Model based signal processing in smart rotating machines

Model-based signal-processing bridges the gap between numerical modelling and experimental testing of rotating machines. The present paper focuses on signal-processing methods exploiting multiple sensors and capable of handling transient dynamics under varying rotation speeds. These methods rely on special features of rotating elements, e.g. cyclic-symmetry, gyroscopic effects, directional whirling and circumferentially traveling deformations. The new methods could be one of the building blocks leading towards smarter and hence better and safer rotating machines. The 'eyes' of 'Smart Rotating Machines' are the sensors and the accompanied, real-time signal processing methods play the role of a 'brain' in the assessment of measured data. Indeed 'smart' also means combining advanced sensing capabilities with an electronic brain aware of the underlying physics laws that are captured in a model. At the moment it seems that the pendulum leans heavily towards numerical modelling. Finite Element models are the basis for analysis and design, while testing and measurements provide only limited validation means for some of the model parameters partly due to poor deployment of sensors and simplistic signal processing procedures. The presentation will highlight the some of the advantages model-based signal processing offers over past and presently used methods and will try to point towards a path leading from older methods and techniques towards present, state-of-the-art methods and further into the future where smart machines will have 'eyes' and 'brains'. Specifically, the presentation will describe spatial, temporal and directional decomposition of rotating machine vibrations during rapid rotational accelerations. Real time signal processing methods that exploit Hilbert transform based decompositions; directional order-tracking and time-frequency maps will be demonstrated via simulations and experiments. The spatial and temporal decomposition method enables a Smart-Machine to assess the true stress and strain levels on parts rotating relative to an array of sensors and thus to enhance safety. The advance in sensors and electronics alongside their price and size reduction together with improved wireless capabilities will benefit the proposed model-based signal processing.