Determination of Dynamic Behavior of Masonry Structure Using with Operational Modal Analysis Technique

The paper presents how to identify natural frequencies and mode shapes of structures by Operational Modal Analysis (OMA) technique, in which the Frequency Domain Decomposition (FDD) method is used. This method is an experimental method only base on the data of measuring the dynamic response of the structures under the excitation due to ambient forces and operational loads to determine the vibration characteristics. Measure vibration (acceleration) and determine spectral density matrix, using the singular values decomposition method of spectral density matrix to determine the natural frequencies and mode shapes of structures. The calculation results show that the natural frequencies, the mode shapes form determined by the OMA technique is consistent with the calculation results according to the theory and show the reliability of the method.KeywordsNatural frequencyMode shapeIdentifyEMAOMAFDD

An Investigation of the Seismic Behaviour of an Ancient Masonry Bastion Using Non-Destructive and Numerical Methods

Beam mode characterization by applying operational modal analysis to neutron detectors data

Operational Modal Analysis (OMA) is a methodology to obtain the modal properties of a structure using the dynamical responses of the system only. That methodology is very useful in aeroelastic in-fligh testing where there are difficulties in measuring directly the aerodynamic loads on aircraft. For risk reduction in the future flight operations of the EOLO at ITA, wind-tunnel tests were performed. EOLO is an Unmanned Aerial Vehicle (UAV) with high aspect ratio and structural flexibility, designed to study aeroelastic phenomena and to evaluate the interaction of flexible effects with the aircraft flight dynamics. In this work The Frequency Domain OMA techniques: Decomposition (FDD), Enhanced Frequency Domain Decomposition (EFDD), Spatial and Frequency Domain Decomposition (SFDD) are applied to the vibrational data from wing tunnel test campaign in different operation conditions, using acceleration and strain measurements. The results between the OMA techniques are compared with previous modal characterization from Ground Vibration Test (GVT) and numerical aeroelastic analysis. The different generations of the frequency domain decomposition methods proved their suitability for use in aircraft aeroelastic characterization using accelerations and strain measurements.

This paper presents the operational modal analysis of a 90-m-high RC minaret of an iconic mosque considered as a landmark of the city. The minaret was monitored for three days with 11 tri-axial MEMS accelerometers. The purpose of the study was to observe the behavior, develop a representative finite element (FE) model, and establish baseline data for health monitoring studies. The modal properties were extracted using three operational modal analysis techniques (OMA): Enhanced Frequency Domain Decomposition (EFDD), Stochastic Subspace Identification (SSI), and Natural Excitation Technique with Eigensystem Realization Algorithm (NExT-ERA). The first 10 identified modes were below 7 Hz. Eight modes out of the ten were bending-dominant, while the remaining two were torsion-dominant. A FE model was also developed in ETABS to ascertain and compare the response of the structure with the identified results. From the FE model, the modes corresponding to the first ten identified modes were considered for comparison with the identified frequencies from ambient monitoring. The maximum 7.71% error was observed between the experimental and numerical frequencies. The error was minimized by using the manual updating the material properties and adding the weight of nonstructural elements. The variation of identified modal frequencies with ambient temperature was observed to be linearly dependent to a reasonable degree. A general trend of decreasing identified frequencies was observed with the rise in temperature.

\nThis work presents a summary of the research study of operational modal analysis (OMA) application for condition monitoring of operating pipelines. Special focus is on the topicality of OMA for definition of the dynamic features of the pipeline (frequencies and mode shapes) in operation. The research was conducted using two operating laboratory models imitated a part of the operating pipeline. The results of finite-element modeling, identification of pipe natural modes and its modification under the influence of virtual failure are discussed. The work considers the results of experimental research of dynamic behavior of the operating pipe models using one of OMA techniques and comparing dynamic properties with the modeled data. The study results demonstrate sensitivity of modal shape parameters to modification of operating pipeline technical state. It is resumed about ability of operating pipeline condition monitoring by measuring dynamic deformations of the operating pipe and OMA techniques application for dynamic properties extraction.\n

Abstract. In the present study we investigate development of operational modal analysis (OMA), different OMA techniques as well as relevant issues and experimental studies. Furthermore, we classify previously performed studies have been conducted so far and consider the most important one. So, first we review the fundamental concepts. Then, the history and application of the OMA method will be examined comprehensively to observe their role in the development of the technique. Three basic methods of FDD, SSI, and Next will be discussed and the research works associated to them will be analyzed.

This paper investigates the use of conventional operational modal analysis (OMA) techniques for modal parameters identification of a rotating system supported by roller bearings. Although largely applied in civil engineering, in-depth studies on different types of systems are still limited in the literature. The novel of the paper is to address such issue by applying conventional OMA methods, such as enhanced frequency domain decomposition (EFDD) and stochastic subspace identification (SSI-data), to identify the modal parameters of a rotating machine, investigating the challenging particularities of these systems due to their inherent operating conditions, especially regarding the presence of harmonic forces, eventually closed-spaced modes, and non-proportional damping due to the bearings. The results presented in the experimental tests showed that, with the use of specific tools, in comparison with traditional experimental modal analysis (EMA), the used OMA methods have managed to successfully identify the modal parameters of a roller bearing supported rotor.

To prevent operational breakdowns, it is essential to inspect drill bits for defects following the manufacturing process. Traditional methods to inspect manufacturing defects are not suitable for the drill bits having helical oil holes. These methods are capable to examine surface characteristics but unable to detect internal defects formed during oil hole manufacturing. In this paper, an Operational Modal Analysis (OMA) technique is applied as a Non-Destructive Testing (NDT) to overcome this limitation in detection of manufacturing defects. In this method, the specimen is excited by broadband random vibration and its structural dynamics is analysed by OMA that segregate un-defected and defected drill bits. The proposed algorithm was verified on multiple sets of specimens, and correctly classified all specimens, achieving 100% detection accuracy. The proposed method offers a solution for a more comprehensive inspection by acquiring the dynamic characteristics of the specimen. Nonetheless, its sensitivity in identifying very small defects requires further exploration.

Cyclostationarity and the cepstrum for operational modal analysis of MIMO systems—Part II: Obtaining scaled mode shapes through finite element model updating

This contribution presents modal testing of a 2‐MW wind turbine on a 100‐m tubular tower with a 93‐m rotor developed by W2E Wind to Energy GmbH. This research is part of the DYNAWIND project of the University of Rostock and W2E. Beside classical modal analysis schemes, this contribution mainly focusses on the application of operational modal analysis techniques to a wind turbine. Specific problems are addressed, and hints for modal testing on wind turbines are given. Furthermore, an effective measurement setup is proposed for identification of the modal parameters of a wind turbine. The measurement campaign is divided in two parts. First, a measurement campaign using 8 sensor positions on a rotor blade was done while the rotor is lying on ground. Second, a detailed measurement campaign was done on the entire wind turbine with the rotor locked in Y position using 61 sensor positions on the tower, the mainframe, the gearbox, the generator, and the low‐voltage unit. While the rotor blade was tested by classical and operational modal analysis techniques, the entire wind turbine was tested by operational modal analysis techniques only. The mode shapes and eigenfrequencies of the wind turbine identified within the measurement campaigns are within the expected range of the design values of the wind turbine. But in contrast, the damping ratios differ strongly from those given in guidelines and literature. Furthermore, a strong influence of aerodynamic damping compared to structural damping is observed for the first tower mode even for a parked wind turbine.

Nowadays Acoustic Modal Analysis often plays a significant role in the optimisation process of the acoustic parameters of all kinds of cavities, e.g. the interior of a car, a train, an airplane etc. A problem with the existing experimental Acoustic Modal Analysis techniques is that one has to use volume acceleration sources which interact with the acoustic system. The Operational Acoustic Modal Analysis (OAMA) technique doesn't suffer from this problem. An important disadvantage of the OAMA approach is that the estimated mode shapes are not correctly scaled. This scaling problem will be tackled in this paper. We will introduce a sensitivity based rescaling technique for the acoustic domain. Local volume changes of the cavity will make a correct estimate of the mode shapes possible. The technique will be validated by some simulations and experiments.

In order to derive mass normalized mode shapes from Operational Modal Analysis (OMA) techniques, additional experiments have to be conducted in the interest of scaling the determined mode shapes. Various investigations have been carried out based on the deterministic perturbed mass matrix, also known as the mass change method. However, the conventional form of this method requires a number of rather costly and sometimes impractical experiments on the structure. In this article, it is intended to use traffic as a stochastic source of mass change to calculate mass scaling factors. Adequate traffic stream on bridges can affect the Eigen properties of the structure efficiently. The vehicles on the bridge are only considered to affect the mass properties, and vehicle-bridge interaction is neglected. A simplified structural model of a bridge is considered and the traffic is modeled as lognormal distribution. Nodal masses induced by the vehicles are converted to time histories to avoid difficulties based on the moving mass problem. Consequently, a method is proposed to produce the modified mass matrix which can be used in the scaling factor equations. Finally, scaling factors of mode shapes are proposed by comparing the unperturbed structure and the perturbed mass matrix structure.

For many engineering areas, the knowledge of the variation of the mechanical properties of hardening materials (such as concrete) since early ages, and throughout service life is of interest not only for academic purposes but also for practical reasons. In case of the precast or in-situ construction industry, tracking the evolution of concrete mechanical properties since the instant of casting is of high importance due to the fact that the volume of the production and the cost of the final product are directly linked to the optimization of the process of removing the formwork (and/or applying pre-stress) as early as possible. The paper presents the application of a recently devised method to track the hardening process of concrete, which is based in the correlation of the changes in the dynamic response of structural systems (that contain the tested material), with the stiffness evolution of the tested material. The paper focuses in the presentation of the operational modal identification tests that were carried out in laboratory and in-situ, as well as the presentation of a new automatic identification algorithm based in the SSI-Data method which was used to process the large amount of recorded data. The results of the tests show the feasibility of the application of Operational Modal Analysis (OMA) techniques for accurately assessing the dynamic response of the tested specimens even in environments with high noise levels. It is also shown that accurate approximations of the instantaneous E-modulus of the concrete can be obtained with the application of the proposed methodology.

This paper will evaluate different automated operational modal analysis techniques for the continuous monitoring of offshore wind turbines. The experimental data has been obtained during a long-term monitoring campaign on an offshore wind turbine in the Belgian North Sea. State-of-the art operational modal analysis techniques and the use of appropriate vibration measurement equipment can provide accurate estimates of natural frequencies, damping ratios and mode shapes of offshore wind turbines. To allow a proper continuous monitoring the methods have been automated and their reliability improved. The advanced modal analysis tools, which will be used, include the poly-reference Least Squares Complex Frequency-domain estimator (pLSCF), commercially known as PolyMAX, the polyreference maximum likelihood estimator (pMLE), and the frequency-domain subspace identification (FSSI) technique. The robustness of these estimators with respect to a possible change in the implementation options that could be defined by the user (e.g. type of polynomial coefficients used, parameter constraint used…) will be investigated. In order to improve the automation of the techniques, an alternative representation for the stabilization charts as well as robust cluster algorithms will be presented.