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标 题: A Study on P-S-N Curve for Rotating Bending Fatigue Test for Bearing Steel
轴承钢旋转弯曲疲劳试验中P-S-N曲线的研究
作 者: KATSUJI TOSHA
DAISUKE UEDA
HIROKAZU SHIMODA
SHIGEO SHIMIZU
关键词: Bearing Steel  [轴承钢]
Fatigue Test  [ 疲劳测试]
Fatigue Limit  [ 疲劳限制]
Non-Metallic Inclusions  [ 非金属夹杂物]
Linear Bearing  [ 直线轴承]
Log-Normal Distribution  [ 对数正态分布]
P-S-N Curve  [ P-S-N-N 曲线]
Rotating Bending  [ 旋转弯曲]
Rating Load  [ 评分加载]
Rating Stress  [ 评分压力]
Statistical Analysis  [ 统计分析]
Weibull Distribution  [ 威布尔分布]
出版年: 2008
期刊名: Tribology Transactions
摩擦学 Transactions
年卷期: 2008, vol.51, no.2
摘 要: A study on the fatigue behavior of bearing steel by using rotating bending fatigue test rigs is carried out for bearing steel (JIS SUJ2 = AISI 52100) heat-treated to HRC58-62. Several P-S-N curves and fatigue life distributions, such as Weibull and log-normal, have been used for the discussion. As a result, the best fit for a life distribution of six lots each with a sample size of around 30 specimens, at stress levels from 0.94 GPa to 1.27 GPa, is obtained by the three-parameter Weibull distribution, followed by the lognormal distribution as second, and the two-parameter Weibull distribution as the third. The observation of the broken section of the test piece reveals that the initiation point of the failure is associated almost always with subsurface nonmetallic inclusions. The fatigue limit could not be observed in the experimental results. It is also proposed that the relationship between the statistical life distributions of the test series and the P-S-N curve can be expressed by the same model as the life formula by introducing a rating stress such as bearing rating load in the three-parameter Weibull and log-normal distribution used.

采用旋转弯曲疲劳试验机对热处理至HRC58-62的轴承钢(JIS SUJ2 = AISI 52100)进行了疲劳行为研究。文中分析了多种P-S-N曲线及疲劳寿命分布,如威布尔分布和对数正态分布。结果表明,在应力范围为0.94 GPa至1.27 GPa、每批样品约30个试样的情况下,六批试样的寿命分布最佳拟合效果由三参数威布尔分布获得,其次为对数正态分布,第三为二参数威布尔分布。通过观察试样断裂部位可发现,失效起始点几乎总是与表面下的非金属夹杂物有关。实验结果中未观察到疲劳极限。此外,建议在所使用的三参数威布尔分布和对数正态分布中引入轴承额定载荷等评定应力,以将测试系列的统计寿命分布与P-S-N曲线之间的关系表达为与寿命公式相同的模型。
中文内容为网络AI翻译,专业术语未必准确,仅供参考。

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