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The growth in recent decades of the nanotechnology area has led to the emergence of new challenges for researchers and engineers, due to the need for the development of sensors and devices to characterize physical phenomena or quantify the properties and characteristics of materials at the nano-scale [1]. The achievable accuracy of devices and instruments related to this field requires state of the art technology and ground breaking research. Contributions to the field of precision manufacturing will have a positive impact on sectors such as medicine, industrial, communications, aviation, aerospace and defence, among others.

Electro-mechanical devices that are usually employed in precision manufacturing processes typically have nonlinear behavior for most representative physical variables, low signal-to-noise ratio, strong influence of environmental factors, the high presence of uncertainty and a huge volume of data generated at high frequencies. Therefore, conventional methods often cannot be applied for the characterization of physical phenomena in these devices. However, the use of advanced signal processing strategies, and experimental modelling techniques are useful and feasible ways for studying physical processes at these devices.Recent researches on precision manufacturing are focused on the development of rotary actuators for positioning with high accuracy [2,3].

The performance of these devices is enhanced by the introduction of control systems to reduce the influence of environmental factors such as temperature [4] and employing magnetic actuators Batimastat to isolate external vibration [5]. The use of multi-sensory monitoring strategies, such as acoustic emission [6] and vibration sensors [7] is chosen to improve device capabilities. Moreover, due to vibration signals with low signal to noise ratio, much attention has been focussed on the use of advanced Anacetrapib computational algorithms for signal processing [8�C10].The main contribution of this paper is the development of a method, based on a computational algorithm for signal analysis in the frequency domain combined with a regression model, to detect nano-scale vibration, and to estimate the eccentricity at the spinning axis of ultra precision rotation devices. This knowledge can be applied to reducing systemic errors, thus reducing manufacturing time.