Spectral identification of nonlinear multi-degree-of-freedom structural systems with fractional derivative terms based on incomplete non-stationary data. (September 2020)
- Record Type:
- Journal Article
- Title:
- Spectral identification of nonlinear multi-degree-of-freedom structural systems with fractional derivative terms based on incomplete non-stationary data. (September 2020)
- Main Title:
- Spectral identification of nonlinear multi-degree-of-freedom structural systems with fractional derivative terms based on incomplete non-stationary data
- Authors:
- dos Santos, Ketson R.M.
Brudastova, Olga
Kougioumtzoglou, Ioannis A. - Abstract:
- Highlights: A spectral identification technique is developed for multi-degree-of-freedom systems. The technique can address nonlinear systems with fractional derivative terms. The technique can account for non-stationary data via harmonic wavelets. The technique can account for incomplete data via a compressive sampling treatment. Abstract: A novel spectral identification technique is developed for determining the parameters of nonlinear and time-variant multi-degree-of-freedom (MDOF) structural systems based on available input-output (excitation-response) realizations. A significant advantage of the technique relates to the fact that it can readily account for the presence of fractional derivative terms in the system governing equations, as well as for the cases of non-stationary, incomplete and/or noise corrupted data. Specifically, the technique relies on recasting the governing equations as a set of multiple-input/multiple-output systems in the wavelet domain. Next, an l 1 -norm minimization procedure based on compressive sampling theory is employed for determining the wavelet coefficients of the available incomplete non-stationary input-output data. Finally, these wavelet coefficients are utilized to reconstruct the non-stationary incomplete signals, and consequently, to determine system related time- and frequency-dependent wavelet-based frequency response functions and associated parameters. Two illustrative MDOF systems are considered in the numerical examples forHighlights: A spectral identification technique is developed for multi-degree-of-freedom systems. The technique can address nonlinear systems with fractional derivative terms. The technique can account for non-stationary data via harmonic wavelets. The technique can account for incomplete data via a compressive sampling treatment. Abstract: A novel spectral identification technique is developed for determining the parameters of nonlinear and time-variant multi-degree-of-freedom (MDOF) structural systems based on available input-output (excitation-response) realizations. A significant advantage of the technique relates to the fact that it can readily account for the presence of fractional derivative terms in the system governing equations, as well as for the cases of non-stationary, incomplete and/or noise corrupted data. Specifically, the technique relies on recasting the governing equations as a set of multiple-input/multiple-output systems in the wavelet domain. Next, an l 1 -norm minimization procedure based on compressive sampling theory is employed for determining the wavelet coefficients of the available incomplete non-stationary input-output data. Finally, these wavelet coefficients are utilized to reconstruct the non-stationary incomplete signals, and consequently, to determine system related time- and frequency-dependent wavelet-based frequency response functions and associated parameters. Two illustrative MDOF systems are considered in the numerical examples for demonstrating the reliability of technique. The first refers to a nonlinear time-variant system with fractional derivative terms, while the second addresses a nonlinear offshore structural system subjected to flow-induced forces. It is worth noting that for the offshore system, a novel recently proposed evolutionary version of the widely used JONSWAP spectrum is employed for modeling the non-stationary free-surface elevation in cases of time-dependent sea states. … (more)
- Is Part Of:
- Structural safety. Volume 86(2020)
- Journal:
- Structural safety
- Issue:
- Volume 86(2020)
- Issue Display:
- Volume 86, Issue 2020 (2020)
- Year:
- 2020
- Volume:
- 86
- Issue:
- 2020
- Issue Sort Value:
- 2020-0086-2020-0000
- Page Start:
- Page End:
- Publication Date:
- 2020-09
- Subjects:
- System identification -- Nonlinear systems -- Fractional derivative -- Generalized harmonic wavelet -- Incomplete data -- Compressive sampling
Structural stability -- Periodicals
Safety factor in engineering -- Periodicals
Reliability (Engineering) -- Periodicals
Constructions -- Stabilité -- Périodiques
Coefficient de sécurité en ingénierie -- Périodiques
Fiabilité -- Périodiques
620.86 - Journal URLs:
- http://www.sciencedirect.com/science/journal/01674730 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.strusafe.2020.101975 ↗
- Languages:
- English
- ISSNs:
- 0167-4730
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 8478.550000
British Library DSC - BLDSS-3PM
British Library STI - ELD Digital store - Ingest File:
- 13498.xml