基于Akima算法和失效概率分布函數(shù)的站場異常工況預(yù)警

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Early warning technology of abnormal conditions in stations based on Akima algorithm and failure probability distribution function

HU Jianlin PetroChina Huabei Oilfield Company，Renqiu O62552，China

Abstract：Toimprovetheinherentsafetylevelofoilandgasstationsandrealizereal-timeearlywarningunderabnomalconditions， thispaperintegratesthemethodbasedonpriorknowledgewithdata-drivenmethods.TheAkimaalgoritmisfrstusedtosmoththe processparameters，andtentedeviationvelocityandaveragefaulttimearecalculated.Theprobabilitydistributionofpreviousfailure dataifittddvatioeloitistegatedtoueproabilitrtioc.allsiiit issetthroughdebging.earlyaingofbnoalconditiosisompleted，andthfldverificationisaidout.euls showthatheRungephenomenondosnotappearinthecurveobtainedbytheAkimainterpolatiomethod.Thecurvepasesthroughall theoriginaldatapointsandretainsthechangetrendoftheoriginalcurve.ThewaringresultsasedontheAkimaalgorithmandfailure probabilitydisributionfunctioncanbeadvancedfurtherthantheconventionalones.Thewaringtimeofheatertemperature，flashtower presure，andseparatrlevelcanbeadvancedyO7，234，and3sspectively.Theinstabilityofparameterchangeswilgeatly shortenthewaingtihileelativelyableparameterangeswillimittedvancingofthewaingi.Thresearchlsan provide a practical reference for improving the integrity management level of the stations.

Keywords：Akima algorithm;failure probabilitydistributionfunction;abnormalconditions;earlywarning; deviationvelocity

油氣站場內(nèi)涉及原油脫水、原油穩(wěn)定、伴生氣脫水、伴生氣脫酸、輕烴回收和采出水處理等多個工藝過程，涉及的介質(zhì)大多具有易燃、易爆、有毒等特性，且生產(chǎn)過程具有連續(xù)性，一旦出現(xiàn)異常工況，不僅影響正常油氣生產(chǎn)，還可能引發(fā)火災(zāi)、爆炸等重大事故[-2]。（剩余5817字）