The main aim of this project is to determine the quality of discharge in wire electrical discharge machining from a database created with a comprehensive set of experiences in both stable and degraded regimes. The project focuses on the study and description of the quality of discharge so that in the future, the control system of the machine is capable of detecting the tendency of the process early and can correct the malfunctioning in advance. Thus, based on previous results (Project “Empirical modelling...

Based on results from previous projects (Empirical modelling of Wire electrical discharge machining to optimise the discharge quality, and Analysis and Diagnosis of discharge quality in wire electrical discharge machining), which show that, although the basic features of the degraded behaviours are the same in both thicknesses analysed, the thresholds met by virtual measures differ. Thus, we propose the definition of one structure that can automatically adapt parameters in a given range of thicknesses, with the aim of...

As part of the grinding process, the aim of this project is to implement a hybrid model in which the artificial neural networks are a necessary complement to the analytic models.  In particular, this approach allows for obtaining parameters of the models that are closer to reality and that allow for, as well as improved knowledge of the process, better simulation of its behaviour with the waiting time of the machine. transfer rumours Thus, we propose the design of an intelligent system capable of estimating the...