Process alarm prognosis based on Logistic and ARMA models

WANG Feng; LI Hongguang; ZANG Hao

doi:10.3969/j.issn.0438-1157.2012.09.043

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Process alarm prognosis based on Logistic and ARMA models

更新时间：2025-12-10

- Process alarm prognosis based on Logistic and ARMA models
- CIESC Journal Issue 9, Pages: 2941-2947(2012)
- 作者机构：
  
  北京化工大学信息科学与技术学院,北京,100029
- 作者简介：
- 基金信息：
- DOI：10.3969/j.issn.0438-1157.2012.09.043
  CLC： P277
- Online First：05 September 2012，
  
  Published：05 September 2012
- 稿件说明：
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WANG Feng, LI Hongguang, ZANG Hao. Process alarm prognosis based on Logistic and ARMA models[J]. CIESC Journal, 2012, (9): 2941-2947.
DOI：

WANG Feng, LI Hongguang, ZANG Hao. Process alarm prognosis based on Logistic and ARMA models[J]. CIESC Journal, 2012, (9): 2941-2947. DOI： 10.3969/j.issn.0438-1157.2012.09.043.

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。

Abstract

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.

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