A model-based approach for online estimation of surface waviness in roll grinding

Abstract

Vibrations onset represents a paramount issue in all grinding processes. The related surface defects appear in the form of micrometric waviness that decreases the finishing quality and in some cases the functionality of the ground workpieces: sometimes, these defects can be also marked on the grinding wheel surface. This paper presents an online model-based approach to identify and quantify the level of waviness starting from multiple acceleration measurements, allowing a continuous monitoring of wheel and/or workpiece defects. The identification algorithm, that exploits a linear model of machine and process dynamics, is based on the application of Least Squares method in the frequency domain. Experiments confirm the good performance of the algorithm that, hence, can be exploited for developing advanced control schemes of the grinding process

Experimental Analysis of Process Parameter Effects on Vibrations in the High-Speed Grinding of a Camshaft

“…Surface waviness is a positively correlated relationship with grinding depth, and the influence mechanism of the grinding velocity and workpiece speed on surface waviness is more complicated [20]; there is obvious interaction between the grinding velocity and workpiece rotational speed. Via matching process parameters with machine dynamics, more stable machining results can be obtained [21] and [22].…”

Frequency domain identification of grinding stiffness and damping

“…In order to minimize the effect of uncertainties on the Euclidean norm of the solution vector, the input/output pair has to minimize the ||•|| 2 -condition number of the identification matrix in Eq. (19). Since the condition number reflects the influence of the input excitation on the grinding process, the most suited input/output candidates are the process DoFs: the co-located FRFswhen input and output DoFs are the sameusually entail the maximum displacement amplitude.…”

“…In [18] grinding tests with variable workpiece dynamics were executed and compared to numerical simulations, in predicting cutting stability. In this scenario, process constants identification is important and can also support advanced schemes for wheel and workpiece waviness monitoring during chatter onset [19].…”

Model-based adaptive process control for surface finish improvement in traverse grinding

“…The estimation of the surface waviness is directly used by the described process controller, but also constitutes a significant realtime surface quality indication for machine operators. The so-called "waviness observer module" (WavObs), presented by Parenti et al [29] has been integrated in the process controller as a brick of the process monitoring layer. This algorithm estimates workpiece and wheel waviness in traverse grinding by adopting a dynamic model-based approach to process the acceleration signals captured on the machine.…”