This article presents the algorithm for the selection of the optimal number of teeth for a biplanetary bevel gear. This transmission device is mainly used in working parts of mining combines and agricultural machines as well as in differential mechanisms of complex mechanical drives. In the systematic search, we used an algorithm for generating induction decision trees, based on entropy growth as a method related to machine learning. A series of tests is performed in a sequence of trees. Other methods may be used, e.g. the „2-3 tree” method, the “digital search tree” or the “AVL tree method”.
In the article was discussed the possibility of structures and information systems complex game trees for the analysis of automatic gearboxes. The purpose of modelling an automatic gearbox with graphs can be versatile, namely: determining the transmission ratio of individual gears, analysing the speed and acceleration of individual rotating elements. In a further step, logic tree-decision methods can be used to analyse functional schemes of selected transmission gears. Instead, for graphs that are models of transmission, parametrically acting tree structures can be used. This allows for the generalization and extension of the algorithmic approach, furthermore in the future it will allow further analyses and syntheses, such as checking the isomorphism of the proposed solutions, determining the validity of construction and / or operating parameters of the analysed gears. The game tree structure describes a space of possible solutions in order to find optimum objective functions. There is the connection with other graphical structures which can be graphs in another sense, or even decision trees with node and/or branch coding.
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