Uncertainty quantification techniques applied to rotating systems: A comparative study

The modeling of mechanical systems involves different parameters that are susceptible to uncertainties. Commonly, the variations result from the mathematical difficulty of representing the peculiarities of the dynamic systems and the lack of knowledge about the physical properties of the materials used in a given application. In this context, the analysis of uncertainties that affect the performance of the system is an important design issue. Uncertainty analysis of dynamic systems has been studied by applying techniques based on stochastic and fuzzy logic approaches. The fuzzy logic technique seems to be more appropriate when the stochastic process that characterizes the uncertainties is unknown. Therefore, in the present contribution, the inherent uncertainties affecting the performance of a horizontal rotating machine are modeled by using both stochastic and fuzzy logic-based analysis. These methodologies have been compared through numerical simulations in terms of the dynamic behavior of the system as represented by rotor orbits, unbalance responses, and frequency response functions. The proposed uncertainty analysis provides additional information that can be useful for design and maintenance purposes.