Operational Modal Analysis Techniques Research Articles

Development and testing of a novel vibratory compaction instrument considering its natural frequency.

This study aims to develop a novel vibratory compaction instrument designed for the preparation of large triaxial soil specimens, offering an efficient alternative to the traditional manual specimen preparation process. However, when the motor frequency closely aligns with the natural frequency of the structure, severe resonance phenomena may occur. This paper employed finite element modal analysis, experimental modal analysis, and operational modal analysis techniques to conduct a multi-objective optimization of the structure, aiming to improve the dynamic characteristics. First, the natural frequency and mode shapes of the vibratory compaction instrument were determined via finite element technology. Subsequently, the optimization of this instrument was conducted by integrating the Kriging surrogate model with the Non-dominated Sorting Genetic Algorithm II (NSGA-II). Finally, the steel column underwent a modal test using impulse stimulation to ascertain its natural frequency, and the stochastic subspace identification (SSI) approach was employed to conduct an operational modal analysis of the vibratory compaction instrument to determine its modal characteristics. The experimental findings corroborated the conclusions obtained from the finite element analysis, validating the precision of the finite element modal analysis and the rationality of the optimized structure. The research results are of significant importance for improving the preparation efficiency of large triaxial specimen, contributing to advancements in soil mechanics testing.

Hybrid operational modal analysis of an operative two-bladed offshore wind turbine

As with any strategic structure, vibration-based structural health monitoring techniques are often used to ensure the structurally safe operation of offshore wind turbines. Among such techniques, Operational Modal Analysis (OMA) methods allow the identification of modal properties, such as natural frequencies, mode shapes and damping, which variation might be caused by damage or operational/environmental factors. This paper investigates the application of OMA techniques on a two-bladed offshore wind turbine, which poses multiple challenges: fundamental OMA assumptions about the applied loads are violated by environmental and operational loads; the closely spaced modes of an offshore wind turbine are hard to identify; and an operative two-bladed offshore wind turbine is a time-variant system. Within this study, three OMA procedures to overcome some of the preceding challenges are discussed: (1) a standard frequency domain decomposition method; (2) a proposed enhanced transmissibility-based approach with a post-processing technique based on the Kurtosis index; and (3) a proposed refined hybrid OMA procedure that combines a transmissibility-based approach, the dedicated post-processing technique based on the Kurtosis index, and the frequency domain decomposition method. A numerical model representative of an operative two-bladed offshore wind turbine is used to compare the three procedures. Based on the comparison, the hybrid method is proven to be a promising new OMA-based procedure that outperforms the stand-alone transmissibility-based approach and the frequency domain decomposition method in identifying the modal properties of a two-bladed offshore wind turbine.

Transmissibility-based operational modal analysis: A unified scheme and uncertainty quantification

The transmissibility-based Operational Modal Analysis (OMA) technique has attracted substantial research interest over the past two decades due to its capability to extract structural modal parameters in the presence of non-white excitation. The transmissibility function used in OMA can be categorized as Response Transmissibility (RT) and Power Spectral Density Transmissibility (PSDT). Modal parameters can be identified by combining RTs from multiple load cases or PSDTs from multiple transfer outputs. Nevertheless, the mathematical formulations and implementation procedures of the various RT-based and PSDT-based methods exhibit significant differences. Furthermore, the uncertainty associated with modal parameter estimates is rarely assessed in these methods. This work aims to propose a scheme that unifies various transmissibility-based OMA algorithms through a consistent parametric formulation. Within this scheme, a universal parametric model and a standardized implementation procedure are developed to accommodate two types of transmissibility in both time and frequency domains and six OMA algorithms; additionally, a generalized framework for quantifying the uncertainties associated with modal parameter estimates is provided. The proposed scheme is finally validated using a planar truss structure.

Structural Condition Assessment of Reinforced Concrete Bridge Using Operational Modal Analysis and Finite Element Model

The integration of Operational Modal Analysis (OMA) and Finite Element Model (FEM) techniques has proven to be a valuable approach for evaluating and maintaining the health of such structures. OMA extracts dynamic characteristics from a bridge's responses to ambient vibrations, while FEM employs computational models to simulate and compare these dynamic behaviours. This comprehensive methodology ensures an accurate representation of the bridge's behaviour and its correlation with real-world conditions. However, a significant challenge arises in assessing the Ultra High Performance Fiber Reinforced Concrete (UHPFRC) pedestrian bridge in Klang, Selangor, launched in October 2022, due to limited available information about OMA and FEM on UHPFRC. This research aims to develop FEM and conduct ambient vibration tests to obtain modal parameters. Moreover, the study investigates OMA techniques in the context of weak excitation sources, filling a critical knowledge gap. By comparing experimental results with FEM, this research provides insights into the feasibility and reliability of OMA under challenging environmental conditions. The principal results reveal significant percentage differences in natural frequencies between FEM and OMA, with the most notable disparities occurring in the first mode. Nevertheless, the mode shapes extracted from OMA closely resemble those from FEM. In conclusion, this research enhances the understanding of UHPFRC pedestrian bridge behaviour and modal analysis techniques.

Linear time periodic system approximation based on Floquet and Fourier transformations for operational modal analysis and damage detection of wind turbine

Operational Modal Analysis (OMA) identifies modal properties of mechanical structures from vibration data collected from a few sensors under operation conditions. These methods are widely used to monitor civil engineering structures that are modeled as time-invariant systems. However, when dealing with wind turbines and rotating machines, many dedicated OMA techniques were developed to deal with the time-periodic behavior. Existing methods pre-process the data to adapt them to classical identification techniques. Yet, these methods present limitations as either requiring a high number of measured rotation periods, assuming the assumption of an isotropic rotor (i.e. undamaged), or the knowledge of the rotational speed. This work proposes to lift these difficulties by proving that the application of the classical system identification methods can produce meaningful estimates for anisotropy monitoring. This observation is based on directly approximating the time-periodic dynamic behavior of the wind turbine as a properly defined time-invariant system under periodic inputs. It results in the possibility of using classical identification methods without modification to retrieve the system matrices of the approximated time-invariant system. This approach does not require knowing the rotor speed, requiring relatively fewer measurements and it is not restricted to isotropic rotors. The identified modes can be used reliably for the monitoring of operating wind turbines and more especially for fault detection, at the expense of losing a part of the complete description of the periodic system. The resulting anisotropy monitoring approach and its capacities are illustrated in two cases. Firstly, on an academic model of a wind turbine and then on an aero-servo-elastic numerical model of a rotating 10 MW wind turbine to demonstrate the ability of the method to deal with realistic and representative data. It is shown for the latest case, from sensors located on the blades of the wind turbine, the approach is able to identify correctly the system properties (frequencies and mode shapes) and is also able to detect efficiently a fault on a blade.

AI-driven Automated Operational Modal Analysis of Bridges

The growing awareness on the daunting challenge posed by ageing civil infrastructure is fostering the increasingly frequent implementation of dense Structural Health Monitoring (SHM) systems. The Italian context represents a formidable example of this trend, especially after the tragic collapse of the Morandi Bridge in 2018 and the release of the National Guidelines on the Assessment and Management of the Risk Condition of Bridges and Viaducts in 2020. This has motivated the implementation of numerous monitoring systems all throughout the national territory, many of them involving heterogeneous and dense sensor networks. The implementation of such a vast number of sensors presents new challenges at the management and decision-making levels, particularly in the signal processing and feature extraction phases. This is particularly critical for vibration-based SHM techniques, in which classical operational modal analysis (OMA) techniques are proving inefficient for handling such large monitoring databases. As an attempt to alleviate these limitations, this contribution presents the development of an AI-driven OMA technique for rapid identification of bridges. The proposed methodology consists of a multi-task deep feedforward neural network capable of extracting the independent modal components from ambient vibration records. Trained in a supervised manner by a Second Order Blind Source Identification (SOBI) method, the developed AI model can extract both the real and complex independent modal components. The effectiveness of the presented approach is illustrated through of a real-world-bridge, the Méndez-Núñez Bridge in Granada, Spain, demonstrating great potential as a computationally efficient OMA technique for on-site edge modal identification of bridges.

An efficient automatic modal identification method based on free vibration response and enhanced Empirical Fourier Decomposition technique

This paper presents an efficient yet practical approach for the automatic modal identification of structures based on their free vibration response. The proposed approach relies on the Empirical Fourier Decomposition (EFD) technique. It implements a new procedure to recognize automatically the number of modal components to be extracted from noisy data in such a way to prevent both mode-mixing and mode-splitting effects. A suitable strategy is adopted to improve the segmentation of the frequency spectrum of the free vibration response, so as to identify accurately the bounds of the frequency spectrum partition corresponding to each modal component. The related modal damping ratios are estimated by means of a robust area-based approach in order to mitigate the noise-induced disturbances whereas a time-domain method based on the phase shift of the free vibration response peaks is employed to identify the mode shapes.The proposed approach is first validated through the analysis of synthetic signals that embed closely spaced components and a lowly excited vibration mode. Finally, the proposed approach is applied to two real bridges. The first case-study deals with the identification of modal frequencies and damping ratios of the cables of a stay-cabled bridge. The second case-study involves the modal identification of a steel railway bridge deck that exhibits two closely spaced vibration modes. The outcomes obtained using the proposed approach based on EFD technique are compared with the results obtained by means of the Variational Mode Decomposition (VMD) technique as well as with those computed through classical operational modal analysis techniques. The consistent estimates produced by means of the proposed approach demonstrate its accuracy and robustness.

Laminated glass slabs design challenges: dynamic identification of a fractured pedestrian walkway

AbstractDesign codes provide requirements for traditional slabs to ensure both safety levels and in‐service functionality criteria. However, for existing structures, an initial diagnostic knowledge phase is essential to characterize the actual health state, e.g. based on structural health monitoring (SHM) with operational modal analysis (OMA) techniques. Considering recent advancements in glass as a structural material, laminated glass (LG) slabs are increasingly used in constructions and are mostly designed to account for the intrinsic brittleness and limited tensile resistance of glass. The latest pre‐code CEN/TS 19100:2021 is paving the road for an imminent future Eurocode 10 dedicated to providing new standards for the innovative use of structural glass. In the current study, a brief review of the design challenges of working with structural glass is presented. After that, the authors provided a simple experimental dynamic identification example of an LG pedestrian walkway located in the Basilica of Aquileia, Trieste (Italy). Specifically, the fundamental mode was compared to a healthy and a partially fractured LG slab. Functionality aspects related to comfort standards with respect to in‐service vibration issues are also detailed.

Reliable modal estimation of high-rise structures via synergistic usage of multiple stabilization diagram-based operational modal analysis techniques

In operational modal analysis, typically only structural responses are available. Errors and uncertainties may exist in modal estimates, thereby leading to discrepancies in the results by different modal identification approaches even analyzing the same data set. To this end, a synergistic usage of multiple stabilization diagram-based modal identification techniques is presented in this paper to reduce the errors and uncertainties in modal estimates associated with modal identification techniques or modeling ideas. The effectiveness and noise robustness of the synergistic strategy are validated via numerical simulation study of a frame structure. Additionally, the synergistic strategy is further utilized to evaluate the dynamic characteristics of a supertall building with 600 m height during a typhoon event. The application of the synergistic strategy to field measurements reveal that the building natural frequencies varied during the typhoon and exhibited significant amplitude-dependent features. Meanwhile, the damping ratios of the skyscraper for all concerned modes remained roughly stable within a range of [0.16%, 0.94%]. This paper aims to provide a practical way or effective tool to enhance the accuracy and confidence in modal estimation of high-rise buildings, thus further revealing the dynamic characteristics of large-scale structures under severe wind excitations.

Effects of post-fracture repeated impacts and short-term temperature gradients on monolithic glass elements bonded by safety films

Weathering and operational conditions, as known, have significant impact on typical constituent materials which are used for many construction applications. Among others, structural glass solutions can suffer for these effects in terms of major modification of material properties of interlayers, bonds, connections, gaskets and polymeric components in general. In this paper, the attention is given to the effects of repeated low-amplitude impacts and short-term temperature gradients for the characterization of load-bearing capacity in monolithic glass elements retrofitted by safety films. Especially for existing glass systems which are made of monolithic glass with limited strength and resistance capacity against ordinary and accidental mechanical loads, safety films are commercially available for retrofit interventions. They are primarily expected to keep together glass fragments in case of breakage, and thus minimize possible injuries. Besides, after first fracture, the so obtained glass-film composite elements have uncertain residual mechanical capacity against ordinary loads, given that it mostly depends on thin films composed of Polyethylene terephthalate (PET)-layers and pressure sensitive adhesives (PSAs). To this aim, a set of experiments (for a total of 950 configurations) is carried out in laboratory conditions (30 °C) on small-scale samples of fractured annealed monolithic glass elements bonded by commercial safety films, under repeated low-amplitude impacts / vibrations (S1-TR series), or additionally subjected to preliminary short-term thermal gradients (S2-TC1 series cooled at +5 °C and S3-TC2 series at −20 °C). Localized impacts are quantified in acceleration peaks in the range of 2 ÷ 14 m/s2 and rotations at supports in the order of 15 ÷ 20°. The interpretation of dynamic experimental results is carried out in terms of post-fracture vibration frequency (based on classical operational modal analysis techniques) and used, with the support of simplified analytical models or Finite Element (FE) numerical simulations, to characterize the response of cracked glass-film samples. Most importantly, the vibration frequency decrease is used to quantify their residual load-bearing capacity under unfavourable conditions, and to quantify the post-critical benefit of thin bonding safety films under unfavourable conditions.

Spectral optimization-based modal identification: A novel operational modal analysis technique

In this work, we introduce a novel method, namely Spectral Optimization-based Modal Identification (SOMI) for estimating the modal parameters of structures. SOMI is developed to estimate highly accurate modal damping ratios and mode shapes using the Frequency Domain Decomposition (FDD) principles. The FDD method (and most of the present modal identification techniques), encounters some problems such as modal complexity, lack of accuracy in the case of large damping ratios, and noticeable error in mode shape estimation. In the FDD formulation, the Singular Value Decomposition (SVD) estimation is precise only for lightly damped structures for obtaining the mode shapes and the Power Spectral Density (PSD) function of the modal coordinates. Moreover, the complexity of the mode shapes obtained from the FDD method is significantly biased and should not be used for physical interpretations. The main idea behind the proposed SOMI method is the elimination of the SVD estimation and obtaining the PSD function of the modal coordinates and the mode shapes with the least approximations. Moreover, the modal damping ratio is directly estimated in the frequency domain without any transformation into time domain using two equations derived in this paper. SOMI method uses optimization to make the PSD function of the modal coordinates follow the theoretical equations and estimates highly accurate mode shapes. In this work, the derivations are given for the displacement, velocity, and acceleration signals. The detailed formulation of the proposed method is presented, it is validated with some examples, and its competitive accuracy is compared with the FDD method. The accuracy and robustness of SOMI in noisy conditions are also assessed, with results indicating its effectiveness in handling noise and maintaining accuracy.

Automated operational modal analysis of bell towers subjected to narrowband input

Vibration-based Structural Health Monitoring (SHM) systems are very attractive to remotely assess the health state of structures of the historical urban landscape, such as bell towers, in operational conditions or after hazardous events, because of their limited invasiveness and the opportunity to enhance the knowledge about their mechanical behavior. The present study focuses on towers because, in spite of their relatively simple structural scheme, aging of materials as well as earthquake-induced damage resulted in a number of structural collapses occurred worldwide over the years. In this context, automated Operational Modal Analysis (OMA) techniques are key elements for the development of vibration-based SHM systems.After recognizing the critical aspects in the development of effective automated OMA procedures able to deal with the operational vibration response of bell towers, the present paper describes a strategy for automated OMA based on power spectral density transmissibility (PSDT) functions. The validation of the procedure is documented with reference to the dynamic response of a bell tower located in a minor center of the Italian Inner Areas, highlighting its effectiveness in identifying the fundamental modes from operational vibrations, and its robustness to the narrowband input associated with swinging bells.

Health Monitoring of Serial Structures Applying Piezoelectric Film Sensors and Modal Passport.

Health monitoring of critical structures, that form parts of serial operating objects, is a pressing task. The Operational Modal Analysis (OMA) techniques could be the optimal solution. An inexpensive measurement system, such as the OMA, uses a lot of sensors for structural response assessment. The health monitoring of serial structures has to also consider possible deviations between samples. A solution providing the OMA application includes the compact measurement system based on piezoelectric film sensors and modal passport (MP) techniques. For validation of the proposed approach, a series of five similar composite cylinders, with a network of piezoelectric film sensors, was used. Applying modal tests on the specimens, and using OMA with MP methods, the set of typical modal parameters was determined and analyzed. The results of the study confirmed the feasibility of the sensor network and its applicability for structural health monitoring of serial samples using OMA methods. The proven effectiveness of OMA/MP techniques, combined with a sensor network, provides a prototype of intelligent sensor technology, which can be used for health monitoring of structures, including those that are part of an operating facility.

Implementation of BCI based semi-automated impact device for performing Impact Synchronous Modal Analysis

Current Impact Synchronous Modal Analysis (ISMA), an operational modal analysis technique incorporated with either manual impact hammer or Automated Phase Controlled Impact Device (APCID) faces challenges on its effectiveness and practicality in real industrial applications. This study utilizes a Brain Computer Interface (BCI) based portable semi-automated impact device with the aim to solve the current issues of ISMA and complement both the manual impact hammer and APCID. A low cost, portable and wireless Electroencephalogram (EEG) device is used with machine learning to predict impact time before the impact using manual impacts and integrated with APCID control to compensate for the behaviour randomness. This semi-automated impact device, also known as EEG-ISMA, provides an accurate, practical, time- and cost-effective solution in performing ISMA during operation with low mean error in impact time prediction, superior cyclic load component suppression capability, accurate modal parameters extraction and shorter time required.

Bridge Modal Parameter Identification from UAV Measurement Based on Empirical Mode Decomposition and Fourier Transform

This paper proposes two approaches, Empirical Mode Decomposition (EMD) and Fourier Transform (FT), to correct the vibration signals measured by an Unmanned Aerial Vehicle (UAV), which overcomes the difficulty of selection of reference points used in other correction methods, such as homography transformation and three-dimensional reconstruction. In the method of this paper, a UAV is used to collect the video of a vibrated bridge, and the displacement signal of the bridge is obtained from the video by Kanade–Lucas–Tomasi (KLT) optical flow method, which contains false displacement caused by the ego-motion of the UAV during the measurement. The false displacement can be effectively eliminated by EMD and FT to obtain the real displacement signal. Finally, the displacement signal is processed by the Operational Modal Analysis (OMA) technique to obtain the bridge modal parameters. The performance of correcting vibration signals and extracting bridge modal parameters from the vibration signals based on EMD, FT, and Differential Filtering (DF) are compared by taking the fixed camera measurement as a reference (the accuracy of measuring bridge vibration with fixed cameras has been verified) in this paper, and it is demonstrated that EMD has better reliability in processing signal measured by UAVs, which is mainly due to the absence of random factors and too much noise in the signal processing process of EMD.

Reducing coherent filtering artefacts in time‐domain operational modal analysis

Signals collected for modal analysis are often filtered in order to reduce sensor noise, out-of-band oscillations, or for dealing with closely-spaced modes. This filtering introduces filtering artefacts into the data due to the non-ideal filter response and is well understood for impulse excitation. However, for ambient vibration data filtering, artefacts become superimposed, preventing their visual identification, and will corrupt the correlation function of the data used in time-domain operational modal analysis (OMA) techniques such as covariance-driven stochastic subspace identification and the random decrement technique. This corruption leads to inaccurate, misleading, biased or spurious frequency and damping estimates, with the inaccuracy increasing for systems with higher damping or lower signal-to-noise ratios. Counter-intuitively, the error in damping estimates is as large for modes with natural frequencies far from the filter cutoff frequency as for modes which are close to the cutoff frequency. In this paper, an alternative to filtering for time-domain OMA, trimming of the correlation of noise from unfiltered correlation functions, is introduced and tested using 10,000 numerically generated ambient vibration data sets. It has been shown that this technique reduces the mean absolute error in the frequency estimates by over 200% and the mean absolute error in the damping estimates by over 400%. Additionally, a new technique which incorporates fitting of filtering artefacts as part of the modal analysis is introduced for where filtering of ambient vibration data is unavoidable and is demonstrated using real-world acceleration data collected from a two-way spanning concrete slab subject to footfall excitation.

Structural Identification of a 90 m High Minaret of a Landmark Structure under Ambient Vibrations

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.

Damping identification of offshore wind turbines using operational modal analysis: a review

Abstract. To increase the contribution of offshore wind energy to the global energy mix in an economically sustainable manner, it is required to reduce the costs associated with the production and operation of offshore wind turbines (OWTs). One of the largest uncertainties and sources of conservatism in design and lifetime prediction for OWTs is the determination of the global damping level of the OWT. Estimation of OWT damping based on field measurement data has hence been subject to considerable research attention and is based on the use of (preferably operational) vibration data obtained from sensors mounted on the structure. As such, it is an output-only problem and can be addressed using state-of-the-art operational modal analysis (OMA) techniques, reviewed in this paper. The evolution of classical time- and frequency-domain OMA techniques has been reviewed; however, the literature shows that the OWT vibration data are often contaminated by rotor speed harmonics of significantly high energy located close to structural modes, which impede classical damping identification. Recent advances in OMA algorithms for known or unknown harmonic frequencies can be used to improve identification in such cases. Further, the transmissibility family of OMA algorithms is purported to be insensitive to harmonics. Based on this review, a classification of OMA algorithms is made according to a set of novel suitability criteria, such that the OMA technique appropriate to the specific OWT vibration measurement setup may be selected. Finally, based on this literature review, it has been identified that the most attractive future path for OWT damping estimation lies in the combination of uncertain non-stationary harmonic frequency measurements with statistical harmonic isolation to enhance classical OMA techniques, orthogonal removal of harmonics from measured vibration signals, and in the robustification of transmissibility-based techniques.

The Demonstrator of Structural Health Monitoring System of Helicopter Composite Blades

The health and usage monitoring systems are widely used for the monitoring of vibrations of power plant units on helicopters. At the same time critical helicopter structures like main and tail rotors or tail boom are still out of permanent monitoring. Practically all non-destructive techniques (NDT), like ultrasound, eddy current, X-ray and others make the inspection of structural components available on the ground only, during the maintenance check or overhaul. The article considers the promising technique for structural health monitoring (SHM) of a helicopter in flight, inter alia, of rotating blades. Actively developing methods of modal analysis, especially “operational” one, open the new opportunity for structural monitoring and its attendant issues. The Operational Modal Analysis (OMA) techniques and the methods of its data application are the basis of the novel concept of “modal passport” for monitoring of helicopter’s blades. There is brief description of basic principles of the modal passport and its trial application. The paper discusses the problems associated with practical application of modal passport to rotating helicopter blades and ways to overcome it. The light coaxial helicopter Ka-26 became the operating platform for experimental study of OMA application and works as the demonstrator of advance SHM techniques. Brief description of measurement system, including equipment and transducers on the blades is presented. The discussed research stage aims to demonstrate the potential of OMA techniques for monitoring of rotating blades, applying the seeded faults to estimate sensitivity of the SHM system. The paper discusses analytical and experimental study of the blade, including FE modelling and comparative analysis with the experimental data. The conclusions of the paper summarize the results of the research stage, outline the novelties and its practical application. The tasks of further works for SHM research stages using the demonstrator are formulated.

Multiple damage detection in a cantilever beam using baseline-free operational modal analysis

Operational Modal Analysis (OMA) or output-only modal analysis allows obtaining modal parameters in operational conditions, i.e., without external excitation. While being more challenging than traditional or Experimental Modal Analysis (EMA), OMA allows to monitor the structural health of a structure in cases where EMA is not practical or feasible. This article presents an introduction to an OMA technique based on Frequency Domain Decomposition (FDD) and its mathematical formalism, and demonstrates its potential for detecting damage in a cantilever beam. A transient dynamic Finite-Element Analysis (FEA) under white noise excitation has been performed in ANSYS Workbench to obtain the acceleration responses of the system. The numerical accelerometers signals along the beam are used for the OMA analysis and multiple cracks are analyzed at different positions along the beam. The technique used for damage detection is Curvature Mode Shape (CMS) analysis, using only the information of the damaged structure, making it a baseline-free method. The technique is shown to be capable of correctly detecting and locating the different damages analyzed.