Application Of Modal Analysis Research Articles

Application of Modal Analysis for the Vibrational Comfort Investigation on Board Ships: a Case Study

Application of Modal Analysis for the Vibrational Comfort Investigation on Board Ships: a Case Study

Development of a Quality Control System Using Modal Analysis to Evaluate a Multi-Point Projection Welding Process.

The article presents the results of the development and research regarding the application of modal analysis to the evaluation of a multi-point projection welding process. The quality control system is based on the information provided by modal analysis for the entire welding station after the previously completed welding process. The research is carried out due to the lack of an effective method for assessing the course of the multi-spot projection welding process in the case of a single current circuit passing through many points at the same time. A study of the applicability of modal analysis in investigating the quality of a multipoint joint was conducted for four DIN 928 nuts welded to a steel profile. The aim of the study was to determine the influence of weld defects on the displacement of resonant frequencies. To realize the objective, the dynamic properties of the entire welding station, including the sample in the frequency domain, were investigated. In the first stage of the study, a finite element method was used to perform modal analysis and examine the form of vibrations for the individual natural frequencies of the welding fixture including the sample. Then, quality verification using the dynamic resistance method was performed, which was compared later with the modal approach. The last stage of the study was to conduct modal analysis in the frequency domain to verify the numerical studies.

Application of modal analysis to multi-objective optimization of gear box

Application of modal analysis to multi-objective optimization of gear box

Application of Modal Strain Energy Analysis to Localize an Added Mass on an Aluminium Plate.

The modal strain energy method is a vibration-based damage detection method that allows the use of passive measurements. The method is based on the measurement and analysis of the modal response of the structure under investigation. The aim of this work is to investigate the application of this method to detect and localise a local change in a structure using acoustic measurements in a fluid around the structure. Firstly, the modal strain energy is presented. The technique is based on the analysis of the modal shapes of undamaged and damaged samples obtained by operational modal analysis. The application of modal strain energy to off-contact acoustic measurements is then discussed. The method is used to detect and locate a local change (an additional mass) in an aluminium plate subjected to a mechanical force. The study begins with numerical simulation using finite element models, followed by experiments on the aluminium plate.

Application of Modal Analysis of Earthquake Force and Natural Frequency Tanjung Baru Bridge

The dynamic response of a structural system can be described by modal analysis. In the present study, the modal analysis that adopts an Undamped Degree of Freedom (Undamped-DOF) System is implemented to describe the modal descriptors such as the natural frequency and mode shape of a bridge. Furthermore, the earthquake load acting on the bridge is also evaluated and hence the possibility of a resonance associated with this load is investigated. For this objective, the earthquake data collected during the past ten years in Indonesia is explored. This study considers the Tanjung Baru Bridge, a prestressed concrete bridge situated on the Medan-Kualanamu-Tebing Tinggi highway, as the case study. The modal analysis and the evaluation of the earthquake load confirm that the possibility of resonance for the Tanjung Baru Bridge is extremely low. The study also proves that this bridge has a sufficient capacity to withstand earthquake loads.

Smooth mode decomposition: Theory and its applications in full-field output-only modal analysis

Full-field output-only modal analysis (OMA) became popular due to its superior spatiotemporal resolution over traditional sensing methods. It provides rich spatial dynamic information, which is essential for high-fidelity modal models, model updating, and non-intrusive health monitoring. However, the full-field sensory techniques implementation in OMA is hurdled by the excessive storage and computational requirements and the temporal aliasing effect. This paper develops a novel modal decomposition method, called smooth mode decomposition (SMD), to tackle these hurdles by exploiting the spatial dynamics and smoothness of the observed field measurements. SMD imposes the smoothness constraint on the identified mode shapes to resolve a set of orthogonal modes, called the smooth orthogonal modes (SOMs), that maximally represent the original field while also keeping the mode shape as smooth as possible. Since the SMD seeks spatially-smooth modal structures, the requirements on the temporal sampling can be relaxed. Hence, the SMD can be applied to nonuniformly and sub-Nyquist sampled full-field measurement data. Moreover, the SOMs converge to linear normal modes of uniformly distributed parameter systems, which provides a physically meaningful decomposition of the measurement data. Through a series of numerical examples, the SMD is compared to other popular covariance-based OMA methods. These examples demonstrate the merit of the proposed method when the vibration system has nonuniform system parameters and when the data is undersampled. Further, a full-field strain measurement technique, the three-dimensional digital image correlation, is utilized where spatiotemporal displacement measurements are obtained from a vibrating cantilever beam. The SMD is shown to provide accurate mode estimates with undersampled experimental data. Statistically, SMD shows its flexibility and quality in modal identification using temporally randomly captured images, which opens an avenue for alleviating storage and processing requirements for image-based full-field OMA.

Triggering of galloping in structures at low Reynolds numbers

The fundamental mechanisms that are important for the triggering of galloping in a flow-induced vibration (FIV) system consisting of the flow past an elastically-mounted body (D-section, isosceles-triangular, rectangular) is investigated in this paper using three key-enabling methodologies: namely, high-fidelity full-order model/computational fluid dynamics simulations, modal analysis based on the determination of an data-driven model using the eigensystem realization algorithm, and use of the Den Hartog stability (galloping) criterion for the assessment of the aerodynamically unstable behavior of the system obtained from classical quasi-steady theory. The synthesis of the results from the application of these three key-enabling technologies is used to study the effect of the Reynolds number Re, the mass ratio m∗, the cross-sectional geometry and the angle of attack of the incident wind direction relative to the orientation of the elastically-mounted body on the suppression or initiation of galloping. In the application of data-driven modal analysis to a FIV system with coupled modes, the importance of identifying correctly which of the coupled modes correspond to the structure mode (SM) possibly taking into account mode switching is stressed, and the failure to do so is shown to lead to a significant underestimation of the value of the reduced velocity Ur associated with the onset of galloping. The range of values of Ur where the SM is positive is related to the flutter lock-in regime for smaller values of Ur (typically for Ur≤7) and to the galloping regime for the larger values of Ur (typically for Ur≥10). The application of data-driven modal analysis to a FIV system shows that increasing Re and decreasing m∗ has two effects: namely, enhancement of the coupling between the structure and wake modes and increases of the range of Ur values where the SM exhibits a positive growth rate. Data-driven modal analysis and the Den Hartog stability criterion is applied to explain the recently observed phenomenon of the collapse of galloping for a rectangular cylinder when the side ratio is decreased below a critical threshold value (between about 0.1 and 0.2). It is shown that galloping appears and disappears when the flat face of a body in directed into (windward of) or away from (leeward of) the incident wind direction. An investigation of the effects of the cross-sectional geometry of the body on the triggering of soft- or hard-galloping is undertaken.

Feasibility of Drone-Based Modal Analysis Using ToF-Grayscale and Tracking Cameras

The application of modal analysis is a well-established procedure for detecting damage in civil structures. However, implementing monitoring systems on civil structures could involve a large number of sensors leading to expensive and cumbersome setups. On the other hand, Unmanned Aerial Vehicles (UAVs) are already employed for monitoring purposes. Moreover, by using UAVs inspections can be executed close to structures and using a single measurement node, that can be moved from one measurement point to another. In this article, a vision-based measurement procedure composed of a system mounted on a prototype drone is presented, in order to perform modal analysis of a structure. This measuring system is equipped with a grayscale camera, a Time-of-Flight (ToF) sensor and a trajectory tracking camera. This composition is necessary to measure vibrations by tracking features on the structure (grayscale camera), to convert vibrations from pixels to millimetres (ToF sensor) and to track the trajectory of the drone (trajectory tracking camera). This latter sensor is used to reduce the effect of the movement of the drone in relation to the vibrations of the structure and to reconstruct the 3D geometry of the structure. The grayscale camera on the drone is synchronized with another fixed grayscale camera, that frames a point on the structure, used as the reference point for modal analysis. This measurement procedure was tested on a mock-up of a structure a few metres in size and the results are compared with those obtained using accelerometers. The outcome of these tests proves that it is possible to correctly measure resonance frequencies (with errors lower than 0.3 %) and to reconstruct mode shapes with cameras assembled on a drone, as well as to reconstruct the 3D geometry of the points measured.

Contributions for enhanced tracking of (onshore) wind turbines modal parameters

The structural performance of wind turbines is highly dependent on their dynamic behaviour, meaning the monitoring of their structural health should take their dynamic response into account, which can be pursued through the continuous application of Operational Modal Analysis (OMA) to time-series recorded on the structure and subsequent tracking of modal properties. However, it is impractical to manually analyse long periods of data, being therefore essential to automatize OMA.Furthermore, it is necessary to link the results obtained in each dataset. This is usually based on the comparison between estimated modal properties and a trusted set of references. However, the identification of said set of references is normally performed manually, taking time, and producing a result that may be biased. Additionally, in the case of wind turbines, due to the diversity of their operating condition, several sets of references have to be defined, making this process even more cumbersome and subjective.In this sense, this work takes advantage from a continuous monitoring program of an onshore wind turbine, to propose and validate a procedure for the automatic determination of a set of reference modal properties and their subsequent use in modal tracking, which is then validated with results from 18 months of continuously recorded data. Additionally, a complementary very expedite procedure for a preliminary evaluation of the wind turbine dominant frequencies, and detection of eventual problematic resonances, is presented and evaluated using alternative sensors (accelerations, strains and rotations) and data from 3 different turbine models.

Critical buses identification for voltage stability assessment considering the application of modal analysis and a robust state estimation with bad data suppression

Critical buses identification for voltage stability assessment considering the application of modal analysis and a robust state estimation with bad data suppression

Applications of Operational Modal Analysis in Gearbox and Induction Motor, Based on Random Decrement Technique and Enhanced Ibrahim Time Method

There have been steadily growing requirements from the academia and industry, demanding non-invasive methods and reliable measurement systems of research devoted to operational mode analysis (OMA). Due to the simplicity of performing only structures surface vibration measurements, OMA is frequently applied in machine fault diagnosis (MFD) and structure health monitoring (SHM). OMA can handle big structures, such as bridges, buildings, machines, etc. However, there is still an open question: how to properly handle the harmonic effects of rotating components and the difficulty of closely estimating space modes are still a nightmare to deal with. Therefore, the main objective of this paper is to identify the structure of natural frequencies by the regeneration of frequency response functions (FRFs) for complex structures based on OMA. The novelty of our approach is to use the random decrement technique (RDT), correlation function estimation (CFE), and enhanced Ibrahim time method (EITM) to overcome OMA’s difficulties and limitations. To reduce further rotational harmonics effects, gear mesh and side band frequencies, digital signal processing techniques based on notching filters, and liftering analysis techniques were also used. All the experiments were performed at the laboratory test rig and conducted by using three accelerometers, one impedance hammer, one force sensor, and one data acquisition board. To reduce data’s variabilities, each test was measured three times for 5 min. The data sampling frequency for all the experiments was 25.6 kHz. To validate the proposed methodology, extensive OMA tests were performed for the generation of FRFs. The measured objects were a steel bar, induction motor, and gearbox. Five structural natural frequencies for the induction motor and eight structural natural frequencies for the gearbox were generated, respectively.

Gaussian mixture model based phase prior learning for video motion estimation

Optic measurement nowadays shows more prominent features over the traditional sensor-based measurement techniques as it does not need sensor installment and can provide simultaneous measurements with very high spatial resolution. Phase-based video processing has been widely used in optic measurement for capturing small motions. It relies on the assumptions that the variance of noise has to be much lower than the pure signal and small motions are encoded in the phase shift of an individual pixel’s color which fundamentally restricts its usefulness. To tackle these issues, this paper proposes a novel perspective of phase estimation by utilizing the image priors on phase patches. The patch group based Gaussian Mixture Model (PG-GMM) learning algorithm is used to learn the nonlocal self-similarity (NSS) prior from training images. Then the phase information is modeled by learned patch group priors, and further optimized using the steps of gaussian component selection and weighted sparse coding. The proposed method is validated in both magnification and modal analysis applications in the example analysis. Compared to the phase-based method, the proposed method achieves high-quality magnifications on the real video signal, with fewer artifacts and better anti-noise performance. Clearer time-domain motion estimates of video components can also be extracted by the proposed method.

Operational Modal Analysis of an Axial Compressor Rotor and Casing System for the Online Identification of a Digital Twin

Modal parameter identification can be a valuable tool in mechanical engineering to predict vibrational behaviour and avoid machine damage during operation. Operational modal analysis is an output-only identification tool motivated by the structural identification of civil engineering structures, which are excited by ambient conditions. This technique is increasingly applied in mechanical engineering in order to characterise the system behaviour during operation as modal parameters can vary under operating conditions. The following study investigates the application of operational modal analysis on an axial compressor under operating conditions. Since the modal parameters of the system change depending on the life history and during the operation of the system, a corresponding data analysis might allow us to identify the present status of the system. Eigenfrequencies and eigenvectors are studied for the use of structural health monitoring approaches. According to the analysis, eigenfrequencies represent robust parameters for the studied purpose. Eigenvectors are sensitive to damages but need further investigation, especially for rotating machinery. This study will help the user to set up a virtual model, which describes the system behaviour for different boundary conditions. This in turn, will provide an accurate prediction of the vibrational behaviour in order to assure a safe operation.

Uncertainty quantification of modal parameter estimates obtained from subspace identification: An experimental validation on a laboratory test of a large-scale wind turbine blade

The uncertainty afflicting modal parameter estimates stems from e.g., the finite data length, unknown, or partly measured inputs and the choice of the identification algorithm. Quantification of the related errors with the statistical Delta method is a recent tool, useful in many modern modal analysis applications e.g., damage diagnosis, reliability analysis, model calibration. In this paper, the Delta method-based uncertainty quantification methodology is validated for obtaining the uncertainty of the modal parameter and the modal indicator estimates in the context of several well-known subspace identification algorithms. The focus of this study is to validate the quality of each Delta method-based approximation with respect to the experimental Monte Carlo distributions of parameter estimates using a statistical distance measure. On top of that, the accuracy in obtaining the related confidence intervals is empirically assessed. The case study is based on data obtained from an extensive experimental campaign of a large scale wind turbine blade tested in a laboratory environment. The results confirm that the Delta method is, on average, adequate to characterize the distribution of the considered estimates solely based on the quantities obtained from one data set, validating the use of this statistical framework for uncertainty quantification in practice.

Application of operational modal analysis to investigate transformer vibration patterns

This paper develops an operational modal analysis application framework for vibration measurement-based condition monitoring of transformer winding structure. Within the framework, load transient signals generated by turning on and off transformer or changing transformer load are used as the broadband excitations. Frequency domain decomposition (FDD) technique is used to process the measured transformer vibration signals to detect possible mechanical changes to the transformer's winding and core structure. Case studies demonstrate the OMA application framework (broadband excitation and FDD) can achieve higher accuracy of natural frequency detection of windings, which can pave a way for online transformer winding and core condition monitoring.

Design and Development of Unibody Quadcopter Structure Using Optimization and Additive Manufacturing Techniques

Quadcopters represent rotary wing configuration of the Unmanned Aerial Vehicles (UAVs) with immense application potential in industrial and strategic contexts. Tradeoff between flight endurance and payload capacity renders design optimization of UAVs a critical activity with substantial impact on the application possibilities. Among the structural parts of a typical Quadcopter, the central body frame constitutes major portion of the total weight. The present study aims at reduction of the frame weight while conforming with structural integrity requirements, through an integrated approach involving topology optimization, part consolidation and design for additive manufacturing (DFAM). Commercial UAV designs consist of multiple parts and fastening elements that necessitate considerable time and effort for assembly. This study reengineers the frame as a monocoque structure with desirable outcomes of weight reduction and less assembly time. The reengineered Quadcopter structure is manufactured through Fused Filament Fabrication (FFF) and characterized with reference to structural, vibrational and fatigue characteristics. Concomitant application of modal analysis, computational fluid dynamics and wind tunnel testing reveals close match between theoretical estimates and experimental results. Assembly and field trials of the monocoque Quadcopter structure affirm betterment of operational superiority and endurance vis-a-vis commercial UAV designs.

Operational Modal Analysis and Non-Linear Dynamic Simulations of a Prototype Low-Rise Masonry Building

This paper focuses on the dynamic behaviour of a low-rise masonry building representing the Italian residential heritage through experimental and numerical analyses. The authors discuss an application of combined Operational Modal Analysis and Finite Element Model updating for indirect estimation of the structural parameters. Two ambient vibration tests were carried out to estimate the structure’s dynamic behaviour in operational conditions. The first experimental setup consisted of accelerometers gathered in a row along the first floor to characterize the local dynamic of the floor. Conversely, the second setup had the accelerometers placed at the building’s corners to characterize the global dynamics. The outcomes of the first setup were used to estimate the mechanical parameters of the floor, while the ones form the second were used to characterize the mechanical parameters of the masonry piers. Therefore, two finite element models were implemented: (i) a single beam with an equivalent section of the floor to grasp the local behaviour of the investigated horizontal structure; (ii) an equivalent frame model of the entire building to characterise the global dynamic behaviour. The model updating process was developed in two phases to seize local and global dynamic responses. The updated numerical model formed the basis for a sensitivity analysis using the modelling parameters. The authors chose to delve into the influence of the floor on the dynamic behaviour of low-rise masonry buildings. With this aim, non-linear dynamic analyses were carried out under different mechanical characteristics of floors, expressing the scatter for ordinary masonry buildings. The displacements’ trends along the height of the building evidenced the notable role of the floor’s stiffness in the non-linear dynamic behaviour of the building. Lastly, the authors derived the fragility curves predicting the seismic performance in failure probability under a highly severe damage state.

Application of modal and harmonic analysis to predict the automotive transmission vibration at an early stage of design

Introduction (problem statement and relevance). The need to increase the operating speeds and input torque of automobile transmissions because of their vibration is becoming a more and more urgent problem.The purpose of the study was to substantiate the applicability of harmonic analysis, which makes it possible to determine the actual values of vibration values during a steady oscillatory process, for the initial assessment of the gearbox vibration activity.Methodology and research methods. The calculation of the gearbox vibration activity was carried out by modal and harmonic analyses, implemented by the finite element method, and followed by the experimental study of gearbox vibration on a test bench.Scientific novelty and results. The presented experimental and calculated results of the research show that the difference between the experimental and calculated values is no more than 4.2%. This proves the possibility of applying modal and harmonic analysis to predict the gearbox vibration state at an early stage of product design at the stand.Practical significance. The given calculation algorithm makes it possible to predict, with a sufficient degree of accuracy, the vibration of the gearbox before the manufacture of a prototype in experimental production.

Obtaining mass normalized mode shapes of motorway bridges based on the effect of traffic movement

Ambient vibration testing has become a promising alternative for the forced vibration method due to its well-established practical advantages on bridge structures. However, because of the unavailability of the input data in output-only vibration tests, the extracted mode shapes are not mass normalized. Mass normalized mode shapes are essential in various modal analysis applications such as flexibility-based damage detection techniques. Mass change method was proposed to resolve this issue for Operational Modal Analysis (OMA); however, there are certain practical issues that limit the applicability of this method to real-world structures. In this paper, we propose to utilize the dynamic effects of the traffic movement over bridges as the required perturbation to the structure's modal properties. Numerous traffic conditions are considered, and uncertainty analyses are performed to evaluate the suitability of the loads in different traffic scenarios. Furthermore, a numerical case study is conducted on Hafez Bridge in the city of Tehran, Iran. Actual traffic conditions are simulated using the traffic micro-simulation method, and vehicle forces and masses are applied to the finite element model of the bridge using the equivalent nodal forces method. OMA is conducted in the time domain, and modal parameters are extracted using the Stochastic Subspace Identification method. Finally, it is shown that using the proposed framework, not only the modal scaling factors are estimated with satisfying accuracy, but also the practical difficulties of the conventional mass change method such as bridge shutdowns are eliminated.

Modal identification of concrete dams under natural excitation

Historically, the dynamic testing of concrete dams has been associated with experimental modal analysis (EMA) and the performance of forced vibrations tests. Nevertheless, this type of tests requires the use of a heavy equipment and the interruption of the regular operation of the structure. An alternative to EMA relies on the application of operational modal analysis (OMA), through the performance of ambient vibration tests, and thus, it is essential to investigate if the application of OMA to concrete dams can provide good results with high levels of accuracy. In this context, this work addresses the performance of ambient vibration tests on concrete dams with quite diverse geometrical attributes and on the application of state-of-art output-only modal identification methods, to gain awareness of the issues that may occur during the application of OMA methods to signals with such low amplitudes (of the order of micro g), such as those that are usually recorded when dealing with these massive structures. More specifically, the paper describes the ambient vibration tests executed on six very different concrete dams. The most relevant modal properties are estimated through the application of modern output-only modal identification techniques, stressing the good level of accuracy achieved, which is quantified through the calculation of modal properties’ uncertainties. Finally, a novel approach considering the uncertainties estimated is used to study the effect of noise on the quality of modal estimates and to qualify the adequacy of sensors to perform these tests on dams.