Reliable material damping ratio determination in machine tool structures

The determination of material damping ratios in machine tools is afflicted with considerable uncertainties. For the estimation of damping ratios different methods are available, each with specific model assumptions and parameters. Depending on the experience already gained with one method, the quality of the resulting values therefore can vary considerably. This paper proposes the simultaneous application of two different calculation methods, namely the logarithmic decrement and the bandwidth method, to the same measured signal. Assuming a decaying, time-limited and very lightly damped response signal, both methods cannot be applied in their original form. Therefore a filter-based logarithmic decrement and a frequency resolution enhanced bandwidth method are used. To demonstrate the capability of the approach, both methods are applied to an analytical three-degree-of-freedom system derived from a measured structure. The damping ratios yielded by both methods deviate less than 1 % from the analytical value. Furthermore, in a real measurement with uncertain system properties and parameter choice, the combined use of both methods can be used to assess the uncertainty of the obtained values. The capability of the proposed method is demonstrated on the basis of the measurement of a small machine tool component.

[1]  C.E. Shannon,et al.  Communication in the Presence of Noise , 1949, Proceedings of the IRE.

[2]  F. Verdun,et al.  Effects of Noise, Time-Domain Damping, Zero-Filling and the FFT Algorithm on the “Exact” Interpolation of Fast Fourier Transform Spectra , 1988 .

[3]  E. Parloo,et al.  Improved modal parameter estimation for lowly damped systems using non-parametric exponential windowing techniques , 2005 .

[4]  A. F. Seybert,et al.  Estimation of damping from response spectra , 1981 .

[5]  Kenan Y. Sanliturk,et al.  Damping uncertainty due to noise and exponential windowing , 2011 .

[6]  D. K. Anthony,et al.  Improving the accuracy of the n-dB method for determining damping of non-lightly damped systems , 2010 .

[7]  Wodek Gawronski,et al.  Advanced Structural Dynamics and Active Control of Structures , 2004 .

[8]  M. P. Norton,et al.  On the estimation of loss factors in lightly damped pipeline systems: Some measurement techniques and their limitations , 1986 .

[9]  Alessandro Agneni,et al.  Damping measurements from truncated signals via Hilbert transform , 1989 .

[10]  Nuno M. M. Maia,et al.  Theoretical and Experimental Modal Analysis , 1997 .

[11]  J. Antoni Leakage-free identification of FRF's with the discrete time Fourier transform , 2006 .

[12]  Valana Wells,et al.  Modal parameter identification using the log decrement method and band-pass filters , 2011 .

[13]  Robert B. Randall Frequency Analysis , 1987 .

[14]  W. Bousman,et al.  Application on the moving-block analysis , 1981 .

[15]  L. Rabiner,et al.  The chirp z-transform algorithm , 1969 .

[16]  R.B. Lake,et al.  Programs for digital signal processing , 1981, Proceedings of the IEEE.

[17]  Richard H. Sherman,et al.  Chaotic communications in the presence of noise , 1993, Optics & Photonics.

[18]  Azizul H. Quazi,et al.  Representation and Analysis of Time‐Limited Signals Using a Complex Exponential Algorithm , 1969 .

[19]  W. Staszewski IDENTIFICATION OF DAMPING IN MDOF SYSTEMS USING TIME-SCALE DECOMPOSITION , 1997 .

[20]  F. H. Chu,et al.  EXPERIMENTAL DETERMINATION OF DAMPING IN MATERIALS AND STRUCTURES. , 1980 .