Measurement uncertainty propagation in spindle error separation techniques - Investigation by means of stochastic spectral method. (June 2019)

• Record Type: Journal Article
• Authors: Shi, Shengyu; Zhang, Hao; Qu, Jinping; Jin, Gang; Kuschmierz, Robert; Czarske, Jürgen
• Is Part Of: International journal of machine tools & manufacture. Volume 141(2019)
• Page Start: 36
• Page End: 45
• Publication Date: 2019-06
• Subjects: Ultra-precision machining -- Two-step spindle error separation method -- Harmonic suppression problem -- Uncertainty propagation -- Roundness measurement; Machine-tools -- Periodicals; Manufacturing processes -- Periodicals; Machines-outils -- Périodiques; Fabrication -- Périodiques; Electronic journals; 621.902
• DOI: 10.1016/j.ijmachtools.2019.03.006
• Languages: English
• ISSNs: 0890-6955

Abstract

Abstract: The spindle is the most critical subsystem in almost all types of machine tools. Error separation techniques provide the state-of-the-art principles for the spindle error measurement, suffering no systematic deviation. However, although substantial research effort has been accomplished, particularly regarding their harmonic suppression problem, they have rarely been applied in industry due to the unpredictable and unstable measurement precision. In this context, this paper changes the research focus from the harmonic suppression problem to the propagation of the measurement uncertainty. First, the system model of the two-step error separation method (TSM) is established, from which the propagation law of the probe uncertainty is analytically derived. The propagation law allows for a quantitative prediction of the resulting uncertainty. Furthermore, three improved TSMs are put forward: the angle-optimized TSM, the hybrid TSM, and the fusion TSM, which enable a significant reduction of the measurement uncertainty and solve the harmonic suppression problem completely. Monte Carlo simulations and experiments validate the propagation law and the viability of the improved approaches. This research, for the first time, realizes the quantitative evaluation and reduction of the measurement uncertainty, and in our opinion, may bring about a paradigm shift for the error separation techniques. Highlights: Uncertainty propagation law in error separation methods is analytically derived. Monte Carlo simulation is performed for verifying the uncertainty propagation law. Improved methods are put forward for inhabiting the uncertainty propagation. Nature of the harmonic suppression problem is unveiled.