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A multi-dimensional direction selection assembly optimization method based on hybrid particle swarm optimization algorithm

A hybrid particle swarm and direction selection technology is applied in the multi-dimensional dimension chain optimization of parts and its selection and assembly pairing. The multi-dimensional direction selection assembly optimization field based on the hybrid particle swarm algorithm can solve the problem of product assembly success rate and assembly function requirements that cannot meet the design requirements. Requirements, assembly success rate, problems with assembly function requirements, parts size and geometric accuracy cannot be guaranteed, etc.

Active Publication Date: 2018-12-25
SOUTH CHINA UNIV OF TECH
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Problems solved by technology

[0003]1) When the design size and shape accuracy of the part are too high, and the processing and manufacturing capacity of the part cannot meet the design requirements, resulting in the part size and shape accuracy cannot be guaranteed, The assembly success rate and assembly function requirements of the product cannot meet the design requirements
[0004]2) Although the processing accuracy of the part meets the design level requirements of the part size and shape and position accuracy, the batch size or shape and position error does not meet the normal due to the large processing error When designing statistical laws such as distribution, there may also be problems with the assembly success rate and assembly function requirements of the product

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  • A multi-dimensional direction selection assembly optimization method based on hybrid particle swarm optimization algorithm
  • A multi-dimensional direction selection assembly optimization method based on hybrid particle swarm optimization algorithm
  • A multi-dimensional direction selection assembly optimization method based on hybrid particle swarm optimization algorithm

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Embodiment Construction

[0079] The embodiments are further described in detail below with reference to the accompanying drawings.

[0080] A multi-dimensional orientation selection assembly optimization method based on hybrid particle swarm optimization, comprising the steps of:

[0081] S1. Construct a multi-dimensional dimension chain model for the batch assembly of various parts;

[0082] S2, constructing a multi-objective optimization model for batch selection and assembly of various parts based on the multi-dimensional dimension chain model;

[0083] S3, using the hybrid particle swarm algorithm to solve the multi-objective optimization model, and finally obtain an assembly pairing scheme in the batch selection assembly of various parts.

[0084] In the step S1, the multi-dimensional dimension chain model is used to consider the assembly guarantee problem required by multiple assembly functions of the product at the same time when assembling various parts, and convert the assembly guarantee pro...

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Abstract

The invention discloses a multi-dimensional direction selection assembly optimization method based on a hybrid particle swarm algorithm, which comprises the following steps: S1, constructing a multi-dimensional dimension chain model aiming at the batch assembly problem of a plurality of parts; S2, based on the multi-dimensional dimension chain model, constructing a multi-objective optimization model for batch selection assembly of a plurality of parts; S3, solving the multi-objective optimization model by using the hybrid particle swarm optimization algorithm, and finally obtaining a pluralityof assembly pairing schemes in batch selection assembly of parts. Based on the hybrid particle swarm optimization algorithm, the invention solves the assembly matching problem of batch assembly of aplurality of parts in the selection assembly, obtains the average assembly precision of the batch products, has higher assembly success rate, and considers the assembly matching optimization of the multi-dimensional dimension chain model of the part assembly, and has more practical value.

Description

technical field [0001] The invention mainly relates to the field of batch selection assembly and manufacturing of various parts, in particular to the problem of multi-dimensional dimension chain optimization of parts and the problem of selecting assembly pairing, product tolerance analysis and tolerance synthesis, and in particular to a multi-dimensional hybrid particle swarm algorithm-based multi-dimensional Orientation selects the assembly optimization method. Background technique [0002] Assembly is one of the important links in the product manufacturing process. In the mass assembly process, the assembly success rate and assembly function requirements are important indicators of product assembly assurance. The assembly success rate and assembly function requirements of the product are affected by the comprehensive effect of the size and shape and position accuracy of the matching features of the parts; when the size and shape and position accuracy of the matching featu...

Claims

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Application Information

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IPC IPC(8): G06F17/50G06N3/00
CPCG06N3/006G06F2111/06G06F30/20Y02P90/30
Inventor 刘伟东刘屿郭锦辉
Owner SOUTH CHINA UNIV OF TECH
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