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01-Applied Mathematics & Information Sciences
An International Journal


Volumes > Volume 07 > No. 4


Optimization of Transverse Load Factor of Helical and Spur Gears Using Genetic Algorithm

PP: 1323-1331
Marija Milojevi´c,
In this paper work, it was discussed the model of meshing gears such that the transverse load factor does not change over time and along the line of contact in order to determine if there is some deviations from the assumed and to determine the extent of their changes. During the optimization all factors which determine transverse load factor, according to [1], [2], [3], [4], [5] and [6] were considered as relevant and as such varied using the genetic algorithm optimization process. Only the factors of the basic rack were pre-approved from [5] and as such are considered to be constant input parameters. It is presented new method for finding the optimal geometry compared to many other relevant factors based on a dynamic optimization of factors relevant to meshing of helical and spur gears that is performed in the form of the simulation of gear meshing along the line of contact. Optimization process of 12 input parameters is performed by genetic algorithm and in addition, many important parameters were computed by linear and non linear interpolation. Using this method, it appeared that the most affecting variable of changing the value of load transverse factor is helix angle b , but, despite of this, the profile shift coefficients x1 and x2 also affected to changing the value of load transverse factor. It is noted that for any number of teeth (from the range 18−54) and any gear ratio (from the range 1−5), this method achieves a value 1 of the load transverse factor, which therefore corresponds to uniform load distribution.

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