Development of an artificial neural network model with graphical user interface for predicting contact area of bias-ply tractor tyres on firm surface

摘要

An Artificial Neural Network (ANN) model was developed for predicting the contact area and ground pressure of bias-ply tractor tyres. A Graphical User Interface (GUI) using Tkinter was created to deploy the developed ANN model. A total of 538 datasets for the 12.4-28, 13.6-28, 14.9-28 and 16.9-28 tyres by varying load on tyres (600 to 1950 kg) and inflation pressure (69 to 234 kPa) were collected from the experimental trials and divided in a ratio of 70:30 for the training and testing of the ANN model, respectively. Another 50 new datasets of all tyres were used for validation purpose. The nominal width and overall diameter of tyre, normal load, and inflation pressure were considered as input parameters for the developed ANN model and the contact area of the tyre was taken as the output parameter. All the input parameters significantly affected the contact area of the tyre, as evident from the sensitivity anal-ysis. The well-trained ANN model coupled with GUI predicted contact area and ground pressure beneath the tyre on firm surface at any inflation pressure and load with a maximum deviation of 2 from the actual values measured as compared to 10 and-9 in case of Komandi model.(c) 2023 ISTVS. Published by Elsevier Ltd. All rights reserved.