Framework for a smart data analytics platform towards process monitoring and alarm management

被引：28

作者：

Hu, Wenkai ^{[1
]}

Shah, Sirish L. ^{[2
]}

Chen, Tongwen ^{[1
]}

机构：

[1] Univ Alberta, Dept Elect & Comp Engn, Edmonton, AB T6G 1H9, Canada

[2] Univ Alberta, Dept Chem & Mat Engn, Edmonton, AB T6G 1H9, Canada

来源：

COMPUTERS & CHEMICAL ENGINEERING | 2018年 / 114卷

基金：

加拿大自然科学与工程研究理事会;

关键词：

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.

引用

页码：225 / 244

页数：20

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