Abstract
This paper presents a new approach in supervision and diagnosis of the cylindrical surface grinding process. Therefore a combination of a process- and a signal-model is used to detect tool wear and grinding chatter oscillations. For the experimental identification of the model parameters a robust least squares algorithm is proposed. Experiments with different series of workpieces were carried out and the method was applied to the experimental data. The results show, that with the process-model approach the tool wear and the influence of wrong process adjustments and drimming conditions can be supervised. The signal-model approach can be used to detect chatter oscillations.
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