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Abstract

A particle-level simulation technique has been developed for modelling fibre suspension flow in a converging channel of a papermachine headbox. The fibre model is represented by a chain of elements connected together. The model was verified by the simulation of rigid fibre dynamics in a simple shear flow. The period of rotation was found to be in a very good agreement with theory and reference data. The model was then employed to simulate fibre motion in a converging channel of a papermachine headbox. Fibre suspension motion was resolved using two-step procedure. Velocity field was calculated by means of a commercial CFD code ANSYS Fluent with RSM turbulence model applied and used as an input to the in-house code allowing to simulate fibre dynamics. Results of the calculations were used to construct the fibre orientation probability distribution (FOPD) which was found to be consistent with available experimental data.
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Abstract

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 in generalized 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.
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