基于云模型与组合赋权的转辙机SOH评估模型  

SOH evaluation model of switch machine based on cloud model and combined weighting

作　　者：张娟娟[1] 黄斌[1] 蒋敏建[1] ZHANG Juanjuan;HUANG Bin;JIANG Minjian(Liuzhou Railway Vocational and Technical College,Liuzhou 545616,China)

机构地区：[1]柳州铁道职业技术学院

出　　处：《铁道科学与工程学报》2019年第8期2100-2106,共7页Journal of Railway Science and Engineering

基　　金：广西高等学校高水平创新团队及卓越学者计划项目(2017KY1239)

摘　　要：当前铁路信号设备智能运维正在起步阶段,针对转辙机机械故障率高且存在模糊性与随机性的特点,建立一种结合云模型与主、客观组合赋权相融合的设备健康状态(SOH,state of health)评估模型。首先,从“设备-环境-人员-管理”4个方面建立影响转辙机SOH的综合指标体系;其次,选择改进AHP法(主观法)与CRITIC法(客观法)理论求取对应20组指标层的权重;再分别采用2种组合赋权法(乘法集成法、动态赋权法)对比求取对应7组部件层的组合权重。然后,通过云模型理论与组合赋权相交,结合云相似度计算设备当前SOH等级。最后,通过一个实例分析验证了该方法的可行性与有效性,为铁路信号设备智能运维提供借鉴。At present,intelligent operation and maintenance of railway signal equipment are in the initial stage.In view of the characteristics of high mechanical failure rate,fuzziness and randomness of switch machine,this paper established a SOH (state of health) evaluation model combining cloud model with subjective and objective weightings.Firstly,a comprehensive index system affecting switch machine SOH was built from four aspects of “equipment-environment-personnel-management”.Secondly,it was chosen to improve the AHP method (subjective method) and the CRITIC method (objective method) theory to find the corresponding 20 groups of index layer weight;Thirdly,two combined weighting methods (multiplication integration method and dynamic weighting method) were used to compare and obtain the combined weights of the corresponding 7 groups of component layers.Then,through the intersection of cloud model theory and combined weighting,the current SOH level of cloud similarity computing equipment was combined.Finally,an example was given to verify the feasibility and effectiveness of this method.This paper provided a reference for intelligent operation and maintenance of railway signal equipment.

关 键 词：转辙机 模糊性 随机性 云模型 SOH AHP法 CRITIC法 

分 类 号：U283.2[交通运输工程—交通信息工程及控制] U284.7[交通运输工程—道路与铁道工程]