Acoustic and Vibration Response Analysis of Heavy-Duty Gearbox
449
Fig. 5 The comparison of amplitude of surface normal acceleration for different eigen frequency
coefficient from experiment was used, the response was overestimated. In case of
multiplying of damping coefficient several times the acceleration starts corresponded
to data from experiment.
The numerical simulation was also used for prediction of sound pressure level
(SPL); the distribution of SPL is shown in Fig. 6. The SPL can be evaluated in the
plane in given distance. The distribution can be helpful for design optimization.
4 Conclusion
The dynamic behavior of the gearbox housing was investigated by using modal
and harmonic analysis. There were used numerical and experimental approaches,
which were simultaneously compared to each other. For that reason, there were
used the same boundary conditions. The computational modal analysis was refined
by using measured density and model of geometry created by using 3D scanning
and reverse engineering. By using this computational model, the difference to the
experimental approach was up to 2.73%. The damping coefficient was determined
449
Fig. 5 The comparison of amplitude of surface normal acceleration for different eigen frequency
coefficient from experiment was used, the response was overestimated. In case of
multiplying of damping coefficient several times the acceleration starts corresponded
to data from experiment.
The numerical simulation was also used for prediction of sound pressure level
(SPL); the distribution of SPL is shown in Fig. 6. The SPL can be evaluated in the
plane in given distance. The distribution can be helpful for design optimization.
4 Conclusion
The dynamic behavior of the gearbox housing was investigated by using modal
and harmonic analysis. There were used numerical and experimental approaches,
which were simultaneously compared to each other. For that reason, there were
used the same boundary conditions. The computational modal analysis was refined
by using measured density and model of geometry created by using 3D scanning
and reverse engineering. By using this computational model, the difference to the
experimental approach was up to 2.73%. The damping coefficient was determined