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In most applications, the structure components have to be tested under different loading conditions before being placed in operation. A reliable and low cost measuring technique is desirable. However, most currently employed measuring approaches can only provide the structural response at several discrete locations. The accuracy of the measurements varies with the location and orientation of the sensors. Practically, it is not possible to place sensors at all the critical locations for different excitations. Therefore, an approach that derives the full field response using a limited set of measured data is desirable. In contrast to experimental full field measurement techniques, the expansion approach involves analytically expanding the limited measurements to all the degrees of freedom of the structure. Among all the analytical methods, the modal expansion method is computationally efficient and thus more suitable for real time expansion of measured data. In this method, the full-field response is approximated by the linear combination of mode shapes. In previous studies, the modal expansion method is limited by errors from mode aliasing, inaccuracy of the calculated mode shapes and the noise in measurements. In order to overcome these limitations, the modal expansion method is enhanced by mode selection and error compensation in this study. First, the key parameters used in modal expansion method were analyzed using a cantilever beam model and a method for optimal placement of sensors was developed. A mode selection method and error compensation method based on operation modal analysis and adaptive compressed sensing techniques were then developed to reduce the effects of mode aliasing, mode shape inaccuracy and measurement noise. The developed approach was further tested virtually using a numerical model of rotor 67. The numerical model was created using a two-way coupled fluid structure interaction technique. By developing these methods, the enhanced modal expansion approach can provide full field response for structures under different load conditions. Compared to the traditional modal expansion method, it can expand the data with high noise and under general dynamic loading. / Doctor of Philosophy / Accurate knowledge of the strain and stress at critical locations of a given structure is crucial when assessing its integrity. However, currently employed measuring approaches can only provide the structural response at several discrete locations. Practically, it is not possible to place sensors at all the critical locations for different excitations. Therefore, an approach that derives the full field response using a limited set of measured data is desirable. Compared to experimental full field measurement techniques, the expansion approach is focused on analytically expanding the limited measurements to all the degrees of freedom of the structure. Among all the analytical methods, the modal expansion method is computationally efficient and thus more suitable for real-time expansion of measured data. The current modal expansion method is limited by errors from mode aliasing, inaccuracy of the mode shapes, and the noise in measurements. Therefore, an enhanced method is proposed to overcome these shortcomings of the modal expansion. The following objectives are accomplished in this study: 1) Develop a method for optimal placement of sensors for modal expansion; 2) Eliminate the mode aliasing effects by determining the significance of participated modes using operational modal analysis techniques; 3) Compensate for the noise in measurements and computational model by implementing the compressed sensing approach. After accomplishing these goals, the developed approach is able to provide full field response for structures under different load conditions. Compared to the traditional modal expansion method, it can expand the data under dynamic loading; it also shows promise in reducing the effects of noise and errors. The developed approach is numerically tested using fluid-structure interaction model of rotor 67 fan blade.

The low frequency (0-500 Hz) automotive noise and vibration behavior is influenced by the rolling dynamics of the tire. Driven by pressing environmental concerns, the automotive industry has strived to innovate fuel-efficient and quieter powertrain systems over the last decade. This has eventually led to the prevalence of hybrid and electric vehicles. With the noise masking effect of the engine orders being absent, the interior structure-borne noise is dominated by the tire pavement interaction under 500 Hz. This necessitates an accurate estimation of rolling tire dynamics. To this date, there is no direct procedure available for modal analysis of rolling tires with tread patterns under realistic operating conditions. The present start-of-art laser vibrometer based non-contact measurements are limited to tread vibration measurement of smooth tires only in a lab environment. This study focuses on devising an innovative strategy to use a wireless Tire Cavity Accelerometer (TCA) and two optical sensors in a tire on drum setup with cleat excitation to characterize dynamics of tread vibration in an appreciably easier, time and cost-effective approach. In this approach, First, the TCA vibration signal in a single test run is clustered into several groups representing an array of virtual sensor position at different circumferential positions. Then modal identification has been performed using both parametric and non-parametric operational modal identification procedures. Furthermore, relevant conclusions are drawn about the observed modal properties of the tire under rolling including the limitations of the proposed method. The method proposed here, as is, can be applied to a treaded tire and can also be implemented in an on-road test setup. / Master of Science / The low frequency(0-500 Hz) interior noise and vibration of an automobile is primarily influenced by the dynamics of the rolling tire. In recent studies, the laser vibrometer with moving mirrors for measurement of vibration on the tread of a rotating tire has been used. However, these are limited to tires without tread pattern. In this study, an innovative experimental way of performing operational modal analysis using the Tire cavity Accelerometer (TCA) and optical sensors is presented. The proposed method is simpler in terms of instrumentation and cost and time-effective. This method, as is, can also be implemented in case of a treaded tire

Timber is a building material that is becoming more common and of interest for use in high-rise buildings. One of the reasons is that timber requires less energy input for the manufacturing process of the material compared to non-wood based materials. When designing high- rise timber buildings it is of great significance to understand the dynamic behavior of the structure. One method to obtain the dynamic properties is to use Operational Modal Analysis, which is based on the structural response from operational use. Finite element (FE) analysis is a tool which can be used for dynamic analysis for large structures. In this study an Operation Modal Analysis (OMA) was conducted on a four-story timber building in Växjö. A finite element model was created of the same building using commercial FE packages. Based on the mode shapes and natural frequencies obtained from the OMA, the FE model was fine-tuned. The purpose of this thesis is to gain knowledge of which parameters that might have a significant role in finite element modelling for a structural dynamic analysis. The aim is to develop a finite element model that accurately simulates the dynamic behavior of the tested building. It was shown from the result that is possible with an enough detailed FE model to capture the dynamic behaviour of a structure. The parameters that had the largest effect on the result can be pointed to the mass and the stiffness of the structure. / Trä är ett byggnadsmaterial som börjar bli allt mer vanligt och är av intresse att använda som stommaterial för höga byggnader. En anledning till detta är att det krävs mindre energi i tillverkningsfasen för trä jämfört med stål och betong. Vid dimensionering av höga träbyggnader är det essentiellt att förstå byggnadens dynamiska egenskaper. För att ta fram en byggnads dynamiska egenskaper kan en metod som benämns Operational Modal Analysis (OMA) tillämpas vilken baseras på byggnadens rörelser vid daglig användning. Finita element (FE) metoden är ett verktyg som kan användas vid dynamisk analys för större byggnader. I detta arbete genomfördes en OMA för ett fyravåningshus med trästomme beläget i Växjö. Genom användning av kommersiella FE-mjukvaror togs en finita element modell av samma byggnad fram. Baserat på de egenfrekvenser och egenmoder erhållna från OMA, uppdaterades FE-modellen därefter. Syftet med detta arbete är att erhålla kunskap kring vilka parametrar som har betydelse vid FE-modellering med hänsyn till dynamisk analys. Syftet är även att validera den prototyp av datainsamlingsenhet som använts vid fältmätningen. Målet med arbetet är att ta fram en FE-modell som på ett korrekt sätt beskriver den testade byggnadens dynamiska beteende. Resultatet av arbetet påvisar att med en tillräckligt detaljerad FE-modell är det möjligt att erhålla en byggnads dynamiska egenskaper. De parametrar som har störst inverkan på resultatet är byggnadens styvhet och inkluderad massa.

Chatter, unstable vibration during machining, damages the tool and workpiece. A proper selection of spindle speed and depth of cut are required to prevent chatter during machining. Such proper cutting conditions are usually determined using vibration models of the machining process. Nonetheless, uncertainties in modeling or changes in dynamics during the machining operations can lead to unstable machining vibrations, and chatter may arise even when stable cutting conditions are used in the process planning stage. As a result, online chatter monitoring systems are key to ensuring chatter-free machining operations. Although various chatter monitoring systems are described in the literature, most of the existing methods are suitable for detecting chatter after vibrations become unstable. In order to prevent poor surface finish resulting from chatter marks during the finishing stages of machining, a new monitoring system that is capable of predicting the occurrence of chatter while vibrations are still stable is required. In this thesis, a new approach for predicting the loss of stability during stable turning operations is developed. The new method is based on the identification of the dynamics of self-excited vibrations during turning operations using Operational Modal Analysis (OMA). The numerical simulations and experimental results presented in this thesis confirm the possibility of using Operational Modal Analysis as an online chatter prediction method during stable machining operations. / Graduate

Made available in DSpace on 2014-06-11T19:27:14Z (GMT). No. of bitstreams: 0 Previous issue date: 2006-05-16Bitstream added on 2014-06-13T18:31:07Z : No. of bitstreams: 1 nunesjr_oa_me_ilha.pdf: 970524 bytes, checksum: 9726745cf5f299c04ce31a23c4988b5c (MD5) / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) / A Análise Modal envolvendo apenas as respostas da estrutura é ainda um desafio que requer o uso de técnicas de identificação especiais. Este trabalho discute a identificação baseada apenas na resposta utilizando um método de identificação no tempo, mais especificamente, o método Identificação Estocástica de Subespaço. É mostrado que uma estrutura vibrando excitada por forças não conhecidas, pode ser modelada como um modelo de espaço de estado estocástico. A partir da aplicação de técnicas numéricas robustas como fatorização QR e Decomposição em Valores Singulares para a matriz bloco de Hankel semi-infinita, contendo os dados de resposta, é obtida a estimativa dos estados do modelo. Uma vez que os estados são conhecidos, o sistema de matrizes é encontrado através da solução de um problema de mínimos quadrados. Encontrado o modelo matemático da estrutura, os parâmetros modais são estimados diretamente através da decomposição em autovalores. O trabalho apresenta ainda uma metodologia que utiliza a função densidade de probabilidade para identificar possíveis componentes harmônicos contidos nos sinais de respostas. Os sinais são filtrados em uma faixa de freqüência contendo um provável modo e é verificado se este corresponde a um modo natural ou operacional. A metodologia é avaliada com dados simulados e experimentais e os resultados obtidos mostraram-se promissores para identificação dos parâmetros modais de sistemas estocásticos lineares e invariantes no tempo, utilizando apenas as respostas. / Modal analysis using output-only measurements is still a challenge in the experimental modal analysis community. It requires the use of special modal identification techniques. This work discusses the concepts involved in the output-only modal analysis and the implementation of the Stochastic Subspace Identification time domain method. It is shown that a vibrating structure excited by an unknown force can be modelled as a stochastic state space model. In this approach, the SSI method estimates the state sequences directly from the response data and the modal parameters are estimated by using the eigenvalues decomposition of the state matrix. The steps of the procedure are implemented using the well-known numerical linear algebra algorithms, Singular Value Decomposition and the QR decomposition. It also includes a methodology based on the Probability Density Function to identify harmonic components of the response signals. The signals are filtering in a range of frequency containing a mode, to verify if it is a natural or operational mode. The approach is evaluated with simulated and experimental data and the results have shown to be promising to identify the modal parameters of stochastic linear time-invariant systems, based only on the output data.

No description available.

Digital models are essential to quantifying the behavior of structural systems. In many cases, the creation of these models involves manual measurements taken in the field, followed by a manual creation of this model using these measurements. Both of these steps are time consuming and prohibitively expensive, leading to a lack of utilization of accurate models. We propose a framework built on the processing of 3D laser scanning data to partially automate the creation of these models. We focus on steel structures, as they represent a gap in current research into this field. Previous research has focused on segmentation of the point cloud data in order to extract relevant geometries. These approaches cannot easily be extended to steel structures, so we propose a novel method of processing this data with the goal of creating a full finite element model from the information extracted. Our approach sidesteps the need for segmentation by directly extracting the centerlines of structural elements. We begin by taking "slices" of the point cloud in the three principal directions. Each of these slices is flattened into an image, which allows us to take advantage of powerful image processing techniques. Within these images we use 2d convolution as a template match to isolate structural cross sections. This gives us the centroids of cross sections in the image space, which we can map back to the point cloud space as points along the centerline of the element. By fitting lines in 3d space to these points, we can determine the equations for the centerline of each element. This information could be easily passed into a finite element modeling software where the cross sections are manually defined for each line element. / Modern buildings require a digital counterpart to the physical structure for accurate analysis. Historically, these digital counterparts would be created by hand using the measurements that the building was intended to be built to. Often this is not accurate enough and the as-built system must be measured on site to capture deviations from the original plans. In these cases, a large amount of time must be invested to send personnel out into the field and take large amounts of measurements of the structure. Additionally, these "hand measurements" are prone to user error. We propose a novel method of gathering these field measurements quickly and accurately by using a technique called "laser scanning". These laser scans essentially take a 3D snapshot of the site, which contains all the geometric information of visible elements. While it is difficult to locate items such as steel beams in the 3D data, the cross sections of these structural elements are easily defined in 2D. Our method involves taking 2D slices of this 3D scan which allows us to locate the cross sections of the structural members by searching for template cross-sectional shapes. Once the cross sections have been isolated, their centers can be mapped back from the 2D slice to the 3D space as points along the centerlines of the structural elements. These centerlines represent one of the most time consuming requirements to building digital models of modern buildings, so this method could drastically reduce the total modeling time required by automating this particular step.

Metal buildings account for over 40% of low-rise construction in the US. Despite this, predictive fundamental period equations that were obtained empirically for mid-rise construction are used in seismic design. Analytical modeling of metal building frames implied that these equations significantly underpredict the period, which led to the development of a new predictive equation. However, experimental tests showed that these models may overestimate the measured period. In this work, further tests were carried out in order to single out possible causes. Buildings were tested during different stages of construction to evaluate how non-structural elements could affect the behavior. Both planar and three-dimensional models were developed to determine if design assumptions are accurate for the purpose of estimating the period. The results from tests showed that, unlike other single-story buildings, non-structural components seem to have negligible effect on the structural behavior. However, several buildings seemed to exhibit signs of fixed conditions at the column base. This assertion was corroborated by updating the analytical models. The two modeling approaches showed good agreement with each other as well, validating the use of planar models to predict the period. Finally, new predictive equations are proposed that take into account the type of cladding, as it was found to be an important variable not previously considered. However, low mass participation ratios coupled with the stiffness provided by the secondary framing put the use of the equivalent lateral force procedure into question. / Master of Science / When designing buildings for earthquake loads it is necessary to know their dynamic properties in order to define the equivalent forces that must be applied. Building codes provide predictive equations that were obtained empirically for typical mid-rise construction. Metal buildings do not fall within the range of buildings tested for their development, and so a new equation was proposed for them based on a database of planar models. However, previous tests implied that this equation was predicting larger periods than those obtained experimentally. In this work, further tests were carried out during different stages of construction to evaluate how non-structural elements could affect the behavior. Models were also created for each building in order to determine if the approach used to develop the metal building database was adequate for estimating the period. The results from tests showed that, unlike other single-story buildings, non-structural components seem to have negligible effect on the structural behavior, and the modeling assumptions within the database were validated. Further analysis showed that the type of cladding (concrete or metal sheeting) had a large influence on the properties of metal buildings. In consequence, a new set of predictive equations is proposed that takes this into account.