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Part classification method based on developable clustering

A classification method and part technology, applied in special data processing applications, instruments, electrical digital data processing, etc., can solve the problems of single classification feature, difficult threshold determination, low classification efficiency and accuracy, etc.

Active Publication Date: 2008-12-03
ZHEJIANG UNIV OF TECH
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AI Technical Summary

Problems solved by technology

[0027] In order to overcome the deficiencies of the existing parts and product classification methods, such as fuzzy correlation degree analysis, difficult quantification of threshold value determination, single classification feature, low classification efficiency and precision, the present invention provides a method with clear correlation degree analysis, high classification efficiency and high precision. Part Classification Method Based on Extension Clustering

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  • Part classification method based on developable clustering
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  • Part classification method based on developable clustering

Examples

Experimental program
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Effect test

Embodiment 1

[0068] refer to figure 1 , a part structure classification method based on extension clustering, starting from the distance formula, the moment value represents the comprehensive relationship change degree of elements. The correlation degree is established through the distance value, and the minimum correlation degree method is used to cluster and analyze the structural elements. It mainly includes two steps, the process of which is shown in figure 1 :

[0069] Step 1: Establish a correlation matrix between parts

[0070] 1) Extract the structural feature node domain of the part.

[0071] Suppose the product set A to be classified n ={R 1 , R 2 ,...,R n},

[0072] where the i-th product R i = { N 1 , c 11 , ...

Embodiment 2

[0107] refer to figure 1 and figure 2 , a method for classifying parts structures based on extension clustering, the processing flow of this embodiment is the same as that of Embodiment 1. The method mainly includes the following steps: Based on the above-mentioned theoretical analysis on extension clustering, an extension cluster analysis is performed on the design of the electric drill product family. In the structural design space, the basic components of the electric drill are set as follows: drill chuck, casing , drill shaft, fan, motor, bearing, and gear are composed of 7 parts. According to the relevant theory of extension clustering method, according to the demand, analyze the existing design products, extract the characteristic parts of each part, and establish the node domain matter-element model R of the parts according to the formula (1) (5) mi (i=1, . . . , 7). Assume that the value of the related part feature node field is:

[0108]

[0109] Select the be...

Embodiment 3

[0133] refer to figure 1 , figure 2 and image 3 , and the method in Example 1, a part structure classification method based on extension clustering, and the corresponding product design modeling software is used to establish and develop a prototype system of the electric drill product family design platform. System design process see image 3 .

[0134] System development background and operating environment: The algorithm of this system is mainly realized by VC6.0++. As a mainstream software development tool provided by Microsoft Corporation, VC6.0++ has unparalleled superiority in both application scope and execution efficiency. For the realization of engineering drawings, UG NX4.0 is selected as the software development platform, which can make full use of UG's product-level modeling technology and knowledge fusion technology to build automation of product design, and at the same time expand to the upper level design of products to a large extent , to realize the int...

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Abstract

The invention relates to a parts classification method based on expansible cluster, which comprises the following steps: 1) the node domain of the structural characteristic of parts is extracted; 2) the characteristic variable numerical value v and the interval V of the parts are determined; 3) the distance formula of each part structure is established; 4) the structural relevancy T(i, j) of parts Ri and Rj is determined; 5) numerical analysis is carried out to a symmetric matrix M; 6) the average relevancy numerical value of cluster analysis is established; 7) the n minus 2 symmetric matrix is obtained by utilizing the algorithm process of step 5) to the newly formed n minus 1 symmetric matrix, the processes are circulated, and when the minimum relevancy is more than K value, the cluster process is terminated and a unique cluster result is obtained: the category of products and the parts of each category. The invention provides a part classification method based on the expansible cluster, which has clear relevancy analysis, high classification efficiency and high accuracy.

Description

technical field [0001] The invention relates to a method for classifying component products. Background technique [0002] The concept of clustering is not a new concept. As early as in the construction industry in the early 20th century, the concept of dividing buildings into building units that can be freely combined according to their functions already existed. Connect and swap. Then, the concept of clustering was introduced into the machinery manufacturing industry, and people further linked the divided modules with the functions of physical products. The modules had clear function definition features, geometric connection interfaces, and function input and output interface features. With the development of computer software technology, the concept of modules has been used in the field of non-physical products. In the software industry, the concept of modules has been widely practiced, and the trend of modularization of large software systems (such as PTC's Windchill sy...

Claims

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Application Information

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IPC IPC(8): G06F17/50G06F17/30
Inventor 赵燕伟苏楠唐辉军赵福贵陈建桂元坤
Owner ZHEJIANG UNIV OF TECH
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