Browsing by Author "Song, Hanwen"

Now showing 1 - 2 of 2
  • Thumbnail Image
    Item
    Comparison of nonlinear system identification methods for free decay measurements with application to jointed structures
    (Elsevier, 2019) Jin, Mengshi; Brake, Matthew R.W.; Song, Hanwen
    Assembled structures are nonlinear. The sources of this nonlinearity could include the jointed interfaces, damage and wear, non-idealized boundary conditions, or other features inherent in real parts. To study these systems and to ascertain if they will be operating in a regime in which the nonlinearity is prominent,ﾠnonlinear system identificationﾠtechniques are needed to assess and characterize the nature of the nonlinearity in the structure. Significant progress over the last few years has focused on using nonlinear system identification to identify damage and other deviations from idealized structures. This research reviews nine different methods for nonlinear system identification (restoring force surface,ﾠHilbert transform, directﾠquadrature, zero-crossing,ﾠshort-time Fourier transform, Gaborﾠwavelet, Morlet wavelet, Morse wavelet, and a neural network-based algorithm) in order to assess their accuracy. The methods are compared by identifying characteristics of two systems: a singleﾠdegree of freedomﾠmodel of a Duffing oscillator and measured data from a jointed structure. Asﾠneural networksﾠare not commonly used for system identification, multiple variations of the method are investigated to study its effectiveness.ﾠPerturbationﾠanalysis is conducted to see the efficacy of the different methods for identifying parameters across a large range of design spaces, and the advantages and disadvantages of each method are discussed. The primary contribution of this paper is a comparison on both analytical and experimental data of multiple widely used system identification methods, and an assessment of when each method is most and least applicable, specifically in the context of jointed structures.
  • Thumbnail Image
    Item
    Identification of Instantaneous Frequency and Damping From Transient Decay Data
    (ASME, 2020) Jin, Mengshi; Chen, Wei; Brake, Matthew R.W.; Song, Hanwen
    Jointed interfaces, damage, wear, or non-idealized boundary conditions often introduce nonlinear characteristics to assembled structures. Consequently, extensive research has been carried out regarding nonlinear system identification. The development of nonlinear system identification is also enabling the intentional application of nonlinearities towards practical fields such as vibration control and energy harvesting. This research proposes a nonlinear identification procedure that consists of two steps: first, the raw data is filtered by the Double Reverse Multimodal Decomposition method that involves system reconstruction, expansion, and filtering twice. Second, the Peak Finding and Fitting method is applied to the filtered signal to extract the instantaneous amplitude and frequency. The identification procedure is applied to the measured responses from a jointed structure to assess its efficacy. The results are compared with those obtained from other well-known methods—the Hilbert transform and zero-crossing methods. The comparison results indicate that the Peaking Finding and Fitting method extracts the amplitude of the response signal more accurately. Consequently, this yields a higher signal-to-noise ratio in the extracted damping values. As a recommended last step, uncertainty assessment is conducted to calculate the 95% confidence intervals of the nonlinear properties of the system.