TY - JOUR
TI - Prediction of thickness of pantograph contact strips using Artificial Neural Networks
AU - Kuźnar, Małgorzata
TI - Prediction of thickness of pantograph contact strips using Artificial Neural Networks
AB - 
	The sliding strip of the current collector (pantograph) of a rail vehicle is an element directly cooperating with the catenary and is exposed to abrasion, electric discharge and various types of damage. It is therefore the most frequently replaced element. However, often sliding strips are exchanged before exceeding the limit thickness value, which increases the costs related to technical maintenance. Because the wear process is dependent on many factors, heuristic methods are necessary to predict the thickness of the sliding strip. Knowing the predicted thickness value, it will be possible to adapt the maintenance cycle. In the article, the results of simulations carried out based on the developed structure of the artificial neural network are also presented.
VL - 2019
IS - Volume 12 Year 2019 (116)
PY - 2019
SN - 0011-4561
C1 - 2353-737X
SP - 173
EP - 180
DO - 10.4467/2353737XCT.19.130.11455
UR - https://ejournals.eu/en/journal/czasopismo-techniczne/article/prediction-of-thickness-of-pantograph-contact-strips-using-artificial-neural-networks
KW - rail vehicles
KW - pantograph
KW - current collector
KW - thickness prediction
KW - sliding cover
KW - artificial neural networks
KW - ANN