基于参数辨识的矿用自卸车平顺性优化  

Mining Dump Truck Ride Optimization Based on Parameter Identification

作　　者：米承继[1] 谷正气[1,2] 伍文广[1] 陶坚[1] 梁小波 彭国谱 

机构地区：[1]湖南大学汽车车身先进设计制造国家重点实验室,长沙410082 [2]湖南工业大学,株洲412007 [3]湘电重型装备股份有限公司,湘潭411100

出　　处：《机械工程学报》2012年第6期109-115,共7页Journal of Mechanical Engineering

基　　金：国家自然科学基金(7150080050);湖南省科技攻关计划重点(O6FJ2001)资助项目

摘　　要：矿用自卸车行驶路况非常恶劣,为改善某型矿用自卸车的平顺性,需要得到油气悬架非线性刚度阻尼特性。利用具有紧支撑正交特性的Daubechies小波和最小二乘法原理辨识油气悬架物理参数,将时变刚度阻尼离散为正交尺度函数下的线性组合,从而把辨识时变物理参数的'黑箱'问题转化为已知尺度函数序列和系统的输入输出来估计线性组合中的时不变系数问题。为验证辨识的刚度阻尼值,在Adams/view中建立整车多体动力学模型,得知辨识参数下的加速度时域响应和功率谱密度与试验结果相差无几,从而验证了该方法的有效性。借助遗传算法优化油气悬架的物理参数,将辨识结果作为优化变量的初始条件,以座椅垂直方向加速度方均根值为目标,优化后目标值下降了51.84%,达到了改善平顺性的目的。In order to optimize mining dump truck ride comfort for bad driving traffic,nonlinear stiffness and damping characteristics of hydro-pneumatic suspension are needed.Time-varying stiffness and damping with linear combination under a series scaling function is scattered,based on Daubechies wavelet＇s compactness and regularization and least-square method.This means to turn ＂black problem＂ of identifying time-varying parameters into identifying invariant coefficients when the scaling function sequence and the input and output of system are known.The multi-rigid body dynamic model of whole truck is built in Adams/view for the sake of testing stiffness and damping of identifying.Time-acceleration and power spectral density under identifying parameter are found to be extremely close to the result of experiment,which implies validity of this method.The physical parameters of hydro-pneumatic suspension by genetic algorithm is optimized,which makes the identifying parameter as the initial condition and makes the root mean square value of the seat acceleration as optimization objective.After optimizing,the value is descended by 51.84%,which achieves the purpose of improving the ride comfort.

关 键 词：平顺性 DAUBECHIES小波 最小二乘法 辨识 尺度函数 遗传算法 

分 类 号：TD57[矿业工程—矿山机电]