Cutter wear prediction method based on milling power

Abstract

The invention relates to a cutter wear prediction method based on milling power. The method comprises the following steps: firstly, establishing a milling force-based power consumption model considering tool wear, and then establishing a milling power-based tool wear prediction model by neglecting the influence of feeding power consumption and adopting a reverse thrust method based on the power consumption model. According to the method, the tool wear in the milling process of the numerical control machine tool is predicted, high prediction precision can be obtained in the middle and later periods of tool wear, and a reliable basis can be provided for the opportunity of tool replacement.

Description

technical field [0001] The invention belongs to the field of mechanical processing, in particular to a tool wear prediction method based on milling power. Background technique [0002] In the process of processing difficult-to-machine materials, the interaction between the tool and the workpiece will lead to a series of defects such as severe tool wear, short tool life, low productivity, and high energy consumption. Among them, severe tool wear leads to frequent tool changes. It is the direct factor that limits the processing efficiency. And in the actual processing of difficult-to-machine materials, severe tool wear will also seriously damage the processing quality of the part surface. When the tool wear exceeds the preset wear limit threshold during processing and the tool is not replaced in time, it will seriously affect the processed parts. Surface quality and processing errors will reduce the service life and reliability of key structural parts of aero-engines, and may...

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Problems solved by technology

The document "Shi K N, Zhang D H, Liu N, et al. A Novel Energy Consumption Model for Milling Process Considering Tool Wear Progression[J]. Journal of Cleaner Production, 2018, 184:152-159." proposed a milling power-based Tool wear prediction method, which uses linear regression method to directly establish the functional relationship between milling power and tool wear, and does not study the principle of the influence of wear on milling power, and the functional relationship under each set of parameters needs to be recalibrated , this method lacks universality and persuasiveness, and it is difficult to accurately predict the tool wear in actual machining

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