Sandro Amador

Operational Modal Analysis based Stress Estimation in Friction Systems

It is possible to estimate the strain response of a structure in unmeasured points by the use of operational modal analysis and modal expansion. Both techniques are based on the assumption that the system is linear. However, this is not always the case since nonlinear elements often violate this assumption. In this paper, the precision of estimating the strain response of a nonlinear system is investigated using the operational response of numerical simulations. Local nonlinearities are introduced by adding friction to the test specimen and this paper finds that this approach of strain estimation can still predict the strains with high precision.

Effect of Friction-Induced Nonlinearity on OMA-Identified Dynamic Characteristics of Offshore Platform Models

The identification of the modal characteristics of engineering systems under operational conditions is commonly conducted with the use of the Operational Modal Analysis (OMA), being a class of useful tools employed within various fields of structural, mechanical as well as marine and naval engineering. The current OMA methods have been advanced on the basis of two fundamental, though, restrictive assumptions: (i) linearity and (ii) stationarity. Nevertheless, there are several applications that are inherently related to various nonlinear mechanisms, which, in turn, violate the two cornerstones of OMA and hence, question its robustness and efficiency. Along these lines, the current study addresses the effect of friction-induced nonlinearity on OMA-identified dynamic characteristics of an experimental set up consisting of a pair of reduced scale offshore platform models that are connected through a friction-based mechanism. Both time-domain and frequency-domain methods were employed to assess the effect of the varying friction-induced nonlinearity on the OMA-identified modal characteristics. The findings of this study reveal that OMA-based methods provide reasonable identification results implying that nonlinear and nonstationary systems can be described by underlying linear systems, even though, in principles, the basic assumptions of linearity and stationarity are violated.

Using correlation functions as free decays

It is a general assumption in OMA that correlation functions are free decays. In multiple input OMA this assumption also implies that any column in the correlation function matrix is to be considered as multiple output free decays. This assumption is discussed in this paper together with issues concerning estimation and application of correlations functions in OMA.

Finite Element Model Updating Using the Local Correspondence Principle

In this, paper an overview of a Finite Element (FE) model updating technique based on the Local Correspondence (LC) principle is presented. The main idea behind the LC technique is to update the FE model by replacing the mode shape vectors and natural frequencies with their corresponding experimental counterparts obtained from an output-only modal testing. This is accomplished by taking advantage of the fact that the inverse mass and stiffness matrices can be expressed as a linear combination of outer products of the mode shape vectors. Aiming at discussing the LC technique from a practical perspective, a simulation study is presented to illustrate its ability to improve the Maximum Assurance Criterion (MAC) between the FE and experimental mode shape vectors so that it gets close to unity.

Comparison of Two (Geometric) Algorithms for Auto OMA

In this paper we compare two geometric algorithms for automatic Operational Modal Analysis(OMA). The compared algorithms are the Shortest Path Algorithm (SPA) that considers shortest paths in the set of poles and the Smallest Sphere Algorithm (SSA) that operates on the set of identified poles to find the set of smallest spheres, containing physical poles. Both algorithm are based on sliding filter stability diagrams recently introduced by Olsen et al. We show how the two algorithms identify system parameters of a simulated system, and illustrate the difference between the identified parameters. The two algorithms are compared and illustrated on simulated data. Different choices of distance measures are discussed and evaluated. It is illustrated how a simple distance measure outperforms traditional distance measures from other Auto OMA algorithms. Traditional measures are unable to discriminate between modes and noise.

Damping Estimation of Friction Systems in Random Vibrations

Friction is one of the most efficient and economical mechanisms to reduce vibrations in structural mechanics. However, the estimation of the equivalent linear damping of the friction damped systems in experimental modal analysis and operational modal analysis can be adversely affected by several assumptions regarding the definition of the linear damping and the identification methods or may be lacking a meaningful interpretation of the damping. Along these lines, this project focuses on assessing the potential to estimate efficiently the equivalent linear damping of friction systems in random vibrations with the use of one novel method and two existing ones, modified, though, appropriately. Results of numerical simulations using the three procedures enabled their preliminary comparative assessment in terms of the related damping estimation potential. Indications from the current study showed that two of the methods estimate efficiently the equivalent linear damping, however, the equivalent linear damping seems to depend on the definition of the equivalence. Nonetheless, it seems that the variation of the equivalent linear damping estimates based on the three aforementioned methods becomes less significant when compared to their actual influence on the linear response.

Application of Frequency Domain Decomposition Identification Technique to Half Spectral Densities

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.

Modal participation in multiple input Ibrahim time domain identification

The Ibrahim time domain (ITD) identification technique was one of the first techniques formulated for multiple output modal analysis based on impulse response functions or general free decays. However, the technique has not been used much in recent decades due to the fact that the technique was originally formulated for single input systems that suffer from well-known problems in case of closely spaced modes. In this paper, a known, but more modern formulation of the ITD technique is discussed. In this formulation the technique becomes multiple input by adding some Toeplitz matrices over a set of free decays. It is shown that a special participation matrix can be defined that cancels out whenever the system matrix is estimated. The participation matrix becomes rank deficient if a mode is missing in the responses, but if any mode is present in one of the considered free decays, the participation matrix has full rank. This secures that all modes will be contained in the estimated system matrix. Finally, it is discussed how correlation functions estimated from the operational responses of structures can be used as free decays for the multiple-input ITD formulation, and the estimation errors of the identification technique are investigated in a simulation study with closely spaced modes. The simulation study shows that the multiple-input formulation provides estimates with significantly smaller errors on both mode shape and natural frequency estimates.