Proceedings of the 2nd International Conference on Mechatronics Engineering and Information Technology (ICMEIT 2017)

Portable Dynamic Weighing System of Yak based on BP Neural Network

Authors
Cai Wen, Zhengyu Xie, Yansong Deng
Corresponding Author
Cai Wen
Available Online May 2017.
DOI
https://doi.org/10.2991/icmeit-17.2017.62How to use a DOI?
Keywords
BP Neural Network, dynamic weighing, portable type, Yak
Abstract
In order to measure the weight of yak more conveniently and effectively, based on BP neural network, this paper provides a portable dynamic weighing System for yak. The wireless transmission mode is adopted between the acquisition module and the instrument in this system and weighing platform is added a handle and a small roller table, which overcome the shortcomings of traditional weighing station that cannot move. In order to further improve the problem of traditional weighing station's low accuracy, using the smoothing mean filter to denoise the original data and according to the output of the shear beam type weighing sensor and the speed of yak, the BP neural model is established, thus the static weight of yak being obtained. By many experiments in matlab, the results show that this system achieves the measurement accuracy of dynamic weighing system and ensures that it can be achieved technically, which has good practical value.
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Proceedings
2nd International Conference on Mechatronics Engineering and Information Technology (ICMEIT 2017)
Part of series
Advances in Computer Science Research
Publication Date
May 2017
ISBN
978-94-6252-338-8
ISSN
2352-538X
DOI
https://doi.org/10.2991/icmeit-17.2017.62How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Cai Wen
AU  - Zhengyu Xie
AU  - Yansong Deng
PY  - 2017/05
DA  - 2017/05
TI  - Portable Dynamic Weighing System of Yak based on BP Neural Network
BT  - 2nd International Conference on Mechatronics Engineering and Information Technology (ICMEIT 2017)
PB  - Atlantis Press
SN  - 2352-538X
UR  - https://doi.org/10.2991/icmeit-17.2017.62
DO  - https://doi.org/10.2991/icmeit-17.2017.62
ID  - Wen2017/05
ER  -