LNG FPSO 압축기 고장시간 예측 방안에 관한 연구

초록

The O&M (Operation and Maintenance) phase of offshore plants with a long life cycle requires heavy charges and moreefforts than the construction phase, and the occurrence of an accident of an offshore plant causes catastrophic damage. So previousstudies have focused on the development of advanced maintenance system to avoid unexpected failures. Nowadays due to theemerging ICTs (Information Communication Technologies) and sensor technologies, it is possible to gather the status data ofequipment and send health monitoring data to administrator of an offshore plant in a real time way, which leads to havingmuch concern on the condition based maintenance policy. In this study, we have reviewed previous studies associated with CBM(Condition-Based Maintenance) of offshore plants, and introduced an algorithm predicting the next failure time of the compressorwhich is one of essential mechanical devices in LNG FPSO (Liquefied Natural Gas Floating Production Storage and Offloadingvessel). To develop the algorithm, continuous time Markov model is applied based on gathered vibration data.

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