考虑低载强化效应的变速器加速试验谱的编制

发布时间：2018-02-13 07:51

本文关键词： 变速器载荷谱低载强化加速试验　出处：《机械传动》2016年04期 　论文类型：期刊论文

【摘要】：变速器室内台架模拟试验是考核、评价和提升其性能的重要手段。以变速器为对象,提出了一种能简化变速器加速疲劳试验程序载荷谱的编制方法。利用无线遥测技术在垫江汽车试验场采集了汽车变速器的实际道路载荷谱,分挡位对实际载荷谱进行了预处理。以2挡载荷为例,应用雨流计数法得到载荷的频次分布矩阵,运用卡方检验发现载荷均值服从均值为91.77 N·m、标准差为163.27 N·m的正态分布,载荷变程服从形状参数为1.346、比例参数为305.489的双参数威布尔分布,并且均值和变程相互独立。利用二维概率分布函数,建立了8×8级二维载荷谱。应用变均值法,将二维载荷谱转化为8级一维载荷谱。依据半轴的损伤特性和低载强化特性,研究强化载荷之间的等强化准则,将强化载荷折算到最佳载荷级,减少了载荷加载频次,提高了试验效率。
[Abstract]:The indoor bench simulation test of transmission is an important means to assess, evaluate and improve its performance. In this paper, a method to simplify the program load spectrum of acceleration fatigue test for transmission is presented. The actual road load spectrum of vehicle transmission is collected by using wireless telemetry technology in Qianjiang Automobile Test Field. The actual load spectrum has been pretreated by dividing the position. Taking the second load as an example, the frequency distribution matrix of the load is obtained by using the rain flow counting method. By using chi-square test, the normal distribution of load average is found to be 91.77 N 路m, and the standard deviation is 163.27 N 路m. The load variable range clothing is a two-parameter Weibull distribution with a shape parameter of 1.346 and a proportional parameter of 305.489, and the mean value and the variable range are independent of each other. By using the two-dimensional probability distribution function, the 2-D load spectrum of 8 脳 8 order is established, and the variable mean value method is used. The 2-D load spectrum is transformed into 8-grade one-dimensional load spectrum. According to the damage characteristics and low-load strengthening characteristics of the half-axis, the equivalent strengthening criterion between the strengthened loads is studied. The enhanced load is converted to the best load level, and the frequency of load loading is reduced. The test efficiency is improved.
【作者单位】：重庆理工大学汽车零部件先进制造技术教育部重点实验室;
【基金】：国家自然科学基金(51205432) 国家科技支撑计划(2012BAH32F01) 重庆市教育委员会科学技术研究项目(KJ1400931) 西华大学汽车工程四川省高校重点实验室开放课题(SZJJ2014-071)
【分类号】：TH132.46

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