Application of Frequency Domain Decomposition Identification Technique to Half Spectral Densities

Sandro Diord Rescinho Amador, Martin Ørum Ørhem, Tobias Friis, Rune Brincker

Research output: Contribution to conferencePaperResearchpeer-review


Because of its simplicity and robustness, the Frequency Domain Decomposition (FDD) identification technique have become very popular in the operational modal analysis community. The basic idea behind this technique consists of computing the singular value decomposition of the power spectral densities estimated with the periodogram (also known as “Welch’s” periodogram) approach to identify the natural frequencies and mode shape vectors. In this paper, the benefits of the application of the FDD technique to half spectral densities - the power spectral densities estimated from the positive part of the correlation functions - are investigated. In order to illustrate such benefits from a practical perspective, the FDD identification results obtained from the half spectral densities, of both simulated and real structures, are compared to those from the classical periodogram-driven FDD.
Original languageEnglish
Publication date2018
Number of pages4
Publication statusPublished - 2018
Event36th International Modal Analysis Conference - Orlando, United States
Duration: 12 Feb 201815 Feb 2018
Conference number: 36


Conference36th International Modal Analysis Conference
CountryUnited States


  • Modal Parameter Estimation
  • Frequency Domain Decomposition
  • Eigenvalue Decomposition
  • Half Spectrum Density
  • Operational Modal Analysis

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