Submitted by Automa??o e Estat?stica (sst@bczm.ufrn.br) on 2017-10-02T23:37:05Z No. of bitstreams: 1 TiagoFernandesDeMiranda_DISSERT.pdf: 5053204 bytes, checksum: 5fe48dfee7a0927d59bdae03b0ab719f (MD5) / Approved for entry into archive by Arlan Eloi Leite Silva (eloihistoriador@yahoo.com.br) on 2017-10-09T20:43:39Z (GMT) No. of bitstreams: 1 TiagoFernandesDeMiranda_DISSERT.pdf: 5053204 bytes, checksum: 5fe48dfee7a0927d59bdae03b0ab719f (MD5) / Made available in DSpace on 2017-10-09T20:43:39Z (GMT). No. of bitstreams: 1 TiagoFernandesDeMiranda_DISSERT.pdf: 5053204 bytes, checksum: 5fe48dfee7a0927d59bdae03b0ab719f (MD5) Previous issue date: 2017-07-03 / Conselho Nacional de Desenvolvimento Cient?fico e Tecnol?gico (CNPq) / Alarmes industriais tem natureza inerentemente ass?ncrona e s?o fundamentais para a manuten??o da seguran?a operacional e sa?de de processos industriais complexos. Entretanto, sistemas de alarmes industriais mal configurados tendem a gerar quantidades excessivas de alarmes, o que os tornam ineficientes. Dentre os poss?veis agentes degradantes de um sistema de alarmes, est?o os alarmes causais. Situa??es de alarmes causais ocorrem quando a ativa??o de um determinado alarme implica na ativa??o de um ou mais alarmes decorrentes, gerando informa??o redundante no sistema de alarmes. Diante da relev?ncia do problema, nesta disserta??o s?o analisados os desempenhos de duas t?cnicas para determina??o de alarmes causais: correla??o cruzada e teste de causalidade de Granger. Como dados de alarmes industriais s?o essencialmente de natureza discreta, antes de se aplicar ambas as t?cnicas, houve a necessidade de se realizar um pr?-processamento sobre os dados de alarmes, atrav?s de uma t?cnica de suaviza??o de sinais. Para obten??o dos resultados, foram utilizados dados de alarmes provenientes de cen?rios de simula??o de gera??o de alarmes e do Benchmark Tennessee Eastman Process. Os resultados obtidos indicam que, em aspectos gerais, o teste de causalidade de Granger obteve maior efici?ncia que a correla??o cruzada na tarefa de indica??o de rela??es causais em alarmes industriais. Tamb?m foram realizados estudos comparativos da aplica??o do teste de causalidade de Granger sobre vari?veis de processo e alarmes no Benchmark Tennessee Eastman Process, indicando suas caracter?sticas. / Industrial alarms are inherently asynchronous in nature and are critical to maintaining the operational safety and health of complex industrial processes. However, poorly configured industrial alarm systems tend to generate excessive amounts of alarms, making them inefficient. Among the possible degrading agents of an alarm system are the causal alarms. Causal alarm situations occur when the activation of a given alarm implies the activation of one or more of the resulting alarms, generating redundant information in the alarm system. Given the relevance of the problem, this dissertation analyzes the performance of two techniques for determining causal alarms: Cross-correlation and Granger causality test. The industrial alarm data is essentially of a discrete nature, before performing both techniques, there was a need to perform a preprocessing on the alarm data, through the signal smoothing technique. To obtain the results, we used alarm data from the alarm generation simulation scenarios and the Tennessee Eastman Process Benchmark. Therefore, the results indicate that, in general aspects, the Granger causality test performed a greater efficiency than the cross-correlation in the task of indicating causal relations between industrial alarms. We also performed comparative studies of the application of the Granger causality test on process variables and alarms in the Tennessee Eastman Process Benchmark, indicating their characteristics.

Submitted by Automa??o e Estat?stica (sst@bczm.ufrn.br) on 2017-02-20T22:47:58Z No. of bitstreams: 1 OdmaksuelAnisioBezerraDantas_DISSERT.pdf: 5356247 bytes, checksum: a2a17290abc4832c7f0cd9ef68881d06 (MD5) / Approved for entry into archive by Arlan Eloi Leite Silva (eloihistoriador@yahoo.com.br) on 2017-02-24T22:03:21Z (GMT) No. of bitstreams: 1 OdmaksuelAnisioBezerraDantas_DISSERT.pdf: 5356247 bytes, checksum: a2a17290abc4832c7f0cd9ef68881d06 (MD5) / Made available in DSpace on 2017-02-24T22:03:21Z (GMT). No. of bitstreams: 1 OdmaksuelAnisioBezerraDantas_DISSERT.pdf: 5356247 bytes, checksum: a2a17290abc4832c7f0cd9ef68881d06 (MD5) Previous issue date: 2016-08-15 / Os sinais ruidosos registrados durante o monitoramento de opera??es de fraturamento hidr?ulico num campo de petr?leo podem trazer informa??es importantes sobre a estrutura do subsolo. Tais informa??es s?o extra?das atrav?s de um conjunto de procedimentos de an?lise e processamento de dados, baseado na t?cnica de Interferometria S?smica de Ru?do Ambiente (ISRA). Na pr?tica, a t?cnica envolve a realiza??o de duas etapas: a correla??o cruzada, que ? equivalente a convolu??o de um dos sinais com o outro reverso no tempo, e o empilhamento (stacking) dos resultados gerados. A resposta encontrada pela mesma ? equivalente a Fun??o de Green emp?rica do meio convolvida com a wavelet da fonte e por esse motivo, a Interferometria S?smica tamb?m ? chamada de recupera??o da Fun??o de Green. Neste trabalho, novas respostas s?smicas foram obtidas atrav?s da combina??o de duas t?cnicas de correla??o cruzada (correla??o cruzada cl?ssica normalizada geometricamente - CCGN e correla??o cruzada de fase - PCC) com duas t?cnicas de empilhamento (empilhamento linear - LS e o empilhamento n?o linear ou ponderado por fase - PWS). Consequentemente, quatro abordagens foram alcan?adas, que ap?s submetidas a um fluxo de processamento padr?o de dados s?smicos resultou em quatro se??es s?smicas empilhadas (LS-PCC - empilhamento linear com correla??o cruzada de fase, LS-CCGN - empilhamento linear com correla??o cruzada cl?ssica normalizada geometricamente, PWS-PCC - empilhamento n?o linear com correla??o cruzada de fase e PWS-CCGN - empilhamento n?o linear com correla??o cruzada cl?ssica normalizada geometricamente). Para interpreta??o dos resultados, uma modelagem s?smica direta foi realizada a fim de obter uma se??o s?smica sint?tica. A interpreta??o dos resultados com o uso de informa??es de dados sint?ticos e da geologia mostrou que alguns eventos correspondentes a marcadores geol?gicos foram recuperados. Isto contribuiu para a comprova??o de que ? poss?vel recuperar as reflex?es de um meio em subsuperf?cie utilizando registros de ru?do s?smico ambiente e a t?cnica de Interferometria S?smica. / The noisy signals recorded during the monitoring hydraulic fracturing operations in an oil field can provide important information on the structure of the subsoil. Such information is extracted through a set of procedures for analyzing and processing data, based on the technique of of Ambient Noise Interferometry Seismic (ANSI). In practice, the technique involves the realization of two steps: the cross-correlation, which is equivalent to a convolution of the signals with each other in reverse time and the stacking the results generated. The answer is found by this is equivalent to empirical Green function convolved the medium of the source wavelet and therefore, the seismic interferometry recovery is also called the Green function. In this work, new seismic responses were obtained by combining two cross-correlation techniques (classical cross-correlation geometrically normalized - CCGN and phase cross-correlation - PCC) with two stacking techniques (linear stack - LS and the nonlinear stack or phase-weighting stack - PWS). Consequently, four approaches have been reached which, after undergoing a standard processing flow of seismic data resulted in four stacked seismic sections (LS-PCC - linear stack with phase cross-correlation, TS-CCGN - linear stack with classical cross-correlation geometrically normalized, PWS-PCC - nonlinear stack with phase cross-correlation and PWS-CCGN - nonlinear stack with classical cross-correlation geometrically normalized). To interpret the results, a direct seismic modeling was performed to obtain a synthetic seismic section. Interpretation of the results with the use of synthetic data information and geology showed that some events corresponding to geological markers were recovered. This adds to the confirmation that is possivel retrieve the reflections of an environment in the subsurface using ambient seismic noise records and seismic interferometry technique.

Submitted by Automa??o e Estat?stica (sst@bczm.ufrn.br) on 2016-08-09T23:00:00Z No. of bitstreams: 1 VirginieD'hour_TESE.pdf: 8753386 bytes, checksum: 2e3e6a55a73239c9eeac2c8def85eb39 (MD5) / Approved for entry into archive by Arlan Eloi Leite Silva (eloihistoriador@yahoo.com.br) on 2016-08-13T00:23:12Z (GMT) No. of bitstreams: 1 VirginieD'hour_TESE.pdf: 8753386 bytes, checksum: 2e3e6a55a73239c9eeac2c8def85eb39 (MD5) / Made available in DSpace on 2016-08-13T00:23:12Z (GMT). No. of bitstreams: 1 VirginieD'hour_TESE.pdf: 8753386 bytes, checksum: 2e3e6a55a73239c9eeac2c8def85eb39 (MD5) Previous issue date: 2015-09-01 / Conselho Nacional de Desenvolvimento Cient?fico e Tecnol?gico (CNPq) / Nesta tese s?o apresentados e discutidos os resultados de correla??o do ru?do s?smico em dois contextos: regi?o intraplaca e Dorsal Meso-oce?nica. O m?todo de interferometria de cauda de onda (coda wave interferometry?CWI) tamb?m foi utilizado para os dados da regi?o intraplaca. A correla??o do ru?do permite recuperar a fun??o de Green emp?rica entre dois receptores , como se uma das esta??es atuasse como uma fonte (virtual). Esta t?cnica ?amplamente utilizado em sismologia para a imagem do subsolo e para monitorar mudan?as estruturais associadas principalmente com erup??es vulc?nicas e terremotos grandes (mb > 6.0). No estudo da regi?o intraplaca, fomos capazes de detectar mudan?as estruturais localizadas relacionadas com esta pequena sequ?ncia de terremotos, cujo evento principal ? de mR 3.7, no Nordeste do Brasil. N?s tamb?m mostramos que a normaliza??o de 1-bit de e o branqueamento spectral provoca perdas de detalhes na forma de onda e que a auto- correla??o de fase, que ? pouco sens?vel ? amplitude , parece ser mais sens?vel e robusta para a nossa an?lise. A an?lise de 6 meses de dados usando correla??es cruzadas detecta claramente altera??es do meio logo ap?s do evento principal, enquanto que as auto- correla??es essencialmente detectam altera??es ap?s 1 m?s. Estas mudan?as na correla??o cruzada e na auto-correla??o podem serexplicadas pela redistribui??o da press?o do fluido ocasionadas mudan?as hidromec?nicas e novos caminhos preferenciais para difus?o de press?o e fuidos , devido a terramotos que ocorrem mais tarde. No estudo da Dorsal Meso-oce?nica, investigamos as mudan?as estruturais associadas a um terremoto de mb 4,9 aolongo da falha transformante de S?o Paulo. Os dados foram registrados por a ?nica esta??o s?smica localizada a menos de 200 km da Dorsal Meso-oce?nica. Os resultados da auto-correla??o de fase por um per?odo de 5 meses, mostram uma forte mudan?a de meio co-s?smica seguido por uma recupera??o p?s-s?smica relativamente r?pida. Esta mudan?a do meio provavelmente est? relacionada aos danos causados pelo terremoto de mb 4.9. O processo de cicatriza??o (enchimento das novas fissuras) que durou 60 dias pode ser decomposto em duas fases, uma recupera??o r?pida na fase p?s-s?smica (de 70% em ~ 30 dias) precoce e uma recupera??o relativamente lenta depois (de 30% em ~ 30 dias) No estudo de interferometria de cauda de onda, monitoramos mudan?as temporais da subsuperf?cie causada pela sequ?ncia de pequenos terremotos intraplaca mencionado anteriormente. O m?todo foi validado com dados sint?ticos. Fomos capazes de detectar uma mudan?a da fonte de 2.5% e uma redu??o de 15% da quantidade dos espalhadores. A partir dos dados reais, observamos uma r?pida diminui??o da correla??o da cauda da onda ap?s do evento s?smico mR 3.7. Isso indica uma mudan?a r?pida do subsolo na regi?o da falha induzida pelo terremoto. / This thesis presents and discusses the results of ambient seismic noise correlation for two different environments: intraplate and Mid-Atlantic Ridge. The coda wave interferometry method has also been tested for the intraplate data. Ambient noise correlation is a method that allows to retrieve the structural response between two receivers from ambient noise records, as if one of the station was a virtual source. It has been largely used in seismology to image the subsurface and to monitor structural changes associated mostly with volcanic eruptions and large earthquakes. In the intraplate study, we were able to detect localized structural changes related to a small earthquake swarm, which main event is mR 3.7, North-East of Brazil. We also showed that the 1-bit normalization and spectral whitening result on the loss of waveform details and that the phase auto-correlation, which is amplitude unbiased, seems to be more sensitive and robust for our analysis of a small earthquake swarm. The analysis of 6 months of data using cross-correlations detect clear medium changes soon after the main event while the auto-correlations detect changes essentially after 1 month. It could be explained by fluid pressure redistribution which can be initiated by hydromechanical changes and opened path ways to shallower depth levels due to later occurring earthquakes. In the Mid-Atlantic Ridge study, we investigate structural changes associated with a mb 4.9 earthquake in the region of the Saint Paul transform fault. The data have been recorded by a single broadband seismic station located at less than 200 km from the Mid-Atlantic ridge. The results of the phase auto-correlation for a 5-month period, show a strong co-seismic medium change followed by a relatively fast post-seismic recovery. This medium change is likely related to the damages caused by the earthquake?s ground shaking. The healing process (filling of the new cracks) that lasted 60 days can be decomposed in two phases, a fast recovery (70% in ~30 days) in the early post-seismic stage and a relatively slow recovery later (30% in ~30 days). In the coda wave interferometry study, we monitor temporal changes of the subsurface caused by the small intraplate earthquake swarm mentioned previously. The method was first validated with synthetics data. We were able to detect a change of 2.5% in the source position and a 15% decrease of the scatterers? amount. Then, from the real data, we observed a rapid decorrelation of the seismic coda after the mR 3.7 seismic event. This indicates a rapid change of the subsurface in the fault?s region induced by the earthquake.