Modelling feed drives based on natural excitation—improving accuracy

Abstract

The current trend in machine tools requires higher efforts for process setup and process monitoring. Hence, digital models gain importance in the field of feed drives. To constantly adjust them to the real counterpart, parameter identification methods, which are suitable to be utilized during operation of the machine, are of primary importance. One of their main drawbacks is that their results strongly depend on the present system excitation. The paper focusses on the accuracy and presents an identification method as well as approaches to reduce excitation dependency. Subsequently, one combination of modules is applied to the NC-axes of a turning-milling-centre.