Identification of modal parameters affecting the dynamic performance of CNC machine tools

To compute, predict and eliminate the instantaneous errors in CNC machine tools requires computationally fast and efficient algorithms. One important aspect of proficient condition monitoring is the use of a mathematical model, which adequately replicates the dynamic behaviour of the machine tool. Recent studies established that the models of the machine tool feed drives have to incorporate explicit damping factors in order to achieve a realistic dynamic performance. The necessity of determining fast and accurately the modal parameters of the model became very important. In answer to this, a novel application of wavelet transform for the determination of damping coefficients and resonance states for the feed drives was developed. It is based on wavelet analysis, which permits the simultaneous identification of signal characteristics in time and frequency domains. The wavelet transform is proved again to be an excellent analysis method for non-stationary signals allowing the individual identification of modes that are close to each other in frequency or damping ratios that are high.