Vermicular graphite cast iron, as a material that can replace gray cast iron, will be widely used in the future. Now we need to solve the problem of poor machinability of vermicular cast iron. Compared with gray cast iron, the tool life of vermicular cast iron is reduced and the production cost is high. Based on the dynamic mechanical behavior of vermicular cast iron, this study constructs the constitutive equation of vermicular cast iron under high temperature and high strain rate, guides the machining simulation of vermicular cast iron, improves the simulation accuracy of machining and reduces the cost of experimental research. In order to solve the problem that cracks are easy to appear in the processing of vermicular cast iron with coated cemented carbide at high speed, PCBN tool is selected for milling vermicular cast iron. At the same time, a reasonable cutting data reasoning model is constructed from the existing cutting data to provide reasonable cutting parameters for cutting workers.
(1) The static tensile test of vermicular graphite cast iron and Hopkinson compression bar test at high temperature and high strain rate are carried out. The J-C constitutive equation of vermicular graphite cast iron at high temperature and high strain rate is constructed and its effectiveness is verified.
(2) The cutting simulation of vermicular graphite cast iron is carried out, and the orthogonal turning experiment and orthogonal milling experiment are carried out respectively to verify the effectiveness of the constitutive equation established in this study.
(3) The cutting force, cutting temperature, tool wear and machined surface integrity of PCBN tool in high-speed milling of vermicular cast iron were studied.
(4) Using the existing cutting data, a reasoning model of vermicular cast iron cutting parameters based on ant colony neural network is constructed, and the effectiveness of the model is verified.