Surface roughness evaluation method based on Hoyer coefficient of processed surface image

A technology of surface roughness and surface processing, which is applied in the field of surface roughness evaluation based on the Hoyer coefficient of processed surface images, can solve the problem of less involvement of feature extraction methods, and achieve the effect of fast evaluation

Active Publication Date: 2022-04-15
LYNCWELL INNOVATION INTELLIGENT SYST ZHEJIANG CO LTD +1
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  • Application Information

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Problems solved by technology

So far, data-driven methods (machine learning, etc.) have been widely used in the evaluation o

Method used

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  • Surface roughness evaluation method based on Hoyer coefficient of processed surface image
  • Surface roughness evaluation method based on Hoyer coefficient of processed surface image
  • Surface roughness evaluation method based on Hoyer coefficient of processed surface image

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Experimental program
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Embodiment 1

[0052] Embodiment 1: through a series of nodular cast iron 500-7 cutting experiments are used to carry out the verification of the method, its flow chart is as follows figure 1 shown, including the following steps:

[0053] S1: Three different machine tools (VMC650E / 850E, XK63100, NBH800) were used for cutting experiments. The size of the workpiece is fixed at 200mm x 140mm x 100mm. The technological parameters of the three machine tools during the experiment are as attached figure 2 Shown are: type VMC650E / 850E machine tool, the milling method is up-cut milling, the tool is a disc milling cutter, the feed speed is 200mm / min, the spindle speed is 960rpm, and the depth of cut is 0.5mm; type XK63100 machine tool, the milling method is down Milling, the tool is a disc milling cutter, the feed rate is 500mm / min, the spindle speed is 450rpm, and the depth of cut is 4mm; type NBH800 machine tool, the milling method is down milling, the tool is a disc milling cutter, the feed rat...

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Abstract

The invention discloses a surface roughness evaluation method based on a Hoyer coefficient of a processed surface image, which mainly comprises the following steps of: acquiring a processed surface picture, converting the processed surface picture into a gray scale space, and then correcting the direction of the image, so that the horizontal direction of the image is consistent with the processing feeding direction; according to the method, line gray information passing through the central point of the image is extracted in the horizontal direction of the image, the Hayer statistical value of the normalized line gray information is calculated, and finally, the surface roughness value of the workpiece is evaluated by adjusting the Hayer statistical value. The method has the advantages of being high in evaluation speed and small in influence on an existing production mode, and the surface roughness of the workpiece can be rapidly evaluated based on the Hoyer coefficient of the machined surface image after the workpiece is machined.

Description

technical field [0001] The invention relates to the technical field of digital image processing, in particular to a method for evaluating surface roughness based on the Hoyer coefficient of processed surface images. Background technique [0002] During the processing, the detailed information of the processing process will inevitably be left on the surface of the processed workpiece, and the change of its conditions will also be left on the topography of the processed surface. As a unique "sensor", how to extract the quality information of the processing process from the analysis of the processed surface texture, and finally extract the key feature information reflecting the surface roughness, is a key problem to be solved urgently. So far, data-driven methods (machine learning, etc.) have been widely used in the evaluation of workpiece surface roughness, however, methods for feature extraction are still less involved. Contents of the invention [0003] The object of the ...

Claims

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Application Information

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IPC IPC(8): G06T5/00G06T7/00G06T7/90
Inventor 李小刚卜宪伟邵正鹏陈雷林苏奔孙浩然孙维方冯光卢成绩黄海玉
Owner LYNCWELL INNOVATION INTELLIGENT SYST ZHEJIANG CO LTD
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