摘要
提出了一种基于Logistic回归模型和ARMA模型相结合的过程报警事件预测方法,从历史数据中提取过程报警事件序列,并分解成报警状态及报警状态的持续时间,对应建立Logistic回归模型和ARMA模型分别对其进行预测,最终实现对过程报警事件的预测。通过数值实例分析和工业过程数据进行了验证,表明该方法能够准确地预测过程报警事件。
A Logistic regression and Autoregressive Moving Average（ARMA）model-based approach to process alarm event prognosis is explicitly introduced in this paper.A sequence of process alarm events which includes states and duration of the alarm events can be extracted from historical data before establishing corresponding Logistic regression and ARMA models,thereby well predicting the process alarm events.A numerical example as well as industrial process data is employed to validate the effectiveness of the proposed methods.
出处
《化工学报》
EI
CAS
CSCD
北大核心
2012年第9期2941-2947,共7页
CIESC Journal
