Modeling and analysis of nonlinear dynamics of machine tool sliding guide

The sliding guide plays a crucial role in CNC (Computerized Numerical Control) machine tools, as its dynamic characteristics can significantly impact the machining quality and reliability. Therefore, this study focuses on the analytical modeling and analysis of the sliding guide system. Firstly, a static model of the sliding guide system is established based on fractal theory. The accuracy of the static model is verified through loading experiments. Utilizing the developed model, the influence of relevant parameters on the bond surface stiffness is analyzed. Subsequently, the concentrated mass method is applied to further develop a nonlinear dynamics model of the system based on the static model. The nonlinear dynamical equation is solved using the Runge–Kutta method. The vibration responses at various excitation frequencies are measured and compared with simulation results, which show good agreement. Lastly, based on the established dynamic model, the study investigates the effects of parameters such as external load, sliding guide material, excitation frequency, tilting surface angle, and slider mass on the dynamic characteristics of the sliding guide system. The main result of this research is to establish the static model of wedge sliding guide based on fractal theory, and further establish the dynamic model of wedge sliding guide on this basis. On the basis of the dynamic model, relevant parameters are discussed, and the effects of different parameters on the dynamic characteristics of the sliding guideway are obtained through the parameter discussion. Based on the results of parametric discussion, the performance of sliding guide can be enhanced by changing the parameters. This study helps to prevent resonance and instability in sliding guide systems. By investigating the analysis and modeling of the sliding guide system, this study aims to enhance the understanding of its dynamic behavior and improve the overall performance of CNC machine tools.