On-Line Wear Measurement for Micro Turning Round Tip Tool Based on Machine Vision

It is well-known that tool life, surface quality, and production time are all impacted by wear on the cutting tool. In this research, we offer a new approach for real-time measurement of tool wear by means of machine vision, with the goal of creating a model for continuous monitoring of tool wear that can determine its degree of wear and its remaining usable life. Before anything else, the system uses machine vision to capture images of tool wear from an on-line CCD camera for a micro turning tool cutter. Captured photos of tool wear are analyzed to pinpoint tool tips and enhance wear detection zones. Images of the tool's wear are taken both before and during the machining operation so that the relevant image column detection is provided to scan pixel columns within the built wear detection zones in the vertical direction. To further improve the accuracy of identified wear edge points, a sub-pixel precise approach for detecting wear edge points is provided. Using the identified wear edge points, the amount of wear on the tool may be calculated. In a five-axis turning center, a micro turning tool cutter made of cemented carbide and stainless steel 1Cr18Ni9Ti are used to conduct experiments and validate a previously devised on-line tool wear assessment system. Results from measurements taken with a microscope and with the suggested approach are compared. The proposed method has been proven to be accurate and useful for real-time monitoring of tool wear.