Predictability may transform maintenance from a cost centre into a profit unit. Industries are indeed investing in innovative technologies to implement the purpose. In this paper we introduce a project meant to develop a robotic tool for the assessment of railway pantographs through a vibration based detection of faults. Nonlinearities such as intense dependence of damping on speed and non-negligible friction in joints make the applicaton particularly challenging. These phenomena could in fact drastically modify the behavior with respect to simpler linear models predictions. Experimental frequency response functions (FRFs) were hence derived for several input amplitudes so as to estimate at which extent modal parameters are related to the energy level. To discriminate the sources of nonlinearity FRFs were carried out even after the damper had been removed. Phase plots shape alteration was then observed for a couple of frequencies and as many amplitudes to delve deeper into dynamics changes. A first indication on the suitability of FRFs to detect faults is pursued considering the absence of the dashpot as an example of defect, i.e. a severe leakage, comparing modal information from the two data sets.

Experimental identification of faults in a railway pantograph mechanism in presence of nonlinear damping (Aimeta 2017)

Santamato, G.;Solazzi, M.;Frisoli, A.
2017

Abstract

Predictability may transform maintenance from a cost centre into a profit unit. Industries are indeed investing in innovative technologies to implement the purpose. In this paper we introduce a project meant to develop a robotic tool for the assessment of railway pantographs through a vibration based detection of faults. Nonlinearities such as intense dependence of damping on speed and non-negligible friction in joints make the applicaton particularly challenging. These phenomena could in fact drastically modify the behavior with respect to simpler linear models predictions. Experimental frequency response functions (FRFs) were hence derived for several input amplitudes so as to estimate at which extent modal parameters are related to the energy level. To discriminate the sources of nonlinearity FRFs were carried out even after the damper had been removed. Phase plots shape alteration was then observed for a couple of frequencies and as many amplitudes to delve deeper into dynamics changes. A first indication on the suitability of FRFs to detect faults is pursued considering the absence of the dashpot as an example of defect, i.e. a severe leakage, comparing modal information from the two data sets.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11382/524121
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