Diseño de Transmisiones de Potencia por Correas Trapezoidales, Tipo Normal, Mediante Redes Neuronales - Celi Gallegos, Juan Gabriel (2020)
The present work is focused on the development of a software application in order to execute calculus at potency transmissions design, by means of classic trapezoidal belts, using Artificial Intelligence, they are Artificial Neuron Networks (ANNs) and the proposed methodology on catalogues: Dunlop, Goodyear, Optibelt and Oleostatic. To begin it was executed the tabulation of 74391 data related to the belt profile, 2828 data associated to the base potency and 3693 data to the additional potency; all of these come from the mentioned catalogues. Using the TKSolver^®, 〖yEd Graph Editor〗^® and 〖j2gml〗^®, software, the Dichromatic Graphs Method (DGM) to generate the solution algorithm was applied, through which the dispositions of ANNs connected among them were determined. Backpropagation ANNs type were trained using Matlab^® Neural Network Toolbox. Thus the ANN1, whose entry are revolutions per minute (rpm)of the minor pulley and the design potency, it predicts the belt profile with a typology 2-20-20-20-1 and a relative average error of 0.17%. the ANN2 predicts the base potency, utilizing as entry variable the belt profile, the rpm and the minor pulley primitive diameter, with a typology 3-20-20-20-1 and a relative error average of 0.24%. the ANN3 predicts the additional potency, considering as entry variable the belt profile, the rpm of the minor pulley and the transmission relation, with a typology of 3-30-30-30-1 and a relative error average of 0.10%. With 〖IBM SPSS Statistics 22〗^®software, the ANNs were validated, through curves contrast, histograms and error surfaces. Finally, the interface of the applicative is done, by means of GUI of Matlab^®, giving to the user a faithful, precise and fast tool, with a minimum computing waste, to speed up and verify mechanic design calculus into the academic and industrial areas. To validate the application 14 study cases were considered developed with others calculus method, whose variables were not considered at the ANNs training phase. Additional to that, the tool generates the designed transmission diagram, accompanied with a result report.