Improve reliability using hotelling T2 technique in a liquefied natural gas plant

A method for improve the reliability in a gas liquefied plant using Hotelling T2 is showed in this paper. The stationery work in this manufacture facilities during a few moths in a year involve a heavy duty service of gas diesel engines and ammonia gas plant for processing the methane gas and extract the condensate fluid of it. Then, a predictive maintenance plan is necessary to prevent a possible malfunction or shut down of the plant and avoid an operational cost increased. We are just sampling the signals from the plant when its working in optimal condition and then we will compare the next incoming data from the machinery versus the previous historical data set. An statistical process control algorithm Hotelling T2 based for monitoring the condition of gas engines and ammonia gas plant will be implemented.Peer Reviewe

Improve reliability using hotelling T2 technique in a liquefied natural gas plant

A method for improve the reliability in a gas liquefied plant using Hotelling T2 is showed in this paper. The stationery work in this manufacture facilities during a few moths in a year involve a heavy duty service of gas diesel engines and ammonia gas plant for processing the methane gas and extract the condensate fluid of it. Then, a predictive maintenance plan is necessary to prevent a possible malfunction or shut down of the plant and avoid an operational cost increased. We are just sampling the signals from the plant when its working in optimal condition and then we will compare the next incoming data from the machinery versus the previous historical data set. An statistical process control algorithm Hotelling T2 based for monitoring the condition of gas engines and ammonia gas plant will be implemented

Principal component analysis to compress acquired data offshore

Telecommunications offshore have connectivity in virtually all parts of the globe via satellite, with increasing bandwidth and lower cost, but still far from levels that are onshore. The principal component analysis (PCA) is a statistical technique that has found application in fields such as biometrics or compression of images, being a common tool for finding patterns in multidimensional data sets. The hypothesis for this work was that it was possible to use the theory of PCA to compress, with sufficient accuracy, the large amount of data that are collected on board to a vessel and then sent by satellite in a more economical or rapid way than the traditional one. The material used were 44 samples of 182 different signals, collected from 19 different equipment on board to “Castillo de Villalba” Liquid Natural Gas carrier vessel. With these data, the PCA algorithm was applied using a computer program developed by the authors, generating new data packets to send by satellite. Different strategies were used in order to ensure that the coefficient of correlation r between original and reconstructed data onshore were equal or greater than 0.95. The results showed that it was possible to save 46.9% in the number of data sent via satellite, in the case of grouping all the 182 signs, with a mean r = 0.95 ± 0.08. This strategy is appropriate for onshore vessel equipment telediagnostic and maintenance decision making, with telecommunication cost or time savings