| Issue |
ITM Web Conf.
Volume 11, 2017
2017 International Conference on Information Science and Technology (IST 2017)
|
|
|---|---|---|
| Article Number | 01014 | |
| Number of page(s) | 6 | |
| Section | Session I: Computational Intelligence | |
| DOI | https://doi.org/10.1051/itmconf/20171101014 | |
| Published online | 23 May 2017 | |
Application of Data Smoothing Method in Signal Processing for Vortex Flow Meters
1 School of Mechanical and Electronic Engineeing, Pingxiang University, 337055 Pingxiang, Jiangxi Province, China
2 School of Law, Pingxiang University, 337055 Pingxiang, Jiangxi Province, China
a Corresponding author: tianchunlai@bit.edu.cn
Vortex flow meter is typical flow measure equipment. Its measurement output signals can easily be impaired by environmental conditions. In order to obtain an improved estimate of the time-averaged velocity from the vortex flow meter, a signal filter method is applied in this paper. The method is based on a simple Savitzky-Golay smoothing filter algorithm. According with the algorithm, a numerical program is developed in Python with the scientific library numerical Numpy. Two sample data sets are processed through the program. The results demonstrate that the processed data is available accepted compared with the original data. The improved data of the time-averaged velocity is obtained within smoothing curves. Finally the simple data smoothing program is useable and stable for this filter.
© Owned by the authors, published by EDP Sciences, 2017
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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