Vision Positioning Method of Cutter Head of Milling Machine

Abstract

The invention relates to a visual positioning method for a milling machine tool bit, and the method comprises the steps: firstly carrying out the graying preprocessing of color image data of a to-be-positioned milling machine tool, extracting highlight details and shadow details, and solving the mean value of a highlight detail image and a shadow detail image, and obtaining a fused gray image; regenerating features based on a deep convolutional neural network UNet, and obtaining a high-precision tool bit position through post-processing of data and key point position regression. According tothe method, only ambient light or a common point light source is needed, the requirements of high light of metal on the light source and the influence on the positioning precision of the cutter are overcome, the size of the detection system is reduced, and compared with a machine vision algorithm, the image processing speed is higher, the system stability is better, the detection cost is low, thepositioning time is short, and the efficiency is high.

Description

[0001] (1) Technical field: [0002] The invention relates to a cutter head positioning method, in particular to a milling machine cutter head visual positioning method. [0003] (two), background technology: [0004] At present, machine vision detection technology is mainly used to detect the position of milling machine tool head. The commonly used detection methods include binary segmentation and edge-based model fitting. When using visual inspection technology to detect the position of the milling machine tool head, the probe can be omitted, and only the visual inspection technology can be used to calibrate the positional relationship between the spindle and the datum. For traditional milling machines or engraving machines, after manual tool change Automatic calibration of tool axis offset. [0005] In the above position detection method, the positioning of the milling machine head requires feature extraction and segmentation operations. The corresponding detection paramete...

AI Technical Summary

Problems solved by technology

[0005] In the above position detection method, the positioning of the milling machine head requires feature extraction and segmentation operations. The corresponding detection parameters, feature positions and related filtering methods need to be manually designed. For various tools, each tool needs to be designed separately. program

At the same time, the detection environment requires a special light source. If the detection light source changes, some methods based on edge detection may not be able to detect the characteristics of the tool under the new light, so that the tool cannot be positioned

[0006] In addition, these traditional visual inspection systems need to be separately integrated into a fixed position of the machine tool, which increases the volume of the machine tool and takes up more space

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