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Modal analysis and parametric model identification play a fundamental role in many fields, especially for the optimization and vibration control of civil structures and complex mechanical systems. In the last decades these techniques have been frequently applied for the development of innovative cutting tools and CNC machine tools. Although several methodologies are available in literature for parametric model identification, there is still a lack of an effective and robust algorithm. In this paper a new algorithm for automatic identification of a parametric model of a linear dynamic Single Input Single Output system with Multiple Degrees of Freedom is presented. Some recent approaches perform the Wavelet decomposition of the Impulse Response in the time-frequency domain. Here a Wavelet-like decomposition of the Frequency Response in the frequency-damping domain is introduced for vibration modes recognition. Afterwards, advanced statistical approaches are applied for vibration modes selection and model generation. The method was successfully tested on a complicated frequency response characterized by several vibration modes, which was obtained from experimental modal analysis performed on a circular saw blade

Wavelet-like Analysis in the Frequency-Damping Domain for Modal Parameters Identification