Abstract: The estimation of gear tooth stiffness is important for finding the load distribution between the gear teeth when two consecutive sets of teeth are in contact. Based on dynamic model a C-program has been developed to compute mesh stiffness. By using this program position dependent mesh stiffness of spur gear tooth for various profile shifts have been computed for a fixed center distance and altering tooth-sum gearing (100 by ± 4%). It is found that the C-program using dynamic model is one of the rapid soft computing technique which helps in design of gears. The mesh tooth stiffness along the path of contact is studied for both 20° and 25° pressure angle gears at various profile shifts. Better tooth stiffness is noticed in case of negative alteration tooth-sum gears compared to standard and positive alteration tooth-sum gears. Also, in case of negative alteration tooth-sum gearing better mesh stiffness is noticed in 20° pressure angle when compared to 25°.
Abstract: A new approach has been developed to estimate the
load share and distribution of worm gear drives, and to calculate the
instantaneous tooth meshing stiffness. In the approach, the worm gear
drive was modelled as a series of spur gear slices, and each slice was
analyzed separately using the well-established formulae of spur gear
loading and stresses. By combining the results obtained for all slices,
the entire envolute worm gear set loading and stressing was obtained. The geometric modelling method presented allows tooth elastic
deformation and tooth root stresses of worm gear drives under
different load conditions to be investigated. Based on the slicing
method introduced in this study, the instantaneous meshing stiffness
and load share are obtained. In comparison with existing methods,
this approach has both good analysis accuracy and less computing
time.
Abstract: In this paper an analytical crack propagation scenario
is proposed which assumes that a crack propagates in the tooth root in
both the crack depth direction and the tooth width direction, and
which is more reasonable and realistic for non-uniform load
distribution cases than the other presented scenarios. An analytical
approach is used for quantifying the loss of time-varying gear mesh
stiffness with the presence of crack propagation in the gear tooth root.
The proposed crack propagation scenario can be applied for crack
propagation modelling and monitoring simulation, but further
research is required for comparison and evaluation of all the
presented crack propagation scenarios from the condition monitoring
point of view.
Abstract: This work presents a numerical model developed to
simulate the dynamics and vibrations of a multistage tractor gearbox.
The effect of time varying mesh stiffness, time varying frictional
torque on the gear teeth, lateral and torsional flexibility of the shafts
and flexibility of the bearings were included in the model. The model
was developed by using the Lagrangian method, and it was applied to
study the effect of three design variables on the vibration and stress
levels on the gears. The first design variable, module, had little effect
on the vibration levels but a higher module resulted to higher bending
stress levels. The second design variable, pressure angle, had little
effect on the vibration levels, but had a strong effect on the stress
levels on the pinion of a high reduction ratio gear pair. A pressure
angle of 25o resulted to lower stress levels for a pinion with 14 teeth
than a pressure angle of 20o. The third design variable, contact ratio,
had a very strong effect on both the vibration levels and bending
stress levels. Increasing the contact ratio to 2.0 reduced both the
vibration levels and bending stress levels significantly. For the gear
train design used in this study, a module of 2.5 and contact ratio of
2.0 for the various meshes was found to yield the best combination
of low vibration levels and low bending stresses. The model can
therefore be used as a tool for obtaining the optimum gear design
parameters for a given multistage spur gear train.