基于模态联合仿真寻优法的机床刀具结合部参数辨识方法

To ensure cutting stability and obtain accurate stability lobes diagram (diagram of cutting speed-cutting depth), need to get the frequency response function (FRF) of the tool nose. The tool tip is in a rotating state during processing, and its frequency response function cannot be directly obtained through the adhesive sensor.Therefore the dynamic parameter identification of the shank structure is the premise for accurate prediction the tool nose's FRF. In order to solve this problem, based on the theory of modal analysis, the method of modal joint optimization simulation was used to identify the dynamic parameter of the joint part. Through the evenly distributed spring damping units to simulate contact characteristics, the modal frequency and amplitude of the modal experiment and finite element analysis were served as the optimized constraints and optimized goals, which were combined with least square method to construct multi-objective optimization function, The nonlinear programming function optimization algorithm was used under MATLAB-ANSYS integration environment to realize the junction parameters identification. By used the method of construct the sample points in order to reduce the number of calls the ANSYS finite element analysis.By used the method of design variable sampling interval normalization process in order to avoid the unreasonable sampling. Brought the optimize recognition results into Ansys model for forecasting tool point FRF. The result showed that the two curves fitting degree of frequency response function are high and the first two order natural frequency of harmonic response analysis error are 0 and 0.04%. The feasibility of this method is verified, which can provide support for further obtaining stable lobe pattern.