Stability prediction and optimization of multi-regenerative weak stiffness grinding system based on microstructured tool

Abstract

Chatter is a serious problem in grinding, which will directly affect machining accuracy, efficiency, tool wear and even damage machine tools. In order to understand and avoid grinding chatter, a stability prediction and optimization method of multi-regenerative weak stiffness grinding system based on microstructured tool is innovatively proposed. It is the first time to use microstructured tools to ensure the system stability without sacrificing the material removal rate, which offers promise for weak stiffness grinding. Firstly, a multi-random geometric model of microstructured grinding wheel is established, considering the shape, distribution, microstructure patterns and truing conditions of abrasive grains. On this basis, considering the regulating effect of microstructure patterns on workpiece regeneration delay and tool wear delay of grinding system with large aspect ratio, a multi-regeneration stability model based on microstructure tool is established. Then, the experiments of grinding wheel microstructuring, internal thread grinding and profile measurement are carried out. The results show that the theoretical model established can accurately predict the grinding stability boundaries. The microstructure types can be arranged in descending order according to the optimization degree of grinding chatter: composite type, cross type, oblique type and linear type. Compared with the grinding wheel without microstructures, the microstructured grinding wheel can increase the speed limit deviation by 12.2 % − 54.0 %, which basically solves the chatter problem at high rotation speed. The wear resistance of microstructured grinding wheel is improved by 44.2 %, the tooth profile angle error and bottom fillet radius of workpiece are reduced by 92.3 % and 90.4 % respectively, and the maximum tooth height difference and average tooth height error are reduced by 90.6 % and 87.5 % respectively.