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Monitoring of Oxygen Content in the Flue Gas at a Coal-Fired Power Plant Using Cloud Modeling Techniques

Han, Xiaojuan, Yan, Yong, Cheng, Cheng, Chen, Yueyan, Zhu, Yanglin (2014) Monitoring of Oxygen Content in the Flue Gas at a Coal-Fired Power Plant Using Cloud Modeling Techniques. IEEE Transactions on Instrumentation and Measurement, 63 (4). pp. 953-963. ISSN 0018-9456. (doi:10.1109/TIM.2013.2287117) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:40851)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided.
Official URL:
http://dx.doi.org/10.1109/TIM.2013.2287117

Abstract

The accurate measurement of oxygen content in the flue gas at a coal-fired power plant is important for the plant operators to realize closed-loop and optimal control. In this paper, eight zirconium oxygen analyzers were used to measure the oxygen content in the flue gas under real plant conditions. A cloud model is incorporated into the measurement system. In consideration of the temporal and spatial characteristics of the oxygen sensors, a quantitative transformation fusion model based on the cloud model theory is established. The oxygen content in the flue gas is calculated using mean value, space fusion, and space-time fusion methods, respectively. The temperatures of both flue gas and cold air are also measured to calculate the heat loss of the flue gas and the combustion efficiency of the boiler. On-plant demonstration results show that the proposed method produces more accurate measurements than those from the mean value method, leading to increased combustion efficiency and reduced heat loss.

Item Type: Article
DOI/Identification number: 10.1109/TIM.2013.2287117
Subjects: T Technology
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Engineering and Digital Arts
Depositing User: Tina Thompson
Date Deposited: 25 Apr 2014 14:50 UTC
Last Modified: 17 Aug 2022 10:57 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/40851 (The current URI for this page, for reference purposes)

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