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2 Archive of Mechanical Engineering

2 2018

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Multiple fault parameter estimation of a fully assembled turbogenerator system

Lal M.

Archive of Mechanical Engineering

2018

Vol. LXV, nr 2

233--252

The present article investigates the dynamic behavior of a fully assembled turbogenerator system inﬂuenced by misalignment. In the past, most of the researchers have neglected the foundation ﬂexibility in the turbogenerator systems in their study, to overcome this modelling error a more realistic model of a turbogenerator system has been attempted by considering ﬂexible shafts, ﬂexiblecoupling, ﬂexible bearings and ﬂexible foundation. Equations of motion for fully assembled turbogenerator system including ﬂexible foundations have been derived by using ﬁnite element method. The methodology developed based on least squares technique requires forced response information to quantify the bearing–coupling–foundation dynamic parameters of the system associated with diﬀerent faults along with residual unbalances.The proposed methodology is tested for the various level of measurement noise and modelling error in the system parameters, i.e., 5% deviation in E (modulus of elasticity) and ρ (density), respectively, for robustness of the algorithm. In a practical sense, the condition analyzed in the present article relates to the identiﬁcation of misalignment and other dynamic parameters viz. bearing and residual unbalance in a rotor integrated with ﬂexible foundation.

Estimation of speed dependent fault parameters in a coupled rotor-bearing system

Lal M., Satapathy M.

Archive of Mechanical Engineering

2018

Vol. LXV, nr 3

327--347

In rotating machineries, misalignment is considered as the second most major cause of failure after unbalance. In this article, model-based multiple fault identiﬁcation technique is presented to estimate speed-dependent coupling misalignment and bearing dynamic parameters in addition with speed independent residual unbalances. For brevity in analysis, a simple coupled rotor bearing system is considered and analytical approach is used to develop the identiﬁcation algorithm. Equations of motion ingeneralized co-ordinates are derived with the help of Lagrange’s equation and least squares ﬁtting approach is used to estimate the speed-dependent fault parameters. Present identiﬁcation algorithm requires independent sets of forced response data which are generated with the help of diﬀerent sets of trial unbalances. To avoid/suppress the ill-conditioning of regression equation, independent sets of forced response data are obtained by rotating the rotor in clock-wise and counter clock-wise directions, alternatively. Robustness of algorithm is checked for diﬀerent levels of measurement noise.