Processing methods of measured runs of torque and angular speed of combustion engine propulsion system

Abstract

In this paper four processing methods of cyclic data runs, namely: Fourier interpolation and transformation, least-squares approximation by means of trigonometric polynomials, synchronous averaging and movable approximation, were presented by using, as an example, discretely measured runs of torque and angular speed. It was demonstrated that for extracting a useful signal out of disturbance background and decomposing the disturbances the appropriate methods are the synchronous averaging and multiple movable approximation. To emerge significant spectral lines from a spectrum the least-squares approximation by using trigonometric polynomials can be applied. The method contains a criterion for signal filtration and is insensitive to disturbances, run truncation and sampling irregularity. Fast Fourier Transform (FFT) may have an auxiliary significance for preliminary spectral analysis. Its main disadvantage is that in order to build a smoothing-out filter its parameters should be determined in advance, e.g. by applying one of the remaining methods.