基于核密度估计算法的T100C列车转向架载荷谱统计研究  

A RESEARCH ON LOAD SPECTRUM STATISTICAL ANALYSIS OF T100C TRAIN BOGIE BASED ON KERNEL DENSITY ESTIMATION ALGORITHM

作　　者：高延杰[1] 杨永发[1] 陈炯[2] 杨灿宇[1] 

机构地区：[1]西南林业大学机械与交通学院,昆明650224 [2]昆明铁路局科学技术研究所,昆明650011

出　　处：《机械强度》2016年第6期1330-1334,共5页Journal of Mechanical Strength

基　　金：中国铁路总公司昆明铁路局科技项目(2014-141-K14J23)资助~~

摘　　要：传统列车载荷谱的统计都是建立在实际测量的基础上,利用威布尔分布拟合测试结果,计算各级载荷。但是整个过程所需测试里程长,费时费力,威布尔参数拟合困难。更重要的是,由于事先假定载荷的分布,所以最终统计结果并不一定能反映样本的真实情况。为了克服传统载荷谱统计方法的不足,在雨流计数方法进行时间—载荷历程统计的基础上,将核密度估计算法用于SRM80型全断面道砟清筛机T100C新型转向架侧架的载荷谱统计工作。结果显示:核密度估计方法能较好的还原载荷谱原貌,弥补小子样数据不足的问题,可以为列车载荷谱统计工作节约人力物力。Traditional train load spectrum statistics are all based on actual measurements, using Weibull distribution to fit test results and calculate load at different levels. But the required testing mileage is long and the entire process is time- consuming. It is also difficult to fit Weibull parameters. More importantly, the final results are not necessarily reflect the real characteristic of a sample due to the assuming of load distribution beforehand. In order to overcome the disadvantages of traditional load spectrum statistical methods, in this paper, we use kernel density estimation techniques in statistical work of side frame load spectrum for SRM80 full ballast cleaning machine＇ s T100C new bogie, which is based on the use of rain-flow counting method in time-load history statistics. Results show that the kernel density estimation method can restore the original load spectrum, remedy the problems of shortage of small sample data and save manpower and resources for train load spectrum statistical work.

关 键 词：转向架 载荷谱 雨流计数 核密度估计 

分 类 号：U273.4[机械工程—车辆工程]