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Reference: ISH2015_333

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Research on Permeation Characteristics of Oil-dissolved gases Based on Hollow Fiber Membrane Doped with Nano-oxide Al2O3



It is of great significance to conduct real time online monitoring of the categories and content of oil-dissolved gases so as to ensure the safety operation of transformer. Thus, gas separation technology is one of key technologies which are used to realize the real time online monitoring. By far, the conventional methods used to separate the fault gases include vacuum degassing, Mechanical oscillation, and Polymer membrane etc., the former two methods were replaced by Dynamic headspace degassing technology and bellows for the reason that they fail to meet the demand of gas online detection. Though the third one is easy to operate and low-cost, the permeation effect is dissatisfied especially for H2?CH4 and CO with a separation efficiency lower than 20%. In order to solve the problem of dissatisfied effect of CH4?C2H6?C2H4?C2H2?H2?CO and CO2 separation, which is caused by the widely-used common fiber membrane and results in a low sensitivity of monitoring, this thesis, based on L-S method, proposes the use of nano-oxide hollow fiber membrane made by taking polytetrafluoroethylene, polyvinylidene fluoride and hexafluoropropylene as polymer materials and doping with nanoparticles of oxide Al2O3 which leads a result of better voids content . The curves of the permeability characteristics of the nano-oxide hollow fiber membrane and common fiber membrane have then been drawn out from the comparative tests of penetration effect. The research findings show that the nano-oxide hollow fiber membrane, under the same temperature and pressure, outperforms the common one by solving the defects of penetration effect and the long equilibration time, and effectively improves gas permeability characteristics of the hollow fiber membrane, which successfully lays down the solid foundation of enhancing the sensitivity of monitoring oil-dissolved gases and provides a good technical support for online monitoring application.

File Size: 455,9 KB

Year: 2015

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