Soft-sensing and Error Analysis of Air Flow

DOI

10.2991/jimet-15.2015.5How to use a DOI?

Keywords

air flow; soft-sensing; error analysis; data fusion

Abstract

To measure air flow in the power plant, regression models are set up with variables according to mechanical analysis and data mining technique, and the results are verified by goodness of fit, F-test and deviance. It is proved that the results using multi-sensor data fusion is more reliable and accurate than the single ones or the arithmetic average value, and based on that, a principle is presented to ensure the data with smaller error is selected. The soft-sensing model of air flow is established by the experiment in a power plant.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Li Jian
AU  - Zhang Bin-wen
PY  - 2015/12
DA  - 2015/12
TI  - Soft-sensing and Error Analysis of Air Flow
BT  - Proceedings of the 2015 Joint International Mechanical, Electronic and Information Technology Conference
PB  - Atlantis Press
SP  - 20
EP  - 23
SN  - 2352-538X
UR  - https://doi.org/10.2991/jimet-15.2015.5
DO  - 10.2991/jimet-15.2015.5
ID  - Jian2015/12
ER  -