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Indirect NOx emission monitoring in natural gas fired boilers

Tutkimustuotosvertaisarvioitu

Standard

Indirect NOx emission monitoring in natural gas fired boilers. / Korpela, Timo; Kumpulainen, Pekka; Majanne, Yrjö; Häyrinen, Anna; Lautala, Pentti.

julkaisussa: Control Engineering Practice, Vuosikerta 65, 01.08.2017, s. 11-25.

Tutkimustuotosvertaisarvioitu

Harvard

Korpela, T, Kumpulainen, P, Majanne, Y, Häyrinen, A & Lautala, P 2017, 'Indirect NOx emission monitoring in natural gas fired boilers', Control Engineering Practice, Vuosikerta. 65, Sivut 11-25. https://doi.org/10.1016/j.conengprac.2017.04.013

APA

Korpela, T., Kumpulainen, P., Majanne, Y., Häyrinen, A., & Lautala, P. (2017). Indirect NOx emission monitoring in natural gas fired boilers. Control Engineering Practice, 65, 11-25. https://doi.org/10.1016/j.conengprac.2017.04.013

Vancouver

Korpela T, Kumpulainen P, Majanne Y, Häyrinen A, Lautala P. Indirect NOx emission monitoring in natural gas fired boilers. Control Engineering Practice. 2017 elo 1;65:11-25. https://doi.org/10.1016/j.conengprac.2017.04.013

Author

Korpela, Timo ; Kumpulainen, Pekka ; Majanne, Yrjö ; Häyrinen, Anna ; Lautala, Pentti. / Indirect NOx emission monitoring in natural gas fired boilers. Julkaisussa: Control Engineering Practice. 2017 ; Vuosikerta 65. Sivut 11-25.

Bibtex - Lataa

@article{6a6085d7de084f2c90bde56154b1b51c,
title = "Indirect NOx emission monitoring in natural gas fired boilers",
abstract = "New emission regulations will increase the need for inexpensive NOx emission monitoring solutions also in smaller power plants. The objective in this study is to find easily maintainable and transparent but still valid models to predict NOx emissions in natural gas fired hot water boilers utilizing existing process instrumentation. With a focus on long-term applicability in practical installations, the performance of linear regression is compared in two municipal 43 MW boilers with three widely used nonlinear methods: multilayer perceptron, support vector regression, and fuzzy inference system. The linear models were the most applicable providing the best estimation results (relative error of 1 applications in practise. However, each boiler model should be identified individually.",
keywords = "Combustion, Estimation, Modelling, Monitoring, Natural gas, NO, Soft sensor",
author = "Timo Korpela and Pekka Kumpulainen and Yrj{\"o} Majanne and Anna H{\"a}yrinen and Pentti Lautala",
year = "2017",
month = "8",
day = "1",
doi = "10.1016/j.conengprac.2017.04.013",
language = "English",
volume = "65",
pages = "11--25",
journal = "Control Engineering Practice",
issn = "0967-0661",
publisher = "Elsevier",

}

RIS (suitable for import to EndNote) - Lataa

TY - JOUR

T1 - Indirect NOx emission monitoring in natural gas fired boilers

AU - Korpela, Timo

AU - Kumpulainen, Pekka

AU - Majanne, Yrjö

AU - Häyrinen, Anna

AU - Lautala, Pentti

PY - 2017/8/1

Y1 - 2017/8/1

N2 - New emission regulations will increase the need for inexpensive NOx emission monitoring solutions also in smaller power plants. The objective in this study is to find easily maintainable and transparent but still valid models to predict NOx emissions in natural gas fired hot water boilers utilizing existing process instrumentation. With a focus on long-term applicability in practical installations, the performance of linear regression is compared in two municipal 43 MW boilers with three widely used nonlinear methods: multilayer perceptron, support vector regression, and fuzzy inference system. The linear models were the most applicable providing the best estimation results (relative error of 1 applications in practise. However, each boiler model should be identified individually.

AB - New emission regulations will increase the need for inexpensive NOx emission monitoring solutions also in smaller power plants. The objective in this study is to find easily maintainable and transparent but still valid models to predict NOx emissions in natural gas fired hot water boilers utilizing existing process instrumentation. With a focus on long-term applicability in practical installations, the performance of linear regression is compared in two municipal 43 MW boilers with three widely used nonlinear methods: multilayer perceptron, support vector regression, and fuzzy inference system. The linear models were the most applicable providing the best estimation results (relative error of 1 applications in practise. However, each boiler model should be identified individually.

KW - Combustion

KW - Estimation

KW - Modelling

KW - Monitoring

KW - Natural gas

KW - NO

KW - Soft sensor

U2 - 10.1016/j.conengprac.2017.04.013

DO - 10.1016/j.conengprac.2017.04.013

M3 - Article

VL - 65

SP - 11

EP - 25

JO - Control Engineering Practice

JF - Control Engineering Practice

SN - 0967-0661

ER -