Industrial part defect detection interval clustering method based on combinatorial optimization algorithm

A combination optimization and defect detection technology, applied in computer parts, computing, image data processing, etc., can solve problems such as not being optimal, complex setting interval combinations, and different optical surfaces.

Active Publication Date: 2021-10-22
CHANGZHOU MICROINTELLIGENCE CO LTD
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Problems solved by technology

This leads to some interval combinations are not a better result
At the same time, the optical surface of the same defect is different, which makes the combination of setting intervals complicated

Method used

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  • Industrial part defect detection interval clustering method based on combinatorial optimization algorithm
  • Industrial part defect detection interval clustering method based on combinatorial optimization algorithm
  • Industrial part defect detection interval clustering method based on combinatorial optimization algorithm

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[0030] In order to make the technical problems, technical solutions and beneficial effects solved by the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0031] See Figure 4 and Figure 8 , a kind of industrial part defect detection interval clustering method based on combinatorial optimization algorithm of the present invention, concrete steps are as follows:

[0032] The first step, data collection: the equipment machine takes a picture of the workpiece, reads the contour points (pixel coordinates) in the original picture, and completes the data collection work. Among them, the equipment machine can be electronic 3C surface defect appearance inspection equipment. The workpieces are electronic 3C workpieces, such as ...

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Abstract

The invention discloses an industrial part defect detection interval clustering method based on a combinatorial optimization algorithm, and the method comprises the following specific steps: 1, collecting data; step 2, performing data cleaning; 3, balancing data distribution; step 4, performing feature selection; 5, selecting positive sample data points, setting interval combinations, gradually shrinking intervals for optimization, and generating rules; and 6, removing the data in the rule from the data set, repeating the step 5 for the remaining data until all positive samples are selected by the rule, obtaining a series of rule descriptions, and ending the combinatorial optimization approximation algorithm. According to the method, positive and negative sample combination optimization clustering distinguishing is carried out on each optical surface with different defects of the industrial part, and certain robustness is achieved, so that multi-project defect accurate detection and division can be ensured.

Description

technical field [0001] The invention relates to the technical field of image data processing, in particular to an interval clustering method for defect detection of industrial parts based on a combined optimization algorithm. Background technique [0002] At present, most methods based on image data processing select physical quantity intervals for clustering based on experience. Differences in physical quantity weights, optical surfaces, and defect types affect the accuracy of positive and negative sample division, and there are many limitations. The most obvious is that the weight of the length and width physical quantities of linear defects is relatively large, and the physical quantity of area is not considered; for massive defects, the weight of the physical quantity of area is relatively large, and the physical quantity of length and width is not considered. This leads to suboptimal results for some interval combinations. At the same time, the optical surfaces of the ...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00G06K9/62
CPCG06T7/0004G06F18/23
Inventor 邱增帅王罡侯大为潘正颐
Owner CHANGZHOU MICROINTELLIGENCE CO LTD
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