  In this paper we will be represent the transformation of a noisy dataset into
a regular and smooth curve. We performed torsion test on 15Cr 15Ni Titanium
modified austenitic stainless steel up to its rupture. We did it these torsion
tests multiple strain rates varying from 0.001 to 25 per Sec and obtained huge
number of data points has been obtained from with a data acquisition rate of
100 Hz. We also have few more data of 1500Hz of the same experiment on a
different material e.g 316 L Austenitic Stainless Steel. Machine is actually
acquiring only torque value and the angle of rotation. The torque vs. twist
data itself will be having a noise, which gets multiplied when we take the
first derivative of torque-twist data. The noise becomes huge and it fluctuates
from desired material properties, although some serrated flow should be present
but the range of serration should not be as the fluctuation observed in our
curve so smoothing was necessary. We will be documenting final shear
stress-strain curve we achieved through Nonparametric Regression Lowess and
Loess, Savitzky Golay filtering, and also the robust Nonparametric Regressions,
body splines and shape preserving curves. The most acceptable one is Savitzky
Golay method for our experiment or one can choose splines or loess or lowess
according to the object of interest.
