Orientador: Milton Dias Junior / Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Mecânica / Made available in DSpace on 2018-08-23T13:57:55Z (GMT). No. of bitstreams: 1 Melo_FabioMenegattide_M.pdf: 4740626 bytes, checksum: d8e7f3016b9b6ecce36397deb6f91e27 (MD5) Previous issue date: 2013 / Resumo: Estruturas do tipo caixa são facilmente encontradas em sistemas mecânicos do cotidiano. Elas estão nas coberturas de motores e equipamentos de ar-condicionado, transformadores e compressores de refrigeradores e em todo sistema cuja cobertura é feita por uma proteção plástica ou metálica. Seu comportamento acústico e vibratório vem sendo estudado há alguns anos uma vez que problemas relacionados a ruído e vibração desses componentes são recorrentes. Como forma de atenuar o ruído radiado por essas estruturas alguns métodos são adotados. Dentre eles está a adição de massa a qual será estudada neste trabalho. Uma caixa retangular é modelada por meio de Elementos Finitos e duas análises realizadas: uma análise estrutural in vácuo de forma a determinar a variação do deslocamento volumétrico líquido e outra, vibroacústica, focando em como o nível de pressão sonora e o padrão de diretividade são afetados pela adição de massa. É possível verificar que a adição de massa muda de maneira significativa as frequências naturais e as formas modais da caixa. Além disso, ela pode reduzir o deslocamento volumétrico líquido daqueles modos com grande deslocamento volumétrico e pode aumentar ou diminuir a resposta acústica dependendo da quantidade de massas adicionadas / Abstract: Box-type structures are easily found in mechanical systems of the everyday. They are covering engines and air-conditioning equipment, transformers and hermetic compressors of refrigerators and every system which covering is made by a plastic or metallic protection. Their vibratory and acoustic behavior have been study for many years once that concerns regarding noise and vibration related to them are recurrent. As a manner to attenuate the noise radiated by these structures some known methods are adopted. One of these, which will be investigated in this work, is adding masses on the structure. A rectangular box is modelled by means of Finite Element approach. Two analyses are performed: a structural in vacuum analysis in order to determine the variation of the net-volume displacement and a vibroacoustic analysis focusing on how the sound pressure level and directivity pattern are affected by adding masses. The latter one is carried out considering fluid-structure interaction. It can be verified that mass addition changes, in a significant way, the natural frequencies and mode shapes of the box. In addition, it may reduce the net-volume displacement of modes which have large net-volume displacement and may increase or decrease the acoustical response of the box depending on the amount of added masses / Mestrado / Mecanica dos Sólidos e Projeto Mecanico / Mestre em Engenharia Mecânica

The main focus of this study is to improve the profitability, availability and condition monitoring of Liquefied Natural Gas (LNG) Floating Production Storage and Offloading platforms (FPSOs). Propane pre-cooled, mixed refrigerant (C3MR) liquefaction is the key process in the production of LNG on FPSOs. LNG liquefaction system equipment has the highest failure rates among the other FPSO equipment, and thus the highest maintenance cost. Improvements in the profitability, availability and condition monitoring were made in two ways: firstly, by making recommendations for the use of redundancy in order to improve system reliability (and hence availability); and secondly, by developing an effective condition-monitoring algorithm that can be used as part of a condition-based maintenance system. C3MR liquefaction system reliability modelling was undertaken using the time-dependent Markov approach. Four different system options were studied, with varying degrees of redundancy. The results of the reliability analysis indicated that the introduction of a standby liquefaction system could be the best option for liquefaction plants in terms of reliability, availability and profitability; this is because the annual profits of medium-sized FPSOs (3MTPA) were estimated to increase by approximately US$296 million, rising from about US$1,190 million to US$1,485.98 million, if redundancy were implemented. The cost-benefit analysis results were based on the average LNG prices (US$500/ton) in 2013 and 2014. Typically, centrifugal turbines, compressors and blowers are the main items of equipment in LNG liquefaction plants. Because centrifugal equipment tops the FPSO equipment failure list, a Condition Monitoring (CM) system for such equipment was proposed and tested to reduce maintenance and shutdown costs, and also to reduce flaring. The proposed CM system was based on a novel FFT-based segmentation, feature selection and fault identification algorithm. A 20 HP industrial air compressor system with a rotational speed of 15,650 RPM was utilised to experimentally emulate five different typical centrifugal equipment machine conditions in the laboratory; this involved training and testing the proposed algorithm with a total of 105 datasets. The fault diagnosis performance of the algorithm was compared with other methods, namely standard FFT classifiers and Neural Network. A sensitivity analysis was performed in order to determine the effect of the time length and position of the signals on the diagnostic performance of the proposed fault identification algorithm. The algorithm was also checked for its ability to identify machine degradation using datasets for which the algorithm was not trained. Moreover, a characterisation table that prioritises the different fault detection techniques and signal features for the diagnosis of centrifugal equipment faults, was introduced to determine the best fault identification technique and signal feature. The results suggested that the proposed automated feature selection and fault identification algorithm is effective and competitive as it yielded a fault identification performance of 100% in 3.5 seconds only in comparison to 57.2 seconds for NN. The sensitivity analysis showed that the algorithm is robust as its fault identification performance was affected by neither the time length nor the position of signals. The characterisation study demonstrated the effectiveness of the AE spectral feature technique over the fault identification techniques and signal features tested in the course of diagnosing centrifugal equipment faults. Moreover, the algorithm performed well in the identification of machine degradation. In summary, the results of this study indicate that the proposed two-pronged approach has the potential to yield a highly reliable LNG liquefaction system with significantly improved availability and profitability profiles.