Analysis of Digital Filters Used in Time-Series Small Heat Flux Measurement

Abstract Noise fluctuation is the most common issue of small heat flux measurement and it disturbs the measurement precision. In the previous studies, how to select an appropriate filter and determine its optimal operating parameter was not given systematically. In this paper, the aim is to explore an effective filter selection and optimal operating parameter determination method for the small heat flux signal. Firstly, six filters with the large range operating parameters were chosen to remove the noise of a set of 10000 numbers time-series heat flux in the range of 5∼10 W/m2. Then, signal-to-noise ratio, standard deviation, mean absolute deviation and correlation coefficient were introduced to comprehensively assess the filtering results. Lastly, the intersection region method is firstly proposed to determine the optimal operating parameters based on the tradeoff between repeatability and fidelity. The numerical results indicated that the signal-to-noise ratio of the sampled heat flux was ranged from 13.310 db to 20.703 db. The standard deviation and correlation coefficient was decreased from 1.111 to 0.093∼0.672 and from 1 to 0.640∼0.883, while the mean absolute deviation was increased from 0 to 0.498∼1.056. When the filter is fixed, the repeatability and fidelity levels of filtered data are contradictory. When comparing the filtering effects of filters, some filters simultaneously showed a high repeatability and fidelity levels. For the heat flux signal in this study, the moving average filter with 51 window width and Savitzky-Golay filters with 101 window width and three highest order are the best choice. The proposed intersection region method with four assessment metrics is effectively to find an appropriate filter with high repeatability and fidelity.