<b>Balancing of a rigid rotor using artificial neural network to predict the correction masses</b> - DOI: 10.4025/actascitechnol.v31i2.3912
Keywords:
rigid balancing, rotor balancing, artificial neural network
Abstract
This paper deals with an analytical model of a rigid rotor supported by hydrodynamic journal bearings where the plane separation technique together with the Artificial Neural Network (ANN) is used to predict the location and magnitude of the correction masses for balancing the rotor bearing system. The rotating system is modeled by applying the rigid shaft Stodola-Green model, in which the shaft gyroscopic moments and rotatory inertia are accounted for, in conjunction with the hydrodynamic cylindrical journal bearing model based on the classical Reynolds equation. A linearized perturbation procedure is employed to render the lubrication equations from the Reynolds equation, which allows predicting the eight linear force coefficients associated with the bearing direct and cross-coupled stiffness and damping coefficients. The results show that the methodology presented is efficient for balancing rotor systems. This paper gives a step further in the monitoring process, since Artificial Neural Network is normally used to predict, not to correct the mass unbalance. The procedure presented can be used in turbo machinery industry to balance rotating machinery that require continuous inspections. Some simulated results will be used in order to clarify the methodology presented.Downloads
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Published
2009-06-17
How to Cite
Santos, F. L., Duarte, M. L. M., Faria, M. T. C. de, & Eduardo, A. C. (2009). <b>Balancing of a rigid rotor using artificial neural network to predict the correction masses</b> - DOI: 10.4025/actascitechnol.v31i2.3912. Acta Scientiarum. Technology, 31(2), 151-157. https://doi.org/10.4025/actascitechnol.v31i2.3912
Issue
Section
Mechanical Engineering
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0.8
2019CiteScore
36th percentile
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0.8
2019CiteScore
36th percentile
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