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A method for system identification in the presence of unknown harmonic excitations based on operational modal analysis

Khodaygan, S ; Sharif University of Technology | 2019

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  1. Type of Document: Article
  2. DOI: 10.4271/2019-01-5007
  3. Publisher: SAE International , 2019
  4. Abstract:
  5. Operational modal analysis techniques classically have been developed based on the assumption that the input to the system is a stationary white noise. While, in many practical cases, the systems are excited by combination of white noise and colored noises (harmonic excitations). Consequently, in conditions where non-white noises are present, the existing OMA methods cannot completely distinguish between the system poles and the induced poles due to colored noises. In order to overcome this weakness of OMA methods, some researches have been conducted in the field. In this paper, a new method is proposed for identifying the modal parameters of the system under the unknown colored noises, based on the Power Spectral Density Transmissibility (PSDT) function. In this work, the proposed methodology is established upon applying the auxiliary force, which can re-excite the system under operational conditions. In order to identify the modal parameters through the PSDT function, an appropriate parametric identification method such as the Poly-reference Least Squares Complex Frequency-domain method (PLSCF), or Poly-Max method, is utilized. Thus, modal parameters of the system poles are identified using a Stabilization Diagram (SD) by overestimating the system model order. To illustrate the efficiency of the proposed methodology, a four DOF vibrational system is considered as a case study through a computer simulation, and the obtained results are compared and discussed for verification. © 2019 SAE International. All rights reserved
  6. Keywords:
  7. Composite beams and girders ; Frequency domain analysis ; Least squares approximations ; Modal analysis ; Poles ; Spectral density ; Complex frequency ; Harmonic excitation ; Modal parameters ; Operational conditions ; Operational modal analysis ; Parametric identification ; Stabilization diagrams ; System modeling ; White noise
  8. Source: 2019 SAE Automotive Technical Papers, WONLYAUTO 2019, 1 January 2019 through 1 January 2019 ; Volume 2019-January, Issue January , 2019 ; 01487191 (ISSN)
  9. URL: https://www.sae.org/publications/technical-papers/content/2019-01-5007