Proceedings of the 2017 2nd International Conference on Control, Automation and Artificial Intelligence (CAAI 2017)

Experiment on Flow Velocity Vector Measurement in EPs by Using 3D-PIV

Authors
Siyang Dai, Yunxiao Cao, Wenxiu Wang, Huanyu Zhao
Corresponding Author
Siyang Dai
Available Online June 2017.
DOI
10.2991/caai-17.2017.54How to use a DOI?
Keywords
component; EPs; 3D-PIV; fine particles; flow velocity vector
Abstract

In the online-plate electrostatic precipitator(EPs), uses three-dimensional PIV technique and image processing technology to observe the fine particles of flow field under -45KV pulse high pressure, and analyzes the motion state of the particles. Comparing with the traditional 2D-PIV technology, 3D-PIV technology can be more accurate and comprehensive to observe flow velocity vector of fine particles in electrode voltage. Avoiding inaccurate observation due to particles overlap. The experimental results show that the method can provide data support for more accurate description of particle motion behavior, which is great significance to improve the electrostatic precipitator.

Copyright
© 2017, 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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Volume Title
Proceedings of the 2017 2nd International Conference on Control, Automation and Artificial Intelligence (CAAI 2017)
Series
Advances in Intelligent Systems Research
Publication Date
June 2017
ISBN
978-94-6252-360-9
ISSN
1951-6851
DOI
10.2991/caai-17.2017.54How to use a DOI?
Copyright
© 2017, 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/).

Cite this article

TY  - CONF
AU  - Siyang Dai
AU  - Yunxiao Cao
AU  - Wenxiu Wang
AU  - Huanyu Zhao
PY  - 2017/06
DA  - 2017/06
TI  - Experiment on Flow Velocity Vector Measurement in EPs by Using 3D-PIV
BT  - Proceedings of the 2017 2nd International Conference on Control, Automation and Artificial Intelligence (CAAI 2017)
PB  - Atlantis Press
SP  - 242
EP  - 244
SN  - 1951-6851
UR  - https://doi.org/10.2991/caai-17.2017.54
DO  - 10.2991/caai-17.2017.54
ID  - Dai2017/06
ER  -