Analytics;
Big data;
Performance monitoring;
Process monitoring;
Alarm systems;
Process data analytics;
Fault detection and diagnosis;
PLANT-WIDE OSCILLATION;
SPECTRAL ENVELOPE;
SIMILARITY ANALYSIS;
CORRELATED ALARMS;
ONLINE METHOD;
TIME-SERIES;
DIAGNOSIS;
SYSTEMS;
DESIGN;
D O I:
10.1016/j.compchemeng.2017.10.010
中图分类号:
TP39 [计算机的应用];
学科分类号:
081203 ;
0835 ;
摘要:
The fusion of information from disparate sources of data is the key step in devising strategies for a smart analytics platform. In the context of the application of analytics in the process industry, this paper provides a framework for seamless integration of information from process and alarm databases complimented with process connectivity information. The discovery of information from such diverse data sources can be subsequently used for process and performance monitoring including alarm rationalization, root cause diagnosis of process faults, hazard and operability analysis, safe and optimal process operation. The utility of the proposed framework is illustrated by several successful industrial case studies. (C) 2017 Elsevier Ltd. All rights reserved.
机构:
Univ Illinois, Dept Chem Engn, Large Scale Syst Res Lab, Urbana, IL 61801 USAUniv Illinois, Dept Chem Engn, Large Scale Syst Res Lab, Urbana, IL 61801 USA
Chiang, LH
Braatz, RD
论文数: 0引用数: 0
h-index: 0
机构:
Univ Illinois, Dept Chem Engn, Large Scale Syst Res Lab, Urbana, IL 61801 USAUniv Illinois, Dept Chem Engn, Large Scale Syst Res Lab, Urbana, IL 61801 USA
机构:
Univ Illinois, Dept Chem Engn, Large Scale Syst Res Lab, Urbana, IL 61801 USAUniv Illinois, Dept Chem Engn, Large Scale Syst Res Lab, Urbana, IL 61801 USA
Chiang, LH
Braatz, RD
论文数: 0引用数: 0
h-index: 0
机构:
Univ Illinois, Dept Chem Engn, Large Scale Syst Res Lab, Urbana, IL 61801 USAUniv Illinois, Dept Chem Engn, Large Scale Syst Res Lab, Urbana, IL 61801 USA