Identification of the smart spring properties from FRFs measurements

The objective of this paper is the dynamic identification of a reduced-scale helicopter blade system that incorporates an active pitch link or smart spring for vibration control. The identification of the Smart Spring parameters, in terms of the masses and stiffnesses associated to its components, is carried out in the frequency domain using a developed sensitivity-based updating method. This method, called Predictor-Corrector, iteratively minimizes a residual vector of correlation functions, defined on the Frequency Response Functions (FRFs), in order to obtain the unknown values of the parameters that well rep- resent the dynamic behavior of the smart spring. In the paper the accuracy of the solution provided by the developed technique is assessed through several numerical analyses. For this purpose, a lumped parameter numerical model of the Smart Spring was developed and the effects of various mass and stiffness distribution scenarios on the modal properties of the system are presented. Due to the nonlinear dynamic behavior of the smart spring system, a linear approximation of the system around a prescribed operative working con- dition is considered. Finally, the developed approach is applied for the identification of the dynamic parameters of a real smart spring system. It is shown that acceptable values of the equivalent lumped parameters were achieved also considering experimental data such as those recorded during a test campaign carried out at the Smart Rotor Laboratory of the Carleton University, thus validating the identification approach.