A Method for System Identification in the Presence of Unknown Harmonic Excitations Based on Operational Modal Analysis

2019-01-5007

01/23/2019

Event
Automotive Technical Papers
Authors Abstract
Content
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.
Meta TagsDetails
DOI
https://doi.org/10.4271/2019-01-5007
Pages
7
Citation
Khodaygan, S., "A Method for System Identification in the Presence of Unknown Harmonic Excitations Based on Operational Modal Analysis," SAE Technical Paper 2019-01-5007, 2019, https://doi.org/10.4271/2019-01-5007.
Additional Details
Publisher
Published
Jan 23, 2019
Product Code
2019-01-5007
Content Type
Technical Paper
Language
English