Prognostic Algorithm for Sensors and Actuators Using Multiresolution Signal Decomposition Technique

Author(s):  
Harbilas Bal ◽  
Subrat Kumar Mohanty ◽  
Nitaigour P. Mahalik ◽  
Kiseon Kim
2020 ◽  
Vol 10 (21) ◽  
pp. 7418
Author(s):  
Grégoire Corradi ◽  
Jean-Jacques Sinou ◽  
Sébastien Besset

This paper is devoted to discussion of the efficiency of reduced models based on a Double Modal Synthesis method that combines a classical modal reduction and a condensation at the frictional interfaces by computing a reduced complex mode basis, for the prediction of squeal noise of mechanical systems subjected to friction-induced vibration. More specifically, the use of the multiresolution signal decomposition of acoustic radiation and wavelet representation will be proposed to analyze details of a pattern on different observation scales ranging from the pixel to the size of the complete acoustic pattern. Based on this approach and the definition of specific resulting criteria, it is possible to quantify the differences in the representation of the acoustic fields for different reduced models and thus to perform convergence studies for different scales of representation in order to evaluate the potential of reduced models. The effectiveness of the proposed approach is tested on the finite element model of a simplified brake system that is composed of a disc and two pads. The contact is modeled by introducing contact elements at the two friction interfaces with the classical Coulomb law and a constant friction coefficient. It is demonstrated that the new proposed criteria, based on multiresolution signal decomposition, allow us to provide satisfactory results for the choice of an efficient reduced model for predicting acoustic radiation due to squeal noise.


2019 ◽  
Vol 2 (1) ◽  
pp. 22-31 ◽  
Author(s):  
Prajna Parimita Mishra ◽  
Chandrashekhar Narayan Bhende ◽  
M. Sabarimalai Manikandan

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