Virtual Sensing for Rotordynamics

During last decades the scientific community focused its attention on energy efficiency solutions. Materials have been developed or improved to avoid energy dispersions and new strategies have been developed in order to exploit at best renewable and non renewable energy sources. Other paths are currently followed to pursue the same goal, for instance, the introduction of innovative monitoring system and techniques. In this framework, the concept of virtual sensing reveals itself as one of the most powerful tools. Several physical quantities are relevant to define the health status of the system. Unfortunately, many of these quantities cannot be directly measured in many practical applications due to lack of specific sensor or to the environment in which the system is operating. As a consequence, state estimation techniques come out as an extremely helpful tool. These techniques allow combining the world of measurements with the one of numerical modeling leading to the estimation of the desired unmeasurable system quantities. In the current research a Kalman Filter based algorithm is applied to investigate and assess the health condition of a rotor system. The system under investigation is a classical example in rotordynamics. The attention is focused on the estimation of one of the most common malfunction in rotating machinery: the unbalance.Copyright © 2016 by ASME