Application of Data Smoothing Method in Signal Processing for Vortex Flow Meters

• Main Authors: Zhang Jun, Zou Tian, Tian Chun-Lai
• Format: Article
• Language: English
• Published: EDP Sciences 2017-01-01
• Series: ITM Web of Conferences
• Online Access: https://doi.org/10.1051/itmconf/20171101014

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.