The goal of railway rolling stock maintenance and replacement approaches is to reduce overall cost while increasing reliability which is multi objective op</span><span style="font-family:Verdana;"&g...The goal of railway rolling stock maintenance and replacement approaches is to reduce overall cost while increasing reliability which is multi objective op</span><span style="font-family:Verdana;">timization problem and a proper predictive maintenance scheduling table sh</span><span style="font-family:Verdana;">ould be adequately designed. We propose Breeding Particle Swarm Optimization (BPSO) model based on the concepts of Breeding Swarm and Genetic Algor</span><span style="font-family:Verdana;">ithm (GA) operators to design this table. The practical experiment shows th</span><span style="font-family:Verdana;">at our model reduces cost while increasing reliability compared to other models previously utilized.展开更多
This study focuses on the quantification of the influence of rolling stock failures(RSFs)on railway infrastructure.Taking the wheel flat,a common RSF,as an example,we introduce four quantification indexes to evaluate ...This study focuses on the quantification of the influence of rolling stock failures(RSFs)on railway infrastructure.Taking the wheel flat,a common RSF,as an example,we introduce four quantification indexes to evaluate the influence on the following four deterioration mechanisms:track settlement(TS),track component fatigue(TCF),abrasive wear(AW),and rolling contact fatigue(RCF).Our results indicate that TS,TCF,and AW increase sharply with the increase of the wheel flat length and the vehicle speed,and this increasing trend becomes more acute with the increase of the wheel flat length and the vehicle speed.At low speeds,RCF increases gradually as the wheel flat length increases;at high speeds,it increases sharply at first and then decreases gradually.The influence of the wheel flat on TCF and AW is the most obvious,followed by TS and RCF.These findings can help infrastructure managers(IMs)to better understand infrastructure conditions related to RSFs and can aid them in managing problems with vehicle abnormality in track access charging.展开更多
文摘The goal of railway rolling stock maintenance and replacement approaches is to reduce overall cost while increasing reliability which is multi objective op</span><span style="font-family:Verdana;">timization problem and a proper predictive maintenance scheduling table sh</span><span style="font-family:Verdana;">ould be adequately designed. We propose Breeding Particle Swarm Optimization (BPSO) model based on the concepts of Breeding Swarm and Genetic Algor</span><span style="font-family:Verdana;">ithm (GA) operators to design this table. The practical experiment shows th</span><span style="font-family:Verdana;">at our model reduces cost while increasing reliability compared to other models previously utilized.
基金Project supported by the Assets4Rail Project Funded by the Shift2Rail Joint Undertaking under the EU’s H2020 Program(No.826250)the China Scholarship Council(No.201707000113)。
文摘This study focuses on the quantification of the influence of rolling stock failures(RSFs)on railway infrastructure.Taking the wheel flat,a common RSF,as an example,we introduce four quantification indexes to evaluate the influence on the following four deterioration mechanisms:track settlement(TS),track component fatigue(TCF),abrasive wear(AW),and rolling contact fatigue(RCF).Our results indicate that TS,TCF,and AW increase sharply with the increase of the wheel flat length and the vehicle speed,and this increasing trend becomes more acute with the increase of the wheel flat length and the vehicle speed.At low speeds,RCF increases gradually as the wheel flat length increases;at high speeds,it increases sharply at first and then decreases gradually.The influence of the wheel flat on TCF and AW is the most obvious,followed by TS and RCF.These findings can help infrastructure managers(IMs)to better understand infrastructure conditions related to RSFs and can aid them in managing problems with vehicle abnormality in track access charging.
