A practical handling of measurement uncertainties in frequency based substructuring. (October 2020)

• Record Type: Journal Article
• Authors: Trainotti, F.; Haeussler, M.; Rixen, D.J.
• Is Part Of: Mechanical systems and signal processing. Volume 144(2020)
• Publication Date: 2020-10
• Subjects: Frequency based substructuring -- Virtual point transformation -- Random uncertainty -- Uncertainty quantification -- Variance -- Covariance; Structural dynamics -- Periodicals; Vibration -- Periodicals; Constructions -- Dynamique -- Périodiques; Vibration -- Périodiques; Structural dynamics; Vibration; Periodicals; 621
• DOI: 10.1016/j.ymssp.2020.106846
• Languages: English
• ISSNs: 0888-3270

Abstract

Highlights: A covariance-based approach is presented for estimating the complex FRF random uncertainty in impact testing. The measurement uncertainty is propagated through common experimental substructuring techniques. A study is conducted on the assumptions underlying the proper application of the propagation formula. The practical implementation of the methodology is illustrated with an experimental case study. Abstract: A proper acquisition of FRFs is a prerequisite for a successful implementation of experimental substructuring techniques in the frequency domain. In this context, the study of uncertainty associated with measurements is of particular interest due to the precision standards required by industrial practice. This paper aims to provide a practical and reliable methodology for the quantification and propagation of the random measurement uncertainty in Frequency Based Substructuring applications. Extending previous studies, the framework presents a covariance-based approach for quantifying the complex-valued random uncertainty on measured FRFs and analytical methods for propagating it through interface modeling and substructures coupling approaches. The assumptions underlying the correct application of the method are investigated. An optimal number of impacts for an appropriate Gaussianity of the FRF distribution is computed based on empirical data. Experimental testing reveals encouraging results in the validation of the small error approximation. Considerable correlation effects between FRFs are found, although their impact on the coupled FRFs uncertainty seems to be limited. The methodology is applied to an experimental example.