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Published in:
2019 | OriginalPaper | Chapter
Use of Artificial Neural Networks for the Estimated Prediction of Haul Trucks Operating States
Authors : Przemysław Bodziony, Rafał Kudelski, Michał Patyk, Zbigniew Kasztelewicz
Published in: Proceedings of the 14th International Scientific Conference: Computer Aided Engineering
Publisher: Springer International Publishing
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Abstract
The paper presents basic information on the prognosis of technical condition estimation by a neural network algorithm. Mining transport systems based on the use of haul trucks should result from a thorough analysis of technical and operating issues - which can have a crucial impact on the cost of minerals extraction. This selection should consider hitherto disregarded criteria, such as technical infallibility, operating parameters like mean failure intensity and fault modes, and the effect analysis based on the information from the past and from the current state etc. The selected forecasting method by the prediction using neural networking has been described. Neural networks can be used for prediction with various levels of success. Considering the above issues, the paper is an attempt to analyse operating parameters and to show the result of prediction using a neural network of backpropagation type on a fleet of haul trucks used to transport minerals in the surface mining.