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Experimental Dynamic Identification of Backlash Using Skeleton Methods by Tegoeh Tjahjowidodo; Farid Al-Bender; Hendrik Van Brussel is a Engineering article available to read on EtoBox.

What is Experimental Dynamic Identification of Backlash Using Skeleton Methods about?

In this paper, we present a practical application of non-linear system identification, namely to a mechanical system with a backlash component, based on the skeleton curve reconstruction technique. In the case presented, the identification procedure employs the instantaneous amplitude and frequency of the input and the output of the base motion system under certain forced excitation. Hilbert transform analysis is a well-known method to extract these instantaneous characteristics; however, it is strictly exact only if the signal is weakly damped. A time-frequency representation technique, the Wavelet transform analysis, is therefore introduced to overcome this problem. The instantaneous characteristics in the signals can be obtained from the ridges and skeletons of the Wavelet transform. We apply both methods to the case study and compare the results, showing that the Wavelet-based extraction is generally more accurate than the Hilbert-analysis-based method. We show further that it is possible to obtain good non-linear identification results using either of the methods.

Who reads Experimental Dynamic Identification of Backlash Using Skeleton Methods?

It is typically read by researchers, students, and practitioners in Engineering.

Author
Tegoeh Tjahjowidodo; Farid Al-Bender; Hendrik Van Brussel
Publisher
Elsevier Science; Elsevier ; Elsevier Inc.; Elsevier BV (ISSN 0888-3270)
Published
2007
Language
EN
Field
Engineering (Physical Sciences)

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