Modal Identification from Ambient Responses using Frequency Domain Decomposition

By R. Brincker, Lingmi Zhang, Palle Andersen. 2000

1,193 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/b16bd297685447c5edd50d8610e84944243b848d

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Citations in the corpus

Some remarks on experimental estimation of damping for seismic design of civil constructions (2010, methodology): “Being the EFDD method based on computation of spectra from recorded data, long records are required to keep low the error on spectrum estimation [30] and, therefore, to extract modal parameters in a reliable way.”
A Review of Vibration-Based Damage Detection in Civil Structures: From Traditional Methods to Machine Learning and Deep Learning Applications (2020, methodology): “Also, various frequency-domain algorithms have been utilized for the same purpose like simple peak-picking of the natural frequencies from frequency response functions [117], Frequency Domain Decomposition (FDD) [118], and Complex Mode Indicator Function (CMIF) [119].”
Structural Health Monitoring Using Wireless Sensor Networks: A Comprehensive Survey (2017, methodology): “The CMIF method, also known as the frequency domain decomposition (FDD) method, is an alternate modal parameter estimation method based off the PP method [39].”
Influence of model order and number of block rows on accuracy and precision of modal parameter estimates in stochastic subspace identification (2014, background): “For instance, when frequency domain methods are considered, such as the enhanced frequency domain decomposition (EFDD) (Brincker et al., 2000; Gade et al., 2005), measurement noise may affect the reliability of estimates.”
Structural health monitoring (SHM) and Nondestructive testing (NDT) of slender masonry structures: A practical review (2021, methodology): “There are two main ways of conducting the analysis of the data, namely in time-domain or in frequency-domain, leading to the two most commonly used techniques for modal parameter identification in Operational Modal Analysis: Frequency Domain Decomposition (FDD) [71] and Stochastic Subspace Identific”
Output-only modal identification of a reinforced concrete bridge from radar-based measurements (2008, methodology): “advanced Frequency Domain Decomposition [8]-[9] and Stochastic Subspace Identification methods [10]-[11].”
Operational modal analysis for estimating the dynamic properties of a stadium structure during a football game (2007, methodology): “Various literature references exist on the method, including the application to FRF data in classical modal analysis [28–31].”
Damping Estimation Using Free Decays and Ambient Vibration Tests (2010, background): “It can be shown [7] that, under some assumptions (w hite noise excitation, low damping and orthogonal mode shapes for close modes), the singul ar values of the spectral matrix are autospectral density functions of single degree of free dom systems with the same frequency and damping as the structure”
Ambient vibration testing of historic masonry towers for structural identification and damage assessment (2007, methodology): “A very good agreement was found between the modal estimates obtained from the Peak Picking [17] and the Frequency Domain Decomposition [18] techniques.”
Automated Frequency Domain Decomposition for Operational Modal Analysis (2007, methodology): “The Frequency Domain Decomposition technique is a way to solve these two problems, Brincker et al [3], [4].”
Explaining operational modal analysis with data from an arch bridge (2011, background): “However, the condition of orthogonality of the mode shapes has to be respected at least between closely spaced modes [25].”