Integral type spiral milling cutter wear image acquisition device and method based on machine vision

Abstract

The invention provides integral type spiral milling cutter wear image acquisition device and method based on machine vision. The integral type spiral milling cutter wear image acquisition device based on machine vision is simple in structure, reasonable in design and convenient to operate, the risks of workpiece scrappage and machine tool damage caused by cutter wear in the actual processing process are reduced, and a cutter is ensured to process constantly with a normal cutting state. The device comprises an installation base, a circumferential rotation assembly and a profile fixing frame, wherein the circumferential rotation assembly comprises an annular guide rail fixedly arranged on the installation base by adopting a cutter axis as a center, multiple circumferential sliding blocks in sliding fit to the circumferential direction of the annular guide rail, an inner gear ring fixed to the inner side of the annular guide rail, and a drive gear meshing with the inner gear ring; the profile fixing frame is arranged in a frame type and is fixed onto the multiple circumferential sliding blocks; a stepping motor, a light source and a camera are fixed onto the profile fixing frame; an output shaft of the stepping motor is perpendicularly and fixedly connected with the drive gear; and the light source and the camera are arranged around the cutter axis and are used for shooting a front cutter surface, a bottom blade and a back cutter surface of the integral type spiral milling cutter.

Description

technical field [0001] The invention relates to the field of detection of the damage state of the integral spiral milling cutter, in particular to a machine vision-based image acquisition device and method for the damage of the integral spiral milling cutter. Background technique [0002] Tool wear and tear is one of the important factors affecting product processing quality and production efficiency. In the actual metal cutting process, if the abnormality of the tool is not found in time and effectively, it is likely to cause the machining quality of the workpiece to be out of tolerance or even damage the machine tool, resulting in very large economic losses. [0003] Tool wear is a gradual change process, and damage is a major form of tool failure when the tool is cut to a certain extent or caused by harsh cutting conditions, especially for brittle tools, when cutting difficult-to-machine materials (such as Titanium alloys, nickel-based superalloys, etc.) or intermittent ...

AI Technical Summary

Problems solved by technology

However, the prerequisite for the application of this technology is to accurately and reliably collect the image of the damaged area of ​​the tool. Otherwise, on the one hand, it will increase the complexity of subsequent image processing, and on the other hand, the accuracy of calculation results will also decrease.

At present, most of the tool wear and damage detection objects based on machine vision are turning tools. The integral helical milling cutter has a more complex geometric structure than the turning tool. The image acquisition scheme of the turning tool is not suitable for the integral helical milling cutter. Generally, there are multiple cutting edges, and the rounded corners have different structural forms, so it is necessary to develop a special image acquisition device

At the same time, in the milling process, multiple cutting areas are often involved in the processing at the same time, so it is necessary to consider dividing it into three different cutting parts: the rake face, the flank face and the tool tip. Most of the current image acquisition devices and solutions are The above-mentioned multi-region image acquisition cannot be effectively realized, resulting in the limitation of the application and development of the tool state detection technology based on machine vision

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