Comparison of Data Noise Filtration Methods for Casting Cooling Curves
Yevgeniya Savchenko-Synyakova, Volodymyr Semenovych Stepashko, Ihor V. Surovtsev, Olena V. Tokova · 2021 IEEE 16th International Conference on Computer Sciences and Information Technologies (CSIT) · 2021
A comparative analysis of different methods for filtering the measured noisy cooling curves of gray cast iron melts is carried out. Three different methods of noise filtering in the data are compared: simple moving average method as a baseline, method of adaptive smoothing as well as the proposed approximative polynomial filtration based on selection of the degree of the polynomial using GMDH. All this methods give a possibility to filter out noise in the data but the moving average and adaptive smoothing methods give only numerical filtration results. In contrast, the result obtained using the method of approximative filtration is a polynomial function which proved to be the most accurate and to keep all the critical points of the initial cooling curve.