Application of Machine Learning in Industrial Boilers: Fault Detection, Diagnosis, and Prognosis

被引：10

作者：

Meng, Yang ^{[1
,2
]}

Wu, Xinyun ^{[3
]}

Oladejo, Jumoke ^{[4
]}

Dong, Xinyue ^{[4
]}

Zhang, Zhiqian ^{[4
]}

Deng, Jie ^{[4
]}

Yan, Yuxin ^{[5
]}

Zhao, Haitao ^{[6
]}

Lester, Edward ^{[7
]}

Wu, Tao ^{[1
,5
]}

Pang, Cheng Heng ^{[3
,4
]}

机构：

[1] Univ Nottingham Ningbo China, Ningbo New Mat Inst, Ningbo 315042, Peoples R China

[2] Chinese Acad Sci, Ctr Excellence Reg Atmospher Environm, Inst Urban Environm, Xiamen 361021, Peoples R China

[3] Univ Nottingham Ningbo China, Municipal Key Lab Clean Energy Convers Technol, Ningbo 315100, Peoples R China

[4] Univ Nottingham Ningbo China, Dept Chem & Environm Engn, Ningbo 315100, Peoples R China

[5] Univ Nottingham Ningbo China, Key Lab Carbonaceous Wastes Proc & Proc Intensifi, Ningbo 315100, Peoples R China

[6] MIT, Dept Mech Engn, Cambridge, MA 02139 USA

[7] Univ Nottingham, Dept Chem & Environm Engn, Nottingham NG7 2RD, England

来源：

CHEMBIOENG REVIEWS | 2021年 / 8卷 / 05期

关键词：

Diagnosis system; Fault detection; Industrial boiler; Machine learning; Prognostics; PRINCIPAL COMPONENT ANALYSIS; ARTIFICIAL NEURAL-NETWORK; SUPPORT VECTOR MACHINE; EXPERT-SYSTEM; ROTATING MACHINERY; DECISION TREE; METAL-OXIDES; DATA-DRIVEN; ASH FUSION; CHALLENGES;

D O I：

10.1002/cben.202100008

中图分类号：

TQ [化学工业];

学科分类号：

0817 ;

摘要：

Enhancement in boiler efficiency via controlled operation could lead to energy savings and reduction in pollutant emission. Activities such as scheduled maintenance could be improved by increasing boiler availability and reducing running costs. However, the time interval between recommended maintenance is varied depending on boilers. The application of fault detection, diagnosis and prognosis (FDDP) in industrial boilers plays an important role in optimizing operation, early-warning of faults, and identification of root causes. This review discusses the application of machine learning (ML)-based algorithms (knowledge-driven and data-driven) for FDDP, thus allowing the identification of fit-for-purpose techniques for specific applications leading to improved efficiency, operability, and safety.

引用

页码：535 / 544

页数：10

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