A universal model for ruled surface's linear cutting with four-axis linkage machine
At present, the ruled surface's multi-axis manufacture is a hot research direction, but its universal mathematic model as key theory problem hasn't been established so far. To solve the problem of ruled surface's manufacture with four-axis linkage machine, we worked out the intersection line between the lateral surface and the horizontal plane of upper-lower guiding device through geometry method, and then established the universal mathematical model to manufacture the lateral surface of the work pieces under the condition that the lower guide is fixed. To verify the exactness of the model, we took the four-edge frustum and triangle-circle frustum as example. The model has universal use value in guiding practical manufacturing.
Identification of angular and positional deviations inherent to 5-axis machining centers with a tilting-rotary table by simultaneous four-axis control movements
This paper describes a method for identifying the eight deviations inherent to five axis control machining centers by means of simultaneous four-axis control movements. Some methods to identify the deviations have been proposed. However, a simultaneous four-axis control technique using a ball bar instrument has not been applied to the measurement of relative displacements between the main spindle and the worktable. Furthermore, the method for assessing the deviations from the trajectories has not been proposed. Thus, in this paper, a calibration method based on the simultaneous four-axis control technique is proposed for five axis control machining centers with a tilting rotary table. To confirm the validity of the proposed method, simulations were conducted. The trajectories were obtained by means of a mathematical model into which the eight deviations were substituted. In the first step, four of the eight deviations were estimated by an observation equation for which two measurement trajectories and six reference ones were used. In the second step, the remaining four deviations were geometrically calculated using the values estimated by the observation equation. As a result, it was found that the proposed method was sufficient to identify the deviations accurately.
Surface roughness monitoring by singular spectrum analysis of vibration signals
Abstract This study assessed two methods for enhanced surface roughness (Ra) monitoring based on the application of singular spectrum analysis (SSA) to vibrations signals generated in workpiece-cutting tool interaction in CNC finish turning operations i.e., the individual analysis of principal components (I-SSA), and the grouping analysis of correlated principal components (G-SSA). Singular spectrum analysis is a non-parametric technique of time series analysis that decomposes a signal into a set of independent additive time series referred to as principal components. A number of experiments with different cutting conditions were performed to assess surface roughness monitoring using both of these methods. The results show that singular spectrum analysis of vibration signal processing discriminated the frequency ranges effective for predicting surface roughness. Grouping analysis of correlated principal components (G-SSA) proved to be the most efficient method for monitoring surface roughness, with optimum prediction and reliability results at a lower analytical-computational cost. Finally, the results show that singular spectrum analysis is an ideal method for analyzing vibration signals applied to the on-line monitoring of surface roughness.