Schmitz, Christian ; Nakhjiri, Mehdi ; Pelz, Peter F. (2022)
Softsensor for the characterisation of the process fluid.
International Conference on Fan Noise, Aerodynamics, Applications and Systems. Darmstadt, Germany (18.04.2018-20.04.2018)
doi: 10.26083/tuprints-00021357
Conference or Workshop Item, Secondary publication, Publisher's Version
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Item Type: | Conference or Workshop Item |
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Type of entry: | Secondary publication |
Title: | Softsensor for the characterisation of the process fluid |
Language: | English |
Date: | 2022 |
Place of Publication: | Darmstadt |
Year of primary publication: | 2018 |
Book Title: | FAN 2018 - Proceedings of the International Conference on Fan Noise, Aerodynamics, Applications and Systems : 18. - 20. April 2018 |
Collation: | 6 Seiten |
Event Title: | International Conference on Fan Noise, Aerodynamics, Applications and Systems |
Event Location: | Darmstadt, Germany |
Event Dates: | 18.04.2018-20.04.2018 |
DOI: | 10.26083/tuprints-00021357 |
Corresponding Links: | |
Origin: | Secondary publication service |
Abstract: | This paper introduces an intelligent fan equipped with a softsensor for the volume flow rate and composition of a two-component process fluid, as e.g. often found in chemical processes. This is done by combining the fans characteristic data with those of cheap pressure and temperature sensors as well as the mixture laws of a two-component gas. An example estimating the percentage of butane for a combustion flow is given. As the experiments show, the estimation uncertainty of the softsensor is 2 % for the butane concentration and 3 % for the volume flow rate and thus of the magnitude of the uncertainties of the used input data. |
Status: | Publisher's Version |
URN: | urn:nbn:de:tuda-tuprints-213572 |
Classification DDC: | 600 Technology, medicine, applied sciences > 620 Engineering and machine engineering |
Divisions: | 16 Department of Mechanical Engineering > Institute for Fluid Systems (FST) (since 01.10.2006) |
Date Deposited: | 13 May 2022 13:59 |
Last Modified: | 03 Apr 2023 11:56 |
URI: | https://tuprints.ulb.tu-darmstadt.de/id/eprint/21357 |
PPN: | 495522287 |
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