摘要
针对轨道车辆走行部关键部件的故障识别问题,本文提出了利用蚁群算法对弹簧的状态参数进行估计。通过对轨道车辆横向动力学方程建立的多元线性回归模型进行处理,得到约束模型。利用蚁群算法的寻优特性,在弹簧的正常、轻微故障和断裂的情况下对约束模型进行寻优计算,验证该算法的有效性。结果表明:该方法可以有效准确地估计轨道车辆走行部关键部件弹簧的实际参数值。通过比较估计值和正常值,可及时判断弹簧的状态,该参数估计方法可为轨道车辆悬挂系统关键部件状态监测提供重要的理论依据。
Aiming at the problem of fault identification of the key components of the running part of rail vehicles,this paper proposes the use of ant colony algorithm to estimate the state parameters of the spring.By processing the multiple linear regression model established by the rail vehicle lateral dynamics equation,the constraint model is obtained.Using the optimization characteristics of the ant colony algorithm,the constraint model is optimized under the condition of normal,minor failure and breakage of the spring to verify the eff ectiveness of the algorithm.The results show that the method can eff ectively and accurately estimate the actual parameter values of the springs of the key components of the running gear of rail vehicles.By comparing the estimated value with the normal value,the state of the spring can be judged in time.This parameter estimation method can provide an important theoretical basis for the state monitoring of the key components of the rail vehicle suspension system.
作者
周宏祥
尧辉明
ZHOU Hongxiang;YAO Huiming(School of Urban Rail Transit,Shanghai University of Engineering Science,Shanghai 201620)
出处
《软件》
2021年第3期86-89,102,共5页
Software
基金
国家自然科学基金资助项目(51975347)。
关键词
轨道车轮
动力学模型
蚁群算法
参数估计
寻优处理
rail wheel
dynamic model
ant colony algorithm
parameter estimation
optimization processing
