Search Results (3)

Three-dimensional elliptical vibration assisted cutting technology has been widely used in the past few years. The piezoelectric stack drive structure is an important part of the three-dimensional elliptical vibration aided cutting system. Its piezoelectric hysteresis characteristics affects the final output of the elliptical trajectory. Aiming at this problem, a piezoelectric hysteresis modeling method based on a generalized Bouc–Wen model is presented in this paper. An improved flower pollination algorithm (IFPASO) was used to identify Bouc–Wen model parameters. Standard test result shows that IFPASO has better algorithm performance. The model identification effect experiment proved that the Bouc–Wen model obtained by IFPASO identification, the highest modeling accuracy of the three axial subsystems, can reach 98.86%. Therefore, the model can describe the piezoelectric hysteresis characteristics of the three axial subsystems of the 3D-EVC system effectively and has higher modeling accuracy and fitting accuracy. Full article

Three-dimensional elliptical vibration cutting (3D-EVC) is one of the machining methods with the most potential in ultra-precision machining; its unique characteristics of intermittent cutting, friction reversal, and ease of chip removal can improve the machinability of materials in the cutting processes. However, there is still not much research about the chattering phenomenon in the 3D-EVC process. Therefore, based on the empirical mode decomposition (EMD) technique and feature extraction, a chatter identification method for 3D-EVC is proposed. In 3D-EVC operations, the vibration signal is collected by the displacement sensors and converted to frequency domain signal by fast Fourier transform (FFT). To identify tool cutting state using the vibration frequency signal, the vibration signals are decomposed using empirical mode decomposition (EMD), a series of intrinsic mode functions (IMFs), so the instantaneous frequency can be reflected by the vibration signals at any point. Then, selecting the primary IMFs which contain rich chatter information as the object in feature extraction identification, and two identification indexes, that is, the mean square frequency and self-correlation coefficient, are calculated for the primary IMFs by MATLAB software, to judge the chatter phenomenon. The experimental results showed that the mean square frequency and self-correlation coefficient of the three cutting states increase with the increase in the instability of the cutting state. The effectiveness of the improved chatter recognition method in 3D-EVC machining is verified. Full article

The poor machinability of Ti-6Al-4V alloy makes it hard to process by conventional processing methods even though it has been widely used in military and civilian enterprise fields. Non-resonant three-dimensional elliptical vibration cutting (3D-EVC) is a novel cutting technique which is a significant development potential for difficult-to-cut materials. However, few studies have been conducted on processing the Ti-6Al-4V alloy using the non-resonant 3D-EVC technique, the effect of surface quality, roughness, topography and freeform surface has not been clearly researched yet. Therefore, the machinability of Ti-6Al-4V alloy using the non-resonant 3D-EVC apparatus is studied in this paper. Firstly, the principle of non-resonant 3D-EVC technique and the model of cutter motion are introduced. Then the tool path is synthesized. The comparison experiments are carried out with traditional continuous cutting (TCC), two-dimension elliptical vibration cutting (2D-EVC), and the non-resonant 3D-EVC method. The experimental results shown that the excellent surface and lower roughness (77.3 nm) could be obtained using the non-resonant 3D-EVC method; the shape and dimension of elliptical cutting mark also relates to the cutting speed and vibration frequency, and the concave/convex spherical surface topography are achieved by non-resonant 3D-EVC in the Ti-6Al-4V alloy. This proved that the non-resonant 3D-EVC technique has the better machinability compared with the TCC and 2D-EVC methods. Full article