,45。
(6) Calculating the velocity and position of the particle i, and calculating the target values, f (p), of the new position of the particlei)＝(f1(pi),f2(pi),f3(pi))，i＝1,2,…,45。
(7) According to the particle piTarget value f (p)i) Updating reference points
For each target component fj(pi) If, if
Is provided with
(8) Updating the particle piThe local optimum position of. If the new position is better than the previous local optimum position, a comparison is made using Chebyshev's polymerization, i.e. gTCH(pi|λi)≤gTCH(pbesti|λi) Then set pbesti＝piOtherwise, the original local optimal position pbest is reservedi。
(9) Using particles piThe global optimal position of the neighbor particle is updated. For particle piNeighbor particle pbGlobal optimum position gbest ofbIf p isiAs a neighbor pbIs better globally, compared using Chebyshev polymerization, i.e. gTCH(pi|λi)≤gTCH(gbestb|λb) Then, set gbestb＝piOtherwise, the global optimal position of the neighbor is not updated.
(10) And (4) judging whether the evolution termination condition is met, if so, storing the global optimal solution of the population and the related physical attributes of the corresponding cable layout into XML, and stopping population evolution, otherwise, continuing the step (6).
The fourth step: the MFC framework of VS2012 is used to develop a program plug-in for generating a cable assembly geometric model using the secondary development interface Pro/Toolkit of the computer-aided design software Creo3.0. The program plug-in is automatically loaded on the Creo3.0 software platform, the cable layout XML file is read, the cable layout scheme and the physical attributes of the cable layout scheme are reconstructed, and the program can automatically construct a geometric model of the cable assembly. Selecting the global coordinate system of the geometric model of the electromechanical product assembly can complete the assembly of the cable assembly shown in fig. 3, and only several layout schemes are randomly selected from the final global optimal file for display.
The parts not involved in the present invention are the same as or can be implemented using the prior art.
Claims (7)
1. A method for realizing the automatic layout of the multi-branch cable assembly of an electromechanical product based on multi-objective optimization is characterized by comprising the following steps:
(1) inputting information of each port, wiring relation and physical attributes of each core wire for electrical connection of a cable assembly to be designed;
(2) determining a plurality of optimization targets and constraint conditions of the cable assembly layout design according to the engineering requirements of the wiring design, recording the number of the optimization targets as M, and setting an optimization function f of the layout schemem(x) M is 1,2, …, M, x is a cable assembly layout scheme;
(3) designing a three-dimensional geometric model based on the structure of an electromechanical product, performing discrete preprocessing on a cable laying space, and generating a cable laying space expressed by a discrete space model;
(4) optimizing and solving the layout of the cable assembly by using a multi-objective particle swarm optimization algorithm (MOPSO/D) based on decomposition, initializing an initial solution by using the discrete cable laying space generated in the step (2), processing optimization constraints, generating a series of non-dominated cable layout schemes, and storing the schemes by using an XML format respectively;
(5) selecting a cable layout meeting the requirement, reading a corresponding XML file in a CAD environment, automatically generating a cable assembly geometric model by using a secondary development interface, and assembling the cable assembly geometric model into an electromechanical product geometric model.
2. The method of claim 1, further comprising: in the step (1), the information of each port includes a spatial position and a plugging vector direction; the wiring relation is a wiring meter or a wiring diagram which is electrically connected; each core physical property includes core cross-sectional shape, size, and linear density.
3. The method of claim 1The method is characterized in that: in the step (2), the total weight of the cable assembly, the ratio of the main road of the bundling section and the open space on the laying path of the cable assembly are taken as optimization targets, and the objective functions are f1(x)、f2(x) And f3(x) Calculated according to the following formula:
f1(x)＝GB+GS
wherein G isB、GSThe total weight of the binding section and the total weight of the non-binding section;
wherein n is the number of the binding sections; l isiIs the length of the bundling segment; n is a radical ofiThe number of cables included for the bundled section; rhojThe linear density of the jth cable in the bundling section;
wherein n is the number of non-binding segments; l isiIs the length of the non-bundled section; rhoiIs the linear density of the ith cable;
wherein, the contribution is the main road occupation ratio of the binding section; n is the number of the binding sections; l isiThe length of the ith bundling section; n is a radical ofiThe number of cables in the ith bundling section;
wherein Openness is an open space on a cable component laying path; n is the number of nodes on the laying path of the cable assembly; viIs the open space volume around the node.
4. The method of claim 1, further comprising: in the step (2), the requirements of attaching the path to the wall, avoiding high-temperature and strong electromagnetic regions, port extension length and minimum bending radius of the cable are taken as constraint conditions.
5. The method of claim 1, further comprising: in the step (3), the cable laying space expressed by the discrete space model includes information such as discrete unit positions, topological relations among the discrete units, and spatial attributes of the discrete units; wherein the spatial attributes include whether obstruction, temperature, electromagnetic strength, openness information.
6. The method of claim 1, further comprising: in the step (4), the specific process for optimizing and solving the cable layout based on the MOPSO/D algorithm is as follows:
the first step is as follows: initializing;
step 1.1, generating W uniform weight vectors according to the target number m and the sampling step length H;
step 1.2, calculating Euclidean distances among the weight vectors of the subproblems, and selecting the smallest B subproblems as neighbors;
and 1.3, according to a cable wiring table, encoding the particles by using the number of the branch points and the spatial positions, randomly generating W particles, and initializing the particle speed. For each particle, first, a path between the terminal point and the branch point and a path between the branch points are generated using a path search algorithm; then, constructing a minimum spanning tree of the branch point, and traversing a path from the search terminal to the nearest branch point; finally, the core wires passing through each branch section are determined according to the wiring relation, the attributes such as the diameter and the linear density of the branch sections are calculated according to the core wire attributes, so that the overall wiring harness layout scheme is generated, and the target value f (p) of the particles is calculated according to the schemei)＝(f1(pi),f2(pi),…,fm(pi))，i＝1,2,…,W；；
Step 1.4 initialize reference point z*；
Step 1.5 setting the local and global optimum particles of the particlePlaced as particles per se, i.e. pbesti＝gbesti＝pi；
The second step is that: population evolution;
step 2.1, calculating the speed and the position of the particle i, and calculating each target value of the new position of the particle;
step 2.2 according to particle piTarget value f (p)i) Updating reference points
Step 2.3 updating the particle piIf the new location is better than the previous location, then pbest is seti＝piOtherwise, the original local optimal position pbest is reservedi；
Step 2.4 Using particles piUpdating the global optimal position of the neighbor particle, for particle piNeighbor particle pbGlobal optimum position gbest ofbIf p isiAs a neighbor pbIs better, then gbest is setb＝piOtherwise, not updating the global optimal position of the neighbor;
and 2.5, judging whether the evolution termination condition is met, if so, respectively storing the global optimal solution of the population and the physical attributes of the diameters, the linear densities and the like of the branch sections of the corresponding cable layout in an XML file, and stopping population evolution, otherwise, continuing the second step.
7. The method of claim 1, further comprising: in the step (5), the process of generating and assembling the geometric model of the cable assembly is as follows:
the first step is as follows: reading a cable layout XML file, reconstructing to obtain physical attributes of the cable such as the diameter, the linear density, the minimum bending radius, the looseness and the like of each branch section, and a discrete path point set of each branch section;
the second step is that: setting physical attributes of each branch section of the cable according to the CAD secondary development interface, generating a continuous path of each branch section of the cable assembly according to discrete path points of each branch section and fitting a sample curve, and creating and generating a geometric model of each branch section;
the third step: and setting an assembly coordinate system of the cable assembly according to the position of each port, and completing the assembly of the cable geometric model to the electromechanical product geometric model.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010061023.9A CN111274757B (en) | 2020-01-19 | 2020-01-19 | Implementation method for automatic layout of electromechanical product multi-branch cable assembly based on multi-objective optimization |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010061023.9A CN111274757B (en) | 2020-01-19 | 2020-01-19 | Implementation method for automatic layout of electromechanical product multi-branch cable assembly based on multi-objective optimization |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN111274757A true CN111274757A (en) | 2020-06-12 |
| CN111274757B CN111274757B (en) | 2024-01-26 |
Family
ID=71001781
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010061023.9A Active CN111274757B (en) | 2020-01-19 | 2020-01-19 | Implementation method for automatic layout of electromechanical product multi-branch cable assembly based on multi-objective optimization |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111274757B (en) |
Cited By (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111859591A (en) * | 2020-07-22 | 2020-10-30 | 成都蓉软科技有限公司 | Automatic wire and cable layout method and device |
| CN112115675A (en) * | 2020-09-21 | 2020-12-22 | 长春理工大学 | Complex wire harness tooling plate design system |
| CN112906170A (en) * | 2021-01-29 | 2021-06-04 | 奇瑞汽车股份有限公司 | Method and device for quickly calculating optimal position of wire harness diagram wire contact |
| CN112906082A (en) * | 2021-02-07 | 2021-06-04 | 南京航空航天大学 | MBD model of cable assembly and automatic generation method thereof |
| CN113987718A (en) * | 2021-11-17 | 2022-01-28 | 中国矿业大学 | Product change scheme design method based on multi-objective particle swarm optimization |
| FR3114894A1 (en) * | 2020-10-05 | 2022-04-08 | Leoni Wiring Systems France | Method for determining an optimized spatial configuration of electrical wiring |
| CN114488785A (en) * | 2021-08-09 | 2022-05-13 | 宁波大学 | MFC actuator trajectory tracking method |
| CN115329710A (en) * | 2022-08-26 | 2022-11-11 | 苏州大学 | Heat pipe constraint component layout optimization method based on genetic algorithm |
| CN115471143A (en) * | 2022-11-10 | 2022-12-13 | 中铁第一勘察设计院集团有限公司 | Method and system for arranging indoor equipment of railway communication machinery and storage medium thereof |
| CN111859591B (en) * | 2020-07-22 | 2024-06-04 | 成都蓉软科技有限公司 | Automatic layout method and device for wires and cables |
Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109871592A (en) * | 2019-01-25 | 2019-06-11 | 南京航空航天大学 | A kind of spatial discretization model towards electronic product cable laying layout optimization |
-
2020
- 2020-01-19 CN CN202010061023.9A patent/CN111274757B/en active Active
Patent Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109871592A (en) * | 2019-01-25 | 2019-06-11 | 南京航空航天大学 | A kind of spatial discretization model towards electronic product cable laying layout optimization |
Non-Patent Citations (3)
| Title |
|---|
| 付宜利;封海波;孙建勋;李荣;马玉林;: "机电产品管路自动敷设的粒子群算法", 机械工程学报, no. 11 * |
| 王发麟: "复杂机电产品线缆敷设若干关键技术研究", 《中国优秀博士学位论文全文数据库》, pages 30 - 46 * |
| 王成恩;柳强;白晓兰;王健熙;李明;: "航空发动机复杂约束空间内管路敷设技术", 计算机集成制造系统, no. 11 * |
Cited By (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111859591B (en) * | 2020-07-22 | 2024-06-04 | 成都蓉软科技有限公司 | Automatic layout method and device for wires and cables |
| CN111859591A (en) * | 2020-07-22 | 2020-10-30 | 成都蓉软科技有限公司 | Automatic wire and cable layout method and device |
| CN112115675A (en) * | 2020-09-21 | 2020-12-22 | 长春理工大学 | Complex wire harness tooling plate design system |
| FR3114894A1 (en) * | 2020-10-05 | 2022-04-08 | Leoni Wiring Systems France | Method for determining an optimized spatial configuration of electrical wiring |
| CN112906170A (en) * | 2021-01-29 | 2021-06-04 | 奇瑞汽车股份有限公司 | Method and device for quickly calculating optimal position of wire harness diagram wire contact |
| CN112906082B (en) * | 2021-02-07 | 2024-02-27 | 南京航空航天大学 | Automatic generation method of MBD model of cable assembly |
| CN112906082A (en) * | 2021-02-07 | 2021-06-04 | 南京航空航天大学 | MBD model of cable assembly and automatic generation method thereof |
| CN114488785A (en) * | 2021-08-09 | 2022-05-13 | 宁波大学 | MFC actuator trajectory tracking method |
| CN114488785B (en) * | 2021-08-09 | 2023-11-14 | 宁波大学 | MFC actuator track tracking method |
| CN113987718B (en) * | 2021-11-17 | 2022-06-03 | 中国矿业大学 | Product change scheme design method based on multi-objective particle swarm optimization |
| CN113987718A (en) * | 2021-11-17 | 2022-01-28 | 中国矿业大学 | Product change scheme design method based on multi-objective particle swarm optimization |
| CN115329710A (en) * | 2022-08-26 | 2022-11-11 | 苏州大学 | Heat pipe constraint component layout optimization method based on genetic algorithm |
| CN115329710B (en) * | 2022-08-26 | 2023-08-29 | 苏州大学 | Heat pipe constraint assembly layout optimization method based on genetic algorithm |
| CN115471143A (en) * | 2022-11-10 | 2022-12-13 | 中铁第一勘察设计院集团有限公司 | Method and system for arranging indoor equipment of railway communication machinery and storage medium thereof |
Also Published As
| Publication number | Publication date |
|---|---|
| CN111274757B (en) | 2024-01-26 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN111274757B (en) | Implementation method for automatic layout of electromechanical product multi-branch cable assembly based on multi-objective optimization | |
| Niu et al. | Ship Pipe Routing Design Using NSGA‐II and Coevolutionary Algorithm | |
| CN109063381B (en) | Automobile wire harness process design method and system based on CAD platform | |
| CN104679947A (en) | Automatic generation method of cable component optimizing structure of mechanical and electrical product | |
| CN111426323B (en) | Routing planning method and device for inspection robot | |
| Zhao et al. | Multi-branch cable harness layout design based on genetic algorithm with probabilistic roadmap method | |
| US11748547B2 (en) | Method of determining a three-dimensional layout of electrical connections of an electric component | |
| CN111030100B (en) | Power distribution network PMU optimal configuration method based on customized inheritance | |
| Sheng et al. | A pointer neural network for the vehicle routing problem with task priority and limited resources | |
| CN111537831A (en) | Power distribution network line fault positioning method and device | |
| Ng et al. | The design and planning of cable harness assemblies | |
| CN113486446B (en) | Single-pipeline multi-target optimization layout method in aircraft fuel tank | |
| KR101722393B1 (en) | Method of selecting position for offshore substation in the wind power plant and method of designing for power grid design in the wind power plant | |
| CN112966419B (en) | Multi-field coupling effect structure design method combining topology optimization and shape optimization | |
| Thantulage | Ant colony optimization based simulation of 3D automatic hose/pipe routing | |
| Blokland et al. | Literature survey on automatic pipe routing | |
| Karlsson et al. | Automatic cable harness layout routing in a customizable 3D environment | |
| CN116739940A (en) | Point cloud completion method, device, equipment and medium | |
| CN112968398B (en) | Intelligent wiring method for BIM cable bridge based on inventory list | |
| Liu et al. | Integrated optimization of pipe routing and clamp layout for aeroengine using improved moalo | |
| Masoudi | Geometric-based optimization algorithms for cable routing and branching in cluttered environments | |
| CN109411025B (en) | Modeling method of mixed dislocation bifurcation atomic structure | |
| Zhang et al. | Multi-objective layout optimization of aircraft multi-branch cable harness based on MOPSO/D | |
| Li | HYBRID OPTIMIZATION ALGORITHM FOR CABLE DESIGN OF ELECTROMECHANICAL PRODUCTS BASED ON A* AND GENETIC ALGORITHM | |
| CN104809280A (en) | Cable interference detection method based on geometrical characteristics |
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 | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |