超洁净轴承钢中夹杂物与滚动接触疲劳寿命的关系  

Relationship of Inclusions and Rolling Contact Fatigue Life for Ultra-Clean Bearing Steel

作　　者：孙飞龙 耿克 俞峰[3] 罗海文[1] SUN Feilong;GENG Ke;YU Feng;LUO Haiwen(Metallurgical Department of Metallurgical and Ecological Engineering,University of Science and Technology Beijing,Beijing 100083,China;Jiangyin Xingcheng Special Steel Works Co.Ltd.,Jiangyin 214400,China;Central Iron and Steel Research Institute,Beijing 100081,China)

机构地区：[1]北京科技大学冶金与生态工程学院,北京100083 [2]江阴兴澄特钢有限公司,江阴214400 [3]钢铁研究总院,北京100081

出　　处：《金属学报》2020年第5期693-703,共11页Acta Metallurgica Sinica

基　　金：国家重点研发计划项目No.2016YFB0300102;国家国际科技合作专项项目No.2015DFG51950;中央高校基本科研业务费专项资金项目No.FRF-TP-18-002C2。

摘　　要：以3种不同工艺工业生产的总O含量均≤6×10^-6的超洁净GCr15轴承钢为研究对象,通过推力片实验测试这3种钢的滚动接触疲劳寿命并获得额定寿命(L10)和中值寿命(L50),通过ASPEX扫描电镜获得各工艺下的夹杂物样本数据并进行统计分析,使用极值法(SEV)和广义Pareto分布法(GPD)估算出样品中最大夹杂物特征尺(CSMI),然后将其与实测L10和L50进行对比和分析。结果表明,SEV法仅检测每个样品的最大夹杂物,无法通过其获得的CSMI来合理解释3种钢L10和L50的变化,2者之间相关性较差;而GPD法分析夹杂物时,需要对阈值尺寸以上的所有夹杂物进行表征和统计分析,可以获得夹杂物的数量密度以及不同类型夹杂物的CSMI,GPD法所预测出的最危险类型TiN夹杂物的CSMI可以合理解释L10的变化,2者之间有较好相关性,但无法据此解释L50的变化;但将总的夹杂物数量密度与TiN夹杂物最大特征尺寸相结合,能合理解释3种钢的L50差异,这是因为当更多样品失效时,裂纹萌生位置将不再仅仅局限于最危险类型夹杂物。因此,最危险类型夹杂物的CSMI与超纯净轴承钢中的早期疲劳失效的L10相关性最强,而夹杂物的数量密度对高概率的中值疲劳寿命L50也有重要影响。The cleanliness of bearing steels produced in China has been greatly improved due to the significant progress in the steelmaking technologies in the past decade,leading to their total oxygen(T.O.)contents lowered to no more than 6×10^-6.Under such a high cleanliness,it is then expected that the influence of non-metallic inclusions on fatigue property should be different from the previous knowledge,because both the size and quantity of inclusions are reduced greatly.Therefore,both inclusions and fatigue properties for three ultra-clean GCr15(100Cr6)bearing steels containing T.O.around 6×10^-6,which were manufactured via different industrial production processes,were studied for this purpose.First,inclusions were characterized by ASPEX SEM and then statically analyzed by the statistics of extreme values(SEV)and the generalized Pareto distribution(GPD).Next,their rolling contact fatigue lives(RCF)L10 and L50 were measured by flat washer tests.Only the largest inclusion in each sample is required for predicting the characteristic sizes of maximum inclusion(CSMI)for the three steels using the SEV method.The calculated CSMIs,however,are not consistent with the variation of either L10 or L50,indicating they are not relevant.In contrast,the types of inclusions above threshold(u)size can be classified and their number density of inclusions quantified when the GPD method is employed.In particularly,the CSMIs of different types of inclusions can be determined.In this case,it has been found that the CSMI of TiN inclusion,which is the most dangerous for initiating cracking,is in a good agreement with the low probability rolling fatigue life(L10),suggesting that they are very correlated.This,however,cannot explain the variation of high-probability fatigue life(L50).Instead,the density of total inclusions also played an important role on the L50 of ultra-clean bearing steels in addition to the CSMI of TiN inclusions.This is reasonable because cracking shall be initiated at not only the most dangerous TiN inclusion during the

关 键 词：轴承钢 夹杂物 滚动接触疲劳寿命 统计极值法 广义Pareto 分布法 

分 类 号：TF762.4[冶金工程—钢铁冶金]