Research and Practice on Predictive Maintenance Model for Large Refinery Unit Equipment
The characteristics of high temperature and high pressure,flammable and explosive,toxic and harmful,and continuous production in the petroleum refining process have very strict requirements for the operation of refining equipment.Only long-term,full load,and uninterrupted safe operation can ensure the safety of production,the continuity of production capacity,and the maximization of economic benefits.Currently,intelligent predictive maintenance of equipment based on big data has become a trend and consensus in the petroleum refining industry.This article explores a method of collecting operational data of large unit equipment in industrial sites,using various analytical methods to establish predictive models,and conducting comprehensive real-time status evaluation,precise positioning of fault locations,and early warning of equipment maintenance for the operation of refining and chemical large unit equipment,in order to achieve predictive maintenance of large unit equipment.
refining and chemical large unitbig dataartificial intelligencepredictive maintenance
NETL
NSTL
万方数据
