977 resultados para Impulse response


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Esse trabalho está baseado na investigação dos detectores de falhas aplicando classificadores de classe única. As falhas a serem detectadas são relativas ao estado de funcionamento de cada componente do circuito, especificamente de suas tolerâncias (falha paramétrica). Usando a função de transferência de cada um dos circuitos são gerados e analisados os sinais de saída com os componentes dentro e fora da tolerância. Uma função degrau é aplicada à entrada do circuito, o sinal de saída desse circuito passa por uma função diferenciadora e um filtro. O sinal de saída do filtro passa por um processo de redução de atributos e finalmente, o sinal segue simultaneamente para os classificadores multiclasse e classe única. Na análise são empregados ferramentas de reconhecimento de padrões e de classificação de classe única. Os classficadores multiclasse são capazes de classificar o sinal de saída do circuito em uma das classes de falha para o qual foram treinados. Eles apresentam um bom desempenho quando as classes de falha não possuem superposição e quando eles não são apresentados a classes de falhas para os quais não foram treinados. Comitê de classificadores de classe única podem classificar o sinal de saída em uma ou mais classes de falha e também podem classificá-lo em nenhuma classe. Eles apresentam desempenho comparável ao classificador multiclasse, mas também são capazes detectar casos de sobreposição de classes de falhas e indicar situações de falhas para os quais não foram treinados (falhas desconhecidas). Os resultados obtidos nesse trabalho mostraram que os classificadores de classe única, além de ser compatível com o desempenho do classificador multiclasse quando não há sobreposição, também detectou todas as sobreposições existentes sugerindo as possíveis falhas.

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O presente trabalho apresenta um estudo referente à aplicação da abordagem Bayesiana como técnica de solução do problema inverso de identificação de danos estruturais, onde a integridade da estrutura é continuamente descrita por um parâmetro estrutural denominado parâmetro de coesão. A estrutura escolhida para análise é uma viga simplesmente apoiada do tipo Euler-Bernoulli. A identificação de danos é baseada em alterações na resposta impulsiva da estrutura, provocadas pela presença dos mesmos. O problema direto é resolvido através do Método de Elementos Finitos (MEF), que, por sua vez, é parametrizado pelo parâmetro de coesão da estrutura. O problema de identificação de danos é formulado como um problema inverso, cuja solução, do ponto de vista Bayesiano, é uma distribuição de probabilidade a posteriori para cada parâmetro de coesão da estrutura, obtida utilizando-se a metodologia de amostragem de Monte Carlo com Cadeia de Markov. As incertezas inerentes aos dados medidos serão contempladas na função de verossimilhança. Três estratégias de solução são apresentadas. Na Estratégia 1, os parâmetros de coesão da estrutura são amostrados de funções densidade de probabilidade a posteriori que possuem o mesmo desvio padrão. Na Estratégia 2, após uma análise prévia do processo de identificação de danos, determina-se regiões da viga potencialmente danificadas e os parâmetros de coesão associados à essas regiões são amostrados a partir de funções de densidade de probabilidade a posteriori que possuem desvios diferenciados. Na Estratégia 3, após uma análise prévia do processo de identificação de danos, apenas os parâmetros associados às regiões identificadas como potencialmente danificadas são atualizados. Um conjunto de resultados numéricos é apresentado levando-se em consideração diferentes níveis de ruído para as três estratégias de solução apresentadas.

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O presente trabalho aborda o problema de identificação de danos em uma estrutura a partir de sua resposta impulsiva. No modelo adotado, a integridade estrutural é continuamente descrita por um parâmetro de coesão. Sendo assim, o Modelo de Elementos Finitos (MEF) é utilizado para discretizar tanto o campo de deslocamentos, quanto o campo de coesão. O problema de identificação de danos é, então, definido como um problema de otimização, cujo objetivo é minimizar, em relação a um vetor de parâmetros nodais de coesão, um funcional definido a partir da diferença entre a resposta impulsiva experimental e a correspondente resposta prevista por um MEF da estrutura. A identificação de danos estruturais baseadas no domínio do tempo apresenta como vantagens a aplicabilidade em sistemas lineares e/ou com elevados níveis de amortecimento, além de apresentar uma elevada sensibilidade à presença de pequenos danos. Estudos numéricos foram realizados considerando-se um modelo de viga de Euler-Bernoulli simplesmente apoiada. Para a determinação do posicionamento ótimo do sensor de deslocamento e do número de pontos da resposta impulsiva, a serem utilizados no processo de identificação de danos, foi considerado o Projeto Ótimo de Experimentos. A posição do sensor e o número de pontos foram determinados segundo o critério D-ótimo. Outros critérios complementares foram também analisados. Uma análise da sensibilidade foi realizada com o intuito de identificar as regiões da estrutura onde a resposta é mais sensível à presença de um dano em um estágio inicial. Para a resolução do problema inverso de identificação de danos foram considerados os métodos de otimização Evolução Diferencial e Levenberg-Marquardt. Simulações numéricas, considerando-se dados corrompidos com ruído aditivo, foram realizadas com o intuito de avaliar a potencialidade da metodologia de identificação de danos, assim como a influência da posição do sensor e do número de dados considerados no processo de identificação. Com os resultados obtidos, percebe-se que o Projeto Ótimo de Experimentos é de fundamental importância para a identificação de danos.

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Nesta Dissertação propõe-se a aplicação de algoritmos genéticos para a síntese de filtros para modular sinais de controladores a estrutura variável e modo deslizante. A modulação do sinal de controle reduz a amplitude do sinal de saída e, consequentemente, pode reduzir o consumo de energia para realizar o controle e o chattering. Esses filtros também são aplicados em sistemas que possuem incertezas paramétricas nos quais nem todas as variáveis de estado são medidas. Nesses sistemas, as incertezas nos parâmetros podem impedir que seus estados sejam estimados com precisão por observadores. A síntese desses filtros necessita da obtenção da envoltória, que é o valor máximo da norma de cada resposta impulsiva admissível no sistema. Após este passo, é sintetizado um filtro que seja um majorante para a envoltória. Neste estudo, três métodos de busca da envoltória por algoritmos genéticos foram criados. Um dos métodos é o preferido, pois apresentou os melhores resultados e o menor tempo computacional.

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Este trabalho tem como objetivos analisar as semelhanças das respostas dos países da Zona do Euro aos choques na política monetária e no câmbio (identificados através de restrições de sinais nas funções impulso-resposta) e investigar a simetria das flutuações na taxa de crescimento do nível de atividade na região através da análise da importância relativa da resposta do crescimento do PIB destes países aos choques comum e específico identificados pelo modelo FAVAR utilizado, que foi estimado através de um método Bayesiano desenvolvido para incorporar prioris de Litterman (1986). A importância do choque comum (relativamente ao específico) nos diversos países, fornece uma medida do grau de integração dos diversos membros da Zona do Euro. O trabalho contribui para a análise do grau de integração dos países da Zona do Euro ao utilizar uma metodologia que permite o uso de um amplo conjunto de variáveis e ao identificar o grau de simetria das flutuações na taxa de crescimento do nível de atividade dos membros da região através da identificação dos choques comuns e específicos. Foram utilizados dados trimestrais de 1999.I a 2013.I para os 17 países da região. Os resultados encontrados apontam para a existência de uma maior integração entre as grandes economias da Zona do Euro ( com exceção da França) e uma integração menor para as menores economias (com exceção da Finlândia).

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Este artigo compara a habilidade preditiva foradaamostra de um modelo DSGE (DynamicStochastic General EquilibriumModel)Novo-Keynesiano, especificado e estimado para o Brasil, com a de um modelo Autorregressivo Vetorial (VAR) e com a de um modelo AutorregressivoVetorial Bayesiano (BVAR). O artigo inova em relação a outros trabalhos similares feitos para o Brasil (Castro et al. (2011) e Caetano e Moura (2013)), ao escolher uma especificação para o modelo DSGE que, ao permitir o uso de um conjunto de informação mais rico, tornou possível computar-se a habilidade preditiva do DSGE a partir de previsões que são,verdadeiramente,previsõesfora da amostra. Ademais, diferentemente de outros artigos que utilizaram dados brasileiros, avalia-se em que medida as respostas das variáveis aos choques na política monetária e no câmbio, obtidas pelo modelo DSGE, se assemelham àquelas de um BVAR estimado através de procedimentos bayesianos desenvolvidos de forma consistente. O modelo DSGE estimado é similar ao utilizado por Justiniano e Preston (2010) e Alpanda (2010). O modelo BVAR foi estimado utilizando uma metodologia semelhante à desenvolvida por Sims e Zha (1998), Waggoner e Zha (2003) e Ramírez, Waggoner e Zha (2007).Os resultados obtidos mostram que o modelo DSGE é capaz de gerar, para algumas variáveis, previsões competitivas em relação às dos outros modelos rivais VAR e BVAR. Além disso, as respostas das variáveis aos choques nas políticas monetária e cambial, nos modelos DSGE e BVAR, são bastante similares.

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Predicting the response of a structure following an impact is of interest in situations where parts of a complex assembly may come into contact. Standard approaches are based on the knowledge of the impulse response function, requiring the knowledge of the modes and the natural frequencies of the structure. In real engineering structures the statistics of higher natural frequencies follows those of the Gaussian Orthogonal Ensemble, this allows the application of random point process theory to get a mean impulse response function by the knowledge of the modal density of the structure. An ensemble averaged time history for both the response and the impact force can be predicted. Once the impact characteristics are known in the time domain, a simple Fourier Transform allows the frequency range of the impact excitation to be calculated. Experimental and numerical results for beams, plates, and cylinders are presented to confirm the validity of the method.

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In this paper, an efficient iterative discrete Fourier transform (DFT) -based channel estimator with good performance for multiple-input and multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) systems such as IEEE 802.11n which retain some sub-carriers as null sub-carriers (or virtual carriers) is proposed. In order to eliminate the mean-square error (MSE) floor effect existed in conventional DFT-based channel estimators, we proposed a low-complexity method to detect the significant channel impulse response (CIR) taps, which neither need any statistical channel information nor a predetermined threshold value. Analysis and simulation results show that the proposed method has much better performance than conventional DFT-based channel estimators and without MSE floor effect.

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本文首先介绍了旋翼飞行机器人控制系统的功能与应用,着重介绍了其中基于tmx320f28335数字信号处理器的无线增稳操控系统工作原理、硬件构架以及软件流程,并对AD转换过程中的关键FIR滤波算法进行说明,详尽比较了不同滤波参数对滤波效果的影响,最后得到该方法可以应用于旋翼飞行机器人增稳控制系统的结论,并将应用该方法滤波后的控制信号应用于实际增稳飞行,以实际数飞行据验证上述结论。

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An high-resolution prestack imaging technique of seismic data is developed in this thesis. By using this technique, the reflected coefficients of sheet sands can be gained in order to understand and identify thin oil reservoirs. One-way wave equation based migration methods can more accurately model seismic wave propagation effect such as multi-arrivals and obtain almost correct reflected energy in the presence of complex inhomogeneous media, and therefore, achieve more superiorities in imaging complex structure. So it is a good choice to apply the proposed high-resolution imaging to the presatck depth migration gathers. But one of the main shorting of one-way wave equation based migration methods is the low computational efficiency, thus the improvement on computational efficiency is first carried out. The method to improve the computational efficiency of prestack depth migration is first presented in this thesis, that is frequency-dependent varying-step depth exploration scheme plus a table-driven, one-point wavefield interpolation technology for wave equation based migration methods; The frequency-dependent varying-step depth exploration scheme reduces the computational cost of wavefield depth extrapolation, and the a table-driven, one-point wavefield interpolation technology reconstructs the extrapolated wavefield with an equal, desired vertical step with high computational efficiency. The proposed varying-step depth extrapolation plus one-point interpolation scheme results in 2/3 reduction in computational cost when compared to the equal-step depth extrapolation of wavefield, but gives the almost same imaging. The frequency-dependent varying-step depth exploration scheme is presented in theory by using the optimum split-step Fourier. But the proposed scheme can also be used by other wave equation based migration methods of the frequency domain. The proposed method is demonstrated by using impulse response, 2-D Marmousi dataset, 3-D salt dataset and the 3-D field dataset. A method of high-resolution prestack imaging is presented in the 2nd part of this thesis. The seismic interference method to solve the relative reflected coefficients is presented. The high-resolution imaging is obtained by introducing a sparseness- constrained least-square inversion into the reflected coefficient imaging. Gaussian regularization is first imposed and a smoothed solution is obtained by solving equation derived from the least-square inversion. Then the Cauchy regularization is introducing to the least-square inversion , the sparse solution of relative reflected coefficients can be obtained, that is high-resolution solution. The proposed scheme can be used together with other prestack imaging if the higher resolution is needed in a target zone. The seismic interference method in theory and the solution to sparseness-constrained least-square inversion are presented. The proposed method is demonstrated by synthetic examples and filed data.

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The processes of seismic wave propagation in phase space and one way wave extrapolation in frequency-space domain, if without dissipation, are essentially transformation under the action of one parameter Lie groups. Consequently, the numerical calculation methods of the propagation ought to be Lie group transformation too, which is known as Lie group method. After a fruitful study on the fast methods in matrix inversion, some of the Lie group methods in seismic numerical modeling and depth migration are presented here. Firstly the Lie group description and method of seismic wave propagation in phase space is proposed, which is, in other words, symplectic group description and method for seismic wave propagation, since symplectic group is a Lie subgroup and symplectic method is a special Lie group method. Under the frame of Hamiltonian, the propagation of seismic wave is a symplectic group transformation with one parameter and consequently, the numerical calculation methods of the propagation ought to be symplectic method. After discrete the wave field in time and phase space, many explicit, implicit and leap-frog symplectic schemes are deduced for numerical modeling. Compared to symplectic schemes, Finite difference (FD) method is an approximate of symplectic method. Consequently, explicit, implicit and leap-frog symplectic schemes and FD method are applied in the same conditions to get a wave field in constant velocity model, a synthetic model and Marmousi model. The result illustrates the potential power of the symplectic methods. As an application, symplectic method is employed to give synthetic seismic record of Qinghai foothills model. Another application is the development of Ray+symplectic reverse-time migration method. To make a reasonable balance between the computational efficiency and accuracy, we combine the multi-valued wave field & Green function algorithm with symplectic reverse time migration and thus develop a new ray+wave equation prestack depth migration method. Marmousi model data and Qinghai foothills model data are processed here. The result shows that our method is a better alternative to ray migration for complex structure imaging. Similarly, the extrapolation of one way wave in frequency-space domain is a Lie group transformation with one parameter Z and consequently, the numerical calculation methods of the extrapolation ought to be Lie group methods. After discrete the wave field in depth and space, the Lie group transformation has the form of matrix exponential and each approximation of it gives a Lie group algorithm. Though Pade symmetrical series approximation of matrix exponential gives a extrapolation method which is traditionally regarded as implicit FD migration, it benefits the theoretic and applying study of seismic imaging for it represent the depth extrapolation and migration method in a entirely different way. While, the technique of coordinates of second kind for the approximation of the matrix exponential begins a new way to develop migration operator. The inversion of matrix plays a vital role in the numerical migration method given by Pade symmetrical series approximation. The matrix has a Toepelitz structure with a helical boundary condition and is easy to inverse with LU decomposition. A efficient LU decomposition method is spectral factorization. That is, after the minimum phase correlative function of each array of matrix had be given by a spectral factorization method, all of the functions are arranged in a position according to its former location to get a lower triangular matrix. The major merit of LU decomposition with spectral factorization (SF Decomposition) is its efficiency in dealing with a large number of matrixes. After the setup of a table of the spectral factorization results of each array of matrix, the SF decomposition can give the lower triangular matrix by reading the table. However, the relationship among arrays is ignored in this method, which brings errors in decomposition method. Especially for numerical calculation in complex model, the errors is fatal. Direct elimination method can give the exact LU decomposition But even it is simplified in our case, the large number of decomposition cost unendurable computer time. A hybrid method is proposed here, which combines spectral factorization with direct elimination. Its decomposition errors is 10 times little than that of spectral factorization, and its decomposition speed is quite faster than that of direct elimination, especially in dealing with a large number of matrix. With the hybrid method, the 3D implicit migration can be expected to apply on real seismic data. Finally, the impulse response of 3D implicit migration operator is presented.

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3D wave equation prestack depth migration is the effective tool for obtaining the exact imaging result of complex geology structures. It's a part of the 3D seismic data processing. 3D seismic data processing belongs to high dimension signal processing, and there are some difficult problems to do with. They are: How to process high dimension operators? How to improve the focusing? and how to construct the deconvolution operator? The realization of 3D wave equation prestack depth migration, not only realized the leap from poststack to prestack, but also provided the important means to solve the difficult problems in high dimension signal processing. In this thesis, I do a series research especially for the solve of the difficult problems around the 3D wave equation prestack depth migration and using it as a mean. So this thesis service for the realization of 3D wave equation prestack depth migration for one side and improve the migration effect for another side. This thesis expatiates in five departs. Summarizes the main contents as the follows: In the first part, I have completed the projection from 3D data point area to low dimension are using de big matrix transfer and trace rearrangement, and realized the liner processing of high dimension signal. Firstly, I present the mathematics expression of 3D seismic data and the mean according to physics, present the basic ideal of big matrix transfer and describe the realization of five transfer models for example. Secondly, I present the basic ideal and rules for the rearrange and parallel calculate of 3D traces, and give a example. In the conventional DMO focusing method, I recall the history of DM0 process firstly, give the fundamental of DMO process and derive the equation of DMO process and it's impulse response. I also prove the equivalence between DMO and prestack time migration, from the kinematic character of DMO. And derive the relationship between DMO base on wave equation and prestack time migration. Finally, I give the example of DMO process flow and synthetic data of theoretical models. In the wave equation prestak depth migration, I firstly recall the history of migration from time to depth, from poststack to prestack and from 2D to 3D. And conclude the main migration methods, point out their merit and shortcoming. Finally, I obtain the common image point sets using the decomposed migration program code.In the residual moveout, I firstly describe the Viterbi algorithm based on Markov process and compound decision theory and how to solve the shortest path problem using Viterbi algorithm. And based on this ideal, I realized the residual moveout of post 3D wave equation prestack depth migration. Finally, I give the example of residual moveout of real 3D seismic data. In the migration Green function, I firstly give the concept of migration Green function and the 2D Green function migration equation for the approximate of far field. Secondly, I prove the equivalence of wave equation depth extrapolation algorithms. And then I derive the equation of Green function migration. Finally, I present the response and migration result of Green function for point resource, analyze the effect of migration aperture to prestack migration result. This research is benefit for people to realize clearly the effect of migration aperture to migration result, and study on the Green function deconvolution to improve the focusing effect of migration.

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Oil and scientific groups have been focusing on the 3D wave equation prestack depth migration since it can solve the complex problems of the geologic structure accurately and maintain the wave information, which is propitious to lithology imaging. The symplectic method was brought up by Feng Kang firstly in 1984 and became the hotspot of numerical computation study. It will be widely applied in many scientific field of necessity because of its great virtue in scientific sense. This paper combines the Symplectic method and the 3-D wave equation prestack depth migration to bring up an effectual numerical computation method of wave field extrapolatation technique under the scientific background mentioned above. At the base of deep analysis of computation method and the performance of PC cluster, a seismic prestack depth migration flow considering the virtue of both seismic migration method and Pc cluster has formatted. The software, named 3D Wave Equation Prestack Depth Migration of Symplectic Method, which is based on the flow, has been enrolled in the National Bureau of Copyright (No. 0013767). Dagang and Daqing Oil Field have now put it into use in the field data processing. In this paper, the one way wave equation operator is decompounded into a phase shift operator and a time shift operator and the correct item with high rank Symplectic method when approaching E exponent. After reviewing eliminating alias frequency of operator, computing the maximum angle of migration and the imaging condition, we present the test result of impulse response of the Symplectic method. Taking the imaging results of the SEG/EAGE salt and overthrust models for example and seeing about the imaging ability with complex geologic structure of our software system, the paper has discussed the effect of the selection of imaging parameters and the effectuation on the migration result of the seismic wavelet and compared the 2-D and 3-D prestack depth migration result of the salt mode. We also present the test result of impulse response with the overthrust model. The imaging result of the two international models indicates that the Symplectic method of 3-D prestack depth migration accommodates great transversal velocity variation and complex geologic structure. The huge computing cost is the key obstruction that 3-D prestack depth migration wave equation cannot be adopted by oil industry. After deep analysis of prestack depth migration flow and the character of PC cluster ,the paper put forward :i)parallel algorithms in shot and frequency domain of the common shot gather 3-D wave equation prestack migration; ii)the optimized setting scheme of breakpoint in field data processing; iii)dynamic and static load balance among the nodes of the PC cluster in the 3-D prestack depth migration. It has been proven that computation periods of the 3-D prestack depth migration imaging are greatly shortened given that adopting the computing method mentioned in the paper. In addition,considering the 3-D wave equation prestack depth migration flow in complex medium and examples of the field data processing, the paper put the emphasis on: i)seismic data relative preprocessing, ii) 2.5D prestack depth migration velocity analysis, iii)3D prestack depth migration. The result of field data processing shows satisfied application ability of the flow put forward in the paper.

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A digital differentiator simply involves the derivation of an input signal. This work includes the presentation of first-degree and second-degree differentiators, which are designed as both infinite-impulse-response (IIR) filters and finite-impulse-response (FIR) filters. The proposed differentiators have low-pass magnitude response characteristics, thereby rejecting noise frequencies higher than the cut-off frequency. Both steady-state frequency-domain characteristics and Time-domain analyses are given for the proposed differentiators. It is shown that the proposed differentiators perform well when compared to previously proposed filters. When considering the time-domain characteristics of the differentiators, the processing of quantized signals proved especially enlightening, in terms of the filtering effects of the proposed differentiators. The coefficients of the proposed differentiators are obtained using an optimization algorithm, while the optimization objectives include magnitude and phase response. The low-pass characteristic of the proposed differentiators is achieved by minimizing the filter variance. The low-pass differentiators designed show the steep roll-off, as well as having highly accurate magnitude response in the pass-band. While having a history of over three hundred years, the design of fractional differentiator has become a ‘hot topic’ in recent decades. One challenging problem in this area is that there are many different definitions to describe the fractional model, such as the Riemann-Liouville and Caputo definitions. Through use of a feedback structure, based on the Riemann-Liouville definition. It is shown that the performance of the fractional differentiator can be improved in both the frequency-domain and time-domain. Two applications based on the proposed differentiators are described in the thesis. Specifically, the first of these involves the application of second degree differentiators in the estimation of the frequency components of a power system. The second example concerns for an image processing, edge detection application.

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This paper uses dynamic impulse response analysis to investigate the interrelationships among stock price volatility, trading volume, and the leverage effect. Dynamic impulse response analysis is a technique for analyzing the multi-step-ahead characteristics of a nonparametric estimate of the one-step conditional density of a strictly stationary process. The technique is the generalization to a nonlinear process of Sims-style impulse response analysis for linear models. In this paper, we refine the technique and apply it to a long panel of daily observations on the price and trading volume of four stocks actively traded on the NYSE: Boeing, Coca-Cola, IBM, and MMM.