Development of a multi-layer perceptron artificial neural network model to determine haul trucks energy consumption  

作　　者：Soofastaei Ali Aminossadati Saiied M. Arefi Mohammad M. Kizil Mehmet S. 

机构地区：[1]School of Mechanical and Mining Engineering.CRC Mining,The University of Queensland [2]Department of Power and Control Engineering,School of Electrical and Computer Engineering,Shiraz University

出　　处：《International Journal of Mining Science and Technology》2016年第2期285-293,共9页矿业科学技术学报（英文版）

基　　金：CRC Mining and The University of Queensland for their financial support for this study

摘　　要：The mining industry annually consumes trillions of British thermal units of energy,a large part of which is saveable.Diesel fuel is a significant source of energy in surface mining operations and haul trucks are the major users of this energy source.Cross vehicle weight,truck velocity and total resistance have been recognised as the key parameters affecting the fuel consumption.In this paper,an artificial neural network model was developed to predict the fuel consumption of haul trucks in surface mines based on the gross vehicle weight,truck velocity and total resistance.The network was trained and tested using real data collected from a surface mining operation.The results indicate that the artificial neural network modelling can accurately predict haul truck fuel consumption based on the values of the haulage parameters considered in this study.The mining industry annually consumes trillions of British thermal units of energy,a large part of which is saveable.Diesel fuel is a significant source of energy in surface mining operations and haul trucks are the major users of this energy source.Cross vehicle weight,truck velocity and total resistance have been recognised as the key parameters affecting the fuel consumption.In this paper,an artificial neural network model was developed to predict the fuel consumption of haul trucks in surface mines based on the gross vehicle weight,truck velocity and total resistance.The network was trained and tested using real data collected from a surface mining operation.The results indicate that the artificial neural network modelling can accurately predict haul truck fuel consumption based on the values of the haulage parameters considered in this study.

关 键 词：Fuel consumption Haul truck Surface mine Artificial neural network 

分 类 号：TD57[矿业工程—矿山机电]