Xinhua Yao

Intelligent fault diagnosis using rough set method and evidence theory for NC machine tools

An intelligent fault diagnostic method was presented to satisfy the development requirements of next-generation intelligent NC machine tools. The framework of fault diagnosis unit was established first, which consisted of signal acquisition, diagnosis rule extraction and fault identification mechanism. The technique of diagnosis rule extraction was then studied and an algorithm for acquisition of decision rules was proposed. The algorithm simplified the analysis of core properties and unnecessary properties, and calculated reduction set by the backwards tracking approach. This algorithm reduced complexity in reductions calculation and improved the efficiency of rule extraction. Finally, to process failure data collected by various sensors, a fault identification mechanism using evidence theory was presented. Feasibility and practicability of the proposed method has been verified by the development and the preliminary application of a prototype system.

Generating HSM-adapted pocketing tool path by region subdivision

High-speed machining (HSM) is an effective manufacturing process to produce parts. In HSM, it is required that the tool path should be smooth and the material removal rate should be constant. However, in geometry, it is nearly impossible to cover an arbitrary pocket with a single form of curves that satisfy both the above two requirements. In this paper, a compromise is made by subdividing the pocket into two kinds of regions: the HSM regions and the low-speed machining (LSM) regions. The HSM regions are selected to be the maximum inscribed circles (MICs) of the pocket. These MICs are calculated in an offset manner. Inside each HSM region, successive concentric circles are filled. The radii of the circles are controlled so that the material removal rate remains constant. The obtained concentric circles are then smoothly linked with pairs of arcs and used as the HSM tool path. For the rest LSM regions, conventional contour parallel tool paths are filled and low cutting speed is applied considering that there might be sharp angles on the pocket boundary. As the HSM regions could take up to 50% of the whole pocket and the cutting speed in HSM regions can be set very high, the average cutting speed for the whole pocket can be enhanced. Several pocket examples are used to verify the feasibility of the proposed HSM tool path generation method.

Volumetric error identification for CNC machine tool based on multi-body system and vector diagonal measurement

To reduce the influence of the geometric error on machining precision of CNC machine, a new method based on multi-body system theory and the laser sequential step diagonal vector measurement method to distinguish the geometric errors of CNC machine tool was presented. Firstly geometric errors modeling of CNC machine tool based on multi-body system theory was established. Then laser sequential step diagonal vector measurement method was introduced. Finally comparison experiments of the directly traditional method and the laser vector diagonal measurement method were done, besides, error compensation experiment of CNC machine tool was done. The results show that the new method combined multi-body system theory and laser sequential step diagonal vector measurement method is feasible to distinguish the geometric errors and after compensation machine accuracy is improved by 63%.

Smooth non-uniform rational B-spline (NURBS) machining with kinematic limit for short linear segments

Set of methods based on non-uniform rational B-spline (NURBS) are proposed in this article, which are adopted to improve the smoothness during short linear numerical control (NC) codes machining. The smoothness refers to two aspects: the contour fairness of CL trajectory and the machining stability of the machine tool. To obtain contour fairness, the optimised knots combination strategy (OKCS) is proposed in least square NURBS fitting from short linear segments, which generates NURBS curve for the next interpolating process. Sequentially, an axis-based look-ahead NURBS interpolator (ALANI) is designed for NURBS interpolation in order to improve the machining stability according to the kinematic limit. Both OKCS and ALANI are simulated and compared with congener algorithms, respectively. Furthermore, algorithms are implemented on digital signal processor (DSP) platform, and actual machining examples are presented at last.

The tool following function-based identification approach for all geometric errors of rotary axes using ballbar

This paper proposes a tool following function-based identification approach (TFFIA) for geometric errors of two rotary axes for one five-axis machine tool. It is comprehensive to identify all geometric errors of rotary errors. Firstly, synthetic error formulas of ballbar originate from the geometric error model of machine tools in order to consider the influences of 21 errors of three translational axes. It makes the approach more reasonable and precise. Secondly, the structures of three measurement patterns of TFFIA are described. Thirdly, in each pattern, errors of rotary axes affecting the accuracy of the sensitive direction are identified. As the result, the identification equations of all 20 errors coincide with the geometric properties of errors. Moreover, the impacts of setup errors of ballbar are eliminated with least square method to improve the precise of TFFIA. According to the structures of three patterns, only three installation of workpiece ball of ballbar are needed in the whole identification of two rotary axes to obtain the required ballbar readings. It greatly shortens the measurement time. Twenty geometric errors of two rotary axes are calculated with identification equations and ballbar readings. Finally, TFFIA is applied to a SmartCNC500 five-axis vertical machining center. The corresponding comparisons are proposed to verify the effectiveness and accuracy of TFFIA.