A Review on Soft Sensors for Monitoring, Control, and Optimization of Industrial Processes

被引：368

作者：

Jiang, Yuchen ^{[1
,2
]}

Yin, Shen ^{[1
]}

Dong, Jingwei ^{[3
]}

Kaynak, Okyay ^{[4
,5
]}

机构：

[1] Harbin Inst Technol, Dept Control Sci & Engn, Harbin 150001, Peoples R China

[2] Tech Univ Munich, Chair Automat Control Engn, D-80333 Munich, Germany

[3] Delft Univ Technol, Delft Ctr Syst & Control, NL-2628 CD Delft, Netherlands

[4] Bogazici Univ, Dept Elect & Elect Engn, TR-34342 Istanbul, Turkey

[5] Univ Sci & Technol Beijing, Sch Automat & Elect Engn, Beijing 100083, Peoples R China

来源：

IEEE SENSORS JOURNAL | 2021年 / 21卷 / 11期

基金：

中国国家自然科学基金;

关键词：

Soft sensor; soft sensing; process monitoring; optimization and control; industrial process; PRINCIPAL COMPONENT REGRESSION; SUPPORT VECTOR MACHINE; JUST-IN-TIME; FEATURE-SELECTION; QUALITY PREDICTION; VARIABLE SELECTION; NEURAL-NETWORK; MISSING DATA; BIG DATA; MODEL;

D O I：

10.1109/JSEN.2020.3033153

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Over the past twenty years, numerous research outcomes have been published, related to the design and implementation of soft sensors. In modern industrial processes, various types of soft sensors are used, which play essential roles in process monitoring, control and optimization. Emerging new theories, advanced techniques and the information infrastructure have enabled the elevation of the performance of soft sensing. However, novel opportunities are accompanied by novel challenges. This work is motivated by these observations and aims to present a comprehensive review of the developments since the start of the millennium. While a few books and review articles are published on the related topics, more focus on the most up-to-the-date advancement is put in this work, from the perspective of systems and control.

引用

页码：12868 / 12881

页数：14

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