CN103593531A - Method for evaluating virtual assembly time of engine through BP algorithm - Google Patents
Method for evaluating virtual assembly time of engine through BP algorithm Download PDFInfo
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- CN103593531A CN103593531A CN201310577494.5A CN201310577494A CN103593531A CN 103593531 A CN103593531 A CN 103593531A CN 201310577494 A CN201310577494 A CN 201310577494A CN 103593531 A CN103593531 A CN 103593531A
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Abstract
The invention discloses a method for evaluating virtual assembly time of an engine through the BP algorithm. The method for evaluating the virtual assembly time of the engine through the BP algorithm comprises the following steps that a model of the engine is established through CATIA; a human-computer interaction mode and an automatic reasoning mode are combined under a virtual environment so that generation of an assembly constraint matrix can be achieved; based on a CATIA/DELMIA simulation trial detaching assembly path plan, a virtual assembly operation environment is established and a virtual assembly operation process is created; an assembly path is measured and the assembly time is calculated; an assembly time evaluation model is established and the assembly time is evaluated. The method has a profound meaning in support tools for assembly design, product automatic assembly, parallel design in the CIMS environment and parallel engineering and the method has a significant research value on research of the assembling ability evaluation technology of products.
Description
Technical field
The invention belongs to assembling capacity research field, relate in particular to a kind of method that the BP of use algorithm is evaluated the virtual installation time of engine.
Background technology
Assembling capacity assessment technique research is towards the important component part in the design (DFA) of assembling.The assembling capacity of product refers to a kind of measurement to Product Assembly complexity, and it is relevant to structure, Assembling resource and the assembly method of product.The assembling capacity evaluation of product is focused on just should considering the assembling link of product and the impact of factor aspect other in the initial stage of design, assembly structure to product under the condition that meets the various performances of product improves, from being beneficial to the aspect of Product Assembly, start product design to evaluate, and pass through afterwards improved design project again according to evaluation result, the product designing not only can be assembled fast and efficiently, and reduce as much as possible assembly cost and mass customization.By the evaluation to product assembling capacity, designer can find the variety of issue existing in design at any time, thereby improve product design and assembly performance, raising quality, reduce the Product Assembly time, reduce costs, therefore the research of the assembling capacity assessment technique of product is had to important economic benefit.Meanwhile, the support facility towards the design of assembling to Parallel Design, concurrent engineering under product automation assembling, CIMS environment, all has deep meaning, and the research of therefore product being carried out to assembling capacity assessment technique has important researching value.
This technology development at home has at present been subject to obstruction, why causing this situation is due to nonstandard commercial system, to domestic, carry out technical information blockade abroad, the at present domestic design software towards assembling lacks very much, also there is to very large gap with exploitation with comparing abroad in the application of software, temporarily do not have sufficient theory to come support assemblies principle of design and design stability, and the personnel that are engaged in that are correlated with are also very rare, therefore, assembling capacity assessment technique uses all in the urgent need to research in theoretical developments and engineering practice.
Summary of the invention
A kind of method that the object of the present invention is to provide the BP of use algorithm to evaluate the virtual installation time of engine, be intended to provides a kind of theoretical reference for assembling capacity assessment technique in theoretical developments and engineering practice utilization.
The present invention is achieved in that a kind of method that the BP of use algorithm is evaluated the virtual installation time of engine comprises the model that uses CATIA to set up engine; Man-machine interaction mode under virtual environment and automated reasoning mode are combined, realize the generation of assembly constraint matrix; The assembly path planning of the emulation examination dismounting based on CATIA/DELMIA, builds virtual assembly work environment and creates virtual assembling course of action; Measure assembly path and calculate installation time; Set up installation time evaluation model and installation time evaluated.
Concrete steps are as follows:
Step 1, use CATIA set up the model of engine, select one-level assembly to simulate assembling.Set up the model of following 15 parts: (flywheel, bent axle, cylinder, piston, piston are buckled, gas admittance valve, air outlet valve, gear, cylinder cap, lighter, cylinder head, fuel tank, air strainer, flywheel lid, exhaust box.
Step 2, man-machine interaction mode under virtual environment and automated reasoning mode are combined, realize the generation of assembly constraint matrix.
The assembly path planning of step 3, the examination of the emulation based on CATIA/DELMIA dismounting, builds virtual assembly work environment and creates virtual assembling course of action.
Step 4, measure assembly path and calculate installation time.Measure the length of assembly path, then divided by the average translational speed of 0.5/ms, draw the installation time of each part.
Step 5, set up installation time evaluation model and installation time is evaluated.
Further, the spatial description of the constraint matrix described in step 2 is as follows:
(1) generation of free interference matrix
First first select the direction of (± x, ± y, ± z) axle, choosing of direction must cover all disassembly directions.If cij=1, represents that part i dismantles the obstruction that is subject to part j in the direction.If cij=0, represents that part i dismantles the obstruction that can not be subject to part j in the direction, obtain six free matrixes.
(2) integrated interference matrix
Based on the examination method of tearing open, six free interference matrixes in step 1 are merged into an integrated interference matrix.
(3) the manual planning of dismounting sequence
The manual planning of the dismounting sequence of integrated interference matrix, then, by sequence upset, draws assembling sequence.
Further, first step 5 needs to draw topology of networks according to experimental data, to network, after initialization, use function Trainrp to carry out, after 449 training, making network error square reach the level of error target goal=0.00001 to neural network.Now the early stage of network model, training finished, and based on BP neural network, the evaluation model of installation time was built up.Only need input evaluate sample by the achievement data sample after standardization, just can obtain evaluating data.
The standardization of sample
Because installation time and assembly quality are all that to be worth less evaluation better.So it is as follows that installation time is carried out to standardization:
T
i=1-（x
i-x
min）/(x
max-?x
min)
T
ifor standardization desired value; x
ibe i sample value; x
minfor i minimum value can getting; x
maxfor i maximal value can getting;
Assembly parts quality is carried out to standardization, and to carry out standardization as follows:
M
i=1-m
i/ m
always* 10
M
ifor standardization desired value, m
ibe i sample value, m
alwaysfor assembly gross mass.
Two samples are merged to standardization, the matrix after standardization is changed into ordered series of numbers as input vector, draw evaluation result.
effect gathers
The method that use BP algorithm of the present invention is evaluated the virtual installation time of engine, is used CATIA modeling, then carries out ELMIA assembling Sequence Planning and DELMIA assembling Sequence Planning, calculates installation time and carries out final BP and evaluate.For the design towards assembling, to the support facility of Parallel Design passage, concurrent engineering under product automation assembling, CIMS environment, all have a meaning of own profound, the research of product being carried out to assembling capacity assessment technique has important researching value.
Accompanying drawing explanation
Fig. 1 is the process flow diagram that use BP algorithm that the embodiment of the present invention provides is evaluated the virtual installation time of engine.
Embodiment
In order to make object of the present invention, technical scheme and advantage clearer, below in conjunction with drawings and Examples, the present invention is further elaborated.Should be appreciated that specific embodiment described herein, only in order to explain the present invention, is not intended to limit the present invention.
Fig. 1 shows the flow process that use BP algorithm of the present invention is evaluated the virtual installation time of engine, and as shown in the figure, the present invention is achieved in that a kind of method that the BP of use algorithm is evaluated the virtual installation time of engine comprises
S101: use CATIA to set up the model of engine;
S102: man-machine interaction mode under virtual environment and automated reasoning mode are combined, realize the generation of assembly constraint matrix;
S103: the assembly path planning of the emulation examination dismounting based on CATIA/DELMIA, build virtual assembly work environment and create virtual assembling course of action;
S104: measure assembly path and calculate installation time;
S105: set up installation time evaluation model and installation time is evaluated;
Concrete steps are as follows:
Step 1, use CATIA set up the model of engine, select one-level assembly to simulate assembling.Set up the model of following 15 parts: (flywheel, bent axle, cylinder, piston, piston are buckled, gas admittance valve, air outlet valve, gear, cylinder cap, lighter, cylinder head, fuel tank, air strainer, flywheel lid, exhaust box.
Step 2, man-machine interaction mode under virtual environment and automated reasoning mode are combined, realize the generation of assembly constraint matrix.
The assembly path planning of step 3, the examination of the emulation based on CATIA/DELMIA dismounting, builds virtual assembly work environment and creates virtual assembling course of action.
Step 4, measure assembly path and calculate installation time.Measure the length of assembly path, then divided by the average translational speed of 0.5/ms, draw the installation time of each part.
Step 5, set up installation time evaluation model and installation time is evaluated.
Further, the spatial description of the constraint matrix described in step 2 is as follows:
(1) generation of free interference matrix
First first select the direction of (± x, ± y, ± z) axle, choosing of direction must cover all disassembly directions.If cij=1, represents that part i dismantles the obstruction that is subject to part j in the direction.If cij=0, represents that part i dismantles the obstruction that can not be subject to part j in the direction, obtain six free matrixes.
(2) integrated interference matrix
Based on the examination method of tearing open, six free interference matrixes in step 1 are merged into an integrated interference matrix.
(3) the manual planning of dismounting sequence
The manual planning of the dismounting sequence of integrated interference matrix, then, by sequence upset, draws assembling sequence.
Further, first step 5 needs to draw topology of networks according to experimental data, to network, after initialization, use function Trainrp to carry out, after 449 training, making network error square reach the level of error target goal=0.00001 to neural network.Now the early stage of network model, training finished, and based on BP neural network, the evaluation model of installation time was built up.Only need input evaluate sample by the achievement data sample after standardization, just can obtain evaluating data.
The standardization of sample
Because installation time and assembly quality are all that to be worth less evaluation better.So it is as follows that installation time is carried out to standardization:
T
i=1-（x
i-x
min）/(x
max-?x
min)
T
ifor standardization desired value; x
ibe i sample value; x
minfor i minimum value can getting; x
maxfor i maximal value can getting;
Assembly parts quality is carried out to standardization, and to carry out standardization as follows:
M
i=1-m
i/ m
always* 10
M
ifor standardization desired value, m
ibe i sample value, m
alwaysfor assembly gross mass.
Two samples are merged to standardization, the matrix after standardization is changed into ordered series of numbers as input vector, draw evaluation result.
The method that use BP algorithm of the present invention is evaluated the virtual installation time of engine, is used CATIA modeling, then carries out ELMIA assembling Sequence Planning and DELMIA assembling Sequence Planning, calculates installation time and carries out final BP and evaluate.Support facility towards the design of assembling to Parallel Design, concurrent engineering under product automation assembling, CIMS environment, all has deep meaning, and the research of product being carried out to assembling capacity assessment technique has important researching value.
Although above-mentioned, by reference to the accompanying drawings the specific embodiment of the present invention is described; but be not limiting the scope of the invention; one of ordinary skill in the art should be understood that; on the basis of technical scheme of the present invention, those skilled in the art do not need to pay various modifications that performing creative labour can make or distortion still within protection scope of the present invention.
Claims (5)
1. a method of using BP algorithm to evaluate the virtual installation time of engine, is characterized in that, the method that this use BP algorithm is evaluated the virtual installation time of engine comprises:
Use CATIA to set up the model of engine; Man-machine interaction mode under virtual environment and automated reasoning mode are combined, realize the generation of assembly constraint matrix; The assembly path planning of the emulation examination dismounting based on CATIA/DELMIA, builds virtual assembly work environment and creates virtual assembling course of action; Measure assembly path and calculate installation time; Set up installation time evaluation model and installation time is evaluated.
2. the method that use BP algorithm as claimed in claim 1 is evaluated the virtual installation time of engine, is characterized in that, the method concrete steps that this use BP algorithm is evaluated the virtual installation time of engine are as follows:
Step 1, use CATIA set up the model of engine, select one-level assembly simulate assembling, set up the model of 15 parts below: flywheel, bent axle, cylinder, piston, piston are buckled, gas admittance valve, air outlet valve, gear, cylinder cap, lighter, cylinder head, fuel tank, air strainer, flywheel cover, exhaust box;
Step 2, man-machine interaction mode under virtual environment and automated reasoning mode are combined, realize the generation of assembly constraint matrix;
The assembly path planning of step 3, the examination of the emulation based on CATIA/DELMIA dismounting, builds virtual assembly work environment and creates virtual assembling course of action;
Step 4, measure assembly path and calculate installation time, measure the length of assembly path, then divided by the average translational speed of 0.5/ms, draw the installation time of each part;
Step 5, set up installation time evaluation model and installation time is evaluated.
3. the method that use BP algorithm as claimed in claim 2 is evaluated the virtual installation time of engine, is characterized in that, the spatial description of the constraint matrix described in step 2 is as follows:
(1) generation of free interference matrix
First first select (± x, ± y, ± z) direction of axle, choosing of direction must cover all disassembly directions, if cij=1, represents that part i dismantles the obstruction that is subject to part j in the direction, if cij=0, represent that part i dismantles the obstruction that can not be subject to part j in the direction, obtain six free matrixes;
(2) integrated interference matrix
Based on the examination method of tearing open, six free interference matrixes in step 1 are merged into an integrated interference matrix;
(3) the manual planning of dismounting sequence
The manual planning of the dismounting sequence of integrated interference matrix, then, by sequence upset, draws assembling sequence.
4. the method that use BP algorithm as claimed in claim 2 is evaluated the virtual installation time of engine, it is characterized in that, first step 5 needs to draw topology of networks according to experimental data, to network after initialization, use function Trainrp to carry out after 449 training neural network, make network error square reach the level of error target goal=0.00001, the training in early stage of network model finishes, based on BP neural network, the evaluation model of installation time is built up, only need input evaluate sample by the achievement data sample after standardization, just can obtain evaluating data.
5. the method that use BP algorithm as claimed in claim 4 is evaluated the virtual installation time of engine, is characterized in that the standardization of sample:
Because installation time and assembly quality are all that to be worth less evaluation better, so it is as follows that installation time is carried out to standardization:
T
i=1-（x
i-x
min）/(x
max-?x
min)
T
ifor standardization desired value; x
ibe i sample value; x
minfor i minimum value can getting; x
maxfor i maximal value can getting;
Assembly parts quality is carried out to standardization as follows:
M
i=1-m
i/ m
always* 10
M
ifor standardization desired value, m
ibe i sample value, m
alwaysfor assembly gross mass;
Two samples are merged to standardization, the matrix after standardization is changed into ordered series of numbers as input vector, draw evaluation result.
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| CN201310577494.5A CN103593531A (en) | 2013-11-19 | 2013-11-19 | Method for evaluating virtual assembly time of engine through BP algorithm |
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104122796A (en) * | 2014-07-17 | 2014-10-29 | 中国科学院自动化研究所 | Intelligent assembly sequence planning method |
| CN104794278A (en) * | 2015-04-21 | 2015-07-22 | 西安电子科技大学 | Optimizing method for product assembly sequences |
| CN106249705A (en) * | 2015-06-10 | 2016-12-21 | 通用汽车环球科技运作有限责任公司 | Assembly system configures |
Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN101739478A (en) * | 2008-11-17 | 2010-06-16 | 北京卫星环境工程研究所 | Spacecraft assembly simulation technique-based virtual assembly system and virtual assembly method |
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2013
- 2013-11-19 CN CN201310577494.5A patent/CN103593531A/en active Pending
Patent Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN101739478A (en) * | 2008-11-17 | 2010-06-16 | 北京卫星环境工程研究所 | Spacecraft assembly simulation technique-based virtual assembly system and virtual assembly method |
Non-Patent Citations (3)
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| HUANG Y M等: "Disassembly matrix for disassembly processes of products", 《INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH》 * |
| 冯禹等: "基于人工神经网络技术的产品可装配性评价", 《计算机集成制造***CIMS》 * |
| 杨骥: "飞机构件虚拟装配技术研究", 《中国优秀硕士学位论文全文数据库 工程科技Ⅱ辑》 * |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104122796A (en) * | 2014-07-17 | 2014-10-29 | 中国科学院自动化研究所 | Intelligent assembly sequence planning method |
| CN104794278A (en) * | 2015-04-21 | 2015-07-22 | 西安电子科技大学 | Optimizing method for product assembly sequences |
| CN106249705A (en) * | 2015-06-10 | 2016-12-21 | 通用汽车环球科技运作有限责任公司 | Assembly system configures |
| CN106249705B (en) * | 2015-06-10 | 2019-12-06 | 通用汽车环球科技运作有限责任公司 | Assembly system configuration |
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