• Korean Chemical Engineering Research
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• v.58 no.2
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• pp.224-229
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• 2020

We propose a machine learning-based method for proactively detecting faults in LDPE processes and predicting equipment lifespan. It is important to detect and prevent unexpected faults in chemical processes in order to maximize safety and productivity. Since LDPE process is a high-pressure process up to 3,000 kg/㎠g or more, once ESD occurs, it can result in productivity loss due to increased maintenance periods. By collecting key variables operation data of the process and using unsupervised machine leaning methods, we developed a fault detection model which detected 4 ESDs 2.4 days prior to the occurrence. In addition, it was confirmed that the life expectancy of a hyper compressor can be predicted by using the physically significant key variables.

• Proceedings of the Korean Society of Marine Engineers Conference
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• 2006.06a
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• pp.229-230
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• 2006

해상플랫폼설치가 불가능한 심해지역이나 파도가 심한 해상에서 원유를 발굴하는 선박형태의 시추설비인데, 심해에서의 시추능력은 물론 기동성까지 겸비한 고부가치선으로서 최근 고(高)유가에 따라 발주가 늘어나고 있는 해양분야의 대표적인 성장엔진으로, 파도와 바람이 심한 해상에서도 안정적 시추가 가능한 최첨단 자동위치 제어시스템, 드릴링장비, 통합제어시스템 등, 드릴쉽이 갖추고 있는 시스템에 대해 간단히 설명한다.